Nitric oxide mediates local activity-dependent excitatory synapse development.

PubMed

Nikonenko, Irina; Nikonenko, Alexander; Mendez, Pablo; Michurina, Tatyana V; Enikolopov, Grigori; Muller, Dominique

2013-10-29

Learning related paradigms play an important role in shaping the development and specificity of synaptic networks, notably by regulating mechanisms of spine growth and pruning. The molecular events underlying these synaptic rearrangements remain poorly understood. Here we identify NO signaling as a key mediator of activity-dependent excitatory synapse development. We find that chronic blockade of NO production in vitro and in vivo interferes with the development of hippocampal and cortical excitatory spine synapses. The effect results from a selective loss of activity-mediated spine growth mechanisms and is associated with morphological and functional alterations of remaining synapses. These effects of NO are mediated by a cGMP cascade and can be reproduced or prevented by postsynaptic expression of vasodilator-stimulated phosphoprotein phospho-mimetic or phospho-resistant mutants. In vivo analyses show that absence of NO prevents the increase in excitatory synapse density induced by environmental enrichment and interferes with the formation of local clusters of excitatory synapses. We conclude that NO plays an important role in regulating the development of excitatory synapses by promoting local activity-dependent spine-growth mechanisms.

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.

Nonlinear multiplicative dendritic integration in neuron and network models

PubMed Central

Zhang, Danke; Li, Yuanqing; Rasch, Malte J.; Wu, Si

2013-01-01

Neurons receive inputs from thousands of synapses distributed across dendritic trees of complex morphology. It is known that dendritic integration of excitatory and inhibitory synapses can be highly non-linear in reality and can heavily depend on the exact location and spatial arrangement of inhibitory and excitatory synapses on the dendrite. Despite this known fact, most neuron models used in artificial neural networks today still only describe the voltage potential of a single somatic compartment and assume a simple linear summation of all individual synaptic inputs. We here suggest a new biophysical motivated derivation of a single compartment model that integrates the non-linear effects of shunting inhibition, where an inhibitory input on the route of an excitatory input to the soma cancels or “shunts” the excitatory potential. In particular, our integration of non-linear dendritic processing into the neuron model follows a simple multiplicative rule, suggested recently by experiments, and allows for strict mathematical treatment of network effects. Using our new formulation, we further devised a spiking network model where inhibitory neurons act as global shunting gates, and show that the network exhibits persistent activity in a low firing regime. PMID:23658543

Synchronous firing patterns of induced pluripotent stem cell-derived cortical neurons depend on the network structure consisting of excitatory and inhibitory neurons.

PubMed

Iida, Shoko; Shimba, Kenta; Sakai, Koji; Kotani, Kiyoshi; Jimbo, Yasuhiko

2018-06-18

The balance between glutamate-mediated excitation and GABA-mediated inhibition is critical to cortical functioning. However, the contribution of network structure consisting of the both neurons to cortical functioning has not been elucidated. We aimed to evaluate the relationship between the network structure and functional activity patterns in vitro. We used mouse induced pluripotent stem cells (iPSCs) to construct three types of neuronal populations; excitatory-rich (Exc), inhibitory-rich (Inh), and control (Cont). Then, we analyzed the activity patterns of these neuronal populations using microelectrode arrays (MEAs). Inhibitory synaptic densities differed between the three types of iPSC-derived neuronal populations, and the neurons showed spontaneously synchronized bursting activity with functional maturation for one month. Moreover, different firing patterns were observed between the three populations; Exc demonstrated the highest firing rates, including frequent, long, and dominant bursts. In contrast, Inh demonstrated the lowest firing rates and the least dominant bursts. Synchronized bursts were enhanced by disinhibition via GABA A receptor blockade. The present study, using iPSC-derived neurons and MEAs, for the first time show that synchronized bursting of cortical networks in vitro depends on the network structure consisting of excitatory and inhibitory neurons. Copyright © 2018 Elsevier Inc. All rights reserved.

Activity-dependent switch of GABAergic inhibition into glutamatergic excitation in astrocyte-neuron networks.

PubMed

Perea, Gertrudis; Gómez, Ricardo; Mederos, Sara; Covelo, Ana; Ballesteros, Jesús J; Schlosser, Laura; Hernández-Vivanco, Alicia; Martín-Fernández, Mario; Quintana, Ruth; Rayan, Abdelrahman; Díez, Adolfo; Fuenzalida, Marco; Agarwal, Amit; Bergles, Dwight E; Bettler, Bernhard; Manahan-Vaughan, Denise; Martín, Eduardo D; Kirchhoff, Frank; Araque, Alfonso

2016-12-24

Interneurons are critical for proper neural network function and can activate Ca 2+ signaling in astrocytes. However, the impact of the interneuron-astrocyte signaling into neuronal network operation remains unknown. Using the simplest hippocampal Astrocyte-Neuron network, i.e., GABAergic interneuron, pyramidal neuron, single CA3-CA1 glutamatergic synapse, and astrocytes, we found that interneuron-astrocyte signaling dynamically affected excitatory neurotransmission in an activity- and time-dependent manner, and determined the sign (inhibition vs potentiation) of the GABA-mediated effects. While synaptic inhibition was mediated by GABA A receptors, potentiation involved astrocyte GABA B receptors, astrocytic glutamate release, and presynaptic metabotropic glutamate receptors. Using conditional astrocyte-specific GABA B receptor ( Gabbr1 ) knockout mice, we confirmed the glial source of the interneuron-induced potentiation, and demonstrated the involvement of astrocytes in hippocampal theta and gamma oscillations in vivo. Therefore, astrocytes decode interneuron activity and transform inhibitory into excitatory signals, contributing to the emergence of novel network properties resulting from the interneuron-astrocyte interplay.

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

PubMed

Blanco, Wilfredo; Bertram, Richard; Tabak, Joël

2017-01-01

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

Network and neuronal membrane properties in hybrid networks reciprocally regulate selectivity to rapid thalamocortical inputs.

PubMed

Pesavento, Michael J; Pinto, David J

2012-11-01

Rapidly changing environments require rapid processing from sensory inputs. Varying deflection velocities of a rodent's primary facial vibrissa cause varying temporal neuronal activity profiles within the ventral posteromedial thalamic nucleus. Local neuron populations in a single somatosensory layer 4 barrel transform sparsely coded input into a spike count based on the input's temporal profile. We investigate this transformation by creating a barrel-like hybrid network with whole cell recordings of in vitro neurons from a cortical slice preparation, embedding the biological neuron in the simulated network by presenting virtual synaptic conductances via a conductance clamp. Utilizing the hybrid network, we examine the reciprocal network properties (local excitatory and inhibitory synaptic convergence) and neuronal membrane properties (input resistance) by altering the barrel population response to diverse thalamic input. In the presence of local network input, neurons are more selective to thalamic input timing; this arises from strong feedforward inhibition. Strongly inhibitory (damping) network regimes are more selective to timing and less selective to the magnitude of input but require stronger initial input. Input selectivity relies heavily on the different membrane properties of excitatory and inhibitory neurons. When inhibitory and excitatory neurons had identical membrane properties, the sensitivity of in vitro neurons to temporal vs. magnitude features of input was substantially reduced. Increasing the mean leak conductance of the inhibitory cells decreased the network's temporal sensitivity, whereas increasing excitatory leak conductance enhanced magnitude sensitivity. Local network synapses are essential in shaping thalamic input, and differing membrane properties of functional classes reciprocally modulate this effect.

Signaling in large-scale neural networks.

PubMed

Berg, Rune W; Hounsgaard, Jørn

2009-02-01

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

Drifting States and Synchronization Induced Chaos in Autonomous Networks of Excitable Neurons.

PubMed

Echeveste, Rodrigo; Gros, Claudius

2016-01-01

The study of balanced networks of excitatory and inhibitory neurons has led to several open questions. On the one hand it is yet unclear whether the asynchronous state observed in the brain is autonomously generated, or if it results from the interplay between external drivings and internal dynamics. It is also not known, which kind of network variabilities will lead to irregular spiking and which to synchronous firing states. Here we show how isolated networks of purely excitatory neurons generically show asynchronous firing whenever a minimal level of structural variability is present together with a refractory period. Our autonomous networks are composed of excitable units, in the form of leaky integrators spiking only in response to driving currents, remaining otherwise quiet. For a non-uniform network, composed exclusively of excitatory neurons, we find a rich repertoire of self-induced dynamical states. We show in particular that asynchronous drifting states may be stabilized in purely excitatory networks whenever a refractory period is present. Other states found are either fully synchronized or mixed, containing both drifting and synchronized components. The individual neurons considered are excitable and hence do not dispose of intrinsic natural firing frequencies. An effective network-wide distribution of natural frequencies is however generated autonomously through self-consistent feedback loops. The asynchronous drifting state is, additionally, amenable to an analytic solution. We find two types of asynchronous activity, with the individual neurons spiking regularly in the pure drifting state, albeit with a continuous distribution of firing frequencies. The activity of the drifting component, however, becomes irregular in the mixed state, due to the periodic driving of the synchronized component. We propose a new tool for the study of chaos in spiking neural networks, which consists of an analysis of the time series of pairs of consecutive interspike intervals. In this space, we show that a strange attractor with a fractal dimension of about 1.8 is formed in the mentioned mixed state.

Drifting States and Synchronization Induced Chaos in Autonomous Networks of Excitable Neurons

PubMed Central

Echeveste, Rodrigo; Gros, Claudius

2016-01-01

The study of balanced networks of excitatory and inhibitory neurons has led to several open questions. On the one hand it is yet unclear whether the asynchronous state observed in the brain is autonomously generated, or if it results from the interplay between external drivings and internal dynamics. It is also not known, which kind of network variabilities will lead to irregular spiking and which to synchronous firing states. Here we show how isolated networks of purely excitatory neurons generically show asynchronous firing whenever a minimal level of structural variability is present together with a refractory period. Our autonomous networks are composed of excitable units, in the form of leaky integrators spiking only in response to driving currents, remaining otherwise quiet. For a non-uniform network, composed exclusively of excitatory neurons, we find a rich repertoire of self-induced dynamical states. We show in particular that asynchronous drifting states may be stabilized in purely excitatory networks whenever a refractory period is present. Other states found are either fully synchronized or mixed, containing both drifting and synchronized components. The individual neurons considered are excitable and hence do not dispose of intrinsic natural firing frequencies. An effective network-wide distribution of natural frequencies is however generated autonomously through self-consistent feedback loops. The asynchronous drifting state is, additionally, amenable to an analytic solution. We find two types of asynchronous activity, with the individual neurons spiking regularly in the pure drifting state, albeit with a continuous distribution of firing frequencies. The activity of the drifting component, however, becomes irregular in the mixed state, due to the periodic driving of the synchronized component. We propose a new tool for the study of chaos in spiking neural networks, which consists of an analysis of the time series of pairs of consecutive interspike intervals. In this space, we show that a strange attractor with a fractal dimension of about 1.8 is formed in the mentioned mixed state. PMID:27708572

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.

Activity-dependent switch of GABAergic inhibition into glutamatergic excitation in astrocyte-neuron networks

PubMed Central

Perea, Gertrudis; Gómez, Ricardo; Mederos, Sara; Covelo, Ana; Ballesteros, Jesús J; Schlosser, Laura; Hernández-Vivanco, Alicia; Martín-Fernández, Mario; Quintana, Ruth; Rayan, Abdelrahman; Díez, Adolfo; Fuenzalida, Marco; Agarwal, Amit; Bergles, Dwight E; Bettler, Bernhard; Manahan-Vaughan, Denise; Martín, Eduardo D; Kirchhoff, Frank; Araque, Alfonso

2016-01-01

Interneurons are critical for proper neural network function and can activate Ca2+ signaling in astrocytes. However, the impact of the interneuron-astrocyte signaling into neuronal network operation remains unknown. Using the simplest hippocampal Astrocyte-Neuron network, i.e., GABAergic interneuron, pyramidal neuron, single CA3-CA1 glutamatergic synapse, and astrocytes, we found that interneuron-astrocyte signaling dynamically affected excitatory neurotransmission in an activity- and time-dependent manner, and determined the sign (inhibition vs potentiation) of the GABA-mediated effects. While synaptic inhibition was mediated by GABAA receptors, potentiation involved astrocyte GABAB receptors, astrocytic glutamate release, and presynaptic metabotropic glutamate receptors. Using conditional astrocyte-specific GABAB receptor (Gabbr1) knockout mice, we confirmed the glial source of the interneuron-induced potentiation, and demonstrated the involvement of astrocytes in hippocampal theta and gamma oscillations in vivo. Therefore, astrocytes decode interneuron activity and transform inhibitory into excitatory signals, contributing to the emergence of novel network properties resulting from the interneuron-astrocyte interplay. DOI: http://dx.doi.org/10.7554/eLife.20362.001 PMID:28012274

The interdependence of excitation and inhibition for the control of dynamic breathing rhythms.

PubMed

Baertsch, Nathan Andrew; Baertsch, Hans Christopher; Ramirez, Jan Marino

2018-02-26

The preBötzinger Complex (preBötC), a medullary network critical for breathing, relies on excitatory interneurons to generate the inspiratory rhythm. Yet, half of preBötC neurons are inhibitory, and the role of inhibition in rhythmogenesis remains controversial. Using optogenetics and electrophysiology in vitro and in vivo, we demonstrate that the intrinsic excitability of excitatory neurons is reduced following large depolarizing inspiratory bursts. This refractory period limits the preBötC to very slow breathing frequencies. Inhibition integrated within the network is required to prevent overexcitation of preBötC neurons, thereby regulating the refractory period and allowing rapid breathing. In vivo, sensory feedback inhibition also regulates the refractory period, and in slowly breathing mice with sensory feedback removed, activity of inhibitory, but not excitatory, neurons restores breathing to physiological frequencies. We conclude that excitation and inhibition are interdependent for the breathing rhythm, because inhibition permits physiological preBötC bursting by controlling refractory properties of excitatory neurons.

Pulse propagation in discrete excitatory networks of integrate-and-fire neurons.

PubMed

Badel, Laurent; Tonnelier, Arnaud

2004-07-01

We study the propagation of solitary waves in a discrete excitatory network of integrate-and-fire neurons. We show the existence and the stability of a fast wave and a family of slow waves. Fast waves are similar to those already described in continuum networks. Stable slow waves have not been previously reported in purely excitatory networks and their propagation is particular to the discrete nature of the network. The robustness of our results is studied in the presence of noise.

Robust Working Memory in an Asynchronously Spiking Neural Network Realized with Neuromorphic VLSI

PubMed Central

Giulioni, Massimiliano; Camilleri, Patrick; Mattia, Maurizio; Dante, Vittorio; Braun, Jochen; Del Giudice, Paolo

2011-01-01

We demonstrate bistable attractor dynamics in a spiking neural network implemented with neuromorphic VLSI hardware. The on-chip network consists of three interacting populations (two excitatory, one inhibitory) of leaky integrate-and-fire (LIF) neurons. One excitatory population is distinguished by strong synaptic self-excitation, which sustains meta-stable states of “high” and “low”-firing activity. Depending on the overall excitability, transitions to the “high” state may be evoked by external stimulation, or may occur spontaneously due to random activity fluctuations. In the former case, the “high” state retains a “working memory” of a stimulus until well after its release. In the latter case, “high” states remain stable for seconds, three orders of magnitude longer than the largest time-scale implemented in the circuitry. Evoked and spontaneous transitions form a continuum and may exhibit a wide range of latencies, depending on the strength of external stimulation and of recurrent synaptic excitation. In addition, we investigated “corrupted” “high” states comprising neurons of both excitatory populations. Within a “basin of attraction,” the network dynamics “corrects” such states and re-establishes the prototypical “high” state. We conclude that, with effective theoretical guidance, full-fledged attractor dynamics can be realized with comparatively small populations of neuromorphic hardware neurons. PMID:22347151

Robust Working Memory in an Asynchronously Spiking Neural Network Realized with Neuromorphic VLSI.

PubMed

Giulioni, Massimiliano; Camilleri, Patrick; Mattia, Maurizio; Dante, Vittorio; Braun, Jochen; Del Giudice, Paolo

2011-01-01

We demonstrate bistable attractor dynamics in a spiking neural network implemented with neuromorphic VLSI hardware. The on-chip network consists of three interacting populations (two excitatory, one inhibitory) of leaky integrate-and-fire (LIF) neurons. One excitatory population is distinguished by strong synaptic self-excitation, which sustains meta-stable states of "high" and "low"-firing activity. Depending on the overall excitability, transitions to the "high" state may be evoked by external stimulation, or may occur spontaneously due to random activity fluctuations. In the former case, the "high" state retains a "working memory" of a stimulus until well after its release. In the latter case, "high" states remain stable for seconds, three orders of magnitude longer than the largest time-scale implemented in the circuitry. Evoked and spontaneous transitions form a continuum and may exhibit a wide range of latencies, depending on the strength of external stimulation and of recurrent synaptic excitation. In addition, we investigated "corrupted" "high" states comprising neurons of both excitatory populations. Within a "basin of attraction," the network dynamics "corrects" such states and re-establishes the prototypical "high" state. We conclude that, with effective theoretical guidance, full-fledged attractor dynamics can be realized with comparatively small populations of neuromorphic hardware neurons.

Decorrelation of Neural-Network Activity by Inhibitory Feedback

PubMed Central

Einevoll, Gaute T.; Diesmann, Markus

2012-01-01

Correlations in spike-train ensembles can seriously impair the encoding of information by their spatio-temporal structure. An inevitable source of correlation in finite neural networks is common presynaptic input to pairs of neurons. Recent studies demonstrate that spike correlations in recurrent neural networks are considerably smaller than expected based on the amount of shared presynaptic input. Here, we explain this observation by means of a linear network model and simulations of networks of leaky integrate-and-fire neurons. We show that inhibitory feedback efficiently suppresses pairwise correlations and, hence, population-rate fluctuations, thereby assigning inhibitory neurons the new role of active decorrelation. We quantify this decorrelation by comparing the responses of the intact recurrent network (feedback system) and systems where the statistics of the feedback channel is perturbed (feedforward system). Manipulations of the feedback statistics can lead to a significant increase in the power and coherence of the population response. In particular, neglecting correlations within the ensemble of feedback channels or between the external stimulus and the feedback amplifies population-rate fluctuations by orders of magnitude. The fluctuation suppression in homogeneous inhibitory networks is explained by a negative feedback loop in the one-dimensional dynamics of the compound activity. Similarly, a change of coordinates exposes an effective negative feedback loop in the compound dynamics of stable excitatory-inhibitory networks. The suppression of input correlations in finite networks is explained by the population averaged correlations in the linear network model: In purely inhibitory networks, shared-input correlations are canceled by negative spike-train correlations. In excitatory-inhibitory networks, spike-train correlations are typically positive. Here, the suppression of input correlations is not a result of the mere existence of correlations between excitatory (E) and inhibitory (I) neurons, but a consequence of a particular structure of correlations among the three possible pairings (EE, EI, II). PMID:23133368

Cortical network modeling: analytical methods for firing rates and some properties of networks of LIF neurons.

PubMed

Tuckwell, Henry C

2006-01-01

The circuitry of cortical networks involves interacting populations of excitatory (E) and inhibitory (I) neurons whose relationships are now known to a large extent. Inputs to E- and I-cells may have their origins in remote or local cortical areas. We consider a rudimentary model involving E- and I-cells. One of our goals is to test an analytic approach to finding firing rates in neural networks without using a diffusion approximation and to this end we consider in detail networks of excitatory neurons with leaky integrate-and-fire (LIF) dynamics. A simple measure of synchronization, denoted by S(q), where q is between 0 and 100 is introduced. Fully connected E-networks have a large tendency to become dominated by synchronously firing groups of cells, except when inputs are relatively weak. We observed random or asynchronous firing in such networks with diverse sets of parameter values. When such firing patterns were found, the analytical approach was often able to accurately predict average neuronal firing rates. We also considered several properties of E-E networks, distinguishing several kinds of firing pattern. Included were those with silences before or after periods of intense activity or with periodic synchronization. We investigated the occurrence of synchronized firing with respect to changes in the internal excitatory postsynaptic potential (EPSP) magnitude in a network of 100 neurons with fixed values of the remaining parameters. When the internal EPSP size was less than a certain value, synchronization was absent. The amount of synchronization then increased slowly as the EPSP amplitude increased until at a particular EPSP size the amount of synchronization abruptly increased, with S(5) attaining the maximum value of 100%. We also found network frequency transfer characteristics for various network sizes and found a linear dependence of firing frequency over wide ranges of the external afferent frequency, with non-linear effects at lower input frequencies. The theory may also be applied to sparsely connected networks, whose firing behaviour was found to change abruptly as the probability of a connection passed through a critical value. The analytical method was also found to be useful for a feed-forward excitatory network and a network of excitatory and inhibitory neurons.

Organization of left–right coordination of neuronal activity in the mammalian spinal cord: Insights from computational modelling

PubMed Central

Shevtsova, Natalia A; Talpalar, Adolfo E; Markin, Sergey N; Harris-Warrick, Ronald M; Kiehn, Ole; Rybak, Ilya A

2015-01-01

Different locomotor gaits in mammals, such as walking or galloping, are produced by coordinated activity in neuronal circuits in the spinal cord. Coordination of neuronal activity between left and right sides of the cord is provided by commissural interneurons (CINs), whose axons cross the midline. In this study, we construct and analyse two computational models of spinal locomotor circuits consisting of left and right rhythm generators interacting bilaterally via several neuronal pathways mediated by different CINs. The CIN populations incorporated in the models include the genetically identified inhibitory (V0D) and excitatory (V0V) subtypes of V0 CINs and excitatory V3 CINs. The model also includes the ipsilaterally projecting excitatory V2a interneurons mediating excitatory drive to the V0V CINs. The proposed network architectures and CIN connectivity allow the models to closely reproduce and suggest mechanistic explanations for several experimental observations. These phenomena include: different speed-dependent contributions of V0D and V0V CINs and V2a interneurons to left–right alternation of neural activity, switching gaits between the left–right alternating walking-like activity and the left–right synchronous hopping-like pattern in mutants lacking specific neuron classes, and speed-dependent asymmetric changes of flexor and extensor phase durations. The models provide insights into the architecture of spinal network and the organization of parallel inhibitory and excitatory CIN pathways and suggest explanations for how these pathways maintain alternating and synchronous gaits at different locomotor speeds. The models propose testable predictions about the neural organization and operation of mammalian locomotor circuits. Key points Coordination of neuronal activity between left and right sides of the mammalian spinal cord is provided by several sets of commissural interneurons (CINs) whose axons cross the midline. Genetically identified inhibitory V0D and excitatory V0V CINs and ipsilaterally projecting excitatory V2a interneurons were shown to secure left–right alternation at different locomotor speeds. We have developed computational models of neuronal circuits in the spinal cord that include left and right rhythm-generating centres interacting bilaterally via three parallel pathways mediated by V0D, V2a–V0V and V3 neuron populations. The models reproduce the experimentally observed speed-dependent left–right coordination in normal mice and the changes in coordination seen in mutants lacking specific neuron classes. The models propose an explanation for several experimental results and provide insights into the organization of the spinal locomotor network and parallel CIN pathways involved in gait control at different locomotor speeds. PMID:25820677

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.

Neuronal adenosine release, and not astrocytic ATP release, mediates feedback inhibition of excitatory activity

PubMed Central

Lovatt, Ditte; Xu, Qiwu; Liu, Wei; Takano, Takahiro; Smith, Nathan A.; Schnermann, Jurgen; Tieu, Kim; Nedergaard, Maiken

2012-01-01

Adenosine is a potent anticonvulsant acting on excitatory synapses through A1 receptors. Cellular release of ATP, and its subsequent extracellular enzymatic degradation to adenosine, could provide a powerful mechanism for astrocytes to control the activity of neural networks during high-intensity activity. Despite adenosine's importance, the cellular source of adenosine remains unclear. We report here that multiple enzymes degrade extracellular ATP in brain tissue, whereas only Nt5e degrades AMP to adenosine. However, endogenous A1 receptor activation during cortical seizures in vivo or heterosynaptic depression in situ is independent of Nt5e activity, and activation of astrocytic ATP release via Ca2+ photolysis does not trigger synaptic depression. In contrast, selective activation of postsynaptic CA1 neurons leads to release of adenosine and synaptic depression. This study shows that adenosine-mediated synaptic depression is not a consequence of astrocytic ATP release, but is instead an autonomic feedback mechanism that suppresses excitatory transmission during prolonged activity. PMID:22421436

Selective functional interactions between excitatory and inhibitory cortical neurons and differential contribution to persistent activity of the slow oscillation.

PubMed

Tahvildari, Babak; Wölfel, Markus; Duque, Alvaro; McCormick, David A

2012-08-29

The neocortex depends upon a relative balance of recurrent excitation and inhibition for its operation. During spontaneous Up states, cortical pyramidal cells receive proportional barrages of excitatory and inhibitory synaptic potentials. Many of these synaptic potentials arise from the activity of nearby neurons, although the identity of these cells is relatively unknown, especially for those underlying the generation of inhibitory synaptic events. To address these fundamental questions, we developed an in vitro submerged slice preparation of the mouse entorhinal cortex that generates robust and regular spontaneous recurrent network activity in the form of the slow oscillation. By performing whole-cell recordings from multiple cell types identified with green fluorescent protein expression and electrophysiological and/or morphological properties, we show that distinct functional subpopulations of neurons exist in the entorhinal cortex, with large variations in contribution to the generation of balanced excitation and inhibition during the slow oscillation. The most active neurons during the slow oscillation are excitatory pyramidal and inhibitory fast spiking interneurons, receiving robust barrages of both excitatory and inhibitory synaptic potentials. Weak action potential activity was observed in stellate excitatory neurons and somatostatin-containing interneurons. In contrast, interneurons containing neuropeptide Y, vasoactive intestinal peptide, or the 5-hydroxytryptamine (serotonin) 3a receptor, were silent. Our data demonstrate remarkable functional specificity in the interactions between different excitatory and inhibitory cortical neuronal subtypes, and suggest that it is the large recurrent interaction between pyramidal neurons and fast spiking interneurons that is responsible for the generation of persistent activity that characterizes the depolarized states of the cortex.

Noise promotes independent control of gamma oscillations and grid firing within recurrent attractor networks

PubMed Central

Solanka, Lukas; van Rossum, Mark CW; Nolan, Matthew F

2015-01-01

Neural computations underlying cognitive functions require calibration of the strength of excitatory and inhibitory synaptic connections and are associated with modulation of gamma frequency oscillations in network activity. However, principles relating gamma oscillations, synaptic strength and circuit computations are unclear. We address this in attractor network models that account for grid firing and theta-nested gamma oscillations in the medial entorhinal cortex. We show that moderate intrinsic noise massively increases the range of synaptic strengths supporting gamma oscillations and grid computation. With moderate noise, variation in excitatory or inhibitory synaptic strength tunes the amplitude and frequency of gamma activity without disrupting grid firing. This beneficial role for noise results from disruption of epileptic-like network states. Thus, moderate noise promotes independent control of multiplexed firing rate- and gamma-based computational mechanisms. Our results have implications for tuning of normal circuit function and for disorders associated with changes in gamma oscillations and synaptic strength. DOI: http://dx.doi.org/10.7554/eLife.06444.001 PMID:26146940

Dynamic Balance of Excitation and Inhibition in Human and Monkey Neocortex

NASA Astrophysics Data System (ADS)

Dehghani, Nima; Peyrache, Adrien; Telenczuk, Bartosz; Le van Quyen, Michel; Halgren, Eric; Cash, Sydney S.; Hatsopoulos, Nicholas G.; Destexhe, Alain

2016-03-01

Balance of excitation and inhibition is a fundamental feature of in vivo network activity and is important for its computations. However, its presence in the neocortex of higher mammals is not well established. We investigated the dynamics of excitation and inhibition using dense multielectrode recordings in humans and monkeys. We found that in all states of the wake-sleep cycle, excitatory and inhibitory ensembles are well balanced, and co-fluctuate with slight instantaneous deviations from perfect balance, mostly in slow-wave sleep. Remarkably, these correlated fluctuations are seen for many different temporal scales. The similarity of these computational features with a network model of self-generated balanced states suggests that such balanced activity is essentially generated by recurrent activity in the local network and is not due to external inputs. Finally, we find that this balance breaks down during seizures, where the temporal correlation of excitatory and inhibitory populations is disrupted. These results show that balanced activity is a feature of normal brain activity, and break down of the balance could be an important factor to define pathological states.

From cognitive networks to seizures: Stimulus evoked dynamics in a coupled cortical network

NASA Astrophysics Data System (ADS)

Lee, Jaejin; Ermentrout, Bard; Bodner, Mark

2013-12-01

Epilepsy is one of the most common neuropathologies worldwide. Seizures arising in epilepsy or in seizure disorders are characterized generally by uncontrolled spread of excitation and electrical activity to a limited region or even over the entire cortex. While it is generally accepted that abnormal excessive firing and synchronization of neuron populations lead to seizures, little is known about the precise mechanisms underlying human epileptic seizures, the mechanisms of transitions from normal to paroxysmal activity, or about how seizures spread. Further complication arises in that seizures do not occur with a single type of dynamics but as many different phenotypes and genotypes with a range of patterns, synchronous oscillations, and time courses. The concept of preventing, terminating, or modulating seizures and/or paroxysmal activity through stimulation of brain has also received considerable attention. The ability of such stimulation to prevent or modulate such pathological activity may depend on identifiable parameters. In this work, firing rate networks with inhibitory and excitatory populations were modeled. Network parameters were chosen to model normal working memory behaviors. Two different models of cognitive activity were developed. The first model consists of a single network corresponding to a local area of the brain. The second incorporates two networks connected through sparser recurrent excitatory connectivity with transmission delays ranging from approximately 3 ms within local populations to 15 ms between populations residing in different cortical areas. The effect of excitatory stimulation to activate working memory behavior through selective persistent activation of populations is examined in the models, and the conditions and transition mechanisms through which that selective activation breaks down producing spreading paroxysmal activity and seizure states are characterized. Specifically, we determine critical parameters and architectural changes that produce the different seizure dynamics in the networks. This provides possible mechanisms for seizure generation. Because seizures arise as attractors in a multi-state system, the system may possibly be returned to its baseline state through some particular stimulation. The ability of stimulation to terminate seizure dynamics in the local and distributed models is studied. We systematically examine when this may occur and the form of the stimulation necessary for the range of seizure dynamics. In both the local and distributed network models, termination is possible for all seizure types observed by stimulation possessing some particular configuration of spatial and temporal characteristics.

Beyond blow-up in excitatory integrate and fire neuronal networks: Refractory period and spontaneous activity.

PubMed

Cáceres, María J; Perthame, Benoît

2014-06-07

The Network Noisy Leaky Integrate and Fire equation is among the simplest model allowing for a self-consistent description of neural networks and gives a rule to determine the probability to find a neuron at the potential v. However, its mathematical structure is still poorly understood and, concerning its solutions, very few results are available. In the midst of them, a recent result shows blow-up in finite time for fully excitatory networks. The intuitive explanation is that each firing neuron induces a discharge of the others; thus increases the activity and consequently the discharge rate of the full network. In order to better understand the details of the phenomena and show that the equation is more complex and fruitful than expected, we analyze further the model. We extend the finite time blow-up result to the case when neurons, after firing, enter a refractory state for a given period of time. We also show that spontaneous activity may occur when, additionally, randomness is included on the firing potential VF in regimes where blow-up occurs for a fixed value of VF. Copyright © 2014 Elsevier Ltd. All rights reserved.

Dissociable effects of local inhibitory and excitatory theta-burst stimulation on large-scale brain dynamics

PubMed Central

Sale, Martin V.; Lord, Anton; Zalesky, Andrew; Breakspear, Michael; Mattingley, Jason B.

2015-01-01

Normal brain function depends on a dynamic balance between local specialization and large-scale integration. It remains unclear, however, how local changes in functionally specialized areas can influence integrated activity across larger brain networks. By combining transcranial magnetic stimulation with resting-state functional magnetic resonance imaging, we tested for changes in large-scale integration following the application of excitatory or inhibitory stimulation on the human motor cortex. After local inhibitory stimulation, regions encompassing the sensorimotor module concurrently increased their internal integration and decreased their communication with other modules of the brain. There were no such changes in modular dynamics following excitatory stimulation of the same area of motor cortex nor were there changes in the configuration and interactions between core brain hubs after excitatory or inhibitory stimulation of the same area. These results suggest the existence of selective mechanisms that integrate local changes in neural activity, while preserving ongoing communication between brain hubs. PMID:25717162

Assessing the Role of Inhibition in Stabilizing Neocortical Networks Requires Large-Scale Perturbation of the Inhibitory Population

PubMed Central

Mrsic-Flogel, Thomas D.

2017-01-01

Neurons within cortical microcircuits are interconnected with recurrent excitatory synaptic connections that are thought to amplify signals (Douglas and Martin, 2007), form selective subnetworks (Ko et al., 2011), and aid feature discrimination. Strong inhibition (Haider et al., 2013) counterbalances excitation, enabling sensory features to be sharpened and represented by sparse codes (Willmore et al., 2011). This balance between excitation and inhibition makes it difficult to assess the strength, or gain, of recurrent excitatory connections within cortical networks, which is key to understanding their operational regime and the computations that they perform. Networks that combine an unstable high-gain excitatory population with stabilizing inhibitory feedback are known as inhibition-stabilized networks (ISNs) (Tsodyks et al., 1997). Theoretical studies using reduced network models predict that ISNs produce paradoxical responses to perturbation, but experimental perturbations failed to find evidence for ISNs in cortex (Atallah et al., 2012). Here, we reexamined this question by investigating how cortical network models consisting of many neurons behave after perturbations and found that results obtained from reduced network models fail to predict responses to perturbations in more realistic networks. Our models predict that a large proportion of the inhibitory network must be perturbed to reliably detect an ISN regime robustly in cortex. We propose that wide-field optogenetic suppression of inhibition under promoters targeting a large fraction of inhibitory neurons may provide a perturbation of sufficient strength to reveal the operating regime of cortex. Our results suggest that detailed computational models of optogenetic perturbations are necessary to interpret the results of experimental paradigms. SIGNIFICANCE STATEMENT Many useful computational mechanisms proposed for cortex require local excitatory recurrence to be very strong, such that local inhibitory feedback is necessary to avoid epileptiform runaway activity (an “inhibition-stabilized network” or “ISN” regime). However, recent experimental results suggest that this regime may not exist in cortex. We simulated activity perturbations in cortical networks of increasing realism and found that, to detect ISN-like properties in cortex, large proportions of the inhibitory population must be perturbed. Current experimental methods for inhibitory perturbation are unlikely to satisfy this requirement, implying that existing experimental observations are inconclusive about the computational regime of cortex. Our results suggest that new experimental designs targeting a majority of inhibitory neurons may be able to resolve this question. PMID:29074575

Input dependent cell assembly dynamics in a model of the striatal medium spiny neuron network.

PubMed

Ponzi, Adam; Wickens, Jeff

2012-01-01

The striatal medium spiny neuron (MSN) network is sparsely connected with fairly weak GABAergic collaterals receiving an excitatory glutamatergic cortical projection. Peri-stimulus time histograms (PSTH) of MSN population response investigated in various experimental studies display strong firing rate modulations distributed throughout behavioral task epochs. In previous work we have shown by numerical simulation that sparse random networks of inhibitory spiking neurons with characteristics appropriate for UP state MSNs form cell assemblies which fire together coherently in sequences on long behaviorally relevant timescales when the network receives a fixed pattern of constant input excitation. Here we first extend that model to the case where cortical excitation is composed of many independent noisy Poisson processes and demonstrate that cell assembly dynamics is still observed when the input is sufficiently weak. However if cortical excitation strength is increased more regularly firing and completely quiescent cells are found, which depend on the cortical stimulation. Subsequently we further extend previous work to consider what happens when the excitatory input varies as it would when the animal is engaged in behavior. We investigate how sudden switches in excitation interact with network generated patterned activity. We show that sequences of cell assembly activations can be locked to the excitatory input sequence and outline the range of parameters where this behavior is shown. Model cell population PSTH display both stimulus and temporal specificity, with large population firing rate modulations locked to elapsed time from task events. Thus the random network can generate a large diversity of temporally evolving stimulus dependent responses even though the input is fixed between switches. We suggest the MSN network is well suited to the generation of such slow coherent task dependent response which could be utilized by the animal in behavior.

Input Dependent Cell Assembly Dynamics in a Model of the Striatal Medium Spiny Neuron Network

PubMed Central

Ponzi, Adam; Wickens, Jeff

2012-01-01

The striatal medium spiny neuron (MSN) network is sparsely connected with fairly weak GABAergic collaterals receiving an excitatory glutamatergic cortical projection. Peri-stimulus time histograms (PSTH) of MSN population response investigated in various experimental studies display strong firing rate modulations distributed throughout behavioral task epochs. In previous work we have shown by numerical simulation that sparse random networks of inhibitory spiking neurons with characteristics appropriate for UP state MSNs form cell assemblies which fire together coherently in sequences on long behaviorally relevant timescales when the network receives a fixed pattern of constant input excitation. Here we first extend that model to the case where cortical excitation is composed of many independent noisy Poisson processes and demonstrate that cell assembly dynamics is still observed when the input is sufficiently weak. However if cortical excitation strength is increased more regularly firing and completely quiescent cells are found, which depend on the cortical stimulation. Subsequently we further extend previous work to consider what happens when the excitatory input varies as it would when the animal is engaged in behavior. We investigate how sudden switches in excitation interact with network generated patterned activity. We show that sequences of cell assembly activations can be locked to the excitatory input sequence and outline the range of parameters where this behavior is shown. Model cell population PSTH display both stimulus and temporal specificity, with large population firing rate modulations locked to elapsed time from task events. Thus the random network can generate a large diversity of temporally evolving stimulus dependent responses even though the input is fixed between switches. We suggest the MSN network is well suited to the generation of such slow coherent task dependent response which could be utilized by the animal in behavior. PMID:22438838

Parallel processing by cortical inhibition enables context-dependent behavior.

PubMed

Kuchibhotla, Kishore V; Gill, Jonathan V; Lindsay, Grace W; Papadoyannis, Eleni S; Field, Rachel E; Sten, Tom A Hindmarsh; Miller, Kenneth D; Froemke, Robert C

2017-01-01

Physical features of sensory stimuli are fixed, but sensory perception is context dependent. The precise mechanisms that govern contextual modulation remain unknown. Here, we trained mice to switch between two contexts: passively listening to pure tones and performing a recognition task for the same stimuli. Two-photon imaging showed that many excitatory neurons in auditory cortex were suppressed during behavior, while some cells became more active. Whole-cell recordings showed that excitatory inputs were affected only modestly by context, but inhibition was more sensitive, with PV + , SOM + , and VIP + interneurons balancing inhibition and disinhibition within the network. Cholinergic modulation was involved in context switching, with cholinergic axons increasing activity during behavior and directly depolarizing inhibitory cells. Network modeling captured these findings, but only when modulation coincidently drove all three interneuron subtypes, ruling out either inhibition or disinhibition alone as sole mechanism for active engagement. Parallel processing of cholinergic modulation by cortical interneurons therefore enables context-dependent behavior.

Locally excitatory, globally inhibitory oscillator networks: theory and application to scene segmentation

NASA Astrophysics Data System (ADS)

Wang, DeLiang; Terman, David

1995-01-01

A novel class of locally excitatory, globally inhibitory oscillator networks (LEGION) is proposed and investigated analytically and by computer simulation. The model of each oscillator corresponds to a standard relaxation oscillator with two time scales. The network exhibits a mechanism of selective gating, whereby an oscillator jumping up to its active phase rapidly recruits the oscillators stimulated by the same pattern, while preventing other oscillators from jumping up. We show analytically that with the selective gating mechanism the network rapidly achieves both synchronization within blocks of oscillators that are stimulated by connected regions and desynchronization between different blocks. Computer simulations demonstrate LEGION's promising ability for segmenting multiple input patterns in real time. This model lays a physical foundation for the oscillatory correlation theory of feature binding, and may provide an effective computational framework for scene segmentation and figure/ground segregation.

Astrocytic GABA transporter activity modulates excitatory neurotransmission

PubMed Central

Boddum, Kim; Jensen, Thomas P.; Magloire, Vincent; Kristiansen, Uffe; Rusakov, Dmitri A.; Pavlov, Ivan; Walker, Matthew C.

2016-01-01

Astrocytes are ideally placed to detect and respond to network activity. They express ionotropic and metabotropic receptors, and can release gliotransmitters. Astrocytes also express transporters that regulate the extracellular concentration of neurotransmitters. Here we report a previously unrecognized role for the astrocytic GABA transporter, GAT-3. GAT-3 activity results in a rise in astrocytic Na+ concentrations and a consequent increase in astrocytic Ca2+ through Na+/Ca2+ exchange. This leads to the release of ATP/adenosine by astrocytes, which then diffusely inhibits neuronal glutamate release via activation of presynaptic adenosine receptors. Through this mechanism, increases in astrocytic GAT-3 activity due to GABA released from interneurons contribute to 'diffuse' heterosynaptic depression. This provides a mechanism for homeostatic regulation of excitatory transmission in the hippocampus. PMID:27886179

Local and global synchronization transitions induced by time delays in small-world neuronal networks with chemical synapses.

PubMed

Yu, Haitao; Wang, Jiang; Du, Jiwei; Deng, Bin; Wei, Xile

2015-02-01

Effects of time delay on the local and global synchronization in small-world neuronal networks with chemical synapses are investigated in this paper. Numerical results show that, for both excitatory and inhibitory coupling types, the information transmission delay can always induce synchronization transitions of spiking neurons in small-world networks. In particular, regions of in-phase and out-of-phase synchronization of connected neurons emerge intermittently as the synaptic delay increases. For excitatory coupling, all transitions to spiking synchronization occur approximately at integer multiples of the firing period of individual neurons; while for inhibitory coupling, these transitions appear at the odd multiples of the half of the firing period of neurons. More importantly, the local synchronization transition is more profound than the global synchronization transition, depending on the type of coupling synapse. For excitatory synapses, the local in-phase synchronization observed for some values of the delay also occur at a global scale; while for inhibitory ones, this synchronization, observed at the local scale, disappears at a global scale. Furthermore, the small-world structure can also affect the phase synchronization of neuronal networks. It is demonstrated that increasing the rewiring probability can always improve the global synchronization of neuronal activity, but has little effect on the local synchronization of neighboring neurons.

Context-Dependent Encoding of Fear and Extinction Memories in a Large-Scale Network Model of the Basal Amygdala

PubMed Central

Vlachos, Ioannis; Herry, Cyril; Lüthi, Andreas; Aertsen, Ad; Kumar, Arvind

2011-01-01

The basal nucleus of the amygdala (BA) is involved in the formation of context-dependent conditioned fear and extinction memories. To understand the underlying neural mechanisms we developed a large-scale neuron network model of the BA, composed of excitatory and inhibitory leaky-integrate-and-fire neurons. Excitatory BA neurons received conditioned stimulus (CS)-related input from the adjacent lateral nucleus (LA) and contextual input from the hippocampus or medial prefrontal cortex (mPFC). We implemented a plasticity mechanism according to which CS and contextual synapses were potentiated if CS and contextual inputs temporally coincided on the afferents of the excitatory neurons. Our simulations revealed a differential recruitment of two distinct subpopulations of BA neurons during conditioning and extinction, mimicking the activation of experimentally observed cell populations. We propose that these two subgroups encode contextual specificity of fear and extinction memories, respectively. Mutual competition between them, mediated by feedback inhibition and driven by contextual inputs, regulates the activity in the central amygdala (CEA) thereby controlling amygdala output and fear behavior. The model makes multiple testable predictions that may advance our understanding of fear and extinction memories. PMID:21437238

The influence of single bursts vs. single spikes at excitatory dendrodendritic synapses

PubMed Central

Masurkar, Arjun V.; Chen, Wei R.

2015-01-01

The synchronization of neuronal activity is thought to enhance information processing. There is much evidence supporting rhythmically bursting external tufted cells (ETCs) of the rodent olfactory bulb glomeruli coordinating the activation of glomerular interneurons and mitral cells via dendrodendritic excitation. However, as bursting has variable significance at axodendritic cortical synapses, it is not clear if ETC bursting imparts a specific functional advantage over the preliminary spike in dendrodendritic synaptic networks. To answer this question, we investigated the influence of single ETC bursts and spikes with the in-vitro rat olfactory bulb preparation at different levels of processing, via calcium imaging of presynaptic ETC dendrites, dual electrical recording of ETC–interneuron synaptic pairs, and multicellular calcium imaging of ETC-induced population activity. Our findings supported single ETC bursts, vs. single spikes, driving robust presynaptic calcium signaling, which in turn was associated with profound extension of the initial monosynaptic spike-driven dendrodendritic excitatory postsynaptic potential. This extension could be driven by either the spike-dependent or spike-independent components of the burst. At the population level, burst-induced excitation was more widespread and reliable compared with single spikes. This further supports the ETC network, in part due to a functional advantage of bursting at excitatory dendrodendritic synapses, coordinating synchronous activity at behaviorally relevant frequencies related to odor processing in vivo. PMID:22277089

Excitatory and inhibitory STDP jointly tune feedforward neural circuits to selectively propagate correlated spiking activity

PubMed Central

Kleberg, Florence I.; Fukai, Tomoki; Gilson, Matthieu

2014-01-01

Spike-timing-dependent plasticity (STDP) has been well established between excitatory neurons and several computational functions have been proposed in various neural systems. Despite some recent efforts, however, there is a significant lack of functional understanding of inhibitory STDP (iSTDP) and its interplay with excitatory STDP (eSTDP). Here, we demonstrate by analytical and numerical methods that iSTDP contributes crucially to the balance of excitatory and inhibitory weights for the selection of a specific signaling pathway among other pathways in a feedforward circuit. This pathway selection is based on the high sensitivity of STDP to correlations in spike times, which complements a recent proposal for the role of iSTDP in firing-rate based selection. Our model predicts that asymmetric anti-Hebbian iSTDP exceeds asymmetric Hebbian iSTDP for supporting pathway-specific balance, which we show is useful for propagating transient neuronal responses. Furthermore, we demonstrate how STDPs at excitatory–excitatory, excitatory–inhibitory, and inhibitory–excitatory synapses cooperate to improve the pathway selection. We propose that iSTDP is crucial for shaping the network structure that achieves efficient processing of synchronous spikes. PMID:24847242

Mechanisms underlying a thalamocortical transformation during active tactile sensation

PubMed Central

Gutnisky, Diego Adrian; Yu, Jianing; Hires, Samuel Andrew; To, Minh-Son; Svoboda, Karel

2017-01-01

During active somatosensation, neural signals expected from movement of the sensors are suppressed in the cortex, whereas information related to touch is enhanced. This tactile suppression underlies low-noise encoding of relevant tactile features and the brain’s ability to make fine tactile discriminations. Layer (L) 4 excitatory neurons in the barrel cortex, the major target of the somatosensory thalamus (VPM), respond to touch, but have low spike rates and low sensitivity to the movement of whiskers. Most neurons in VPM respond to touch and also show an increase in spike rate with whisker movement. Therefore, signals related to self-movement are suppressed in L4. Fast-spiking (FS) interneurons in L4 show similar dynamics to VPM neurons. Stimulation of halorhodopsin in FS interneurons causes a reduction in FS neuron activity and an increase in L4 excitatory neuron activity. This decrease of activity of L4 FS neurons contradicts the "paradoxical effect" predicted in networks stabilized by inhibition and in strongly-coupled networks. To explain these observations, we constructed a model of the L4 circuit, with connectivity constrained by in vitro measurements. The model explores the various synaptic conductance strengths for which L4 FS neurons actively suppress baseline and movement-related activity in layer 4 excitatory neurons. Feedforward inhibition, in concert with recurrent intracortical circuitry, produces tactile suppression. Synaptic delays in feedforward inhibition allow transmission of temporally brief volleys of activity associated with touch. Our model provides a mechanistic explanation of a behavior-related computation implemented by the thalamocortical circuit. PMID:28591219

Dynamics of networks of excitatory and inhibitory neurons in response to time-dependent inputs.

PubMed

Ledoux, Erwan; Brunel, Nicolas

2011-01-01

We investigate the dynamics of recurrent networks of excitatory (E) and inhibitory (I) neurons in the presence of time-dependent inputs. The dynamics is characterized by the network dynamical transfer function, i.e., how the population firing rate is modulated by sinusoidal inputs at arbitrary frequencies. Two types of networks are studied and compared: (i) a Wilson-Cowan type firing rate model; and (ii) a fully connected network of leaky integrate-and-fire (LIF) neurons, in a strong noise regime. We first characterize the region of stability of the "asynchronous state" (a state in which population activity is constant in time when external inputs are constant) in the space of parameters characterizing the connectivity of the network. We then systematically characterize the qualitative behaviors of the dynamical transfer function, as a function of the connectivity. We find that the transfer function can be either low-pass, or with a single or double resonance, depending on the connection strengths and synaptic time constants. Resonances appear when the system is close to Hopf bifurcations, that can be induced by two separate mechanisms: the I-I connectivity and the E-I connectivity. Double resonances can appear when excitatory delays are larger than inhibitory delays, due to the fact that two distinct instabilities exist with a finite gap between the corresponding frequencies. In networks of LIF neurons, changes in external inputs and external noise are shown to be able to change qualitatively the network transfer function. Firing rate models are shown to exhibit the same diversity of transfer functions as the LIF network, provided delays are present. They can also exhibit input-dependent changes of the transfer function, provided a suitable static non-linearity is incorporated.

Glutamate-Bound NMDARs Arising from In Vivo-like Network Activity Extend Spatio-temporal Integration in a L5 Cortical Pyramidal Cell Model

PubMed Central

Farinella, Matteo; Ruedt, Daniel T.; Gleeson, Padraig; Lanore, Frederic; Silver, R. Angus

2014-01-01

In vivo, cortical pyramidal cells are bombarded by asynchronous synaptic input arising from ongoing network activity. However, little is known about how such ‘background’ synaptic input interacts with nonlinear dendritic mechanisms. We have modified an existing model of a layer 5 (L5) pyramidal cell to explore how dendritic integration in the apical dendritic tuft could be altered by the levels of network activity observed in vivo. Here we show that asynchronous background excitatory input increases neuronal gain and extends both temporal and spatial integration of stimulus-evoked synaptic input onto the dendritic tuft. Addition of fast and slow inhibitory synaptic conductances, with properties similar to those from dendritic targeting interneurons, that provided a ‘balanced’ background configuration, partially counteracted these effects, suggesting that inhibition can tune spatio-temporal integration in the tuft. Excitatory background input lowered the threshold for NMDA receptor-mediated dendritic spikes, extended their duration and increased the probability of additional regenerative events occurring in neighbouring branches. These effects were also observed in a passive model where all the non-synaptic voltage-gated conductances were removed. Our results show that glutamate-bound NMDA receptors arising from ongoing network activity can provide a powerful spatially distributed nonlinear dendritic conductance. This may enable L5 pyramidal cells to change their integrative properties as a function of local network activity, potentially allowing both clustered and spatially distributed synaptic inputs to be integrated over extended timescales. PMID:24763087

Excitatory motor neurons are local oscillators for backward locomotion

PubMed Central

Guan, Sihui Asuka; Fouad, Anthony D; Meng, Jun; Kawano, Taizo; Huang, Yung-Chi; Li, Yi; Alcaire, Salvador; Hung, Wesley; Lu, Yangning; Qi, Yingchuan Billy; Jin, Yishi; Alkema, Mark; Fang-Yen, Christopher

2018-01-01

Cell- or network-driven oscillators underlie motor rhythmicity. The identity of C. elegans oscillators remains unknown. Through cell ablation, electrophysiology, and calcium imaging, we show: (1) forward and backward locomotion is driven by different oscillators; (2) the cholinergic and excitatory A-class motor neurons exhibit intrinsic and oscillatory activity that is sufficient to drive backward locomotion in the absence of premotor interneurons; (3) the UNC-2 P/Q/N high-voltage-activated calcium current underlies A motor neuron’s oscillation; (4) descending premotor interneurons AVA, via an evolutionarily conserved, mixed gap junction and chemical synapse configuration, exert state-dependent inhibition and potentiation of A motor neuron’s intrinsic activity to regulate backward locomotion. Thus, motor neurons themselves derive rhythms, which are dually regulated by the descending interneurons to control the reversal motor state. These and previous findings exemplify compression: essential circuit properties are conserved but executed by fewer numbers and layers of neurons in a small locomotor network. PMID:29360035

Excitatory motor neurons are local oscillators for backward locomotion.

PubMed

Gao, Shangbang; Guan, Sihui Asuka; Fouad, Anthony D; Meng, Jun; Kawano, Taizo; Huang, Yung-Chi; Li, Yi; Alcaire, Salvador; Hung, Wesley; Lu, Yangning; Qi, Yingchuan Billy; Jin, Yishi; Alkema, Mark; Fang-Yen, Christopher; Zhen, Mei

2018-01-23

Cell- or network-driven oscillators underlie motor rhythmicity. The identity of C. elegans oscillators remains unknown. Through cell ablation, electrophysiology, and calcium imaging, we show: (1) forward and backward locomotion is driven by different oscillators; (2) the cholinergic and excitatory A-class motor neurons exhibit intrinsic and oscillatory activity that is sufficient to drive backward locomotion in the absence of premotor interneurons; (3) the UNC-2 P/Q/N high-voltage-activated calcium current underlies A motor neuron's oscillation; (4) descending premotor interneurons AVA, via an evolutionarily conserved, mixed gap junction and chemical synapse configuration, exert state-dependent inhibition and potentiation of A motor neuron's intrinsic activity to regulate backward locomotion. Thus, motor neurons themselves derive rhythms, which are dually regulated by the descending interneurons to control the reversal motor state. These and previous findings exemplify compression: essential circuit properties are conserved but executed by fewer numbers and layers of neurons in a small locomotor network. © 2017, Gao et al.

Excitation-neurogenesis coupling in adult neural stem/progenitor cells.

PubMed

Deisseroth, Karl; Singla, Sheela; Toda, Hiroki; Monje, Michelle; Palmer, Theo D; Malenka, Robert C

2004-05-27

A wide variety of in vivo manipulations influence neurogenesis in the adult hippocampus. It is not known, however, if adult neural stem/progenitor cells (NPCs) can intrinsically sense excitatory neural activity and thereby implement a direct coupling between excitation and neurogenesis. Moreover, the theoretical significance of activity-dependent neurogenesis in hippocampal-type memory processing networks has not been explored. Here we demonstrate that excitatory stimuli act directly on adult hippocampal NPCs to favor neuron production. The excitation is sensed via Ca(v)1.2/1.3 (L-type) Ca(2+) channels and NMDA receptors on the proliferating precursors. Excitation through this pathway acts to inhibit expression of the glial fate genes Hes1 and Id2 and increase expression of NeuroD, a positive regulator of neuronal differentiation. These activity-sensing properties of the adult NPCs, when applied as an "excitation-neurogenesis coupling rule" within a Hebbian neural network, predict significant advantages for both the temporary storage and the clearance of memories.

Downstream effects of hippocampal sharp wave ripple oscillations on medial entorhinal cortex layer V neurons in vitro.

PubMed

Roth, Fabian C; Beyer, Katinka M; Both, Martin; Draguhn, Andreas; Egorov, Alexei V

2016-12-01

The entorhinal cortex (EC) is a critical component of the medial temporal lobe (MTL) memory system. Local networks within the MTL express a variety of state-dependent network oscillations that are believed to organize neuronal activity during memory formation. The peculiar pattern of sharp wave-ripple complexes (SPW-R) entrains neurons by a very fast oscillation at ∼200 Hz in the hippocampal areas CA3 and CA1 and then propagates through the "output loop" into the EC. The precise mechanisms of SPW-R propagation and the resulting cellular input patterns in the mEC are, however, largely unknown. We therefore investigated the activity of layer V (LV) principal neurons of the medial EC (mEC) during SPW-R oscillations in horizontal mouse brain slices. Intracellular recordings in the mEC were combined with extracellular monitoring of propagating network activity. SPW-R in CA1 were regularly followed by negative field potential deflections in the mEC. Propagation of SPW-R activity from CA1 to the mEC was mostly monosynaptic and excitatory, such that synaptic input to mEC LV neurons directly reflected unit activity in CA1. Comparison with propagating network activity from CA3 to CA1 revealed a similar role of excitatory long-range connections for both regions. However, SPW-R-induced activity in CA1 involved strong recruitment of rhythmic synaptic inhibition and corresponding fast field oscillations, in contrast to the mEC. These differences between features of propagating SPW-R emphasize the differential processing of network activity by each local network of the hippocampal output loop. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

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.

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

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.

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.

Resting-state hemodynamics are spatiotemporally coupled to synchronized and symmetric neural activity in excitatory neurons.

PubMed

Ma, Ying; Shaik, Mohammed A; Kozberg, Mariel G; Kim, Sharon H; Portes, Jacob P; Timerman, Dmitriy; Hillman, Elizabeth M C

2016-12-27

Brain hemodynamics serve as a proxy for neural activity in a range of noninvasive neuroimaging techniques including functional magnetic resonance imaging (fMRI). In resting-state fMRI, hemodynamic fluctuations have been found to exhibit patterns of bilateral synchrony, with correlated regions inferred to have functional connectivity. However, the relationship between resting-state hemodynamics and underlying neural activity has not been well established, making the neural underpinnings of functional connectivity networks unclear. In this study, neural activity and hemodynamics were recorded simultaneously over the bilateral cortex of awake and anesthetized Thy1-GCaMP mice using wide-field optical mapping. Neural activity was visualized via selective expression of the calcium-sensitive fluorophore GCaMP in layer 2/3 and 5 excitatory neurons. Characteristic patterns of resting-state hemodynamics were accompanied by more rapidly changing bilateral patterns of resting-state neural activity. Spatiotemporal hemodynamics could be modeled by convolving this neural activity with hemodynamic response functions derived through both deconvolution and gamma-variate fitting. Simultaneous imaging and electrophysiology confirmed that Thy1-GCaMP signals are well-predicted by multiunit activity. Neurovascular coupling between resting-state neural activity and hemodynamics was robust and fast in awake animals, whereas coupling in urethane-anesthetized animals was slower, and in some cases included lower-frequency (<0.04 Hz) hemodynamic fluctuations that were not well-predicted by local Thy1-GCaMP recordings. These results support that resting-state hemodynamics in the awake and anesthetized brain are coupled to underlying patterns of excitatory neural activity. The patterns of bilaterally-symmetric spontaneous neural activity revealed by wide-field Thy1-GCaMP imaging may depict the neural foundation of functional connectivity networks detected in resting-state fMRI.

Resting-state hemodynamics are spatiotemporally coupled to synchronized and symmetric neural activity in excitatory neurons

PubMed Central

Ma, Ying; Shaik, Mohammed A.; Kozberg, Mariel G.; Portes, Jacob P.; Timerman, Dmitriy

2016-01-01

Brain hemodynamics serve as a proxy for neural activity in a range of noninvasive neuroimaging techniques including functional magnetic resonance imaging (fMRI). In resting-state fMRI, hemodynamic fluctuations have been found to exhibit patterns of bilateral synchrony, with correlated regions inferred to have functional connectivity. However, the relationship between resting-state hemodynamics and underlying neural activity has not been well established, making the neural underpinnings of functional connectivity networks unclear. In this study, neural activity and hemodynamics were recorded simultaneously over the bilateral cortex of awake and anesthetized Thy1-GCaMP mice using wide-field optical mapping. Neural activity was visualized via selective expression of the calcium-sensitive fluorophore GCaMP in layer 2/3 and 5 excitatory neurons. Characteristic patterns of resting-state hemodynamics were accompanied by more rapidly changing bilateral patterns of resting-state neural activity. Spatiotemporal hemodynamics could be modeled by convolving this neural activity with hemodynamic response functions derived through both deconvolution and gamma-variate fitting. Simultaneous imaging and electrophysiology confirmed that Thy1-GCaMP signals are well-predicted by multiunit activity. Neurovascular coupling between resting-state neural activity and hemodynamics was robust and fast in awake animals, whereas coupling in urethane-anesthetized animals was slower, and in some cases included lower-frequency (<0.04 Hz) hemodynamic fluctuations that were not well-predicted by local Thy1-GCaMP recordings. These results support that resting-state hemodynamics in the awake and anesthetized brain are coupled to underlying patterns of excitatory neural activity. The patterns of bilaterally-symmetric spontaneous neural activity revealed by wide-field Thy1-GCaMP imaging may depict the neural foundation of functional connectivity networks detected in resting-state fMRI. PMID:27974609

Parvalbumin interneuron mediated feedforward inhibition controls signal output in the deep layers of the perirhinal‐entorhinal cortex

PubMed Central

Willems, Janske G. P.; Wadman, Wytse J.

2018-01-01

Abstract The perirhinal (PER) and lateral entorhinal (LEC) cortex form an anatomical link between the neocortex and the hippocampus. However, neocortical activity is transmitted through the PER and LEC to the hippocampus with a low probability, suggesting the involvement of the inhibitory network. This study explored the role of interneuron mediated inhibition, activated by electrical stimulation in the agranular insular cortex (AiP), in the deep layers of the PER and LEC. Activated synaptic input by AiP stimulation rarely evoked action potentials in the PER‐LEC deep layer excitatory principal neurons, most probably because the evoked synaptic response consisted of a small excitatory and large inhibitory conductance. Furthermore, parvalbumin positive (PV) interneurons—a subset of interneurons projecting onto the axo‐somatic region of principal neurons—received synaptic input earlier than principal neurons, suggesting recruitment of feedforward inhibition. This synaptic input in PV interneurons evoked varying trains of action potentials, explaining the fast rising, long lasting synaptic inhibition received by deep layer principal neurons. Altogether, the excitatory input from the AiP onto deep layer principal neurons is overruled by strong feedforward inhibition. PV interneurons, with their fast, extensive stimulus‐evoked firing, are able to deliver this fast evoked inhibition in principal neurons. This indicates an essential role for PV interneurons in the gating mechanism of the PER‐LEC network. PMID:29341361

Data-driven inference of network connectivity for modeling the dynamics of neural codes in the insect antennal lobe

PubMed Central

Shlizerman, Eli; Riffell, Jeffrey A.; Kutz, J. Nathan

2014-01-01

The antennal lobe (AL), olfactory processing center in insects, is able to process stimuli into distinct neural activity patterns, called olfactory neural codes. To model their dynamics we perform multichannel recordings from the projection neurons in the AL driven by different odorants. We then derive a dynamic neuronal network from the electrophysiological data. The network consists of lateral-inhibitory neurons and excitatory neurons (modeled as firing-rate units), and is capable of producing unique olfactory neural codes for the tested odorants. To construct the network, we (1) design a projection, an odor space, for the neural recording from the AL, which discriminates between distinct odorants trajectories (2) characterize scent recognition, i.e., decision-making based on olfactory signals and (3) infer the wiring of the neural circuit, the connectome of the AL. We show that the constructed model is consistent with biological observations, such as contrast enhancement and robustness to noise. The study suggests a data-driven approach to answer a key biological question in identifying how lateral inhibitory neurons can be wired to excitatory neurons to permit robust activity patterns. PMID:25165442

Homeostatic Scaling of Excitability in Recurrent Neural Networks

PubMed Central

Remme, Michiel W. H.; Wadman, Wytse J.

2012-01-01

Neurons adjust their intrinsic excitability when experiencing a persistent change in synaptic drive. This process can prevent neural activity from moving into either a quiescent state or a saturated state in the face of ongoing plasticity, and is thought to promote stability of the network in which neurons reside. However, most neurons are embedded in recurrent networks, which require a delicate balance between excitation and inhibition to maintain network stability. This balance could be disrupted when neurons independently adjust their intrinsic excitability. Here, we study the functioning of activity-dependent homeostatic scaling of intrinsic excitability (HSE) in a recurrent neural network. Using both simulations of a recurrent network consisting of excitatory and inhibitory neurons that implement HSE, and a mean-field description of adapting excitatory and inhibitory populations, we show that the stability of such adapting networks critically depends on the relationship between the adaptation time scales of both neuron populations. In a stable adapting network, HSE can keep all neurons functioning within their dynamic range, while the network is undergoing several (patho)physiologically relevant types of plasticity, such as persistent changes in external drive, changes in connection strengths, or the loss of inhibitory cells from the network. However, HSE cannot prevent the unstable network dynamics that result when, due to such plasticity, recurrent excitation in the network becomes too strong compared to feedback inhibition. This suggests that keeping a neural network in a stable and functional state requires the coordination of distinct homeostatic mechanisms that operate not only by adjusting neural excitability, but also by controlling network connectivity. PMID:22570604

Associative plasticity in intracortical inhibitory circuits in human motor cortex.

PubMed

Russmann, Heike; Lamy, Jean-Charles; Shamim, Ejaz A; Meunier, Sabine; Hallett, Mark

2009-06-01

Paired associative stimulation (PAS) is a transcranial magnetic stimulation technique inducing Hebbian-like synaptic plasticity in the human motor cortex (M1). PAS is produced by repetitive pairing of a peripheral nerve shock and a transcranial magnetic stimulus (TMS). Its effect is assessed by a change in size of a motor evoked response (MEP). MEP size results from excitatory and inhibitory influences exerted on cortical pyramidal cells, but no robust effects on inhibitory networks have been demonstrated so far. In 38 healthy volunteers, we assessed whether a PAS intervention influences three intracortical inhibitory circuits: short (SICI) and long (LICI) intracortical inhibitions reflecting activity of GABA(A) and GABA(B) interneurons, respectively, and long afferent inhibition (LAI) reflecting activity of somatosensory inputs. After PAS, MEP sizes, LICI and LAI levels were significantly changed while changes of SICI were inconsistent. The changes in LICI and LAI lasted 45 min after PAS. Their direction depended on the delay between the arrival time of the afferent volley at the cortex and the TMS-induced cortical activation during the PAS. PAS influences inhibitory circuits in M1. PAS paradigms can demonstrate Hebbian-like plasticity at selected inhibitory networks as well as excitatory networks.

Frequency-selective augmenting responses by short-term synaptic depression in cat neocortex

PubMed Central

Houweling, Arthur R; Bazhenov, Maxim; Timofeev, Igor; Grenier, François; Steriade, Mircea; Sejnowski, Terrence J

2002-01-01

Thalamic stimulation at frequencies between 5 and 15 Hz elicits incremental or ‘augmenting’ cortical responses. Augmenting responses can also be evoked in cortical slices and isolated cortical slabs in vivo. Here we show that a realistic network model of cortical pyramidal cells and interneurones including short-term plasticity of inhibitory and excitatory synapses replicates the main features of augmenting responses as obtained in isolated slabs in vivo. Repetitive stimulation of synaptic inputs at frequencies around 10 Hz produced postsynaptic potentials that grew in size and carried an increasing number of action potentials resulting from the depression of inhibitory synaptic currents. Frequency selectivity was obtained through the relatively weak depression of inhibitory synapses at low frequencies, and strong depression of excitatory synapses together with activation of a calcium-activated potassium current at high frequencies. This network resonance is a consequence of short-term synaptic plasticity in a network of neurones without intrinsic resonances. These results suggest that short-term plasticity of cortical synapses could shape the dynamics of synchronized oscillations in the brain. PMID:12122156

The influence of single bursts versus single spikes at excitatory dendrodendritic synapses.

PubMed

Masurkar, Arjun V; Chen, Wei R

2012-02-01

The synchronization of neuronal activity is thought to enhance information processing. There is much evidence supporting rhythmically bursting external tufted cells (ETCs) of the rodent olfactory bulb glomeruli coordinating the activation of glomerular interneurons and mitral cells via dendrodendritic excitation. However, as bursting has variable significance at axodendritic cortical synapses, it is not clear if ETC bursting imparts a specific functional advantage over the preliminary spike in dendrodendritic synaptic networks. To answer this question, we investigated the influence of single ETC bursts and spikes with the in vitro rat olfactory bulb preparation at different levels of processing, via calcium imaging of presynaptic ETC dendrites, dual electrical recording of ETC -interneuron synaptic pairs, and multicellular calcium imaging of ETC-induced population activity. Our findings supported single ETC bursts, versus single spikes, driving robust presynaptic calcium signaling, which in turn was associated with profound extension of the initial monosynaptic spike-driven dendrodendritic excitatory postsynaptic potential. This extension could be driven by either the spike-dependent or spike-independent components of the burst. At the population level, burst-induced excitation was more widespread and reliable compared with single spikes. This further supports the ETC network, in part due to a functional advantage of bursting at excitatory dendrodendritic synapses, coordinating synchronous activity at behaviorally relevant frequencies related to odor processing in vivo. © 2012 The Authors. European Journal of Neuroscience © 2012 Federation of European Neuroscience Societies and Blackwell Publishing Ltd.

Chaos and Correlated Avalanches in Excitatory Neural Networks with Synaptic Plasticity

NASA Astrophysics Data System (ADS)

Pittorino, Fabrizio; Ibáñez-Berganza, Miguel; di Volo, Matteo; Vezzani, Alessandro; Burioni, Raffaella

2017-03-01

A collective chaotic phase with power law scaling of activity events is observed in a disordered mean field network of purely excitatory leaky integrate-and-fire neurons with short-term synaptic plasticity. The dynamical phase diagram exhibits two transitions from quasisynchronous and asynchronous regimes to the nontrivial, collective, bursty regime with avalanches. In the homogeneous case without disorder, the system synchronizes and the bursty behavior is reflected into a period doubling transition to chaos for a two dimensional discrete map. Numerical simulations show that the bursty chaotic phase with avalanches exhibits a spontaneous emergence of persistent time correlations and enhanced Kolmogorov complexity. Our analysis reveals a mechanism for the generation of irregular avalanches that emerges from the combination of disorder and deterministic underlying chaotic dynamics.

Impossibility of asymptotic synchronization for pulse-coupled oscillators with delayed excitatory coupling.

PubMed

Wu, Wei; Chen, Tianping

2009-12-01

Fireflies, as one of the most spectacular examples of synchronization in nature, have been investigated widely. In 1990, Mirollo and Strogatz proposed a pulse-coupled oscillator model to explain the synchronization of South East Asian fireflies (Pteroptyx malaccae). However, transmission delays were not considered in their model. In fact, when transmission delays are introduced, the dynamic behaviors of pulse-coupled networks change a lot. In this paper, pulse-coupled oscillator networks with delayed excitatory coupling are studied. A concept of synchronization, named weak asymptotic synchronization, which is weaker than asymptotic synchronization, is proposed. We prove that for pulse-coupled oscillator networks with delayed excitatory coupling, weak asymptotic synchronization cannot occur.

GABAergic neurons in ferret visual cortex participate in functionally specific networks

PubMed Central

Wilson, Daniel E.; Smith, Gordon B.; Jacob, Amanda; Walker, Theo; Dimidschstein, Jordane; Fishell, Gord J.; Fitzpatrick, David

2017-01-01

Summary Functional circuits in the visual cortex require the coordinated activity of excitatory and inhibitory neurons. Molecular genetic approaches in the mouse have led to the ‘local nonspecific pooling principle’ of inhibitory connectivity, in which inhibitory neurons are untuned for stimulus features due to the random pooling of local inputs. However, it remains unclear whether this principle generalizes to species with a columnar organization of feature selectivity such as carnivores, primates, and humans. Here we use virally-mediated GABAergic-specific GCaMP6f expression to demonstrate that inhibitory neurons in ferret visual cortex respond robustly and selectively to oriented stimuli. We find that the tuning of inhibitory neurons is inconsistent with the local non-specific pooling of excitatory inputs, and that inhibitory neurons exhibit orientation-specific noise correlations with local and distant excitatory neurons. These findings challenge the generality of the non-specific pooling principle for inhibitory neurons, suggesting different rules for functional excitatory-inhibitory interactions in non-murine species. PMID:28279352

Continuous attractor network models of grid cell firing based on excitatory–inhibitory interactions

PubMed Central

Shipston‐Sharman, Oliver; Solanka, Lukas

2016-01-01

Abstract Neurons in the medial entorhinal cortex encode location through spatial firing fields that have a grid‐like organisation. The challenge of identifying mechanisms for grid firing has been addressed through experimental and theoretical investigations of medial entorhinal circuits. Here, we discuss evidence for continuous attractor network models that account for grid firing by synaptic interactions between excitatory and inhibitory cells. These models assume that grid‐like firing patterns are the result of computation of location from velocity inputs, with additional spatial input required to oppose drift in the attractor state. We focus on properties of continuous attractor networks that are revealed by explicitly considering excitatory and inhibitory neurons, their connectivity and their membrane potential dynamics. Models at this level of detail can account for theta‐nested gamma oscillations as well as grid firing, predict spatial firing of interneurons as well as excitatory cells, show how gamma oscillations can be modulated independently from spatial computations, reveal critical roles for neuronal noise, and demonstrate that only a subset of excitatory cells in a network need have grid‐like firing fields. Evaluating experimental data against predictions from detailed network models will be important for establishing the mechanisms mediating grid firing. PMID:27870120

Training Excitatory-Inhibitory Recurrent Neural Networks for Cognitive Tasks: A Simple and Flexible Framework

PubMed Central

Wang, Xiao-Jing

2016-01-01

The ability to simultaneously record from large numbers of neurons in behaving animals has ushered in a new era for the study of the neural circuit mechanisms underlying cognitive functions. One promising approach to uncovering the dynamical and computational principles governing population responses is to analyze model recurrent neural networks (RNNs) that have been optimized to perform the same tasks as behaving animals. Because the optimization of network parameters specifies the desired output but not the manner in which to achieve this output, “trained” networks serve as a source of mechanistic hypotheses and a testing ground for data analyses that link neural computation to behavior. Complete access to the activity and connectivity of the circuit, and the ability to manipulate them arbitrarily, make trained networks a convenient proxy for biological circuits and a valuable platform for theoretical investigation. However, existing RNNs lack basic biological features such as the distinction between excitatory and inhibitory units (Dale’s principle), which are essential if RNNs are to provide insights into the operation of biological circuits. Moreover, trained networks can achieve the same behavioral performance but differ substantially in their structure and dynamics, highlighting the need for a simple and flexible framework for the exploratory training of RNNs. Here, we describe a framework for gradient descent-based training of excitatory-inhibitory RNNs that can incorporate a variety of biological knowledge. We provide an implementation based on the machine learning library Theano, whose automatic differentiation capabilities facilitate modifications and extensions. We validate this framework by applying it to well-known experimental paradigms such as perceptual decision-making, context-dependent integration, multisensory integration, parametric working memory, and motor sequence generation. Our results demonstrate the wide range of neural activity patterns and behavior that can be modeled, and suggest a unified setting in which diverse cognitive computations and mechanisms can be studied. PMID:26928718

Neural Sequence Generation Using Spatiotemporal Patterns of Inhibition.

PubMed

Cannon, Jonathan; Kopell, Nancy; Gardner, Timothy; Markowitz, Jeffrey

2015-11-01

Stereotyped sequences of neural activity are thought to underlie reproducible behaviors and cognitive processes ranging from memory recall to arm movement. One of the most prominent theoretical models of neural sequence generation is the synfire chain, in which pulses of synchronized spiking activity propagate robustly along a chain of cells connected by highly redundant feedforward excitation. But recent experimental observations in the avian song production pathway during song generation have shown excitatory activity interacting strongly with the firing patterns of inhibitory neurons, suggesting a process of sequence generation more complex than feedforward excitation. Here we propose a model of sequence generation inspired by these observations in which a pulse travels along a spatially recurrent excitatory chain, passing repeatedly through zones of local feedback inhibition. In this model, synchrony and robust timing are maintained not through redundant excitatory connections, but rather through the interaction between the pulse and the spatiotemporal pattern of inhibition that it creates as it circulates the network. These results suggest that spatially and temporally structured inhibition may play a key role in sequence generation.

Dynamics of neuromodulatory feedback determines frequency modulation in a reduced respiratory network: a computational study.

PubMed

Toporikova, Natalia; Butera, Robert J

2013-02-01

Neuromodulators, such as amines and neuropeptides, alter the activity of neurons and neuronal networks. In this work, we investigate how neuromodulators, which activate G(q)-protein second messenger systems, can modulate the bursting frequency of neurons in a critical portion of the respiratory neural network, the pre-Bötzinger complex (preBötC). These neurons are a vital part of the ponto-medullary neuronal network, which generates a stable respiratory rhythm whose frequency is regulated by neuromodulator release from the nearby Raphe nucleus. Using a simulated 50-cell network of excitatory preBötC neurons with a heterogeneous distribution of persistent sodium conductance and Ca(2+), we determined conditions for frequency modulation in such a network by simulating interaction between Raphe and preBötC nuclei. We found that the positive feedback between the Raphe excitability and preBötC activity induces frequency modulation in the preBötC neurons. In addition, the frequency of the respiratory rhythm can be regulated via phasic release of excitatory neuromodulators from the Raphe nucleus. We predict that the application of a G(q) antagonist will eliminate this frequency modulation by the Raphe and keep the network frequency constant and low. In contrast, application of a G(q) agonist will result in a high frequency for all levels of Raphe stimulation. Our modeling results also suggest that high [K(+)] requirement in respiratory brain slice experiments may serve as a compensatory mechanism for low neuromodulatory tone. Copyright © 2012 Elsevier B.V. All rights reserved.

Stability and instability of a neuron network with excitatory and inhibitory small-world connections.

PubMed

Yu, Dongyuan; Xu, Xu; Zhou, Jing; Li, Eric

2017-05-01

This study considers a delayed neural network with excitatory and inhibitory shortcuts. The global stability of the trivial equilibrium is investigated based on Lyapunov's direct method and the delay-dependent criteria are obtained. It is shown that both the excitatory and inhibitory shortcuts decrease the stability interval, but a time delay can be employed as a global stabilizer. In addition, we analyze the bounds of the eigenvalues of the adjacent matrix using matrix perturbation theory and then obtain the generalized sufficient conditions for local stability. The possibility of small inhibitory shortcuts is helpful for maintaining stability. The mechanisms of instability, bifurcation modes, and chaos are also investigated. Compared with methods based on mean-field theory, the proposed method can guarantee the stability of the system in most cases with random events. The proposed method is effective for cases where excitatory and inhibitory shortcuts exist simultaneously in the network. Copyright © 2017 Elsevier Ltd. All rights reserved.

How well do mean field theories of spiking quadratic-integrate-and-fire networks work in realistic parameter regimes?

PubMed

Grabska-Barwińska, Agnieszka; Latham, Peter E

2014-06-01

We use mean field techniques to compute the distribution of excitatory and inhibitory firing rates in large networks of randomly connected spiking quadratic integrate and fire neurons. These techniques are based on the assumption that activity is asynchronous and Poisson. For most parameter settings these assumptions are strongly violated; nevertheless, so long as the networks are not too synchronous, we find good agreement between mean field prediction and network simulations. Thus, much of the intuition developed for randomly connected networks in the asynchronous regime applies to mildly synchronous networks.

Impaired fast-spiking interneuron function in a genetic mouse model of depression

PubMed Central

Sauer, Jonas-Frederic; Strüber, Michael; Bartos, Marlene

2015-01-01

Rhythmic neuronal activity provides a frame for information coding by co-active cell assemblies. Abnormal brain rhythms are considered as potential pathophysiological mechanisms causing mental disease, but the underlying network defects are largely unknown. We find that mice expressing truncated Disrupted-in-Schizophrenia 1 (Disc1), which mirror a high-prevalence genotype for human psychiatric illness, show depression-related behavior. Theta and low-gamma synchrony in the prelimbic cortex (PrlC) is impaired in Disc1 mice and inversely correlated with the extent of behavioural despair. While weak theta activity is driven by the hippocampus, disturbance of low-gamma oscillations is caused by local defects of parvalbumin (PV)-expressing fast-spiking interneurons (FS-INs). The number of FS-INs is reduced, they receive fewer excitatory inputs, and form fewer release sites on targets. Computational analysis indicates that weak excitatory input and inhibitory output of FS-INs may lead to impaired gamma oscillations. Our data link network defects with a gene mutation underlying depression in humans. DOI: http://dx.doi.org/10.7554/eLife.04979.001 PMID:25735038

Serotonin increases synaptic activity in olfactory bulb glomeruli

PubMed Central

Brill, Julia; Shao, Zuoyi; Puche, Adam C.; Wachowiak, Matt

2016-01-01

Serotoninergic fibers densely innervate olfactory bulb glomeruli, the first sites of synaptic integration in the olfactory system. Acting through 5HT2A receptors, serotonin (5HT) directly excites external tufted cells (ETCs), key excitatory glomerular neurons, and depolarizes some mitral cells (MCs), the olfactory bulb's main output neurons. We further investigated 5HT action on MCs and determined its effects on the two major classes of glomerular interneurons: GABAergic/dopaminergic short axon cells (SACs) and GABAergic periglomerular cells (PGCs). In SACs, 5HT evoked a depolarizing current mediated by 5HT2C receptors but did not significantly impact spike rate. 5HT had no measurable direct effect in PGCs. Serotonin increased spontaneous excitatory and inhibitory postsynaptic currents (sEPSCs and sIPSCs) in PGCs and SACs. Increased sEPSCs were mediated by 5HT2A receptors, suggesting that they are primarily due to enhanced excitatory drive from ETCs. Increased sIPSCs resulted from elevated excitatory drive onto GABAergic interneurons and augmented GABA release from SACs. Serotonin-mediated GABA release from SACs was action potential independent and significantly increased miniature IPSC frequency in glomerular neurons. When focally applied to a glomerulus, 5HT increased MC spontaneous firing greater than twofold but did not increase olfactory nerve-evoked responses. Taken together, 5HT modulates glomerular network activity in several ways: 1) it increases ETC-mediated feed-forward excitation onto MCs, SACs, and PGCs; 2) it increases inhibition of glomerular interneurons; 3) it directly triggers action potential-independent GABA release from SACs; and 4) these network actions increase spontaneous MC firing without enhancing responses to suprathreshold sensory input. This may enhance MC sensitivity while maintaining dynamic range. PMID:26655822

Serotonin increases synaptic activity in olfactory bulb glomeruli.

PubMed

Brill, Julia; Shao, Zuoyi; Puche, Adam C; Wachowiak, Matt; Shipley, Michael T

2016-03-01

Serotoninergic fibers densely innervate olfactory bulb glomeruli, the first sites of synaptic integration in the olfactory system. Acting through 5HT2A receptors, serotonin (5HT) directly excites external tufted cells (ETCs), key excitatory glomerular neurons, and depolarizes some mitral cells (MCs), the olfactory bulb's main output neurons. We further investigated 5HT action on MCs and determined its effects on the two major classes of glomerular interneurons: GABAergic/dopaminergic short axon cells (SACs) and GABAergic periglomerular cells (PGCs). In SACs, 5HT evoked a depolarizing current mediated by 5HT2C receptors but did not significantly impact spike rate. 5HT had no measurable direct effect in PGCs. Serotonin increased spontaneous excitatory and inhibitory postsynaptic currents (sEPSCs and sIPSCs) in PGCs and SACs. Increased sEPSCs were mediated by 5HT2A receptors, suggesting that they are primarily due to enhanced excitatory drive from ETCs. Increased sIPSCs resulted from elevated excitatory drive onto GABAergic interneurons and augmented GABA release from SACs. Serotonin-mediated GABA release from SACs was action potential independent and significantly increased miniature IPSC frequency in glomerular neurons. When focally applied to a glomerulus, 5HT increased MC spontaneous firing greater than twofold but did not increase olfactory nerve-evoked responses. Taken together, 5HT modulates glomerular network activity in several ways: 1) it increases ETC-mediated feed-forward excitation onto MCs, SACs, and PGCs; 2) it increases inhibition of glomerular interneurons; 3) it directly triggers action potential-independent GABA release from SACs; and 4) these network actions increase spontaneous MC firing without enhancing responses to suprathreshold sensory input. This may enhance MC sensitivity while maintaining dynamic range. Copyright © 2016 the American Physiological Society.

Global competition and local cooperation in a network of neural oscillators

NASA Astrophysics Data System (ADS)

Terman, David; Wang, DeLiang

An architecture of locally excitatory, globally inhibitory oscillator networks is proposed and investigated both analytically and by computer simulation. The model for each oscillator corresponds to a standard relaxation oscillator with two time scales. Oscillators are locally coupled by a scheme that resembles excitatory synaptic coupling, and each oscillator also inhibits other oscillators through a common inhibitor. Oscillators are driven to be oscillatory by external stimulation. The network exhibits a mechanism of selective gating, whereby an oscillator jumping up to its active phase rapidly recruits the oscillators stimulated by the same pattern, while preventing the other oscillators from jumping up. We show analytically that with the selective gating mechanism, the network rapidly achieves both synchronization within blocks of oscillators that are stimulated by connected regions and desynchronization between different blocks. Computer simulations demonstrate the model's promising ability for segmenting multiple input patterns in real time. This model lays a physical foundation for the oscillatory correlation theory of feature binding and may provide an effective computational framework for scene segmentation and figure/ ground segregation.

Seizures as imbalanced up states: excitatory and inhibitory conductances during seizure-like events

PubMed Central

Cressman, John R.; Schiff, Steven J.

2013-01-01

Precisely timed and dynamically balanced excitatory (E) and inhibitory (I) conductances underlie the basis of neural network activity. Normal E/I balance is often shifted in epilepsy, resulting in neuronal network hyperexcitability and recurrent seizures. However, dynamics of the actual excitatory and inhibitory synaptic conductances (ge and gi, respectively) during seizures remain unknown. To study the dynamics of E and I network balance, we calculated ge and gi during the initiation, body, and termination of seizure-like events (SLEs) in the rat hippocampus in vitro. Repetitive emergent SLEs in 4-aminopyridine (100 μM) and reduced extracellular magnesium (0.6 mM) were recorded in the identified CA1 pyramidal cells (PC) and oriens-lacunosum moleculare (O-LM) interneurons. Calculated ge/gi ratio dynamics showed that the initiation stage of the SLEs was dominated by inhibition in the PCs and was more balanced in the O-LM cells. During the body of the SLEs, the balance shifted toward excitation, with ge and gi peaking in both cell types at nearly the same time. In the termination phase, PCs were again dominated by inhibition, whereas O-LM cells experienced persistent excitatory synaptic barrage. In this way, increased excitability of interneurons may play roles in both seizure initiation (Žiburkus J, Cressman JR, Barreto E, Schiff SJ. J Neurophysiol 95: 3948–3954, 2006) and in their termination. Overall, SLE stages can be characterized in PC and O-LM cells by dynamically distinct changes in the balance of ge and gi, where a temporal sequence of imbalance shifts with the changing firing patterns of the cellular subtypes comprising the hyperexcitable microcircuits. PMID:23221405

Estimating network parameters from combined dynamics of firing rate and irregularity of single neurons.

PubMed

Hamaguchi, Kosuke; Riehle, Alexa; Brunel, Nicolas

2011-01-01

High firing irregularity is a hallmark of cortical neurons in vivo, and modeling studies suggest a balance of excitation and inhibition is necessary to explain this high irregularity. Such a balance must be generated, at least partly, from local interconnected networks of excitatory and inhibitory neurons, but the details of the local network structure are largely unknown. The dynamics of the neural activity depends on the local network structure; this in turn suggests the possibility of estimating network structure from the dynamics of the firing statistics. Here we report a new method to estimate properties of the local cortical network from the instantaneous firing rate and irregularity (CV(2)) under the assumption that recorded neurons are a part of a randomly connected sparse network. The firing irregularity, measured in monkey motor cortex, exhibits two features; many neurons show relatively stable firing irregularity in time and across different task conditions; the time-averaged CV(2) is widely distributed from quasi-regular to irregular (CV(2) = 0.3-1.0). For each recorded neuron, we estimate the three parameters of a local network [balance of local excitation-inhibition, number of recurrent connections per neuron, and excitatory postsynaptic potential (EPSP) size] that best describe the dynamics of the measured firing rates and irregularities. Our analysis shows that optimal parameter sets form a two-dimensional manifold in the three-dimensional parameter space that is confined for most of the neurons to the inhibition-dominated region. High irregularity neurons tend to be more strongly connected to the local network, either in terms of larger EPSP and inhibitory PSP size or larger number of recurrent connections, compared with the low irregularity neurons, for a given excitatory/inhibitory balance. Incorporating either synaptic short-term depression or conductance-based synapses leads many low CV(2) neurons to move to the excitation-dominated region as well as to an increase of EPSP size.

Topologically invariant macroscopic statistics in balanced networks of conductance-based integrate-and-fire neurons.

PubMed

Yger, Pierre; El Boustani, Sami; Destexhe, Alain; Frégnac, Yves

2011-10-01

The relationship between the dynamics of neural networks and their patterns of connectivity is far from clear, despite its importance for understanding functional properties. Here, we have studied sparsely-connected networks of conductance-based integrate-and-fire (IF) neurons with balanced excitatory and inhibitory connections and with finite axonal propagation speed. We focused on the genesis of states with highly irregular spiking activity and synchronous firing patterns at low rates, called slow Synchronous Irregular (SI) states. In such balanced networks, we examined the "macroscopic" properties of the spiking activity, such as ensemble correlations and mean firing rates, for different intracortical connectivity profiles ranging from randomly connected networks to networks with Gaussian-distributed local connectivity. We systematically computed the distance-dependent correlations at the extracellular (spiking) and intracellular (membrane potential) levels between randomly assigned pairs of neurons. The main finding is that such properties, when they are averaged at a macroscopic scale, are invariant with respect to the different connectivity patterns, provided the excitatory-inhibitory balance is the same. In particular, the same correlation structure holds for different connectivity profiles. In addition, we examined the response of such networks to external input, and found that the correlation landscape can be modulated by the mean level of synchrony imposed by the external drive. This modulation was found again to be independent of the external connectivity profile. We conclude that first and second-order "mean-field" statistics of such networks do not depend on the details of the connectivity at a microscopic scale. This study is an encouraging step toward a mean-field description of topological neuronal networks.

Functional neuroanatomy of the central noradrenergic system.

PubMed

Szabadi, Elemer

2013-08-01

The central noradrenergic neurone, like the peripheral sympathetic neurone, is characterized by a diffusely arborizing terminal axonal network. The central neurones aggregate in distinct brainstem nuclei, of which the locus coeruleus (LC) is the most prominent. LC neurones project widely to most areas of the neuraxis, where they mediate dual effects: neuronal excitation by α₁-adrenoceptors and inhibition by α₂-adrenoceptors. The LC plays an important role in physiological regulatory networks. In the sleep/arousal network the LC promotes wakefulness, via excitatory projections to the cerebral cortex and other wakefulness-promoting nuclei, and inhibitory projections to sleep-promoting nuclei. The LC, together with other pontine noradrenergic nuclei, modulates autonomic functions by excitatory projections to preganglionic sympathetic, and inhibitory projections to preganglionic parasympathetic neurones. The LC also modulates the acute effects of light on physiological functions ('photomodulation'): stimulation of arousal and sympathetic activity by light via the LC opposes the inhibitory effects of light mediated by the ventrolateral preoptic nucleus on arousal and by the paraventricular nucleus on sympathetic activity. Photostimulation of arousal by light via the LC may enable diurnal animals to function during daytime. LC neurones degenerate early and progressively in Parkinson's disease and Alzheimer's disease, leading to cognitive impairment, depression and sleep disturbance.

A neural network model of memory and higher cognitive functions.

PubMed

Vogel, David D

2005-01-01

I first describe a neural network model of associative memory in a small region of the brain. The model depends, unconventionally, on disinhibition of inhibitory links between excitatory neurons rather than long-term potentiation (LTP) of excitatory projections. The model may be shown to have advantages over traditional neural network models both in terms of information storage capacity and biological plausibility. The learning and recall algorithms are independent of network architecture, and require no thresholds or finely graded synaptic strengths. Several copies of this local network are then connected by means of many, weak, reciprocal, excitatory projections that allow one region to control the recall of information in another to produce behaviors analogous to serial memory, classical and operant conditioning, secondary reinforcement, refabrication of memory, and fabrication of possible future events. The network distinguishes between perceived and recalled events, and can predicate its response on the absence as well as the presence of particular stimuli. Some of these behaviors are achieved in ways that seem to provide instances of self-awareness and imagination, suggesting that consciousness may emerge as an epiphenomenon in simple brains.

Role of physical and mental training in brain network configuration

PubMed Central

Foster, Philip P.

2015-01-01

It is hypothesized that the topology of brain networks is constructed by connecting nodes which may be continuously remodeled by appropriate training. Efficiency of physical and/or mental training on the brain relies on the flexibility of networks' architecture molded by local remodeling of proteins and synapses of excitatory neurons producing transformations in network topology. Continuous remodeling of proteins of excitatory neurons is fine-tuning the scaling and strength of excitatory synapses up or down via regulation of intra-cellular metabolic and regulatory networks of the genome-transcriptome-proteome interface. Alzheimer's disease is a model of “energy cost-driven small-world network disorder” with dysfunction of high-energy cost wiring as the network global efficiency is impaired by the deposition of an informed agent, the amyloid-β, selectively targeting high-degree nodes. In schizophrenia, the interconnectivity and density of rich-club networks are significantly reduced. Training-induced homeostatic synaptogenesis-enhancement, presumably via reconfiguration of brain networks into greater small-worldness, appears essential in learning, memory, and executive functions. A macroscopic cartography of creation-removal of synaptic connections in a macro-network, and at the intra-cellular scale, micro-networks regulate the physiological mechanisms for the preferential attachment of synapses. The strongest molecular relationship of exercise and functional connectivity was identified for brain-derived neurotrophic factor (BDNF). The allele variant, rs7294919, also shows a powerful relationship with the hippocampal volume. How the brain achieves this unique quest of reconfiguration remains a puzzle. What are the underlying mechanisms of synaptogenesis promoting communications brain ↔ muscle and brain ↔ brain in such trainings? What is the respective role of independent mental, physical, or combined-mental-physical trainings? Physical practice seems to be playing an instrumental role in the cognitive enhancement (brain ↔ muscle com.). However, mental training, meditation or virtual reality (films, games) require only minimal motor activity and cardio-respiratory stimulation. Therefore, other potential paths (brain ↔ brain com.) molding brain networks are nonetheless essential. Patients with motor neuron disease/injury (e.g., amyotrophic lateral sclerosis, traumatism) also achieve successful cognitive enhancement albeit they may only elicit mental practice. PMID:26157387

Role of physical and mental training in brain network configuration.

PubMed

Foster, Philip P

2015-01-01

It is hypothesized that the topology of brain networks is constructed by connecting nodes which may be continuously remodeled by appropriate training. Efficiency of physical and/or mental training on the brain relies on the flexibility of networks' architecture molded by local remodeling of proteins and synapses of excitatory neurons producing transformations in network topology. Continuous remodeling of proteins of excitatory neurons is fine-tuning the scaling and strength of excitatory synapses up or down via regulation of intra-cellular metabolic and regulatory networks of the genome-transcriptome-proteome interface. Alzheimer's disease is a model of "energy cost-driven small-world network disorder" with dysfunction of high-energy cost wiring as the network global efficiency is impaired by the deposition of an informed agent, the amyloid-β, selectively targeting high-degree nodes. In schizophrenia, the interconnectivity and density of rich-club networks are significantly reduced. Training-induced homeostatic synaptogenesis-enhancement, presumably via reconfiguration of brain networks into greater small-worldness, appears essential in learning, memory, and executive functions. A macroscopic cartography of creation-removal of synaptic connections in a macro-network, and at the intra-cellular scale, micro-networks regulate the physiological mechanisms for the preferential attachment of synapses. The strongest molecular relationship of exercise and functional connectivity was identified for brain-derived neurotrophic factor (BDNF). The allele variant, rs7294919, also shows a powerful relationship with the hippocampal volume. How the brain achieves this unique quest of reconfiguration remains a puzzle. What are the underlying mechanisms of synaptogenesis promoting communications brain ↔ muscle and brain ↔ brain in such trainings? What is the respective role of independent mental, physical, or combined-mental-physical trainings? Physical practice seems to be playing an instrumental role in the cognitive enhancement (brain ↔ muscle com.). However, mental training, meditation or virtual reality (films, games) require only minimal motor activity and cardio-respiratory stimulation. Therefore, other potential paths (brain ↔ brain com.) molding brain networks are nonetheless essential. Patients with motor neuron disease/injury (e.g., amyotrophic lateral sclerosis, traumatism) also achieve successful cognitive enhancement albeit they may only elicit mental practice.

Macroscopic phase-resetting curves for spiking neural networks

NASA Astrophysics Data System (ADS)

Dumont, Grégory; Ermentrout, G. Bard; Gutkin, Boris

2017-10-01

The study of brain rhythms is an open-ended, and challenging, subject of interest in neuroscience. One of the best tools for the understanding of oscillations at the single neuron level is the phase-resetting curve (PRC). Synchronization in networks of neurons, effects of noise on the rhythms, effects of transient stimuli on the ongoing rhythmic activity, and many other features can be understood by the PRC. However, most macroscopic brain rhythms are generated by large populations of neurons, and so far it has been unclear how the PRC formulation can be extended to these more common rhythms. In this paper, we describe a framework to determine a macroscopic PRC (mPRC) for a network of spiking excitatory and inhibitory neurons that generate a macroscopic rhythm. We take advantage of a thermodynamic approach combined with a reduction method to simplify the network description to a small number of ordinary differential equations. From this simplified but exact reduction, we can compute the mPRC via the standard adjoint method. Our theoretical findings are illustrated with and supported by numerical simulations of the full spiking network. Notably our mPRC framework allows us to predict the difference between effects of transient inputs to the excitatory versus the inhibitory neurons in the network.

Intermittent Hypoxia Enhances Functional Connectivity of Midcervical Spinal Interneurons

PubMed Central

Streeter, Kristi A.; Sunshine, Michael D.; Patel, Shreya; Gonzalez-Rothi, Elisa J.; Reier, Paul J.

2017-01-01

Brief, intermittent oxygen reductions [acute intermittent hypoxia (AIH)] evokes spinal plasticity. Models of AIH-induced neuroplasticity have focused on motoneurons; however, most midcervical interneurons (C-INs) also respond to hypoxia. We hypothesized that AIH would alter the functional connectivity between C-INs and induce persistent changes in discharge. Bilateral phrenic nerve activity was recorded in anesthetized and ventilated adult male rats and a multielectrode array was used to record C4/5 spinal discharge before [baseline (BL)], during, and 15 min after three 5 min hypoxic episodes (11% O2, H1–H3). Most C-INs (94%) responded to hypoxia by either increasing or decreasing firing rate. Functional connectivity was examined by cross-correlating C-IN discharge. Correlograms with a peak or trough were taken as evidence for excitatory or inhibitory connectivity between C-IN pairs. A subset of C-IN pairs had increased excitatory cross-correlations during hypoxic episodes (34%) compared with BL (19%; p < 0.0001). Another subset had a similar response following each episode (40%) compared with BL (19%; p < 0.0001). In the latter group, connectivity remained elevated 15 min post-AIH (30%; p = 0.0002). Inhibitory C-IN connectivity increased during H1–H3 (4.5%; p = 0.0160), but was reduced 15 min post-AIH (0.5%; p = 0.0439). Spike-triggered averaging indicated that a subset of C-INs is synaptically coupled to phrenic motoneurons and excitatory inputs to these “pre-phrenic” cells increased during AIH. We conclude that AIH alters connectivity of the midcervical spinal network. To our knowledge, this is the first demonstration that AIH induces plasticity within the propriospinal network. SIGNIFICANCE STATEMENT Acute intermittent hypoxia (AIH) can trigger spinal plasticity associated with sustained increases in respiratory, somatic, and/or autonomic motor output. The impact of AIH on cervical spinal interneuron (C-IN) discharge and connectivity is unknown. Our results demonstrate that AIH recruits excitatory C-INs into the spinal respiratory (phrenic) network. AIH also enhances excitatory and reduces inhibitory connections among the C-IN network. We conclude that C-INs are part of the respiratory, somatic, and/or autonomic response to AIH, and that propriospinal plasticity may contribute to sustained increases in motor output after AIH. PMID:28751456

Recurrent Coupling Improves Discrimination of Temporal Spike Patterns

PubMed Central

Yuan, Chun-Wei; Leibold, Christian

2012-01-01

Despite the ubiquitous presence of recurrent synaptic connections in sensory neuronal systems, their general functional purpose is not well understood. A recent conceptual advance has been achieved by theories of reservoir computing in which recurrent networks have been proposed to generate short-term memory as well as to improve neuronal representation of the sensory input for subsequent computations. Here, we present a numerical study on the distinct effects of inhibitory and excitatory recurrence in a canonical linear classification task. It is found that both types of coupling improve the ability to discriminate temporal spike patterns as compared to a purely feed-forward system, although in different ways. For a large class of inhibitory networks, the network’s performance is optimal as long as a fraction of roughly 50% of neurons per stimulus is active in the resulting population code. Thereby the contribution of inactive neurons to the neural code is found to be even more informative than that of the active neurons, generating an inherent robustness of classification performance against temporal jitter of the input spikes. Excitatory couplings are found to not only produce a short-term memory buffer but also to improve linear separability of the population patterns by evoking more irregular firing as compared to the purely inhibitory case. As the excitatory connectivity becomes more sparse, firing becomes more variable, and pattern separability improves. We argue that the proposed paradigm is particularly well-suited as a conceptual framework for processing of sensory information in the auditory pathway. PMID:22586392

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.

Synchronization in a non-uniform network of excitatory spiking neurons

NASA Astrophysics Data System (ADS)

Echeveste, Rodrigo; Gros, Claudius

Spontaneous synchronization of pulse coupled elements is ubiquitous in nature and seems to be of vital importance for life. Networks of pacemaker cells in the heart, extended populations of southeast asian fireflies, and neuronal oscillations in cortical networks, are examples of this. In the present work, a rich repertoire of dynamical states with different degrees of synchronization are found in a network of excitatory-only spiking neurons connected in a non-uniform fashion. In particular, uncorrelated and partially correlated states are found without the need for inhibitory neurons or external currents. The phase transitions between these states, as well the robustness, stability, and response of the network to external stimulus are studied.

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

PubMed Central

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

2011-01-01

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

Cortical Dynamics in Presence of Assemblies of Densely Connected Weight-Hub Neurons

PubMed Central

Setareh, Hesam; Deger, Moritz; Petersen, Carl C. H.; Gerstner, Wulfram

2017-01-01

Experimental measurements of pairwise connection probability of pyramidal neurons together with the distribution of synaptic weights have been used to construct randomly connected model networks. However, several experimental studies suggest that both wiring and synaptic weight structure between neurons show statistics that differ from random networks. Here we study a network containing a subset of neurons which we call weight-hub neurons, that are characterized by strong inward synapses. We propose a connectivity structure for excitatory neurons that contain assemblies of densely connected weight-hub neurons, while the pairwise connection probability and synaptic weight distribution remain consistent with experimental data. Simulations of such a network with generalized integrate-and-fire neurons display regular and irregular slow oscillations akin to experimentally observed up/down state transitions in the activity of cortical neurons with a broad distribution of pairwise spike correlations. Moreover, stimulation of a model network in the presence or absence of assembly structure exhibits responses similar to light-evoked responses of cortical layers in optogenetically modified animals. We conclude that a high connection probability into and within assemblies of excitatory weight-hub neurons, as it likely is present in some but not all cortical layers, changes the dynamics of a layer of cortical microcircuitry significantly. PMID:28690508

Global dysrhythmia of cerebro-basal ganglia-cerebellar networks underlies motor tics following striatal disinhibition.

PubMed

McCairn, Kevin W; Iriki, Atsushi; Isoda, Masaki

2013-01-09

Motor tics, a cardinal symptom of Tourette syndrome (TS), are hypothesized to arise from abnormalities within cerebro-basal ganglia circuits. Yet noninvasive neuroimaging of TS has previously identified robust activation in the cerebellum. To date, electrophysiological properties of cerebellar activation and its role in basal ganglia-mediated tic expression remain unknown. We performed multisite, multielectrode recordings of single-unit activity and local field potentials from the cerebellum, basal ganglia, and primary motor cortex using a pharmacologic monkey model of motor tics/TS. Following microinjections of bicuculline into the sensorimotor putamen, periodic tics occurred predominantly in the orofacial region, and a sizable number of cerebellar neurons showed phasic changes in activity associated with tic episodes. Specifically, 64% of the recorded cerebellar cortex neurons exhibited increases in activity, and 85% of the dentate nucleus neurons displayed excitatory, inhibitory, or multiphasic responses. Critically, abnormal discharges of cerebellar cortex neurons and excitatory-type dentate neurons mostly preceded behavioral tic onset, indicating their central origins. Latencies of pathological activity in the cerebellum and primary motor cortex substantially overlapped, suggesting that aberrant signals may be traveling along divergent pathways to these structures from the basal ganglia. Furthermore, the occurrence of tic movement was most closely associated with local field potential spikes in the cerebellum and primary motor cortex, implying that these structures may function as a gate to release overt tic movements. These findings indicate that tic-generating networks in basal ganglia mediated tic disorders extend beyond classical cerebro-basal ganglia circuits, leading to global network dysrhythmia including cerebellar circuits.

State-dependent interactions between excitatory neuromodulators in the neuronal control of breathing

PubMed Central

Doi, Atsushi; Ramirez, Jan-Marino

2010-01-01

All neuronal networks are modulated by multiple neuropeptides and biogenic amines. Yet, few studies investigate how different modulators interact to regulate network activity. Here we explored the state-dependent functional interactions between three excitatory neuromodulators acting on neurokinin1 (NK1), alpha1 noradrenergic (α1 NE) and 5-HT2 serotonin receptors (5-HT2) within the Pre-Bötzinger complex (pre-BötC), an area critical for the generation of breathing. In anesthetized, in vivo mice the reliance on endogenous NK1 activation depended on spontaneous breathing frequency and the modulatory state of the animal. Endogenous NK1 activation had no significant respiratory effect when stimulating raphe magnus and/or locus ceruleus, but became critical, when α1 NE and 5-HT2 receptors were pharmacologically blocked. The dependence of the centrally generated respiratory rhythm on NK1 activation was blunted in the presence of α1 NE and 5-HT2 agonists as demonstrated in slices containing the pre-BötC. We conclude that a modulators’ action is determined by the concurrent modulation and interaction with other neuromodulators. Deficiencies in one neuromodulator are immediately compensated by the action of other neuromodulators. This interplay could play a role in the state-dependency of certain breathing disorders. PMID:20554877

Effects of Electrical and Optogenetic Deep Brain Stimulation on Synchronized Oscillatory Activity in Parkinsonian Basal Ganglia.

PubMed

Ratnadurai-Giridharan, Shivakeshavan; Cheung, Chung C; Rubchinsky, Leonid L

2017-11-01

Conventional deep brain stimulation of basal ganglia uses high-frequency regular electrical pulses to treat Parkinsonian motor symptoms but has a series of limitations. Relatively new and not yet clinically tested, optogenetic stimulation is an effective experimental stimulation technique to affect pathological network dynamics. We compared the effects of electrical and optogenetic stimulation of the basal gangliaon the pathologicalParkinsonian rhythmic neural activity. We studied the network response to electrical stimulation and excitatory and inhibitory optogenetic stimulations. Different stimulations exhibit different interactions with pathological activity in the network. We studied these interactions for different network and stimulation parameter values. Optogenetic stimulation was found to be more efficient than electrical stimulation in suppressing pathological rhythmicity. Our findings indicate that optogenetic control of neural synchrony may be more efficacious than electrical control because of the different ways of how stimulations interact with network dynamics.

Synaptic and intrinsic activation of GABAergic neurons in the cardiorespiratory brainstem network.

PubMed

Frank, Julie G; Mendelowitz, David

2012-01-01

GABAergic pathways in the brainstem play an essential role in respiratory rhythmogenesis and interactions between the respiratory and cardiovascular neuronal control networks. However, little is known about the identity and function of these GABAergic inhibitory neurons and what determines their activity. In this study we have identified a population of GABAergic neurons in the ventrolateral medulla that receive increased excitatory post-synaptic potentials during inspiration, but also have spontaneous firing in the absence of synaptic input. Using transgenic mice that express GFP under the control of the Gad1 (GAD67) gene promoter, we determined that this population of GABAergic neurons is in close apposition to cardioinhibitory parasympathetic cardiac neurons in the nucleus ambiguus (NA). These neurons fire in synchronization with inspiratory activity. Although they receive excitatory glutamatergic synaptic inputs during inspiration, this excitatory neurotransmission was not altered by blocking nicotinic receptors, and many of these GABAergic neurons continue to fire after synaptic blockade. The spontaneous firing in these GABAergic neurons was not altered by the voltage-gated calcium channel blocker cadmium chloride that blocks both neurotransmission to these neurons and voltage-gated Ca(2+) currents, but spontaneous firing was diminished by riluzole, demonstrating a role of persistent sodium channels in the spontaneous firing in these cardiorespiratory GABAergic neurons that possess a pacemaker phenotype. The spontaneously firing GABAergic neurons identified in this study that increase their activity during inspiration would support respiratory rhythm generation if they acted primarily to inhibit post-inspiratory neurons and thereby release inspiration neurons to increase their activity. This population of inspiratory-modulated GABAergic neurons could also play a role in inhibiting neurons that are most active during expiration and provide a framework for respiratory sinus arrhythmia as there is an increase in heart rate during inspiration that occurs via inhibition of premotor parasympathetic cardioinhibitory neurons in the NA during inspiration.

Failed cooperative, but not competitive, interaction between large-scale brain networks impairs working memory in schizophrenia.

PubMed

Pu, W; Luo, Q; Palaniyappan, L; Xue, Z; Yao, S; Feng, J; Liu, Z

2016-04-01

A large-scale network named the default mode network (DMN) dynamically cooperates and competes with an external attention system (EAS) to facilitate various cognitive functioning that is prominently impaired in schizophrenia. However, it is unclear whether the cognitive deficit in schizophrenia is related to the disrupted competition and/or cooperation between these two networks. A total of 35 schizophrenia patients and 30 healthy controls were scanned using gradient-echo echo-planar imaging during n-back working memory (WM) processing. Brain activities of the DMN and EAS were measured using general linear modelling of the functional magnetic resonance imaging data. Dynamic interaction between the DMN and EAS was decomposed into two directions using Granger causality analysis. We observed a significant failure of DMN suppression in patients with schizophrenia, which was significantly related to WM/attentional deficit. Granger causality modelling showed that in healthy controls, while the EAS inhibitorily influenced the DMN, the DMN exerted an 'excitatory' or cooperative influence back on the EAS, especially in those with lower WM accuracy. In schizophrenia, this 'excitatory' DMN→EAS influence within the reciprocal EAS-DMN loop was significantly reduced, especially in patients with WM/attentional deficit. The dynamic interaction between the DMN and EAS is likely to be comprised of both competitive and cooperative influences. In healthy controls, both the 'inhibitory' EAS→DMN interaction and 'excitatory' DMN→EAS interaction are correlated with WM performance. In schizophrenia, reduced 'cooperative' influence from the DMN to dorsal nodes of the EAS occurs in the context of non-suppression of the DMN and may form a possible pathophysiological substrate of WM deficit and attention disorder.

Entorhinal Cortical Ocean Cells Encode Specific Contexts and Drive Context-Specific Fear Memory

PubMed Central

Kitamura, Takashi; Sun, Chen; Martin, Jared; Kitch, Lacey J; Schnitzer, Mark J; Tonegawa, Susumu

2016-01-01

Summary Forming distinct representations and memories of multiple contexts and episodes is thought to be a crucial function of the hippocampal-entorhinal cortical network. The hippocampal dentate gyrus (DG) and CA3 are known to contribute to these functions but the role of the entorhinal cortex (EC) is poorly understood. Here, we show that Ocean cells, excitatory stellate neurons in the medial EC layer II projecting into DG and CA3, rapidly form a distinct representation of a novel context and drive context-specific activation of downstream CA3 cells as well as context-specific fear memory. In contrast, Island cells, excitatory pyramidal neurons in the medial EC layer II projecting into CA1, are indifferent to context-specific encoding or memory. On the other hand, Ocean cells are dispensable for temporal association learning, for which Island cells are crucial. Together, the two excitatory medial EC layer II inputs to the hippocampus have complementary roles in episodic memory. PMID:26402611

Excitatory Cerebellar Nucleocortical Circuit Provides Internal Amplification during Associative Conditioning.

PubMed

Gao, Zhenyu; Proietti-Onori, Martina; Lin, Zhanmin; Ten Brinke, Michiel M; Boele, Henk-Jan; Potters, Jan-Willem; Ruigrok, Tom J H; Hoebeek, Freek E; De Zeeuw, Chris I

2016-02-03

Closed-loop circuitries between cortical and subcortical regions can facilitate precision of output patterns, but the role of such networks in the cerebellum remains to be elucidated. Here, we characterize the role of internal feedback from the cerebellar nuclei to the cerebellar cortex in classical eyeblink conditioning. We find that excitatory output neurons in the interposed nucleus provide efference-copy signals via mossy fibers to the cerebellar cortical zones that belong to the same module, triggering monosynaptic responses in granule and Golgi cells and indirectly inhibiting Purkinje cells. Upon conditioning, the local density of nucleocortical mossy fiber terminals significantly increases. Optogenetic activation and inhibition of nucleocortical fibers in conditioned animals increases and decreases the amplitude of learned eyeblink responses, respectively. Our data show that the excitatory nucleocortical closed-loop circuitry of the cerebellum relays a corollary discharge of premotor signals and suggests an amplifying role of this circuitry in controlling associative motor learning. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Depolarizing GABA/glycine synaptic events switch from excitation to inhibition during frequency increases

NASA Astrophysics Data System (ADS)

Branchereau, Pascal; Cattaert, Daniel; Delpy, Alain; Allain, Anne-Emilie; Martin, Elodie; Meyrand, Pierre

2016-02-01

By acting on their ionotropic chloride channel receptors, GABA and glycine represent the major inhibitory transmitters of the central nervous system. Nevertheless, in various brain structures, depolarizing GABAergic/glycinergic postsynaptic potentials (dGPSPs) lead to dual inhibitory (shunting) and excitatory components, the functional consequences of which remain poorly acknowledged. Indeed, the extent to which each component prevails during dGPSP is unclear. Understanding the mechanisms predicting the dGPSP outcome on neural network activity is therefore a major issue in neurobiology. By combining electrophysiological recordings of spinal embryonic mouse motoneurons and modelling study, we demonstrate that increasing the chloride conductance (gCl) favors inhibition either during a single dGPSP or during trains in which gCl summates. Finally, based on this summation mechanism, the excitatory effect of EPSPs is overcome by dGPSPs in a frequency-dependent manner. These results reveal an important mechanism by which dGPSPs protect against the overexcitation of neural excitatory circuits.

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.

The central pattern generator underlying swimming in Dendronotus iris: a simple half-center network oscillator with a twist.

PubMed

Sakurai, Akira; Katz, Paul S

2016-10-01

The nudibranch mollusc, Dendronotus iris, swims by rhythmically flexing its body from left to right. We identified a bilaterally represented interneuron, Si3, that provides strong excitatory drive to the previously identified Si2, forming a half-center oscillator, which functions as the central pattern generator (CPG) underlying swimming. As with Si2, Si3 inhibited its contralateral counterpart and exhibited rhythmic bursts in left-right alternation during the swim motor pattern. Si3 burst almost synchronously with the contralateral Si2 and was coactive with the efferent impulse activity in the contralateral body wall nerve. Perturbation of bursting in either Si3 or Si2 by current injection halted or phase-shifted the swim motor pattern, suggesting that they are both critical CPG members. Neither Si2 nor Si3 exhibited endogenous bursting properties when activated alone; activation of all four neurons was necessary to initiate and maintain the swim motor pattern. Si3 made a strong excitatory synapse onto the contralateral Si2 to which it is also electrically coupled. When Si3 was firing tonically but not exhibiting bursting, artificial enhancement of the Si3-to-Si2 synapse using dynamic clamp caused all four neurons to burst. In contrast, negation of the Si3-to-Si2 synapse by dynamic clamp blocked ongoing swim motor patterns. Together, these results suggest that the Dendronotus swim CPG is organized as a "twisted" half-center oscillator in which each "half" is composed of two excitatory-coupled neurons from both sides of the brain, each of which inhibits its contralateral counterpart. Consisting of only four neurons, this is perhaps the simplest known network oscillator for locomotion. Copyright © 2016 the American Physiological Society.

A Markov model for the temporal dynamics of balanced random networks of finite size

PubMed Central

Lagzi, Fereshteh; Rotter, Stefan

2014-01-01

The balanced state of recurrent networks of excitatory and inhibitory spiking neurons is characterized by fluctuations of population activity about an attractive fixed point. Numerical simulations show that these dynamics are essentially nonlinear, and the intrinsic noise (self-generated fluctuations) in networks of finite size is state-dependent. Therefore, stochastic differential equations with additive noise of fixed amplitude cannot provide an adequate description of the stochastic dynamics. The noise model should, rather, result from a self-consistent description of the network dynamics. Here, we consider a two-state Markovian neuron model, where spikes correspond to transitions from the active state to the refractory state. Excitatory and inhibitory input to this neuron affects the transition rates between the two states. The corresponding nonlinear dependencies can be identified directly from numerical simulations of networks of leaky integrate-and-fire neurons, discretized at a time resolution in the sub-millisecond range. Deterministic mean-field equations, and a noise component that depends on the dynamic state of the network, are obtained from this model. The resulting stochastic model reflects the behavior observed in numerical simulations quite well, irrespective of the size of the network. In particular, a strong temporal correlation between the two populations, a hallmark of the balanced state in random recurrent networks, are well represented by our model. Numerical simulations of such networks show that a log-normal distribution of short-term spike counts is a property of balanced random networks with fixed in-degree that has not been considered before, and our model shares this statistical property. Furthermore, the reconstruction of the flow from simulated time series suggests that the mean-field dynamics of finite-size networks are essentially of Wilson-Cowan type. We expect that this novel nonlinear stochastic model of the interaction between neuronal populations also opens new doors to analyze the joint dynamics of multiple interacting networks. PMID:25520644

Cortical network models of impulse firing in the resting and active states predict cortical energetics

PubMed Central

Bennett, Maxwell R.; Farnell, Les; Gibson, William G.; Lagopoulos, Jim

2015-01-01

Measurements of the cortical metabolic rate of glucose oxidation [CMRglc(ox)] have provided a number of interesting and, in some cases, surprising observations. One is the decline in CMRglc(ox) during anesthesia and non-rapid eye movement (NREM) sleep, and another, the inverse relationship between the resting-state CMRglc(ox) and the transient following input from the thalamus. The recent establishment of a quantitative relationship between synaptic and action potential activity on the one hand and CMRglc(ox) on the other allows neural network models of such activity to probe for possible mechanistic explanations of these phenomena. We have carried out such investigations using cortical models consisting of networks of modules with excitatory and inhibitory neurons, each receiving excitatory inputs from outside the network in addition to intermodular connections. Modules may be taken as regions of cortical interest, the inputs from outside the network as arising from the thalamus, and the intermodular connections as long associational fibers. The model shows that the impulse frequency of different modules can differ from each other by less than 10%, consistent with the relatively uniform CMRglc(ox) observed across different regions of cortex. The model also shows that, if correlations of the average impulse rate between different modules decreases, there is a concomitant decrease in the average impulse rate in the modules, consistent with the observed drop in CMRglc(ox) in NREM sleep and under anesthesia. The model also explains why a transient thalamic input to sensory cortex gives rise to responses with amplitudes inversely dependent on the resting-state frequency, and therefore resting-state CMRglc(ox). PMID:25775588

Balanced cortical microcircuitry for spatial working memory based on corrective feedback control.

PubMed

Lim, Sukbin; Goldman, Mark S

2014-05-14

A hallmark of working memory is the ability to maintain graded representations of both the spatial location and amplitude of a memorized stimulus. Previous work has identified a neural correlate of spatial working memory in the persistent maintenance of spatially specific patterns of neural activity. How such activity is maintained by neocortical circuits remains unknown. Traditional models of working memory maintain analog representations of either the spatial location or the amplitude of a stimulus, but not both. Furthermore, although most previous models require local excitation and lateral inhibition to maintain spatially localized persistent activity stably, the substrate for lateral inhibitory feedback pathways is unclear. Here, we suggest an alternative model for spatial working memory that is capable of maintaining analog representations of both the spatial location and amplitude of a stimulus, and that does not rely on long-range feedback inhibition. The model consists of a functionally columnar network of recurrently connected excitatory and inhibitory neural populations. When excitation and inhibition are balanced in strength but offset in time, drifts in activity trigger spatially specific negative feedback that corrects memory decay. The resulting networks can temporally integrate inputs at any spatial location, are robust against many commonly considered perturbations in network parameters, and, when implemented in a spiking model, generate irregular neural firing characteristic of that observed experimentally during persistent activity. This work suggests balanced excitatory-inhibitory memory circuits implementing corrective negative feedback as a substrate for spatial working memory. Copyright © 2014 the authors 0270-6474/14/346790-17$15.00/0.

Nlgn4 knockout induces network hypo-excitability in juvenile mouse somatosensory cortex in vitro.

PubMed

Delattre, V; La Mendola, D; Meystre, J; Markram, H; Markram, K

2013-10-09

Neuroligins (Nlgns) are postsynaptic cell adhesion molecules that form transynaptic complexes with presynaptic neurexins and regulate synapse maturation and plasticity. We studied the impact of the loss of Nlgn4 on the excitatory and inhibitory circuits in somatosensory cortical slices of juvenile mice by electrically stimulating these circuits using a multi-electrode array and recording the synaptic input to single neurons using the patch-clamp technique. We detected a decreased network response to stimulation in both excitatory and inhibitory circuits of Nlgn4 knock-out animals as compared to wild-type controls, and a decreased excitation-inhibition ratio. These data indicate that Nlgn4 is involved in the regulation of excitatory and inhibitory circuits and contributes to a balanced circuit response to stimulation.

[Function of glutamate in pattern-gene-rating network is modified by nitric oxide NO].

PubMed

D'iakonova, T L; D'iakonova, V E

2007-03-01

In previous study on the terrestrial snail Helix pomatia, it has been shown that responsiveness of certain neurons to glutamate is controlled by NO; specifically, the donors of NO produced transformation of inhibitory responses to excitatory ones. Here, we extend this study to buccal neurons related to feeding behavior of the pond snail L. stagnalis. Glutamate is known to operate in the standard three-phase feeding pattern as a phase transmitter which mediates the effects of the second phase interneuron N2v. In isolated CNS, we recorded motor neuron B4 that was inhibited during firing of glutamatergic N2v, but expressed excitatory glutamate receptors as well. In some preparations (n = 17), bath application of 0.1 mM glutamate resulted in profound hyperpolarization of, and cessation of synaptic inputs to, the B4. Following treatment for 10-15 min with the NO donor sodium nitroprusside (n = 9), glutamate effect on B4 became excitatory, and a peculiar, sustained two-phase rhythmic activity of the pattern-generating network appeared. In other non-treated preparations (n = 12), 0.1 mM glutamate produced depolarization and excitation of B4, supplemented, in 8 cases, with emergence of the above mentioned two-phase rhythmic activity. Pretreatment for 10-20 min with the NO scavenger 2-phenyl-4,4,5,5-tetramethylimidazoline-1-oxyl-3-oxide (n = 7) abolished these effects of glutamate. Our results suggest that 1) glutamate role in buccal rhythm generation depends on NO level, and 2) this mechanism is involved in modification of the feeding behavior in Lymnaea.

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

PubMed

Bonansco, Christian; Fuenzalida, Marco

2016-01-01

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

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

PubMed Central

Bonansco, Christian; Fuenzalida, Marco

2016-01-01

Synaptic plasticity is the capacity generated by experience to modify the neural function and, thereby, adapt our behaviour. Long-term plasticity of glutamatergic and GABAergic transmission occurs in a concerted manner, finely adjusting the excitatory-inhibitory (E/I) balance. Imbalances of E/I function are related to several neurological diseases including epilepsy. Several evidences have demonstrated that astrocytes are able to control the synaptic plasticity, with astrocytes being active partners in synaptic physiology and E/I balance. Here, we revise molecular evidences showing the epileptic stage as an abnormal form of long-term brain plasticity and propose the possible participation of astrocytes to the abnormal increase of glutamatergic and decrease of GABAergic neurotransmission in epileptic networks. PMID:27006834

Comparisons of Neuronal and Excitatory Network Properties between the Rat Brainstem Nuclei that Participate in Vertical and Horizontal Gaze Holding

PubMed Central

Sugimura, Taketoshi; Yanagawa, Yuchio

2017-01-01

Gaze holding is primarily controlled by neural structures including the prepositus hypoglossi nucleus (PHN) for horizontal gaze and the interstitial nucleus of Cajal (INC) for vertical and torsional gaze. In contrast to the accumulating findings of the PHN, there is no report regarding the membrane properties of INC neurons or the local networks in the INC. In this study, to verify whether the neural structure of the INC is similar to that of the PHN, we investigated the neuronal and network properties of the INC using whole-cell recordings in rat brainstem slices. Three types of afterhyperpolarization (AHP) profiles and five firing patterns observed in PHN neurons were also observed in INC neurons. However, the overall distributions based on the AHP profile and the firing patterns of INC neurons were different from those of PHN neurons. The application of burst stimulation to a nearby site of a recorded INC neuron induced an increase in the frequency of spontaneous EPSCs. The duration of the increased EPSC frequency of INC neurons was not significantly different from that of PHN neurons. The percent of duration reduction induced by a Ca2+-permeable AMPA (CP-AMPA) receptor antagonist was significantly smaller in the INC than in the PHN. These findings suggest that local excitatory networks that activate sustained EPSC responses also exist in the INC, but their activation mechanisms including the contribution of CP-AMPA receptors differ between the INC and the PHN. PMID:28966973

A Corticocortical Circuit Directly Links Retrosplenial Cortex to M2 in the Mouse

PubMed Central

Radulovic, Jelena

2016-01-01

Retrosplenial cortex (RSC) is a dorsomedial parietal area involved in a range of cognitive functions, including episodic memory, navigation, and spatial memory. Anatomically, the RSC receives inputs from dorsal hippocampal networks and in turn projects to medial neocortical areas. A particularly prominent projection extends rostrally to the posterior secondary motor cortex (M2), suggesting a functional corticocortical link from the RSC to M2 and thus a bridge between hippocampal and neocortical networks involved in mnemonic and sensorimotor aspects of navigation. We investigated the cellular connectivity in this RSC→M2 projection in the mouse using optogenetic photostimulation, retrograde labeling, and electrophysiology. Axons from RSC formed monosynaptic excitatory connections onto M2 pyramidal neurons across layers and projection classes, including corticocortical/intratelencephalic neurons (reciprocally and callosally projecting) in layers 2–6, pyramidal tract neurons (corticocollicular, corticopontine) in layer 5B, and, to a lesser extent, corticothalamic neurons in layer 6. In addition to these direct connections, disynaptic connections were made via posterior parietal cortex (RSC→PPC→M2) and anteromedial thalamus (RSC→AM→M2). In the reverse direction, axons from M2 monosynaptically excited M2-projecting corticocortical neurons in the RSC, especially in the superficial layers of the dysgranular region. These findings establish an excitatory RSC→M2 corticocortical circuit that engages diverse types of excitatory projection neurons in the downstream area, suggesting a basis for direct communication from dorsal hippocampal networks involved in spatial memory and navigation to neocortical networks involved in diverse aspects of sensorimotor integration and motor control. SIGNIFICANCE STATEMENT Corticocortical pathways interconnect cortical areas extensively, but the cellular connectivity in these pathways remains largely uncharacterized. Here, we show that a posterior part of secondary motor cortex receives corticocortical axons from the rostral retrosplenial cortex (RSC) and these form monosynaptic excitatory connections onto a wide spectrum of excitatory projection neurons in this area. Our results define a cellular basis for direct communication from RSC to this medial frontal area, suggesting a direct link from dorsal hippocampal networks involved in spatial cognition and navigation (the “map”) to sensorimotor networks involved the control of movement (the “motor”). PMID:27605612

Structural network heterogeneities and network dynamics: a possible dynamical mechanism for hippocampal memory reactivation.

NASA Astrophysics Data System (ADS)

Jablonski, Piotr; Poe, Gina; Zochowski, Michal

2007-03-01

The hippocampus has the capacity for reactivating recently acquired memories and it is hypothesized that one of the functions of sleep reactivation is the facilitation of consolidation of novel memory traces. The dynamic and network processes underlying such a reactivation remain, however, unknown. We show that such a reactivation characterized by local, self-sustained activity of a network region may be an inherent property of the recurrent excitatory-inhibitory network with a heterogeneous structure. The entry into the reactivation phase is mediated through a physiologically feasible regulation of global excitability and external input sources, while the reactivated component of the network is formed through induced network heterogeneities during learning. We show that structural changes needed for robust reactivation of a given network region are well within known physiological parameters.

Structural network heterogeneities and network dynamics: A possible dynamical mechanism for hippocampal memory reactivation

NASA Astrophysics Data System (ADS)

Jablonski, Piotr; Poe, Gina R.; Zochowski, Michal

2007-01-01

The hippocampus has the capacity for reactivating recently acquired memories and it is hypothesized that one of the functions of sleep reactivation is the facilitation of consolidation of novel memory traces. The dynamic and network processes underlying such a reactivation remain, however, unknown. We show that such a reactivation characterized by local, self-sustained activity of a network region may be an inherent property of the recurrent excitatory-inhibitory network with a heterogeneous structure. The entry into the reactivation phase is mediated through a physiologically feasible regulation of global excitability and external input sources, while the reactivated component of the network is formed through induced network heterogeneities during learning. We show that structural changes needed for robust reactivation of a given network region are well within known physiological parameters.

Membrane Properties and the Balance between Excitation and Inhibition Control Gamma-Frequency Oscillations Arising from Feedback Inhibition

PubMed Central

Economo, Michael N.; White, John A.

2012-01-01

Computational studies as well as in vivo and in vitro results have shown that many cortical neurons fire in a highly irregular manner and at low average firing rates. These patterns seem to persist even when highly rhythmic signals are recorded by local field potential electrodes or other methods that quantify the summed behavior of a local population. Models of the 30–80 Hz gamma rhythm in which network oscillations arise through ‘stochastic synchrony’ capture the variability observed in the spike output of single cells while preserving network-level organization. We extend upon these results by constructing model networks constrained by experimental measurements and using them to probe the effect of biophysical parameters on network-level activity. We find in simulations that gamma-frequency oscillations are enabled by a high level of incoherent synaptic conductance input, similar to the barrage of noisy synaptic input that cortical neurons have been shown to receive in vivo. This incoherent synaptic input increases the emergent network frequency by shortening the time scale of the membrane in excitatory neurons and by reducing the temporal separation between excitation and inhibition due to decreased spike latency in inhibitory neurons. These mechanisms are demonstrated in simulations and in vitro current-clamp and dynamic-clamp experiments. Simulation results further indicate that the membrane potential noise amplitude has a large impact on network frequency and that the balance between excitatory and inhibitory currents controls network stability and sensitivity to external inputs. PMID:22275859

GABAa excitation and synaptogenesis after Status Epilepticus - A computational study.

PubMed

França, Keite Lira de Almeida; de Almeida, Antônio-Carlos Guimarães; Saddow, Stephen E; Santos, Luiz Eduardo Canton; Scorza, Carla Alessandra; Scorza, Fulvio Alexandre; Rodrigues, Antônio Márcio

2018-03-08

The role of GABAergic neurotransmission on epileptogenesis has been the subject of speculation according to different approaches. However, it is a very complex task to specifically consider the action of the GABAa neurotransmitter, which, in its dependence on the intracellular level of Cl - , can change its effect from inhibitory to excitatory. We have developed a computational model that represents the dentate gyrus and is composed of three different populations of neurons (granule cells, interneurons and mossy cells) that are mutually interconnected. The interconnections of the neurons were based on compensation theory with Hebbian and anti-Hebbian rules. The model also incorporates non-synaptic mechanisms to control the ionic homeostasis and was able to reproduce ictal discharges. The goal of the work was to investigate the hypothesis that the observed aberrant sprouting is promoted by GABAa excitatory action. Conjointly with the abnormal sprouting of the mossy fibres, the simulations show a reduction of the mossy cells connections in the network and an increased inhibition of the interneurons as a response of the neuronal network to control the activity. This finding contributes to increasing the changes in the connectivity of the neuronal circuitry and to increasing the epileptiform activity occurrences.

Impact of adaptation currents on synchronization of coupled exponential integrate-and-fire neurons.

PubMed

Ladenbauer, Josef; Augustin, Moritz; Shiau, LieJune; Obermayer, Klaus

2012-01-01

The ability of spiking neurons to synchronize their activity in a network depends on the response behavior of these neurons as quantified by the phase response curve (PRC) and on coupling properties. The PRC characterizes the effects of transient inputs on spike timing and can be measured experimentally. Here we use the adaptive exponential integrate-and-fire (aEIF) neuron model to determine how subthreshold and spike-triggered slow adaptation currents shape the PRC. Based on that, we predict how synchrony and phase locked states of coupled neurons change in presence of synaptic delays and unequal coupling strengths. We find that increased subthreshold adaptation currents cause a transition of the PRC from only phase advances to phase advances and delays in response to excitatory perturbations. Increased spike-triggered adaptation currents on the other hand predominantly skew the PRC to the right. Both adaptation induced changes of the PRC are modulated by spike frequency, being more prominent at lower frequencies. Applying phase reduction theory, we show that subthreshold adaptation stabilizes synchrony for pairs of coupled excitatory neurons, while spike-triggered adaptation causes locking with a small phase difference, as long as synaptic heterogeneities are negligible. For inhibitory pairs synchrony is stable and robust against conduction delays, and adaptation can mediate bistability of in-phase and anti-phase locking. We further demonstrate that stable synchrony and bistable in/anti-phase locking of pairs carry over to synchronization and clustering of larger networks. The effects of adaptation in aEIF neurons on PRCs and network dynamics qualitatively reflect those of biophysical adaptation currents in detailed Hodgkin-Huxley-based neurons, which underscores the utility of the aEIF model for investigating the dynamical behavior of networks. Our results suggest neuronal spike frequency adaptation as a mechanism synchronizing low frequency oscillations in local excitatory networks, but indicate that inhibition rather than excitation generates coherent rhythms at higher frequencies.

Impact of Adaptation Currents on Synchronization of Coupled Exponential Integrate-and-Fire Neurons

PubMed Central

Ladenbauer, Josef; Augustin, Moritz; Shiau, LieJune; Obermayer, Klaus

2012-01-01

The ability of spiking neurons to synchronize their activity in a network depends on the response behavior of these neurons as quantified by the phase response curve (PRC) and on coupling properties. The PRC characterizes the effects of transient inputs on spike timing and can be measured experimentally. Here we use the adaptive exponential integrate-and-fire (aEIF) neuron model to determine how subthreshold and spike-triggered slow adaptation currents shape the PRC. Based on that, we predict how synchrony and phase locked states of coupled neurons change in presence of synaptic delays and unequal coupling strengths. We find that increased subthreshold adaptation currents cause a transition of the PRC from only phase advances to phase advances and delays in response to excitatory perturbations. Increased spike-triggered adaptation currents on the other hand predominantly skew the PRC to the right. Both adaptation induced changes of the PRC are modulated by spike frequency, being more prominent at lower frequencies. Applying phase reduction theory, we show that subthreshold adaptation stabilizes synchrony for pairs of coupled excitatory neurons, while spike-triggered adaptation causes locking with a small phase difference, as long as synaptic heterogeneities are negligible. For inhibitory pairs synchrony is stable and robust against conduction delays, and adaptation can mediate bistability of in-phase and anti-phase locking. We further demonstrate that stable synchrony and bistable in/anti-phase locking of pairs carry over to synchronization and clustering of larger networks. The effects of adaptation in aEIF neurons on PRCs and network dynamics qualitatively reflect those of biophysical adaptation currents in detailed Hodgkin-Huxley-based neurons, which underscores the utility of the aEIF model for investigating the dynamical behavior of networks. Our results suggest neuronal spike frequency adaptation as a mechanism synchronizing low frequency oscillations in local excitatory networks, but indicate that inhibition rather than excitation generates coherent rhythms at higher frequencies. PMID:22511861

Bifurcation Analysis on Phase-Amplitude Cross-Frequency Coupling in Neural Networks with Dynamic Synapses

PubMed Central

Sase, Takumi; Katori, Yuichi; Komuro, Motomasa; Aihara, Kazuyuki

2017-01-01

We investigate a discrete-time network model composed of excitatory and inhibitory neurons and dynamic synapses with the aim at revealing dynamical properties behind oscillatory phenomena possibly related to brain functions. We use a stochastic neural network model to derive the corresponding macroscopic mean field dynamics, and subsequently analyze the dynamical properties of the network. In addition to slow and fast oscillations arising from excitatory and inhibitory networks, respectively, we show that the interaction between these two networks generates phase-amplitude cross-frequency coupling (CFC), in which multiple different frequency components coexist and the amplitude of the fast oscillation is modulated by the phase of the slow oscillation. Furthermore, we clarify the detailed properties of the oscillatory phenomena by applying the bifurcation analysis to the mean field model, and accordingly show that the intermittent and the continuous CFCs can be characterized by an aperiodic orbit on a closed curve and one on a torus, respectively. These two CFC modes switch depending on the coupling strength from the excitatory to inhibitory networks, via the saddle-node cycle bifurcation of a one-dimensional torus in map (MT1SNC), and may be associated with the function of multi-item representation. We believe that the present model might have potential for studying possible functional roles of phase-amplitude CFC in the cerebral cortex. PMID:28424606

Integrated plasticity at inhibitory and excitatory synapses in the cerebellar circuit.

PubMed

Mapelli, Lisa; Pagani, Martina; Garrido, Jesus A; D'Angelo, Egidio

2015-01-01

The way long-term potentiation (LTP) and depression (LTD) are integrated within the different synapses of brain neuronal circuits is poorly understood. In order to progress beyond the identification of specific molecular mechanisms, a system in which multiple forms of plasticity can be correlated with large-scale neural processing is required. In this paper we take as an example the cerebellar network, in which extensive investigations have revealed LTP and LTD at several excitatory and inhibitory synapses. Cerebellar LTP and LTD occur in all three main cerebellar subcircuits (granular layer, molecular layer, deep cerebellar nuclei) and correspondingly regulate the function of their three main neurons: granule cells (GrCs), Purkinje cells (PCs) and deep cerebellar nuclear (DCN) cells. All these neurons, in addition to be excited, are reached by feed-forward and feed-back inhibitory connections, in which LTP and LTD may either operate synergistically or homeostatically in order to control information flow through the circuit. Although the investigation of individual synaptic plasticities in vitro is essential to prove their existence and mechanisms, it is insufficient to generate a coherent view of their impact on network functioning in vivo. Recent computational models and cell-specific genetic mutations in mice are shedding light on how plasticity at multiple excitatory and inhibitory synapses might regulate neuronal activities in the cerebellar circuit and contribute to learning and memory and behavioral control.

Response sensitivity of barrel neuron subpopulations to simulated thalamic input.

PubMed

Pesavento, Michael J; Rittenhouse, Cynthia D; Pinto, David J

2010-06-01

Our goal is to examine the relationship between neuron- and network-level processing in the context of a well-studied cortical function, the processing of thalamic input by whisker-barrel circuits in rodent neocortex. Here we focus on neuron-level processing and investigate the responses of excitatory and inhibitory barrel neurons to simulated thalamic inputs applied using the dynamic clamp method in brain slices. Simulated inputs are modeled after real thalamic inputs recorded in vivo in response to brief whisker deflections. Our results suggest that inhibitory neurons require more input to reach firing threshold, but then fire earlier, with less variability, and respond to a broader range of inputs than do excitatory neurons. Differences in the responses of barrel neuron subtypes depend on their intrinsic membrane properties. Neurons with a low input resistance require more input to reach threshold but then fire earlier than neurons with a higher input resistance, regardless of the neuron's classification. Our results also suggest that the response properties of excitatory versus inhibitory barrel neurons are consistent with the response sensitivities of the ensemble barrel network. The short response latency of inhibitory neurons may serve to suppress ensemble barrel responses to asynchronous thalamic input. Correspondingly, whereas neurons acting as part of the barrel circuit in vivo are highly selective for temporally correlated thalamic input, excitatory barrel neurons acting alone in vitro are less so. These data suggest that network-level processing of thalamic input in barrel cortex depends on neuron-level processing of the same input by excitatory and inhibitory barrel neurons.

Identification of neuronal network properties from the spectral analysis of calcium imaging signals in neuronal cultures.

PubMed

Tibau, Elisenda; Valencia, Miguel; Soriano, Jordi

2013-01-01

Neuronal networks in vitro are prominent systems to study the development of connections in living neuronal networks and the interplay between connectivity, activity and function. These cultured networks show a rich spontaneous activity that evolves concurrently with the connectivity of the underlying network. In this work we monitor the development of neuronal cultures, and record their activity using calcium fluorescence imaging. We use spectral analysis to characterize global dynamical and structural traits of the neuronal cultures. We first observe that the power spectrum can be used as a signature of the state of the network, for instance when inhibition is active or silent, as well as a measure of the network's connectivity strength. Second, the power spectrum identifies prominent developmental changes in the network such as GABAA switch. And third, the analysis of the spatial distribution of the spectral density, in experiments with a controlled disintegration of the network through CNQX, an AMPA-glutamate receptor antagonist in excitatory neurons, reveals the existence of communities of strongly connected, highly active neurons that display synchronous oscillations. Our work illustrates the interest of spectral analysis for the study of in vitro networks, and its potential use as a network-state indicator, for instance to compare healthy and diseased neuronal networks.

Cortical GABAergic excitation contributes to epileptic activities around human glioma

PubMed Central

Pallud, Johan; Varlet, Pascale; Cresto, Noemie; Baulac, Michel; Duyckaerts, Charles; Kourdougli, Nazim; Chazal, Geneviève; Devaux, Bertrand; Rivera, Claudio; Miles, Richard; Capelle, Laurent; Huberfeld, Gilles

2015-01-01

Rationale Diffuse brain gliomas induce seizures in a majority of patients. As in most epileptic disorders, excitatory glutamatergic mechanisms are involved in the generation of epileptic activities in the neocortex surrounding gliomas. However, chloride homeostasis is known to be perturbed in glial tumor cells. Thus the contribution of GABAergic mechanisms which depend on intracellular chloride and which are defective or pro-epileptic in other structural epilepsies merits closer study. Objective We studied in neocortical slices from the peritumoral security margin resected around human brain gliomas, the occurrence, networks, cells and signaling basis of epileptic activities. Results Postoperative glioma tissue from 69% of patients spontaneously generated interictal-like discharges. These events were synchronized, with a high frequency oscillation signature, in superficial layers of neocortex around glioma areas with tumor infiltration. Interictal-like events depended on both glutamatergic transmission and on depolarizing GABAergic signaling. About 65% of pyramidal cells were depolarized by GABA released by interneurons. This effect was related to perturbations in Chloride homeostasis, due to changes in expression of chloride co-transporters: KCC2 was reduced and expression of NKCC1 increased. Ictal-like activities were initiated by convulsant stimuli exclusively in these epileptogenic areas. Conclusions Epileptic activities are sustained by excitatory effects of GABA in the peritumoral human neocortex, as in temporal lobe epilepsies. Glutamate and GABA signaling are involved in oncogenesis and chloride homeostasis is perturbed. These same factors, induce an imbalance between synaptic excitatory and inhibition underly epileptic discharges in tumor patients. PMID:25009229

The Influence of Mexican Hat Recurrent Connectivity on Noise Correlations and Stimulus Encoding

PubMed Central

Meyer, Robert; Ladenbauer, Josef; Obermayer, Klaus

2017-01-01

Noise correlations are a common feature of neural responses and have been observed in many cortical areas across different species. These correlations can influence information processing by enhancing or diminishing the quality of the neural code, but the origin of these correlations is still a matter of controversy. In this computational study we explore the hypothesis that noise correlations are the result of local recurrent excitatory and inhibitory connections. We simulated two-dimensional networks of adaptive spiking neurons with local connection patterns following Gaussian kernels. Noise correlations decay with distance between neurons but are only observed if the range of excitatory connections is smaller than the range of inhibitory connections (“Mexican hat” connectivity) and if the connection strengths are sufficiently strong. These correlations arise from a moving blob-like structure of evoked activity, which is absent if inhibitory interactions have a smaller range (“inverse Mexican hat” connectivity). Spatially structured external inputs fixate these blobs to certain locations and thus effectively reduce noise correlations. We further investigated the influence of these network configurations on stimulus encoding. On the one hand, the observed correlations diminish information about a stimulus encoded by a network. On the other hand, correlated activity allows for more precise encoding of stimulus information if the decoder has only access to a limited amount of neurons. PMID:28539881

Hunger and Satiety Signaling: Modeling Two Hypothalamomedullary Pathways for Energy Homeostasis.

PubMed

Nakamura, Kazuhiro; Nakamura, Yoshiko

2018-06-04

The recent discovery of the medullary circuit driving "hunger responses" - reduced thermogenesis and promoted feeding - has greatly expanded our knowledge on the central neural networks for energy homeostasis. However, how hypothalamic hunger and satiety signals generated under fasted and fed conditions, respectively, control the medullary autonomic and somatic motor mechanisms remains unknown. Here, in reviewing this field, we propose two hypothalamomedullary neural pathways for hunger and satiety signaling. To trigger hunger signaling, neuropeptide Y activates a group of neurons in the paraventricular hypothalamic nucleus (PVH), which then stimulate an excitatory pathway to the medullary circuit to drive the hunger responses. In contrast, melanocortin-mediated satiety signaling activates a distinct group of PVH neurons, which then stimulate a putatively inhibitory pathway to the medullary circuit to counteract the hunger signaling. The medullary circuit likely contains inhibitory and excitatory premotor neurons whose alternate phasic activation generates the coordinated masticatory motor rhythms to promote feeding. © 2018 The Authors. BioEssays Published by WILEY Periodicals, Inc.

Hopf bifurcation in a nonlocal nonlinear transport equation stemming from stochastic neural dynamics

NASA Astrophysics Data System (ADS)

Drogoul, Audric; Veltz, Romain

2017-02-01

In this work, we provide three different numerical evidences for the occurrence of a Hopf bifurcation in a recently derived [De Masi et al., J. Stat. Phys. 158, 866-902 (2015) and Fournier and löcherbach, Ann. Inst. H. Poincaré Probab. Stat. 52, 1844-1876 (2016)] mean field limit of a stochastic network of excitatory spiking neurons. The mean field limit is a challenging nonlocal nonlinear transport equation with boundary conditions. The first evidence relies on the computation of the spectrum of the linearized equation. The second stems from the simulation of the full mean field. Finally, the last evidence comes from the simulation of the network for a large number of neurons. We provide a "recipe" to find such bifurcation which nicely complements the works in De Masi et al. [J. Stat. Phys. 158, 866-902 (2015)] and Fournier and löcherbach [Ann. Inst. H. Poincaré Probab. Stat. 52, 1844-1876 (2016)]. This suggests in return to revisit theoretically these mean field equations from a dynamical point of view. Finally, this work shows how the noise level impacts the transition from asynchronous activity to partial synchronization in excitatory globally pulse-coupled networks.

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.

An integrate-and-fire model for synchronized bursting in a network of cultured cortical neurons.

PubMed

French, D A; Gruenstein, E I

2006-12-01

It has been suggested that spontaneous synchronous neuronal activity is an essential step in the formation of functional networks in the central nervous system. The key features of this type of activity consist of bursts of action potentials with associated spikes of elevated cytoplasmic calcium. These features are also observed in networks of rat cortical neurons that have been formed in culture. Experimental studies of these cultured networks have led to several hypotheses for the mechanisms underlying the observed synchronized oscillations. In this paper, bursting integrate-and-fire type mathematical models for regular spiking (RS) and intrinsic bursting (IB) neurons are introduced and incorporated through a small-world connection scheme into a two-dimensional excitatory network similar to those in the cultured network. This computer model exhibits spontaneous synchronous activity through mechanisms similar to those hypothesized for the cultured experimental networks. Traces of the membrane potential and cytoplasmic calcium from the model closely match those obtained from experiments. We also consider the impact on network behavior of the IB neurons, the geometry and the small world connection scheme.

Human brain networks function in connectome-specific harmonic waves.

PubMed

Atasoy, Selen; Donnelly, Isaac; Pearson, Joel

2016-01-21

A key characteristic of human brain activity is coherent, spatially distributed oscillations forming behaviour-dependent brain networks. However, a fundamental principle underlying these networks remains unknown. Here we report that functional networks of the human brain are predicted by harmonic patterns, ubiquitous throughout nature, steered by the anatomy of the human cerebral cortex, the human connectome. We introduce a new technique extending the Fourier basis to the human connectome. In this new frequency-specific representation of cortical activity, that we call 'connectome harmonics', oscillatory networks of the human brain at rest match harmonic wave patterns of certain frequencies. We demonstrate a neural mechanism behind the self-organization of connectome harmonics with a continuous neural field model of excitatory-inhibitory interactions on the connectome. Remarkably, the critical relation between the neural field patterns and the delicate excitation-inhibition balance fits the neurophysiological changes observed during the loss and recovery of consciousness.

Regulation of Brain-Derived Neurotrophic Factor Exocytosis and Gamma-Aminobutyric Acidergic Interneuron Synapse by the Schizophrenia Susceptibility Gene Dysbindin-1.

PubMed

Yuan, Qiang; Yang, Feng; Xiao, Yixin; Tan, Shawn; Husain, Nilofer; Ren, Ming; Hu, Zhonghua; Martinowich, Keri; Ng, Julia S; Kim, Paul J; Han, Weiping; Nagata, Koh-Ichi; Weinberger, Daniel R; Je, H Shawn

2016-08-15

Genetic variations in dystrobrevin binding protein 1 (DTNBP1 or dysbindin-1) have been implicated as risk factors in the pathogenesis of schizophrenia. The encoded protein dysbindin-1 functions in the regulation of synaptic activity and synapse development. Intriguingly, a loss of function mutation in Dtnbp1 in mice disrupted both glutamatergic and gamma-aminobutyric acidergic transmission in the cerebral cortex; pyramidal neurons displayed enhanced excitability due to reductions in inhibitory synaptic inputs. However, the mechanism by which reduced dysbindin-1 activity causes inhibitory synaptic deficits remains unknown. We investigated the role of dysbindin-1 in the exocytosis of brain-derived neurotrophic factor (BDNF) from cortical excitatory neurons, organotypic brain slices, and acute slices from dysbindin-1 mutant mice and determined how this change in BDNF exocytosis transsynaptically affected the number of inhibitory synapses formed on excitatory neurons via whole-cell recordings, immunohistochemistry, and live-cell imaging using total internal reflection fluorescence microscopy. A decrease in dysbindin-1 reduces the exocytosis of BDNF from cortical excitatory neurons, and this reduction in BDNF exocytosis transsynaptically resulted in reduced inhibitory synapse numbers formed on excitatory neurons. Furthermore, application of exogenous BDNF rescued the inhibitory synaptic deficits caused by the reduced dysbindin-1 level in both cultured cortical neurons and slice cultures. Taken together, our results demonstrate that these two genes linked to risk for schizophrenia (BDNF and dysbindin-1) function together to regulate interneuron development and cortical network activity. This evidence supports the investigation of the association between dysbindin-1 and BDNF in humans with schizophrenia. Copyright © 2016 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Optogenetic dissection reveals multiple rhythmogenic modules underlying locomotion

PubMed Central

Hägglund, Martin; Dougherty, Kimberly J.; Borgius, Lotta; Itohara, Shigeyoshi; Iwasato, Takuji; Kiehn, Ole

2013-01-01

Neural networks in the spinal cord known as central pattern generators produce the sequential activation of muscles needed for locomotion. The overall locomotor network architectures in limbed vertebrates have been much debated, and no consensus exists as to how they are structured. Here, we use optogenetics to dissect the excitatory and inhibitory neuronal populations and probe the organization of the mammalian central pattern generator. We find that locomotor-like rhythmic bursting can be induced unilaterally or independently in flexor or extensor networks. Furthermore, we show that individual flexor motor neuron pools can be recruited into bursting without any activity in other nearby flexor motor neuron pools. Our experiments differentiate among several proposed models for rhythm generation in the vertebrates and show that the basic structure underlying the locomotor network has a distributed organization with many intrinsically rhythmogenic modules. PMID:23798384

Dissecting local circuits in vivo: integrated optogenetic and electrophysiology approaches for exploring inhibitory regulation of cortical activity.

PubMed

Cardin, Jessica A

2012-01-01

Local cortical circuit activity in vivo comprises a complex and flexible series of interactions between excitatory and inhibitory neurons. Our understanding of the functional interactions between these different neural populations has been limited by the difficulty of identifying and selectively manipulating the diverse and sparsely represented inhibitory interneuron classes in the intact brain. The integration of recently developed optical tools with traditional electrophysiological techniques provides a powerful window into the role of inhibition in regulating the activity of excitatory neurons. In particular, optogenetic targeting of specific cell classes reveals the distinct impacts of local inhibitory populations on other neurons in the surrounding local network. In addition to providing the ability to activate or suppress spiking in target cells, optogenetic activation identifies extracellularly recorded neurons by class, even when naturally occurring spike rates are extremely low. However, there are several important limitations on the use of these tools and the interpretation of resulting data. The purpose of this article is to outline the uses and limitations of optogenetic tools, along with current methods for achieving cell type-specific expression, and to highlight the advantages of an experimental approach combining optogenetics and electrophysiology to explore the role of inhibition in active networks. To illustrate the efficacy of these combined approaches, I present data comparing targeted manipulations of cortical fast-spiking, parvalbumin-expressing and low threshold-spiking, somatostatin-expressing interneurons in vivo. Copyright © 2011 Elsevier Ltd. All rights reserved.

A Million-Plus Neuron Model of the Hippocampal Dentate Gyrus: Critical Role for Topography in Determining Spatiotemporal Network Dynamics.

PubMed

Hendrickson, Phillip J; Yu, Gene J; Song, Dong; Berger, Theodore W

2016-01-01

This paper describes a million-plus granule cell compartmental model of the rat hippocampal dentate gyrus, including excitatory, perforant path input from the entorhinal cortex, and feedforward and feedback inhibitory input from dentate interneurons. The model includes experimentally determined morphological and biophysical properties of granule cells, together with glutamatergic AMPA-like EPSP and GABAergic GABAA-like IPSP synaptic excitatory and inhibitory inputs, respectively. Each granule cell was composed of approximately 200 compartments having passive and active conductances distributed throughout the somatic and dendritic regions. Modeling excitatory input from the entorhinal cortex was guided by axonal transport studies documenting the topographical organization of projections from subregions of the medial and lateral entorhinal cortex, plus other important details of the distribution of glutamatergic inputs to the dentate gyrus. Information contained within previously published maps of this major hippocampal afferent were systematically converted to scales that allowed the topographical distribution and relative synaptic densities of perforant path inputs to be quantitatively estimated for inclusion in the current model. Results showed that when medial and lateral entorhinal cortical neurons maintained Poisson random firing, dentate granule cells expressed, throughout the million-cell network, a robust nonrandom pattern of spiking best described as a spatiotemporal "clustering." To identify the network property or properties responsible for generating such firing "clusters," we progressively eliminated from the model key mechanisms, such as feedforward and feedback inhibition, intrinsic membrane properties underlying rhythmic burst firing, and/or topographical organization of entorhinal afferents. Findings conclusively identified topographical organization of inputs as the key element responsible for generating a spatiotemporal distribution of clustered firing. These results uncover a functional organization of perforant path afferents to the dentate gyrus not previously recognized: topography-dependent clusters of granule cell activity as "functional units" or "channels" that organize the processing of entorhinal signals. This modeling study also reveals for the first time how a global signal processing feature of a neural network can evolve from one of its underlying structural characteristics.

A Million-Plus Neuron Model of the Hippocampal Dentate Gyrus: Critical Role for Topography in Determining Spatio-Temporal Network Dynamics

PubMed Central

Hendrickson, Phillip J.; Yu, Gene J.; Song, Dong; Berger, Theodore W.

2016-01-01

Goal This manuscript describes a million-plus granule cell compartmental model of the rat hippocampal dentate gyrus, including excitatory, perforant path input from the entorhinal cortex, and feedforward and feedback inhibitory input from dentate interneurons. Methods The model includes experimentally determined morphological and biophysical properties of granule cells, together with glutamatergic AMPA-like EPSP and GABAergic GABAA-like IPSP synaptic excitatory and inhibitory inputs, respectively. Each granule cell was composed of approximately 200 compartments having passive and active conductances distributed throughout the somatic and dendritic regions. Modeling excitatory input from the entorhinal cortex was guided by axonal transport studies documenting the topographical organization of projections from subregions of the medial and lateral entorhinal cortex, plus other important details of the distribution of glutamatergic inputs to the dentate gyrus. Information contained within previously published maps of this major hippocampal afferent were systematically converted to scales that allowed the topographical distribution and relative synaptic densities of perforant path inputs to be quantitatively estimated for inclusion in the current model. Results Results showed that when medial and lateral entorhinal cortical neurons maintained Poisson random firing, dentate granule cells expressed, throughout the million-cell network, a robust, non-random pattern of spiking best described as spatio-temporal “clustering”. To identify the network property or properties responsible for generating such firing “clusters”, we progressively eliminated from the model key mechanisms such as feedforward and feedback inhibition, intrinsic membrane properties underlying rhythmic burst firing, and/or topographical organization of entorhinal afferents. Conclusion Findings conclusively identified topographical organization of inputs as the key element responsible for generating a spatio-temporal distribution of clustered firing. These results uncover a functional organization of perforant path afferents to the dentate gyrus not previously recognized: topography-dependent clusters of granule cell activity as “functional units” or “channels” that organize the processing of entorhinal signals. This modeling study also reveals for the first time how a global signal processing feature of a neural network can evolve from one of its underlying structural characteristics. PMID:26087482

Animal-to-animal variability in the phasing of the crustacean cardiac motor pattern: an experimental and computational analysis

PubMed Central

Williams, Alex H.; Kwiatkowski, Molly A.; Mortimer, Adam L.; Marder, Eve; Zeeman, Mary Lou

2013-01-01

The cardiac ganglion (CG) of Homarus americanus is a central pattern generator that consists of two oscillatory groups of neurons: “small cells” (SCs) and “large cells” (LCs). We have shown that SCs and LCs begin their bursts nearly simultaneously but end their bursts at variable phases. This variability contrasts with many other central pattern generator systems in which phase is well maintained. To determine both the consequences of this variability and how CG phasing is controlled, we modeled the CG as a pair of Morris-Lecar oscillators coupled by electrical and excitatory synapses and constructed a database of 15,000 simulated networks using random parameter sets. These simulations, like our experimental results, displayed variable phase relationships, with the bursts beginning together but ending at variable phases. The model suggests that the variable phasing of the pattern has important implications for the functional role of the excitatory synapses. In networks in which the two oscillators had similar duty cycles, the excitatory coupling functioned to increase cycle frequency. In networks with disparate duty cycles, it functioned to decrease network frequency. Overall, we suggest that the phasing of the CG may vary without compromising appropriate motor output and that this variability may critically determine how the network behaves in response to manipulations. PMID:23446690

Impaired action potential initiation in GABAergic interneurons causes hyperexcitable networks in an epileptic mouse model carrying a human Na(V)1.1 mutation.

PubMed

Hedrich, Ulrike B S; Liautard, Camille; Kirschenbaum, Daniel; Pofahl, Martin; Lavigne, Jennifer; Liu, Yuanyuan; Theiss, Stephan; Slotta, Johannes; Escayg, Andrew; Dihné, Marcel; Beck, Heinz; Mantegazza, Massimo; Lerche, Holger

2014-11-05

Mutations in SCN1A and other ion channel genes can cause different epileptic phenotypes, but the precise mechanisms underlying the development of hyperexcitable networks are largely unknown. Here, we present a multisystem analysis of an SCN1A mouse model carrying the NaV1.1-R1648H mutation, which causes febrile seizures and epilepsy in humans. We found a ubiquitous hypoexcitability of interneurons in thalamus, cortex, and hippocampus, without detectable changes in excitatory neurons. Interestingly, somatic Na(+) channels in interneurons and persistent Na(+) currents were not significantly changed. Instead, the key mechanism of interneuron dysfunction was a deficit of action potential initiation at the axon initial segment that was identified by analyzing action potential firing. This deficit increased with the duration of firing periods, suggesting that increased slow inactivation, as recorded for recombinant mutated channels, could play an important role. The deficit in interneuron firing caused reduced action potential-driven inhibition of excitatory neurons as revealed by less frequent spontaneous but not miniature IPSCs. Multiple approaches indicated increased spontaneous thalamocortical and hippocampal network activity in mutant mice, as follows: (1) more synchronous and higher-frequency firing was recorded in primary neuronal cultures plated on multielectrode arrays; (2) thalamocortical slices examined by field potential recordings revealed spontaneous activities and pathological high-frequency oscillations; and (3) multineuron Ca(2+) imaging in hippocampal slices showed increased spontaneous neuronal activity. Thus, an interneuron-specific generalized defect in action potential initiation causes multisystem disinhibition and network hyperexcitability, which can well explain the occurrence of seizures in the studied mouse model and in patients carrying this mutation. Copyright © 2014 the authors 0270-6474/14/3414874-16$15.00/0.

The Effect of Inhibitory Neuron on the Evolution Model of Higher-Order Coupling Neural Oscillator Population

PubMed Central

Qi, Yi; Wang, Rubin; Jiao, Xianfa; Du, Ying

2014-01-01

We proposed a higher-order coupling neural network model including the inhibitory neurons and examined the dynamical evolution of average number density and phase-neural coding under the spontaneous activity and external stimulating condition. The results indicated that increase of inhibitory coupling strength will cause decrease of average number density, whereas increase of excitatory coupling strength will cause increase of stable amplitude of average number density. Whether the neural oscillator population is able to enter the new synchronous oscillation or not is determined by excitatory and inhibitory coupling strength. In the presence of external stimulation, the evolution of the average number density is dependent upon the external stimulation and the coupling term in which the dominator will determine the final evolution. PMID:24516505

Excitatory Synaptic Drive and Feedforward Inhibition in the Hippocampal CA3 Circuit Are Regulated by SynCAM 1.

PubMed

Park, Kellie A; Ribic, Adema; Laage Gaupp, Fabian M; Coman, Daniel; Huang, Yuegao; Dulla, Chris G; Hyder, Fahmeed; Biederer, Thomas

2016-07-13

Select adhesion proteins control the development of synapses and modulate their structural and functional properties. Despite these important roles, the extent to which different synapse-organizing mechanisms act across brain regions to establish connectivity and regulate network properties is incompletely understood. Further, their functional roles in different neuronal populations remain to be defined. Here, we applied diffusion tensor imaging (DTI), a modality of magnetic resonance imaging (MRI), to map connectivity changes in knock-out (KO) mice lacking the synaptogenic cell adhesion protein SynCAM 1. This identified reduced fractional anisotropy in the hippocampal CA3 area in absence of SynCAM 1. In agreement, mossy fiber refinement in CA3 was impaired in SynCAM 1 KO mice. Mossy fibers make excitatory inputs onto postsynaptic specializations of CA3 pyramidal neurons termed thorny excrescences and these structures were smaller in the absence of SynCAM 1. However, the most prevalent targets of mossy fibers are GABAergic interneurons and SynCAM 1 loss unexpectedly reduced the number of excitatory terminals onto parvalbumin (PV)-positive interneurons in CA3. SynCAM 1 KO mice additionally exhibited lower postsynaptic GluA1 expression in these PV-positive interneurons. These synaptic imbalances in SynCAM 1 KO mice resulted in CA3 disinhibition, in agreement with reduced feedforward inhibition in this network in the absence of SynCAM 1-dependent excitatory drive onto interneurons. In turn, mice lacking SynCAM 1 were impaired in memory tasks involving CA3. Our results support that SynCAM 1 modulates excitatory mossy fiber inputs onto both interneurons and principal neurons in the hippocampal CA3 area to balance network excitability. This study advances our understanding of synapse-organizing mechanisms on two levels. First, the data support that synaptogenic proteins guide connectivity and can function in distinct brain regions even if they are expressed broadly. Second, the results demonstrate that a synaptogenic process that controls excitatory inputs to both pyramidal neurons and interneurons can balance excitation and inhibition. Specifically, the study reveals that hippocampal CA3 connectivity is modulated by the synapse-organizing adhesion protein SynCAM 1 and identifies a novel, SynCAM 1-dependent mechanism that controls excitatory inputs onto parvalbumin-positive interneurons. This enables SynCAM 1 to regulate feedforward inhibition and set network excitability. Further, we show that diffusion tensor imaging is sensitive to these cellular refinements affecting neuronal connectivity. Copyright © 2016 the authors 0270-6474/16/367465-12$15.00/0.

A neural mass model of basal ganglia nuclei simulates pathological beta rhythm in Parkinson's disease

NASA Astrophysics Data System (ADS)

Liu, Fei; Wang, Jiang; Liu, Chen; Li, Huiyan; Deng, Bin; Fietkiewicz, Chris; Loparo, Kenneth A.

2016-12-01

An increase in beta oscillations within the basal ganglia nuclei has been shown to be associated with movement disorder, such as Parkinson's disease. The motor cortex and an excitatory-inhibitory neuronal network composed of the subthalamic nucleus (STN) and the external globus pallidus (GPe) are thought to play an important role in the generation of these oscillations. In this paper, we propose a neuron mass model of the basal ganglia on the population level that reproduces the Parkinsonian oscillations in a reciprocal excitatory-inhibitory network. Moreover, it is shown that the generation and frequency of these pathological beta oscillations are varied by the coupling strength and the intrinsic characteristics of the basal ganglia. Simulation results reveal that increase of the coupling strength induces the generation of the beta oscillation, as well as enhances the oscillation frequency. However, for the intrinsic properties of each nucleus in the excitatory-inhibitory network, the STN primarily influences the generation of the beta oscillation while the GPe mainly determines its frequency. Interestingly, describing function analysis applied on this model theoretically explains the mechanism of pathological beta oscillations.

Dynamic changes in neural circuit topology following mild mechanical injury in vitro.

PubMed

Patel, Tapan P; Ventre, Scott C; Meaney, David F

2012-01-01

Despite its enormous incidence, mild traumatic brain injury is not well understood. One aspect that needs more definition is how the mechanical energy during injury affects neural circuit function. Recent developments in cellular imaging probes provide an opportunity to assess the dynamic state of neural networks with single-cell resolution. In this article, we developed imaging methods to assess the state of dissociated cortical networks exposed to mild injury. We estimated the imaging conditions needed to achieve accurate measures of network properties, and applied these methodologies to evaluate if mild mechanical injury to cortical neurons produces graded changes to either spontaneous network activity or altered network topology. We found that modest injury produced a transient increase in calcium activity that dissipated within 1 h after injury. Alternatively, moderate mechanical injury produced immediate disruption in network synchrony, loss in excitatory tone, and increased modular topology. A calcium-activated neutral protease (calpain) was a key intermediary in these changes; blocking calpain activation restored the network nearly completely to its pre-injury state. Together, these findings show a more complex change in neural circuit behavior than previously reported for mild mechanical injury, and highlight at least one important early mechanism responsible for these changes.

Gamma Rhythm Simulations in Alzheimer's Disease

NASA Astrophysics Data System (ADS)

Montgomery, Samuel; Perez, Carlos; Ullah, Ghanim

The different neural rhythms that occur during the sleep-wake cycle regulate the brain's multiple functions. Memory acquisition occurs during fast gamma rhythms during consciousness, while slow oscillations mediate memory consolidation and erasure during sleep. At the neural network level, these rhythms are generated by the finely timed activity within excitatory and inhibitory neurons. In Alzheimer's Disease (AD) the function of inhibitory neurons is compromised due to an increase in amyloid beta (A β) leading to elevated sodium leakage from extracellular space in the hippocampus. Using a Hodgkin-Huxley formalism, heightened sodium leakage current into inhibitory neurons is observed to compromise functionality. Using a simple two neuron system it was observed that as the conductance of the sodium leakage current is increased in inhibitory neurons there is a significant decrease in spiking frequency regarding the membrane potential. This triggers a significant increase in excitatory spiking leading to aberrant network behavior similar to that seen in AD patients. The next step is to extend this model to a larger neuronal system with varying synaptic densities and conductance strengths as well as deterministic and stochastic drives.

Shunting inhibition improves robustness of gamma oscillations in hippocampal interneuron networks by homogenizing firing rates.

PubMed

Vida, Imre; Bartos, Marlene; Jonas, Peter

2006-01-05

Networks of GABAergic neurons are key elements in the generation of gamma oscillations in the brain. Computational studies suggested that the emergence of coherent oscillations requires hyperpolarizing inhibition. Here, we show that GABA(A) receptor-mediated inhibition in mature interneurons of the hippocampal dentate gyrus is shunting rather than hyperpolarizing. Unexpectedly, when shunting inhibition is incorporated into a structured interneuron network model with fast and strong synapses, coherent oscillations emerge. In comparison to hyperpolarizing inhibition, networks with shunting inhibition show several advantages. First, oscillations are generated with smaller tonic excitatory drive. Second, network frequencies are tuned to the gamma band. Finally, robustness against heterogeneity in the excitatory drive is markedly improved. In single interneurons, shunting inhibition shortens the interspike interval for low levels of drive but prolongs it for high levels, leading to homogenization of neuronal firing rates. Thus, shunting inhibition may confer increased robustness to gamma oscillations in the brain.

Synaptic Impairment and Robustness of Excitatory Neuronal Networks with Different Topologies

PubMed Central

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

2017-01-01

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

Neocortical inhibitory activities and long-range afferents contribute to the synchronous onset of silent states of the neocortical slow oscillation.

PubMed

Lemieux, Maxime; Chauvette, Sylvain; Timofeev, Igor

2015-02-01

During slow-wave sleep, neurons of the thalamocortical network are engaged in a slow oscillation (<1 Hz), which consists of an alternation between the active and the silent states. Several studies have provided insights on the transition from the silent, which are essentially periods of disfacilitation, to the active states. However, the conditions leading to the synchronous onset of the silent state remain elusive. We hypothesized that a synchronous input to local inhibitory neurons could contribute to the transition to the silent state in the cat suprasylvian gyrus during natural sleep and under ketamine-xylazine anesthesia. After partial and complete deafferentation of the cortex, we found that the silent state onset was more variable among remote sites. We found that the transition to the silent state was preceded by a reduction in excitatory postsynaptic potentials and firing probability in cortical neurons. We tested the impact of chloride-mediated inhibition in the silent-state onset. We uncovered a long-duration (100-300 ms) inhibitory barrage occurring about 250 ms before the silent state onset in 3-6% of neurons during anesthesia and in 12-15% of cases during natural sleep. These inhibitory activities caused a decrease in cortical firing that reduced the excitatory drive in the neocortical network. That chain reaction of disfacilitation ends up on the silent state. Electrical stimuli could trigger a network silent state with a maximal efficacy in deep cortical layers. We conclude that long-range afferents to the neocortex and chloride-mediated inhibition play a role in the initiation of the silent state. Copyright © 2015 the American Physiological Society.

Spiking neural network model for memorizing sequences with forward and backward recall.

PubMed

Borisyuk, Roman; Chik, David; Kazanovich, Yakov; da Silva Gomes, João

2013-06-01

We present an oscillatory network of conductance based spiking neurons of Hodgkin-Huxley type as a model of memory storage and retrieval of sequences of events (or objects). The model is inspired by psychological and neurobiological evidence on sequential memories. The building block of the model is an oscillatory module which contains excitatory and inhibitory neurons with all-to-all connections. The connection architecture comprises two layers. A lower layer represents consecutive events during their storage and recall. This layer is composed of oscillatory modules. Plastic excitatory connections between the modules are implemented using an STDP type learning rule for sequential storage. Excitatory neurons in the upper layer project star-like modifiable connections toward the excitatory lower layer neurons. These neurons in the upper layer are used to tag sequences of events represented in the lower layer. Computer simulations demonstrate good performance of the model including difficult cases when different sequences contain overlapping events. We show that the model with STDP type or anti-STDP type learning rules can be applied for the simulation of forward and backward replay of neural spikes respectively. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

The Mammalian Cortex as a Self-Organizing Complex System: Multi-Scale Homeostatic Approaches to Criticality via Dynamical Balance of Inhibition against Excitation

NASA Astrophysics Data System (ADS)

Ng, Tony T.

The mammalian cortex is a highly structured network of densely packed neurons that interact strongly with each other in very specific ways. Loosely speaking, neurons are cells that fire clicks at each other as a means of communication. Common sites of communication, known as synapses, are enabled by transmitter molecules released from presynaptic sender cells, which bind to receptors on postsynaptic receiver cells. There are two major classes of neurons - excitatory ones that prompt their downstream neighbors to fire spikes through depolarization, and inhibitory ones that suppress spike activity of their postsynaptic partners via hyperpolarization. Depolarization and hyperpolarization make membrane potential of a cell more positive and more negative, respectively. A sufficiently depolarized neuron fires a spike, which technically is called an action potential. In this thesis, we focus on the interplay between three of the cortex's most ubiquitous features and examine some of the consequences that their interactions have on cortical dynamics. One of the features, widespread projections between clusters of excitatory neurons, is topological. The two remaining features, homeostasis and balance between the amount of excitatory and inhibitory activity are dynamical. Here, homeostasis refers to the regulatory mechanism of individual cells or collections of cells that maintains constant levels of spike activity over time. Simply by varying the average homeostatic firing rate in clusters of excitatory neurons or by tuning the common homoeostatic rate of individual inhibitory neurons, we show via simulation that cluster-based activity bursts can exhibit critical dynamics and display power-law distributions with exponents that are consistent with those found in in vivo experiments of awake animals. Criticality is an idea that originated in statistical physics. At the critical point, activity levels of sites across an entire system, such as those of different cortical regions across the brain, can dynamically correlate not only over short distances, but also over large distances. The spatial extent of time-varying signal propagation can range from a couple of regions to a dozen regions to hundreds and thousands of regions and beyond. It has been shown in previous studies that size of a network's pattern repertoire, degree of information transmission from stimuli to responses, and potential to respond to a large range of stimulus intensities, are maximized at the critical state. In addition to demonstrating the presence of criticality in our class of networks, we show that (1) another pervasive connectivity motif in the cortex is incapable of supporting criticality, (2) excitation-inhibition balance modulates the distribution of spike-based bursts of various sizes, (3) how critical dynamics at the cluster level emerges from excitation-inhibition balance, and (4) how we can reconcile differences in burst statistics at spike-based and cluster-based levels observed in animal experiments.

V3 spinal neurons establish a robust and balanced locomotor rhythm during walking.

PubMed

Zhang, Ying; Narayan, Sujatha; Geiman, Eric; Lanuza, Guillermo M; Velasquez, Tomoko; Shanks, Bayle; Akay, Turgay; Dyck, Jason; Pearson, Keir; Gosgnach, Simon; Fan, Chen-Ming; Goulding, Martyn

2008-10-09

A robust and well-organized rhythm is a key feature of many neuronal networks, including those that regulate essential behaviors such as circadian rhythmogenesis, breathing, and locomotion. Here we show that excitatory V3-derived neurons are necessary for a robust and organized locomotor rhythm during walking. When V3-mediated neurotransmission is selectively blocked by the expression of the tetanus toxin light chain subunit (TeNT), the regularity and robustness of the locomotor rhythm is severely perturbed. A similar degeneration in the locomotor rhythm occurs when the excitability of V3-derived neurons is reduced acutely by ligand-induced activation of the allatostatin receptor. The V3-derived neurons additionally function to balance the locomotor output between both halves of the spinal cord, thereby ensuring a symmetrical pattern of locomotor activity during walking. We propose that the V3 neurons establish a regular and balanced motor rhythm by distributing excitatory drive between both halves of the spinal cord.

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.

Regulating the dorsal neural tube expression of Ptf1a through a distal 3' enhancer.

PubMed

Mona, Bishakha; Avila, John M; Meredith, David M; Kollipara, Rahul K; Johnson, Jane E

2016-10-01

Generating the correct balance of inhibitory and excitatory neurons in a neural network is essential for normal functioning of a nervous system. The neural network in the dorsal spinal cord functions in somatosensation where it modulates and relays sensory information from the periphery. PTF1A is a key transcriptional regulator present in a specific subset of neural progenitor cells in the dorsal spinal cord, cerebellum and retina that functions to specify an inhibitory neuronal fate while suppressing excitatory neuronal fates. Thus, the regulation of Ptf1a expression is critical for determining mechanisms controlling neuronal diversity in these regions of the nervous system. Here we identify a sequence conserved, tissue-specific enhancer located 10.8kb 3' of the Ptf1a coding region that is sufficient to direct expression to dorsal neural tube progenitors that give rise to neurons in the dorsal spinal cord in chick and mouse. DNA binding motifs for Paired homeodomain (Pd-HD) and zinc finger (ZF) transcription factors are required for enhancer activity. Mutations in these sequences implicate the Pd-HD motif for activator function and the ZF motif for repressor function. Although no repressor transcription factor was identified, both PAX6 and SOX3 can increase enhancer activity in reporter assays. Thus, Ptf1a is regulated by active and repressive inputs integrated through multiple sequence elements within a highly conserved sequence downstream of the Ptf1a gene. Copyright © 2016 Elsevier Inc. All rights reserved.

Hyperconnectivity and slow synapses during early development of medial prefrontal cortex in a mouse model for mental retardation and autism.

PubMed

Testa-Silva, Guilherme; Loebel, Alex; Giugliano, Michele; de Kock, Christiaan P J; Mansvelder, Huibert D; Meredith, Rhiannon M

2012-06-01

Neuronal theories of neurodevelopmental disorders (NDDs) of autism and mental retardation propose that abnormal connectivity underlies deficits in attentional processing. We tested this theory by studying unitary synaptic connections between layer 5 pyramidal neurons within medial prefrontal cortex (mPFC) networks in the Fmr1-KO mouse model for mental retardation and autism. In line with predictions from neurocognitive theory, we found that neighboring pyramidal neurons were hyperconnected during a critical period in early mPFC development. Surprisingly, excitatory synaptic connections between Fmr1-KO pyramidal neurons were significantly slower and failed to recover from short-term depression as quickly as wild type (WT) synapses. By 4-5 weeks of mPFC development, connectivity rates were identical for both KO and WT pyramidal neurons and synapse dynamics changed from depressing to facilitating responses with similar properties in both groups. We propose that the early alteration in connectivity and synaptic recovery are tightly linked: using a network model, we show that slower synapses are essential to counterbalance hyperconnectivity in order to maintain a dynamic range of excitatory activity. However, the slow synaptic time constants induce decreased responsiveness to low-frequency stimulation, which may explain deficits in integration and early information processing in attentional neuronal networks in NDDs.

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

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

Dynamical responses to external stimuli for both cases of excitatory and inhibitory synchronization in a complex neuronal network.

PubMed

Kim, Sang-Yoon; Lim, Woochang

2017-10-01

For studying how dynamical responses to external stimuli depend on the synaptic-coupling type, we consider two types of excitatory and inhibitory synchronization (i.e., synchronization via synaptic excitation and inhibition) in complex small-world networks of excitatory regular spiking (RS) pyramidal neurons and inhibitory fast spiking (FS) interneurons. For both cases of excitatory and inhibitory synchronization, effects of synaptic couplings on dynamical responses to external time-periodic stimuli S ( t ) (applied to a fraction of neurons) are investigated by varying the driving amplitude A of S ( t ). Stimulated neurons are phase-locked to external stimuli for both cases of excitatory and inhibitory couplings. On the other hand, the stimulation effect on non-stimulated neurons depends on the type of synaptic coupling. The external stimulus S ( t ) makes a constructive effect on excitatory non-stimulated RS neurons (i.e., it causes external phase lockings in the non-stimulated sub-population), while S ( t ) makes a destructive effect on inhibitory non-stimulated FS interneurons (i.e., it breaks up original inhibitory synchronization in the non-stimulated sub-population). As results of these different effects of S ( t ), the type and degree of dynamical response (e.g., synchronization enhancement or suppression), characterized by the dynamical response factor [Formula: see text] (given by the ratio of synchronization degree in the presence and absence of stimulus), are found to vary in a distinctly different way, depending on the synaptic-coupling type. Furthermore, we also measure the matching degree between the dynamics of the two sub-populations of stimulated and non-stimulated neurons in terms of a "cross-correlation" measure [Formula: see text]. With increasing A , based on [Formula: see text], we discuss the cross-correlations between the two sub-populations, affecting the dynamical responses to S ( t ).

Stuck in default mode: inefficient cross-frequency synchronization may lead to age-related short-term memory decline.

PubMed

Pinal, Diego; Zurrón, Montserrat; Díaz, Fernando; Sauseng, Paul

2015-04-01

Aging-related decline in short-term memory capacity seems to be caused by deficient balancing of task-related and resting state brain networks activity; however, the exact neural mechanism underlying this deficit remains elusive. Here, we studied brain oscillatory activity in healthy young and old adults during visual information maintenance in a delayed match-to-sample task. Particular emphasis was on long range phase:amplitude coupling of frontal alpha (8-12 Hz) and posterior fast oscillatory activity (>30 Hz). It is argued that through posterior fast oscillatory activity nesting into the excitatory or the inhibitory phase of frontal alpha wave, long-range networks can be efficiently coupled or decoupled, respectively. On the basis of this mechanism, we show that healthy, elderly participants exhibit a lack of synchronization in task-relevant networks while maintaining synchronized regions of the resting state network. Lacking disconnection of this resting state network is predictive of aging-related short-term memory decline. These results support the idea of inefficient orchestration of competing brain networks in the aging human brain and identify the neural mechanism responsible for this control breakdown. Copyright © 2015 Elsevier Inc. All rights reserved.

Leader neurons in leaky integrate and fire neural network simulations.

PubMed

Zbinden, Cyrille

2011-10-01

In this paper, we highlight the topological properties of leader neurons whose existence is an experimental fact. Several experimental studies show the existence of leader neurons in population bursts of activity in 2D living neural networks (Eytan and Marom, J Neurosci 26(33):8465-8476, 2006; Eckmann et al., New J Phys 10(015011), 2008). A leader neuron is defined as a neuron which fires at the beginning of a burst (respectively network spike) more often than we expect by chance considering its mean firing rate. This means that leader neurons have some burst triggering power beyond a chance-level statistical effect. In this study, we characterize these leader neuron properties. This naturally leads us to simulate neural 2D networks. To build our simulations, we choose the leaky integrate and fire (lIF) neuron model (Gerstner and Kistler 2002; Cessac, J Math Biol 56(3):311-345, 2008), which allows fast simulations (Izhikevich, IEEE Trans Neural Netw 15(5):1063-1070, 2004; Gerstner and Naud, Science 326:379-380, 2009). The dynamics of our lIF model has got stable leader neurons in the burst population that we simulate. These leader neurons are excitatory neurons and have a low membrane potential firing threshold. Except for these two first properties, the conditions required for a neuron to be a leader neuron are difficult to identify and seem to depend on several parameters involved in the simulations themselves. However, a detailed linear analysis shows a trend of the properties required for a neuron to be a leader neuron. Our main finding is: A leader neuron sends signals to many excitatory neurons as well as to few inhibitory neurons and a leader neuron receives only signals from few other excitatory neurons. Our linear analysis exhibits five essential properties of leader neurons each with different relative importance. This means that considering a given neural network with a fixed mean number of connections per neuron, our analysis gives us a way of predicting which neuron is a good leader neuron and which is not. Our prediction formula correctly assesses leadership for at least ninety percent of neurons.

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

Dynamics of excitatory synaptic components in sustained firing at low rates.

PubMed

Wyart, Claire; Cocco, Simona; Bourdieu, Laurent; Léger, Jean-Francois; Herr, Catherine; Chatenay, Didier

2005-06-01

Sustained firing is necessary for the persistent activity associated with working memory. The relative contributions of the reverberation of excitation and of the temporal dynamics of the excitatory postsynaptic potential (EPSP) to the maintenance of activity are difficult to evaluate in classical preparations. We used simplified models of synchronous excitatory networks, hippocampal autapses and pairs, to study the synaptic mechanisms underlying firing at low rates. Calcium imaging and cell attached recordings showed that these neurons spontaneously fired bursts of action potentials that lasted for seconds over a wide range of frequencies. In 2-wk-old cells, the median firing frequency was low (11 +/- 8.8 Hz), whereas in 3- to 4-wk-old cells, it decreased to a very low value (2 +/- 1.3 Hz). In both cases, we have shown that the slowest synaptic component supported firing. In 2-wk-old autapses, antagonists of N-methyl-d-aspartate receptors (NMDARs) induced rare isolated spikes showing that the NMDA component of the EPSP was essential for bursts at low frequency. In 3- to 4-wk-old neurons, the very low frequency firing was maintained without the NMDAR activation. However EGTA-AM or alpha-methyl-4-carboxyphenylglycine (MCPG) removed the very slow depolarizing component of the EPSP and prevented the sustained firing at very low rate. A metabotropic glutamate receptor (mGluR)-activated calcium sensitive conductance is therefore responsible for a very slow synaptic component associated with firing at very low rate. In addition, our observations suggested that the asynchronous release of glutamate might participate also in the recurring bursting.

On the Dynamics of the Spontaneous Activity in Neuronal Networks

PubMed Central

Bonifazi, Paolo; Ruaro, Maria Elisabetta; Torre, Vincent

2007-01-01

Most neuronal networks, even in the absence of external stimuli, produce spontaneous bursts of spikes separated by periods of reduced activity. The origin and functional role of these neuronal events are still unclear. The present work shows that the spontaneous activity of two very different networks, intact leech ganglia and dissociated cultures of rat hippocampal neurons, share several features. Indeed, in both networks: i) the inter-spike intervals distribution of the spontaneous firing of single neurons is either regular or periodic or bursting, with the fraction of bursting neurons depending on the network activity; ii) bursts of spontaneous spikes have the same broad distributions of size and duration; iii) the degree of correlated activity increases with the bin width, and the power spectrum of the network firing rate has a 1/f behavior at low frequencies, indicating the existence of long-range temporal correlations; iv) the activity of excitatory synaptic pathways mediated by NMDA receptors is necessary for the onset of the long-range correlations and for the presence of large bursts; v) blockage of inhibitory synaptic pathways mediated by GABAA receptors causes instead an increase in the correlation among neurons and leads to a burst distribution composed only of very small and very large bursts. These results suggest that the spontaneous electrical activity in neuronal networks with different architectures and functions can have very similar properties and common dynamics. PMID:17502919

Distinct sets of FGF receptors sculpt excitatory and inhibitory synaptogenesis.

PubMed

Dabrowski, Ania; Terauchi, Akiko; Strong, Cameron; Umemori, Hisashi

2015-05-15

Neurons in the brain must establish a balanced network of excitatory and inhibitory synapses during development for the brain to function properly. An imbalance between these synapses underlies various neurological and psychiatric disorders. The formation of excitatory and inhibitory synapses requires precise molecular control. In the hippocampus, the structure crucial for learning and memory, fibroblast growth factor 22 (FGF22) and FGF7 specifically promote excitatory or inhibitory synapse formation, respectively. Knockout of either Fgf gene leads to excitatory-inhibitory imbalance in the mouse hippocampus and manifests in an altered susceptibility to epileptic seizures, underscoring the importance of FGF-dependent synapse formation. However, the receptors and signaling mechanisms by which FGF22 and FGF7 induce excitatory and inhibitory synapse differentiation are unknown. Here, we show that distinct sets of overlapping FGF receptors (FGFRs), FGFR2b and FGFR1b, mediate excitatory or inhibitory presynaptic differentiation in response to FGF22 and FGF7. Excitatory presynaptic differentiation is impaired in Fgfr2b and Fgfr1b mutant mice; however, inhibitory presynaptic defects are only found in Fgfr2b mutants. FGFR2b and FGFR1b are required for an excitatory presynaptic response to FGF22, whereas only FGFR2b is required for an inhibitory presynaptic response to FGF7. We further find that FGFRs are required in the presynaptic neuron to respond to FGF22, and that FRS2 and PI3K, but not PLCγ, mediate FGF22-dependent presynaptic differentiation. Our results reveal the specific receptors and signaling pathways that mediate FGF-dependent presynaptic differentiation, and thereby provide a mechanistic understanding of precise excitatory and inhibitory synapse formation in the mammalian brain. © 2015. Published by The Company of Biologists Ltd.

[Cholinergic nature of hypothalamo-cortical excitatory effects].

PubMed

Kozhechkin, S N

1982-05-01

Excitatory effect of electric stimulation of the ventro-caudal area of the lateral hypothalamus on the neurons of the rabbit optic cortex was seen mainly in the cells whose activity increased under the influence of acetylcholine applied microiontophoretically. Meanwhile atropine applied microiontophoretically decreased or completely blocked the hypothalamic excitatory effect as well as that of acetylcholine. Atropine did not change the depressing influence of the rostral region of the lateral hypothalamus on the neuronal cortical activity. It is concluded that the hypothalamo-cortical excitatory relationships are M-cholinergic in nature.

Dynamics of excitatory and inhibitory networks are differentially altered by selective attention.

PubMed

Snyder, Adam C; Morais, Michael J; Smith, Matthew A

2016-10-01

Inhibition and excitation form two fundamental modes of neuronal interaction, yet we understand relatively little about their distinct roles in service of perceptual and cognitive processes. We developed a multidimensional waveform analysis to identify fast-spiking (putative inhibitory) and regular-spiking (putative excitatory) neurons in vivo and used this method to analyze how attention affects these two cell classes in visual area V4 of the extrastriate cortex of rhesus macaques. We found that putative inhibitory neurons had both greater increases in firing rate and decreases in correlated variability with attention compared with putative excitatory neurons. Moreover, the time course of attention effects for putative inhibitory neurons more closely tracked the temporal statistics of target probability in our task. Finally, the session-to-session variability in a behavioral measure of attention covaried with the magnitude of this effect. Together, these results suggest that selective targeting of inhibitory neurons and networks is a critical mechanism for attentional modulation. Copyright © 2016 the American Physiological Society.

Dynamics of excitatory and inhibitory networks are differentially altered by selective attention

PubMed Central

Snyder, Adam C.; Morais, Michael J.

2016-01-01

Inhibition and excitation form two fundamental modes of neuronal interaction, yet we understand relatively little about their distinct roles in service of perceptual and cognitive processes. We developed a multidimensional waveform analysis to identify fast-spiking (putative inhibitory) and regular-spiking (putative excitatory) neurons in vivo and used this method to analyze how attention affects these two cell classes in visual area V4 of the extrastriate cortex of rhesus macaques. We found that putative inhibitory neurons had both greater increases in firing rate and decreases in correlated variability with attention compared with putative excitatory neurons. Moreover, the time course of attention effects for putative inhibitory neurons more closely tracked the temporal statistics of target probability in our task. Finally, the session-to-session variability in a behavioral measure of attention covaried with the magnitude of this effect. Together, these results suggest that selective targeting of inhibitory neurons and networks is a critical mechanism for attentional modulation. PMID:27466133

Aberrant excitatory rewiring of layer V pyramidal neurons early after neocortical trauma

PubMed Central

Takahashi, D. Koji; Isabel, Feng Gu; Parada, Shri Vyas; Prince, David A.

2016-01-01

Lesioned neuronal circuits form new functional connections after a traumatic brain injury (TBI). In humans and animal models, aberrant excitatory connections that form after TBI may contribute to the pathogenesis of post-traumatic epilepsy. Partial neocortical isolation (“undercut” or “UC”) leads to altered neuronal circuitry and network hyperexcitability recorded in vivo and in brain slices from chronically lesioned neocortex. Recent data suggest a critical period for maladaptive excitatory circuit formation within the first 3 days post UC injury (Graber and Prince, 1999, 2004; Li et al., 2011, 2012b). The present study focuses on alterations in excitatory connectivity within this critical period. Immunoreactivity (IR) for growth-associated protein (GAP)-43 was increased in the UC cortex 3 days after injury. Some GAP-43-expressing excitatory terminals targeted the somata of layer V pyramidal (Pyr) neurons, a domain usually innervated predominantly by inhibitory terminals. Immunocytochemical analysis of pre- and postsynaptic markers showed that putative excitatory synapses were present on somata of these neurons in UC neocortex. Excitatory postsynaptic currents from UC layer V Pyr cells displayed properties consistent with perisomatic inputs and also reflected an increase in the number of synaptic contacts. Laser scanning photostimulation (LSPS) experiments demonstrated reorganized excitatory connectivity after injury within the UC. Concurrent with these changes, spontaneous epileptiform bursts developed in UC slices. Results suggest that aberrant reorganization of excitatory connectivity contributes to early neocortical hyperexcitability in this model. The findings are relevant for understanding the pathophysiology of neocortical post-traumatic epileptogenesis and are important in terms of the timing of potential prophylactic treatments. PMID:26956396

Aberrant excitatory rewiring of layer V pyramidal neurons early after neocortical trauma.

PubMed

Takahashi, D Koji; Gu, Feng; Parada, Isabel; Vyas, Shri; Prince, David A

2016-07-01

Lesioned neuronal circuits form new functional connections after a traumatic brain injury (TBI). In humans and animal models, aberrant excitatory connections that form after TBI may contribute to the pathogenesis of post-traumatic epilepsy. Partial neocortical isolation ("undercut" or "UC") leads to altered neuronal circuitry and network hyperexcitability recorded in vivo and in brain slices from chronically lesioned neocortex. Recent data suggest a critical period for maladaptive excitatory circuit formation within the first 3days post UC injury (Graber and Prince 1999, 2004; Li et al. 2011, 2012b). The present study focuses on alterations in excitatory connectivity within this critical period. Immunoreactivity (IR) for growth-associated protein (GAP)-43 was increased in the UC cortex 3days after injury. Some GAP-43-expressing excitatory terminals targeted the somata of layer V pyramidal (Pyr) neurons, a domain usually innervated predominantly by inhibitory terminals. Immunocytochemical analysis of pre- and postsynaptic markers showed that putative excitatory synapses were present on somata of these neurons in UC neocortex. Excitatory postsynaptic currents from UC layer V Pyr cells displayed properties consistent with perisomatic inputs and also reflected an increase in the number of synaptic contacts. Laser scanning photostimulation (LSPS) experiments demonstrated reorganized excitatory connectivity after injury within the UC. Concurrent with these changes, spontaneous epileptiform bursts developed in UC slices. Results suggest that aberrant reorganization of excitatory connectivity contributes to early neocortical hyperexcitability in this model. The findings are relevant for understanding the pathophysiology of neocortical post-traumatic epileptogenesis and are important in terms of the timing of potential prophylactic treatments. Copyright © 2016 Elsevier Inc. All rights reserved.

Relationship between physiological excitatory and inhibitory measures of excitability in the left vs. right human motor cortex and peripheral electrodermal activity.

PubMed

Bracco, Martina; Turriziani, Patrizia; Smirni, Daniela; Mangano, Renata Giuseppa; Oliveri, Massimiliano

2017-02-22

The current study was aimed at investigating the relationships of excitatory and inhibitory circuits of the left vs. right primary motor cortex with peripheral electrodermal activity (EDA). Ten healthy subjects participated in two experimental sessions. In each session, EDA was recorded for 10min from the palmar surface of the left hand. Immediately after EDA recording, Transcranial Magnetic Stimulation (TMS) was used to probe excitatory and inhibitory circuits of the left or right primary motor cortex using two protocols of stimulation: the input-output curve for recording of motor evoked potentials, for testing excitatory circuits; the long-interval cortical inhibition (LICI) protocol, for testing inhibitory circuits. In both cases, motor evoked potentials were recorded with surface electrodes from a contralateral hand muscle. The main results showed that in the right motor cortex, excitatory circuits directly correlate and inhibitory circuits inversely correlate with sympathetic activation. In the left motor cortex, both excitatory and inhibitory circuits are inversely correlated with sympathetic activation. These findings may suggest a bi-hemispheric mode of control of vegetative system by motor cortices, with the right hemisphere mainly involved in sympathetic control. Copyright © 2017. Published by Elsevier B.V.

Changes in inhibitory CA1 network in dual pathology model of epilepsy.

PubMed

Ouardouz, Mohamed; Carmant, Lionel

2012-01-01

The combination of two precipitating factors appears to be more and more recognized in patients with temporal lobe epilepsy. Using a two-hit rat model, with a neonatal freeze lesion mimicking a focal cortical malformation combined with hyperthermia-induced seizures mimicking febrile seizures, we have previously reported an increase of inhibition in CA1 pyramidal cells at P20. Here, we investigated the changes affecting excitatory and inhibitory drive onto CA1 interneurons to better define the changes in CA1 inhibitory networks and their paradoxical role in epileptogenesis, using electrophysiological recordings in CA1 hippocampus from rat pups (16-20 d old). We investigated interneurons in CA1 hippocampal area located in stratum oriens (Or) and at the border of strata lacunosum and moleculare (L-M). Our results revealed an increase of the excitatory drive to both types of interneurons with no change in the inhibitory drive. The mechanisms underlying the increase of excitatory synaptic currents (EPSCs) in both types of interneurons are different. In Or interneurons, the amplitude of spontaneous and miniature EPSCs increased, while their frequency was not affected suggesting changes at the post-synaptic level. In L-M interneurons, the frequency of spontaneous EPSCs increases, but the amplitude is not affected. Analyses of miniature EPSCs showed no changes in both their frequency and amplitude. We concluded that L-M interneurons increase in excitatory drive is due to a change in Shaffer collateral axon excitability. The changes described here in CA1 inhibitory network may actually contribute to the epileptogenicity observed in this dual pathology model by increasing pyramidal cell synchronization.

Tau Pathology Induces Excitatory Neuron Loss, Grid Cell Dysfunction and Spatial Memory Deficits Reminiscent of Early Alzheimer's Disease

PubMed Central

Fu, Hongjun; Rodriguez, Gustavo A.; Herman, Mathieu; Emrani, Sheina; Nahmani, Eden; Barrett, Geoffrey; Figueroa, Helen Y.; Goldberg, Eliana

2017-01-01

Summary The earliest stages of Alzheimer's disease (AD) are characterized by the formation of mature tangles in the entorhinal cortex and disorientation and confusion navigating familiar places. The medial entorhinal cortex (MEC) contains specialized neurons called grid cells that form part of the spatial navigation system. Here we show in a transgenic mouse model expressing mutant human tau predominantly in the EC that the formation of mature tangles in old mice was associated with excitatory cell loss and deficits in grid cell function, including destabilized grid fields and reduced firing rates, as well as altered network activity. Overt tau pathology in the aged mice was accompanied by spatial memory deficits. Therefore, tau pathology initiated in the entorhinal cortex could lead to deficits in grid cell firing and underlie the deterioration of spatial cognition seen in human AD. PMID:28111080

Collective behavior of networks with linear (VLSI) integrate-and-fire neurons.

PubMed

Fusi, S; Mattia, M

1999-04-01

We analyze in detail the statistical properties of the spike emission process of a canonical integrate-and-fire neuron, with a linear integrator and a lower bound for the depolarization, as often used in VLSI implementations (Mead, 1989). The spike statistics of such neurons appear to be qualitatively similar to conventional (exponential) integrate-and-fire neurons, which exhibit a wide variety of characteristics observed in cortical recordings. We also show that, contrary to current opinion, the dynamics of a network composed of such neurons has two stable fixed points, even in the purely excitatory network, corresponding to two different states of reverberating activity. The analytical results are compared with numerical simulations and are found to be in good agreement.

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

Encoding Time in Feedforward Trajectories of a Recurrent Neural Network Model.

PubMed

Hardy, N F; Buonomano, Dean V

2018-02-01

Brain activity evolves through time, creating trajectories of activity that underlie sensorimotor processing, behavior, and learning and memory. Therefore, understanding the temporal nature of neural dynamics is essential to understanding brain function and behavior. In vivo studies have demonstrated that sequential transient activation of neurons can encode time. However, it remains unclear whether these patterns emerge from feedforward network architectures or from recurrent networks and, furthermore, what role network structure plays in timing. We address these issues using a recurrent neural network (RNN) model with distinct populations of excitatory and inhibitory units. Consistent with experimental data, a single RNN could autonomously produce multiple functionally feedforward trajectories, thus potentially encoding multiple timed motor patterns lasting up to several seconds. Importantly, the model accounted for Weber's law, a hallmark of timing behavior. Analysis of network connectivity revealed that efficiency-a measure of network interconnectedness-decreased as the number of stored trajectories increased. Additionally, the balance of excitation (E) and inhibition (I) shifted toward excitation during each unit's activation time, generating the prediction that observed sequential activity relies on dynamic control of the E/I balance. Our results establish for the first time that the same RNN can generate multiple functionally feedforward patterns of activity as a result of dynamic shifts in the E/I balance imposed by the connectome of the RNN. We conclude that recurrent network architectures account for sequential neural activity, as well as for a fundamental signature of timing behavior: Weber's law.

Temporal sequence learning in winner-take-all networks of spiking neurons demonstrated in a brain-based device.

PubMed

McKinstry, Jeffrey L; Edelman, Gerald M

2013-01-01

Animal behavior often involves a temporally ordered sequence of actions learned from experience. Here we describe simulations of interconnected networks of spiking neurons that learn to generate patterns of activity in correct temporal order. The simulation consists of large-scale networks of thousands of excitatory and inhibitory neurons that exhibit short-term synaptic plasticity and spike-timing dependent synaptic plasticity. The neural architecture within each area is arranged to evoke winner-take-all (WTA) patterns of neural activity that persist for tens of milliseconds. In order to generate and switch between consecutive firing patterns in correct temporal order, a reentrant exchange of signals between these areas was necessary. To demonstrate the capacity of this arrangement, we used the simulation to train a brain-based device responding to visual input by autonomously generating temporal sequences of motor actions.

Purinergic modulation of preBötzinger complex inspiratory rhythm in rodents: the interaction between ATP and adenosine

PubMed Central

Zwicker, J D; Rajani, V; Hahn, L B; Funk, G D

2011-01-01

Abstract ATP signalling in the CNS is mediated by a three-part system comprising the actions of ATP (and ADP) at P2 receptors (P2Rs), adenosine (ADO) at P1 receptors (P1Rs), and ectonucleotidases that degrade ATP into ADO. ATP excites preBötzinger complex (preBötC) inspiratory rhythm-generating networks where its release attenuates the hypoxic depression of breathing. Its metabolite, ADO, inhibits breathing through unknown mechanisms that may involve the preBötC. Our objective is to understand the dynamics of this signalling system and its influence on preBötC networks. We show that the preBötC of mouse and rat is sensitive to P2Y1 purinoceptor (P2Y1R) activation, responding with a >2-fold increase in frequency. Remarkably, the mouse preBötC is insensitive to ATP. Only after block of A1 ADORs is the ATP-evoked, P2Y1R-mediated frequency increase observed. This demonstrates that ATP is rapidly degraded to ADO, which activates inhibitory A1Rs, counteracting the P2Y1R-mediated excitation. ADO sensitivity of mouse preBötC was confirmed by a frequency decrease that was absent in rat. Differential ectonucleotidase activities are likely to contribute to the negligible ATP sensitivity of mouse preBötC. Real-time PCR analysis of ectonucleotidase isoforms in preBötC punches revealed TNAP (degrades ATP to ADO) or ENTPDase2 (favours production of excitatory ADP) as the primary constituent in mouse and rat, respectively. These data further establish the sensitivity of this vital network to P2Y1R-mediated excitation, emphasizing that individual components of the three-part signalling system dramatically alter network responses to ATP. Data also suggest therapeutic potential may derive from methods that alter the ATP–ADO balance to favour the excitatory actions of ATP. PMID:21788352

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.

Mechanisms of excitatory synapse maturation by trans-synaptic organizing complexes

PubMed Central

McMahon, Samuel A.; Díaz, Elva

2011-01-01

Synapses are specialized cell-cell adhesion contacts that mediate communication within neural networks. During development, excitatory synapses are generated by step-wise recruitment of pre- and postsynaptic proteins to sites of contact. Several classes of synaptic organizing complexes have been identified that function during the initial stages of synapse formation. However, mechanisms underlying the later stages of synapse development are less well understood. In recent years, molecules have been discovered that appear to play a role in synapse maturation. In this review, we highlight recent findings that have provided key insights for understanding postsynaptic maturation of developing excitatory synapses with a focus on recruitment of AMPA receptors to developing synapses. PMID:21242087

Entorhinal stellate cells show preferred spike phase-locking to theta inputs that is enhanced by correlations in synaptic activity

PubMed Central

Fernandez, Fernando R.; Malerba, Paola; Bressloff, Paul C.; White, John A.

2013-01-01

In active networks, excitatory and inhibitory synaptic inputs generate membrane voltage fluctuations that drive spike activity in a probabilistic manner. Despite this, some cells in vivo show a strong propensity to precisely lock to the local field potential and maintain a specific spike-phase relationship relative to other cells. In recordings from rat medial entorhinal cortical stellate cells, we measured spike phase-locking in response to sinusoidal “test” inputs in the presence of different forms of background membrane voltage fluctuations, generated via dynamic clamp. We find that stellate cells show strong and robust spike phase-locking to theta (4–12 Hz) inputs. This response occurs under a wide variety of background membrane voltage fluctuation conditions that include a substantial increase in overall membrane conductance. Furthermore, the IH current present in stellate cells is critical to the enhanced spike phase-locking response at theta. Finally, we show that correlations between inhibitory and excitatory conductance fluctuations, which can arise through feed-back and feed-forward inhibition, can substantially enhance the spike phase-locking response. The enhancement in locking is a result of a selective reduction in the size of low frequency membrane voltage fluctuations due to cancelation of inhibitory and excitatory current fluctuations with correlations. Hence, our results demonstrate that stellate cells have a strong preference for spike phase-locking to theta band inputs and that the absolute magnitude of locking to theta can be modulated by the properties of background membrane voltage fluctuations. PMID:23554484

Respiratory Network Stability and Modulatory Response to Substance P Require Nalcn.

PubMed

Yeh, Szu-Ying; Huang, Wei-Hsiang; Wang, Wei; Ward, Christopher S; Chao, Eugene S; Wu, Zhenyu; Tang, Bin; Tang, Jianrong; Sun, Jenny J; Esther van der Heijden, Meike; Gray, Paul A; Xue, Mingshan; Ray, Russell S; Ren, Dejian; Zoghbi, Huda Y

2017-04-19

Respiration is a rhythmic activity as well as one that requires responsiveness to internal and external circumstances; both the rhythm and neuromodulatory responses of breathing are controlled by brainstem neurons in the preBötzinger complex (preBötC) and the retrotrapezoid nucleus (RTN), but the specific ion channels essential to these activities remain to be identified. Because deficiency of sodium leak channel, non-selective (Nalcn) causes lethal apnea in humans and mice, we investigated Nalcn function in these neuronal groups. We found that one-third of mice lacking Nalcn in excitatory preBötC neurons died soon after birth; surviving mice developed apneas in adulthood. Interestingly, in both preBötC and RTN neurons, the Nalcn current influences the resting membrane potential, contributes to maintenance of stable network activity, and mediates modulatory responses to the neuropeptide substance P. These findings reveal Nalcn's specific role in both rhythmic stability and responsiveness to neuropeptides within the respiratory network. Copyright © 2017 Elsevier Inc. All rights reserved.

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

Spatiotemporal discrimination in neural networks with short-term synaptic plasticity

NASA Astrophysics Data System (ADS)

Shlaer, Benjamin; Miller, Paul

2015-03-01

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

Control strategies of 3-cell Central Pattern Generator via global stimuli

NASA Astrophysics Data System (ADS)

Lozano, Álvaro; Rodríguez, Marcos; Barrio, Roberto

2016-03-01

The study of the synchronization patterns of small neuron networks that control several biological processes has become an interesting growing discipline. Some of these synchronization patterns of individual neurons are related to some undesirable neurological diseases, and they are believed to play a crucial role in the emergence of pathological rhythmic brain activity in different diseases, like Parkinson’s disease. We show how, with a suitable combination of short and weak global inhibitory and excitatory stimuli over the whole network, we can switch between different stable bursting patterns in small neuron networks (in our case a 3-neuron network). We develop a systematic study showing and explaining the effects of applying the pulses at different moments. Moreover, we compare the technique on a completely symmetric network and on a slightly perturbed one (a much more realistic situation). The present approach of using global stimuli may allow to avoid undesirable synchronization patterns with nonaggressive stimuli.

Cultured networks of excitatory projection neurons and inhibitory interneurons for studying human cortical neurotoxicity

PubMed Central

Xu, Jin-Chong; Fan, Jing; Wang, Xueqing; Eacker, Stephen M.; Kam, Tae-In; Chen, Li; Yin, Xiling; Zhu, Juehua; Chi, Zhikai; Jiang, Haisong; Chen, Rong; Dawson, Ted M.; Dawson, Valina L.

2017-01-01

Translating neuroprotective treatments from discovery in cell and animal models to the clinic has proven challenging. To reduce the gap between basic studies of neurotoxicity and neuroprotection and clinically relevant therapies, we developed a human cortical neuron culture system from human embryonic stem cells (ESCs) or inducible pluripotent stem cells (iPSCs) that generated both excitatory and inhibitory neuronal networks resembling the composition of the human cortex. This methodology used timed administration of retinoic acid (RA) to FOXG1 neural precursor cells leading to differentiation of neuronal populations representative of the six cortical layers with both excitatory and inhibitory neuronal networks that were functional and homeostatically stable. In human cortical neuron cultures, excitotoxicity or ischemia due to oxygen and glucose deprivation led to cell death that was dependent on N-methyl-D-aspartate (NMDA) receptors, nitric oxide (NO), and the poly (ADP-ribose) polymerase (PARP)-dependent cell death, a cell death pathway designated parthanatos to separate it from apoptosis, necroptosis and other forms of cell death. Neuronal cell death was attenuated by PARP inhibitors that are currently in clinical trials for cancer treatment. This culture system provides a new platform for the study of human cortical neurotoxicity and suggests that PARP inhibitors may be useful for ameliorating excitotoxic and ischemic cell death in human neurons. PMID:27053772

The gamma cycle.

PubMed

Fries, Pascal; Nikolić, Danko; Singer, Wolf

2007-07-01

Activated neuronal groups typically engage in rhythmic synchronization in the gamma-frequency range (30-100 Hz). Experimental and modeling studies demonstrate that each gamma cycle is framed by synchronized spiking of inhibitory interneurons. Here, we review evidence suggesting that the resulting rhythmic network inhibition interacts with excitatory input to pyramidal cells such that the more excited cells fire earlier in the gamma cycle. Thus, the amplitude of excitatory drive is recoded into phase values of discharges relative to the gamma cycle. This recoding enables transmission and read out of amplitude information within a single gamma cycle without requiring rate integration. Furthermore, variation of phase relations can be exploited to facilitate or inhibit exchange of information between oscillating cell assemblies. The gamma cycle could thus serve as a fundamental computational mechanism for the implementation of a temporal coding scheme that enables fast processing and flexible routing of activity, supporting fast selection and binding of distributed responses. This review is part of the INMED/TINS special issue Physiogenic and pathogenic oscillations: the beauty and the beast, based on presentations at the annual INMED/TINS symposium (http://inmednet.com).

Electrophysiological evidence showing muscarinic agonist-antagonist activities of N-desmethylclozapine using hippocampal excitatory and inhibitory neurons.

PubMed

Sugawara, Yuto; Kikuchi, Yui; Yoneda, Mitsugu; Ohno-Shosaku, Takako

2016-07-01

The atypical antipsychotic clozapine is widely used for treatment-resistant schizophrenic patients. Clozapine and its major active metabolite, N-desmethylclozapine (NDMC), have complex pharmacological properties, and interact with various neurotransmitter receptors. There are several biochemical studies reporting that NDMC exhibits a partial agonist profile at the human recombinant M1 muscarinic receptors. However, direct electrophysiological evidence showing the ability of NDMC to activate native M1 receptors in intact neurons is poor. Using rat hippocampal neurons, we previously demonstrated that activation of muscarinic receptors by a muscarinic agonist, oxotremorine M (oxo-M), induces a decrease in outward K(+)current at -40mV. In the present study, using this muscarinic current response we assessed agonist and antagonist activities of clozapine and NDMC at native muscarinic receptors in intact hippocampal excitatory and inhibitory neurons. Suppression of the oxo-M-induced current response by the M1 antagonist pirenzepine was evident only in excitatory neurons, while the M3 antagonist darifenacin was effective in both types of neurons. Muscarinic agonist activity of NDMC was higher than that of clozapine, higher in excitatory neurons than in inhibitory neurons, sensitive to pirenzepine, and partially masked when co-applied with clozapine. Muscarinic antagonist activity of clozapine as well as NDMC was not different between excitatory and inhibitory neurons, but clozapine was more effective than NDMC. These results demonstrate that NDMC has the ability to activate native M1 receptors expressed in hippocampal excitatory neurons, but its agonist activity might be limited in clozapine-treated patients because of the presence of excessive clozapine with muscarinic antagonist activity. Copyright © 2016 Elsevier B.V. All rights reserved.

Selective modulation of intracortical inhibition by low-intensity Theta Burst Stimulation.

PubMed

McAllister, S M; Rothwell, J C; Ridding, M C

2009-04-01

Theta Burst Stimulation (TBS) is a repetitive transcranial magnetic stimulation paradigm which has effects on both excitatory and inhibitory intracortical pathways when applied at an intensity of 80% of active motor threshold. As intracortical inhibitory pathways have a lower threshold for activation than excitatory pathways, we sought to determine whether it was possible to selectively target cortical inhibitory circuitry by reducing the intensity of TBS to 70% of active motor threshold. Motor evoked potentials (MEPs), short latency intracortical facilitation (SICF), intracortical facilitation (ICF) and short interval intracortical inhibition (SICI) were measured at baseline, 5-20 and 20-35 min following continuous (cTBS) and intermittent (iTBS) low-intensity TBS in nine healthy subjects. Low-intensity cTBS significantly reduced SICI 5-20 min following stimulation, whilst having no effect on MEPs, SICF or ICF. Low-intensity iTBS had no effect on SICI, MEPs, SICF or ICF. It is possible to selectively target intracortical inhibitory networks for modulation by low-intensity TBS, however, responses may critically depend upon the particular paradigm chosen. These findings have important implications for the treatment of neurological disorders where abnormal levels of intracortical inhibition are present, such as Parkinson's disease and focal hand dystonia and requires further investigation.

Bottom-up driven involuntary auditory evoked field change: constant sound sequencing amplifies but does not sharpen neural activity.

PubMed

Okamoto, Hidehiko; Stracke, Henning; Lagemann, Lothar; Pantev, Christo

2010-01-01

The capability of involuntarily tracking certain sound signals during the simultaneous presence of noise is essential in human daily life. Previous studies have demonstrated that top-down auditory focused attention can enhance excitatory and inhibitory neural activity, resulting in sharpening of frequency tuning of auditory neurons. In the present study, we investigated bottom-up driven involuntary neural processing of sound signals in noisy environments by means of magnetoencephalography. We contrasted two sound signal sequencing conditions: "constant sequencing" versus "random sequencing." Based on a pool of 16 different frequencies, either identical (constant sequencing) or pseudorandomly chosen (random sequencing) test frequencies were presented blockwise together with band-eliminated noises to nonattending subjects. The results demonstrated that the auditory evoked fields elicited in the constant sequencing condition were significantly enhanced compared with the random sequencing condition. However, the enhancement was not significantly different between different band-eliminated noise conditions. Thus the present study confirms that by constant sound signal sequencing under nonattentive listening the neural activity in human auditory cortex can be enhanced, but not sharpened. Our results indicate that bottom-up driven involuntary neural processing may mainly amplify excitatory neural networks, but may not effectively enhance inhibitory neural circuits.

Mu-opioid receptors modulate the stability of dendritic spines

PubMed Central

Liao, Dezhi; Lin, Hang; Law, Ping Yee; Loh, Horace H.

2005-01-01

Opioids classically regulate the excitability of neurons by suppressing synaptic GABA release from inhibitory neurons. Here, we report a role for opioids in modulating excitatory synaptic transmission. By activating ubiquitously clustered μ-opioid receptor (MOR) in excitatory synapses, morphine caused collapse of preexisting dendritic spines and decreased synaptic α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptors. Meanwhile, the opioid antagonist naloxone increased the density of spines. Chronic treatment with morphine decreased the density of dendritic spines even in the presence of Tetrodotoxin, a sodium channel blocker, indicating that the morphine's effect was not caused by altered activity in neural network through suppression of GABA release. The effect of morphine on dendritic spines was absent in transgenic mice lacking MORs and was blocked by CTOP (D-Phe-Cys-Tyr-D-Trp-Orn-Thr-Pen-ThrNH2), a μ-receptor antagonist. These data together with others suggest that endogenous opioids and/or constitutive activity of MORs participate in maintaining normal morphology and function of spines, challenging the classical model of opioids. Abnormal alteration of spines may occur in drug addiction when opioid receptors are overactivated by exogenous opiates. PMID:15659552

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.

Neural correlates of consciousness during general anesthesia using functional magnetic resonance imaging (fMRI).

PubMed

Bonhomme, V; Boveroux, P; Brichant, J F; Laureys, S; Boly, M

2012-01-01

This paper reviews the current knowledge about the mechanisms of anesthesia-induced alteration of consciousness. It is now evident that hypnotic anesthetic agents have specific brain targets whose function is hierarchically altered in a dose-dependent manner. Higher order networks, thought to be involved in mental content generation, as well as sub-cortical networks involved in thalamic activity regulation seems to be affected first by increasing concentrations of hypnotic agents that enhance inhibitory neurotransmission. Lower order sensory networks are preserved, including thalamo-cortical connectivity into those networks, even at concentrations that suppress responsiveness, but cross-modal sensory interactions are inhibited. Thalamo-cortical connectivity into the consciousness networks decreases with increasing concentrations of those agents, and is transformed into an anti-correlated activity between the thalamus and the cortex for the deepest levels of sedation, when the subject is non responsive. Future will tell us whether these brain function alterations are also observed with hypnotic agents that mainly inhibit excitatory neurotransmission. The link between the observations made using fMRI and the identified biochemical targets of hypnotic anesthetic agents still remains to be identified.

Feedforward Inhibition Allows Input Summation to Vary in Recurrent Cortical Networks

PubMed Central

2018-01-01

Abstract Brain computations depend on how neurons transform inputs to spike outputs. Here, to understand input-output transformations in cortical networks, we recorded spiking responses from visual cortex (V1) of awake mice of either sex while pairing sensory stimuli with optogenetic perturbation of excitatory and parvalbumin-positive inhibitory neurons. We found that V1 neurons’ average responses were primarily additive (linear). We used a recurrent cortical network model to determine whether these data, as well as past observations of nonlinearity, could be described by a common circuit architecture. Simulations showed that cortical input-output transformations can be changed from linear to sublinear with moderate (∼20%) strengthening of connections between inhibitory neurons, but this change away from linear scaling depends on the presence of feedforward inhibition. Simulating a variety of recurrent connection strengths showed that, compared with when input arrives only to excitatory neurons, networks produce a wider range of output spiking responses in the presence of feedforward inhibition. PMID:29682603

Functional Evaluation of Biological Neurotoxins in Networked Cultures of Stem Cell-derived Central Nervous System Neurons

PubMed Central

Hubbard, Kyle; Beske, Phillip; Lyman, Megan; McNutt, Patrick

2015-01-01

Therapeutic and mechanistic studies of the presynaptically targeted clostridial neurotoxins (CNTs) have been limited by the need for a scalable, cell-based model that produces functioning synapses and undergoes physiological responses to intoxication. Here we describe a simple and robust method to efficiently differentiate murine embryonic stem cells (ESCs) into defined lineages of synaptically active, networked neurons. Following an 8 day differentiation protocol, mouse embryonic stem cell-derived neurons (ESNs) rapidly express and compartmentalize neurotypic proteins, form neuronal morphologies and develop intrinsic electrical responses. By 18 days after differentiation (DIV 18), ESNs exhibit active glutamatergic and γ-aminobutyric acid (GABA)ergic synapses and emergent network behaviors characterized by an excitatory:inhibitory balance. To determine whether intoxication with CNTs functionally antagonizes synaptic neurotransmission, thereby replicating the in vivo pathophysiology that is responsible for clinical manifestations of botulism or tetanus, whole-cell patch clamp electrophysiology was used to quantify spontaneous miniature excitatory post-synaptic currents (mEPSCs) in ESNs exposed to tetanus neurotoxin (TeNT) or botulinum neurotoxin (BoNT) serotypes /A-/G. In all cases, ESNs exhibited near-complete loss of synaptic activity within 20 hr. Intoxicated neurons remained viable, as demonstrated by unchanged resting membrane potentials and intrinsic electrical responses. To further characterize the sensitivity of this approach, dose-dependent effects of intoxication on synaptic activity were measured 20 hr after addition of BoNT/A. Intoxication with 0.005 pM BoNT/A resulted in a significant decrement in mEPSCs, with a median inhibitory concentration (IC50) of 0.013 pM. Comparisons of median doses indicate that functional measurements of synaptic inhibition are faster, more specific and more sensitive than SNARE cleavage assays or the mouse lethality assay. These data validate the use of synaptically coupled, stem cell-derived neurons for the highly specific and sensitive detection of CNTs. PMID:25742030

Flexibility in the patterning and control of axial locomotor networks in lamprey.

PubMed

Buchanan, James T

2011-12-01

In lower vertebrates, locomotor burst generators for axial muscles generally produce unitary bursts that alternate between the two sides of the body. In lamprey, a lower vertebrate, locomotor activity in the axial ventral roots of the isolated spinal cord can exhibit flexibility in the timings of bursts to dorsally-located myotomal muscle fibers versus ventrally-located myotomal muscle fibers. These episodes of decreased synchrony can occur spontaneously, especially in the rostral spinal cord where the propagating body waves of swimming originate. Application of serotonin, an endogenous spinal neurotransmitter known to presynaptically inhibit excitatory synapses in lamprey, can promote decreased synchrony of dorsal-ventral bursting. These observations suggest the possible existence of dorsal and ventral locomotor networks with modifiable coupling strength between them. Intracellular recordings of motoneurons during locomotor activity provide some support for this model. Pairs of motoneurons innervating myotomal muscle fibers of similar ipsilateral dorsoventral location tend to have higher correlations of fast synaptic activity during fictive locomotion than do pairs of motoneurons innervating myotomes of different ipsilateral dorsoventral locations, suggesting their control by different populations of premotor interneurons. Further, these different motoneuron pools receive different patterns of excitatory and inhibitory inputs from individual reticulospinal neurons, conveyed in part by different sets of premotor interneurons. Perhaps, then, the locomotor network of the lamprey is not simply a unitary burst generator on each side of the spinal cord that activates all ipsilateral body muscles simultaneously. Instead, the burst generator on each side may comprise at least two coupled burst generators, one controlling motoneurons innervating dorsal body muscles and one controlling motoneurons innervating ventral body muscles. The coupling strength between these two ipsilateral burst generators may be modifiable and weakening when greater swimming maneuverability is required. Variable coupling of intrasegmental burst generators in the lamprey may be a precursor to the variable coupling of burst generators observed in the control of locomotion in the joints of limbed vertebrates.

Structure and plasticity potential of neural networks in the cerebral cortex

NASA Astrophysics Data System (ADS)

Fares, Tarec Edmond

In this thesis, we first described a theoretical framework for the analysis of spine remodeling plasticity. We provided a quantitative description of two models of spine remodeling in which the presence of a bouton is either required or not for the formation of a new synapse. We derived expressions for the density of potential synapses in the neuropil, the connectivity fraction, which is the ratio of actual to potential synapses, and the number of structurally different circuits attainable with spine remodeling. We calculated these parameters in mouse occipital cortex, rat CA1, monkey V1, and human temporal cortex. We found that on average a dendritic spine can choose among 4-7 potential targets in rodents and 10-20 potential targets in primates. The neuropil's potential for structural circuit remodeling is highest in rat CA1 (7.1-8.6 bits/mum3) and lowest in monkey V1 (1.3-1.5 bits/mum 3 We next studied the role neuron morphology plays in defining synaptic connectivity. As previously stated it is clear that only pairs of neurons with closely positioned axonal and dendritic branches can be synaptically coupled. For excitatory neurons in the cerebral cortex, ). We also evaluated the lower bound of neuron selectivity in the choice of synaptic partners. Post-synaptic excitatory neurons in rodents make synaptic contacts with more than 21-30% of pre-synaptic axons encountered with new spine growth. Primate neurons appear to be more selective, making synaptic connections with more than 7-15% of encountered axons. We next studied the role neuron morphology plays in defining synaptic connectivity. As previously stated it is clear that only pairs of neurons with closely positioned axonal and dendritic branches can be synaptically coupled. For excitatory neurons in the cerebral cortex, such axo-dendritic oppositions, or potential synapses, must be bridged by dendritic spines to form synaptic connections. To explore the rules by which synaptic connections are formed within the constraints imposed by neuron morphology, we compared the distributions of the numbers of actual and potential synapses between pre- and post-synaptic neurons forming different laminar projections in rat barrel cortex. Quantitative comparison explicitly ruled out the hypothesis that individual synapses between neurons are formed independently of each other. Instead, the data are consistent with a cooperative scheme of synapse formation, where multiple-synaptic connections between neurons are stabilized, while neurons that do not establish a critical number of synapses are not likely to remain synaptically coupled. In the above two projects, analysis of potential synapse numbers played an important role in shaping our understanding of connectivity and structural plasticity. In the third part of this thesis, we shift our attention to the study of the distribution of potential synapse numbers. This distribution is dependent on the details of neuron morphology and it defines synaptic connectivity patterns attainable with spine remodeling. To better understand how the distribution of potential synapse numbers is influenced by the overlap and the shapes of axonal and dendritic arbors, we first analyzed uniform disconnected arbors generated in silico. The resulting distributions are well described by binomial functions. We used a dataset of neurons reconstructed in 3D and generated the potential synapse distributions for neurons of different classes. Quantitative analysis showed that the binomial distribution is a good fit to this data as well. All distributions considered clustered into two categories, inhibitory to inhibitory and excitatory to excitatory projections. We showed that the distributions of potential synapse numbers are universally described by a family of single parameter (p) binomial functions, where p = 0.08, and for the inhibitory and p = 0.19 for the excitatory projections. In the last part of this thesis an attempt is made to incorporate some of the biological constraints we considered thus far, into an artificial neural network model. It became clear that several features of synaptic connectivity are ubiquitous among different cortical networks: (1) neural networks are predominately excitatory, containing roughly 80% of excitatory neurons and synapses, (2) neural networks are only sparsely interconnected, where the probabilities of finding connected neurons are always less than 50% even for neighboring cells, (3) the distribution of connection strengths has been shown to have a slow non-exponential decay. In the attempt to understand the advantage of such network architecture for learning and memory, we analyzed the associative memory capacity of a biologically constrained perceptron-like neural network model. The artificial neural network we consider consists of robust excitatory and inhibitory McCulloch and Pitts neurons with a constant firing threshold. Our theoretical results show that the capacity for associative memory storage in such networks increases with an addition of a small fraction of inhibitory neurons, while the connection probability remains below 50%. (Abstract shortened by UMI.)

Pathological effect of homeostatic synaptic scaling on network dynamics in diseases of the cortex.

PubMed

Fröhlich, Flavio; Bazhenov, Maxim; Sejnowski, Terrence J

2008-02-13

Slow periodic EEG discharges are common in CNS disorders. The pathophysiology of this aberrant rhythmic activity is poorly understood. We used a computational model of a neocortical network with a dynamic homeostatic scaling rule to show that loss of input (partial deafferentation) can trigger network reorganization that results in pathological periodic discharges. The decrease in average firing rate in the network by deafferentation was compensated by homeostatic synaptic scaling of recurrent excitation among pyramidal cells. Synaptic scaling succeeded in recovering the network target firing rate for all degrees of deafferentation (fraction of deafferented cells), but there was a critical degree of deafferentation for pathological network reorganization. For deafferentation degrees below this value, homeostatic upregulation of recurrent excitation had minimal effect on the macroscopic network dynamics. For deafferentation above this threshold, however, a slow periodic oscillation appeared, patterns of activity were less sparse, and bursting occurred in individual neurons. Also, comparison of spike-triggered afferent and recurrent excitatory conductances revealed that information transmission was strongly impaired. These results suggest that homeostatic plasticity can lead to secondary functional impairment in case of cortical disorders associated with cell loss.

Rescue of deficient amygdala tonic γ-aminobutyric acidergic currents in the Fmr-/y mouse model of fragile X syndrome by a novel γ-aminobutyric acid type A receptor-positive allosteric modulator.

PubMed

Martin, Brandon S; Martinez-Botella, Gabriel; Loya, Carlos M; Salituro, Francesco G; Robichaud, Albert J; Huntsman, Molly M; Ackley, Mike A; Doherty, James J; Corbin, Joshua G

2016-06-01

Alterations in the ratio of excitatory to inhibitory transmission are emerging as a common component of many nervous system disorders, including autism spectrum disorders (ASDs). Tonic γ-aminobutyric acidergic (GABAergic) transmission provided by peri- and extrasynaptic GABA type A (GABAA ) receptors powerfully controls neuronal excitability and plasticity and, therefore, provides a rational therapeutic target for normalizing hyperexcitable networks across a variety of disorders, including ASDs. Our previous studies revealed tonic GABAergic deficits in principal excitatory neurons in the basolateral amygdala (BLA) in the Fmr1(-/y) knockout (KO) mouse model fragile X syndrome. To correct amygdala deficits in tonic GABAergic neurotransmission in Fmr1(-/y) KO mice, we developed a novel positive allosteric modulator of GABAA receptors, SGE-872, based on endogenously active neurosteroids. This study shows that SGE-872 is nearly as potent and twice as efficacious for positively modulating GABAA receptors as its parent molecule, allopregnanolone. Furthermore, at submicromolar concentrations (≤1 μM), SGE-872 is selective for tonic, extrasynaptic α4β3δ-containing GABAA receptors over typical synaptic α1β2γ2 receptors. We further find that SGE-872 strikingly rescues the tonic GABAergic transmission deficit in principal excitatory neurons in the Fmr1(-/y) KO BLA, a structure heavily implicated in the neuropathology of ASDs. Therefore, the potent and selective action of SGE-872 on tonic GABAA receptors containing α4 subunits may represent a novel and highly useful therapeutic avenue for ASDs and related disorders involving hyperexcitability of neuronal networks. © 2015 Wiley Periodicals, Inc.

An artificial network model for estimating the network structure underlying partially observed neuronal signals.

PubMed

Komatsu, Misako; Namikawa, Jun; Chao, Zenas C; Nagasaka, Yasuo; Fujii, Naotaka; Nakamura, Kiyohiko; Tani, Jun

2014-01-01

Many previous studies have proposed methods for quantifying neuronal interactions. However, these methods evaluated the interactions between recorded signals in an isolated network. In this study, we present a novel approach for estimating interactions between observed neuronal signals by theorizing that those signals are observed from only a part of the network that also includes unobserved structures. We propose a variant of the recurrent network model that consists of both observable and unobservable units. The observable units represent recorded neuronal activity, and the unobservable units are introduced to represent activity from unobserved structures in the network. The network structures are characterized by connective weights, i.e., the interaction intensities between individual units, which are estimated from recorded signals. We applied this model to multi-channel brain signals recorded from monkeys, and obtained robust network structures with physiological relevance. Furthermore, the network exhibited common features that portrayed cortical dynamics as inversely correlated interactions between excitatory and inhibitory populations of neurons, which are consistent with the previous view of cortical local circuits. Our results suggest that the novel concept of incorporating an unobserved structure into network estimations has theoretical advantages and could provide insights into brain dynamics beyond what can be directly observed. Copyright © 2014 Elsevier Ireland Ltd and the Japan Neuroscience Society. All rights reserved.

Bistability and up/down state alternations in inhibition-dominated randomly connected networks of LIF neurons.

PubMed

Tartaglia, Elisa M; Brunel, Nicolas

2017-09-20

Electrophysiological recordings in cortex in vivo have revealed a rich variety of dynamical regimes ranging from irregular asynchronous states to a diversity of synchronized states, depending on species, anesthesia, and external stimulation. The average population firing rate in these states is typically low. We study analytically and numerically a network of sparsely connected excitatory and inhibitory integrate-and-fire neurons in the inhibition-dominated, low firing rate regime. For sufficiently high values of the external input, the network exhibits an asynchronous low firing frequency state (L). Depending on synaptic time constants, we show that two scenarios may occur when external inputs are decreased: (1) the L state can destabilize through a Hopf bifucation as the external input is decreased, leading to synchronized oscillations spanning d δ to β frequencies; (2) the network can reach a bistable region, between the low firing frequency network state (L) and a quiescent one (Q). Adding an adaptation current to excitatory neurons leads to spontaneous alternations between L and Q states, similar to experimental observations on UP and DOWN states alternations.

Meth math: modeling temperature responses to methamphetamine.

PubMed

Molkov, Yaroslav I; Zaretskaia, Maria V; Zaretsky, Dmitry V

2014-04-15

Methamphetamine (Meth) can evoke extreme hyperthermia, which correlates with neurotoxicity and death in laboratory animals and humans. The objective of this study was to uncover the mechanisms of a complex dose dependence of temperature responses to Meth by mathematical modeling of the neuronal circuitry. On the basis of previous studies, we composed an artificial neural network with the core comprising three sequentially connected nodes: excitatory, medullary, and sympathetic preganglionic neuronal (SPN). Meth directly stimulated the excitatory node, an inhibitory drive targeted the medullary node, and, in high doses, an additional excitatory drive affected the SPN node. All model parameters (weights of connections, sensitivities, and time constants) were subject to fitting experimental time series of temperature responses to 1, 3, 5, and 10 mg/kg Meth. Modeling suggested that the temperature response to the lowest dose of Meth, which caused an immediate and short hyperthermia, involves neuronal excitation at a supramedullary level. The delay in response after the intermediate doses of Meth is a result of neuronal inhibition at the medullary level. Finally, the rapid and robust increase in body temperature induced by the highest dose of Meth involves activation of high-dose excitatory drive. The impairment in the inhibitory mechanism can provoke a life-threatening temperature rise and makes it a plausible cause of fatal hyperthermia in Meth users. We expect that studying putative neuronal sites of Meth action and the neuromediators involved in a detailed model of this system may lead to more effective strategies for prevention and treatment of hyperthermia induced by amphetamine-like stimulants.

Meth math: modeling temperature responses to methamphetamine

PubMed Central

Molkov, Yaroslav I.; Zaretskaia, Maria V.

2014-01-01

Methamphetamine (Meth) can evoke extreme hyperthermia, which correlates with neurotoxicity and death in laboratory animals and humans. The objective of this study was to uncover the mechanisms of a complex dose dependence of temperature responses to Meth by mathematical modeling of the neuronal circuitry. On the basis of previous studies, we composed an artificial neural network with the core comprising three sequentially connected nodes: excitatory, medullary, and sympathetic preganglionic neuronal (SPN). Meth directly stimulated the excitatory node, an inhibitory drive targeted the medullary node, and, in high doses, an additional excitatory drive affected the SPN node. All model parameters (weights of connections, sensitivities, and time constants) were subject to fitting experimental time series of temperature responses to 1, 3, 5, and 10 mg/kg Meth. Modeling suggested that the temperature response to the lowest dose of Meth, which caused an immediate and short hyperthermia, involves neuronal excitation at a supramedullary level. The delay in response after the intermediate doses of Meth is a result of neuronal inhibition at the medullary level. Finally, the rapid and robust increase in body temperature induced by the highest dose of Meth involves activation of high-dose excitatory drive. The impairment in the inhibitory mechanism can provoke a life-threatening temperature rise and makes it a plausible cause of fatal hyperthermia in Meth users. We expect that studying putative neuronal sites of Meth action and the neuromediators involved in a detailed model of this system may lead to more effective strategies for prevention and treatment of hyperthermia induced by amphetamine-like stimulants. PMID:24500434

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.

Differential Alterations in Excitatory and Inhibitory Networks Involving Dentate Granule Cells Following Chronic Treatment with Distinct Classes of NMDAR Antagonists in Hippocampal Slice Cultures

DTIC Science & Technology

2010-03-08

1992; Jung and McNaughton, 1993); (2) low incidence of recurrent excitatory synapses between granule cells (Molnar and Nadler, 1999; Okazaki et al...neurons, dentate granule cells have a relatively more negative resting membrane potential and exhibit low-frequency firing (Staley et al., 1992; Jung ...inhibition plays a dual role in brain function and possibly seizure occurrence through balancing excitation and synchronizing neuronal firing. An

Contribution of intrinsic properties and synaptic inputs to motoneuron discharge patterns: a simulation study

PubMed Central

ElBasiouny, Sherif M.; Rymer, W. Zev; Heckman, C. J.

2012-01-01

Motoneuron discharge patterns reflect the interaction of synaptic inputs with intrinsic conductances. Recent work has focused on the contribution of conductances mediating persistent inward currents (PICs), which amplify and prolong the effects of synaptic inputs on motoneuron discharge. Certain features of human motor unit discharge are thought to reflect a relatively stereotyped activation of PICs by excitatory synaptic inputs; these features include rate saturation and de-recruitment at a lower level of net excitation than that required for recruitment. However, PIC activation is also influenced by the pattern and spatial distribution of inhibitory inputs that are activated concurrently with excitatory inputs. To estimate the potential contributions of PIC activation and synaptic input patterns to motor unit discharge patterns, we examined the responses of a set of cable motoneuron models to different patterns of excitatory and inhibitory inputs. The models were first tuned to approximate the current- and voltage-clamp responses of low- and medium-threshold spinal motoneurons studied in decerebrate cats and then driven with different patterns of excitatory and inhibitory inputs. The responses of the models to excitatory inputs reproduced a number of features of human motor unit discharge. However, the pattern of rate modulation was strongly influenced by the temporal and spatial pattern of concurrent inhibitory inputs. Thus, even though PIC activation is likely to exert a strong influence on firing rate modulation, PIC activation in combination with different patterns of excitatory and inhibitory synaptic inputs can produce a wide variety of motor unit discharge patterns. PMID:22031773

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.

Plasticity of cortical inhibition in dystonia is impaired after motor learning and paired-associative stimulation.

PubMed

Meunier, Sabine; Russmann, Heike; Shamim, Ejaz; Lamy, Jean-Charles; Hallett, Mark

2012-03-01

Artificial induction of plasticity by paired associative stimulation (PAS) in healthy volunteers (HV) demonstrates Hebbian-like plasticity in selected inhibitory networks as well as excitatory networks. In a group of 17 patients with focal hand dystonia and a group of 19 HV, we evaluated how PAS and the learning of a simple motor task influence the circuits supporting long-interval intracortical inhibition (LICI, reflecting activity of GABA(B) interneurons) and long-latency afferent inhibition (LAI, reflecting activity of somatosensory inputs to the motor cortex). In HV, PAS and motor learning induced long-term potentiation (LTP)-like plasticity of excitatory networks and a lasting decrease of LAI and LICI in the motor representation of the targeted or trained muscle. The better the motor performance, the larger was the decrease of LAI. Although motor performance in the patient group was similar to that of the control group, LAI did not decrease during the motor learning as it did in the control group. In contrast, LICI was normally modulated. In patients the results after PAS did not match those obtained after motor learning: LAI was paradoxically increased and LICI did not exhibit any change. In the normal situation, decreased excitability in inhibitory circuits after induction of LTP-like plasticity may help to shape the cortical maps according to the new sensorimotor task. In patients, the abnormal or absent modulation of afferent and intracortical long-interval inhibition might indicate maladaptive plasticity that possibly contributes to the difficulty that they have to learn a new sensorimotor task. © 2012 The Authors. European Journal of Neuroscience © 2012 Federation of European Neuroscience Societies and Blackwell Publishing Ltd.

Serotonin targets inhibitory synapses to induce modulation of network functions

PubMed Central

Manzke, Till; Dutschmann, Mathias; Schlaf, Gerald; Mörschel, Michael; Koch, Uwe R.; Ponimaskin, Evgeni; Bidon, Olivier; Lalley, Peter M.; Richter, Diethelm W.

2009-01-01

The cellular effects of serotonin (5-HT), a neuromodulator with widespread influences in the central nervous system, have been investigated. Despite detailed knowledge about the molecular biology of cellular signalling, it is not possible to anticipate the responses of neuronal networks to a global action of 5-HT. Heterogeneous expression of various subtypes of serotonin receptors (5-HTR) in a variety of neurons differently equipped with cell-specific transmitter receptors and ion channel assemblies can provoke diverse cellular reactions resulting in various forms of network adjustment and, hence, motor behaviour. Using the respiratory network as a model for reciprocal synaptic inhibition, we demonstrate that 5-HT1AR modulation primarily affects inhibition through glycinergic synapses. Potentiation of glycinergic inhibition of both excitatory and inhibitory neurons induces a functional reorganization of the network leading to a characteristic change of motor output. The changes in network operation are robust and help to overcome opiate-induced respiratory depression. Hence, 5-HT1AR activation stabilizes the rhythmicity of breathing during opiate medication of pain. PMID:19651659

On a phase diagram for random neural networks with embedded spike timing dependent plasticity.

PubMed

Turova, Tatyana S; Villa, Alessandro E P

2007-01-01

This paper presents an original mathematical framework based on graph theory which is a first attempt to investigate the dynamics of a model of neural networks with embedded spike timing dependent plasticity. The neurons correspond to integrate-and-fire units located at the vertices of a finite subset of 2D lattice. There are two types of vertices, corresponding to the inhibitory and the excitatory neurons. The edges are directed and labelled by the discrete values of the synaptic strength. We assume that there is an initial firing pattern corresponding to a subset of units that generate a spike. The number of activated externally vertices is a small fraction of the entire network. The model presented here describes how such pattern propagates throughout the network as a random walk on graph. Several results are compared with computational simulations and new data are presented for identifying critical parameters of the model.

Pathway and Cell-Specific Kappa-Opioid Receptor Modulation of Excitatory-Inhibitory Balance Differentially Gates D1 and D2 Accumbens Neuron Activity

PubMed Central

Tejeda, Hugo A.; Wu, Jocelyn; Kornspun, Alana R.; Pignatelli, Marco; Kashtelyan, Vadim; Krashes, Michael J.; Lowell, Brad B.; Carlezon, William A.; Bonci, Antonello

2018-01-01

Endogenous dynorphin signaling via the kappa-opioid receptor (KOR) in the nucleus accumbens (NAcc) powerfully mediates negative affective states and stress reactivity. Excitatory inputs from the hippocampus and amygdala play a fundamental role in shaping the activity of both NAcc D1 and D2 MSNs, which encode positive and negative motivational valences, respectively. However, a circuit-based mechanism by which KOR modulation of excitation-inhibition balance modifies D1 and D2 MSN activity is lacking. Here, we provide a comprehensive synaptic framework wherein presynaptic KOR inhibition decreases excitatory drive of D1 MSN activity by the amygdala, but not hippocampus. Conversely, presynaptic inhibition by KORs of inhibitory synapses on D2 MSNs enhances integration of excitatory drive by the amygdala and hippocampus. In conclusion, we describe a circuit-based mechanism showing differential gating of afferent control of D1 and D2 MSN activity by KORs in a pathway specific manner. PMID:28056342

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

Regulating Cortical Oscillations in an Inhibition-Stabilized Network.

PubMed

Jadi, Monika P; Sejnowski, Terrence J

2014-04-21

Understanding the anatomical and functional architecture of the brain is essential for designing neurally inspired intelligent systems. Theoretical and empirical studies suggest a role for narrowband oscillations in shaping the functional architecture of the brain through their role in coding and communication of information. Such oscillations are ubiquitous signals in the electrical activity recorded from the brain. In the cortex, oscillations detected in the gamma range (30-80 Hz) are modulated by behavioral states and sensory features in complex ways. How is this regulation achieved? Although several underlying principles for the genesis of these oscillations have been proposed, a unifying account for their regulation has remained elusive. In a network of excitatory and inhibitory neurons operating in an inhibition-stabilized regime, we show that strongly superlinear responses of inhibitory neurons facilitate bidirectional regulation of oscillation frequency and power. In such a network, the balance of drives to the excitatory and inhibitory populations determines how the power and frequency of oscillations are modulated. The model accounts for the puzzling increase in their frequency with the salience of visual stimuli, and a decrease with their size. Oscillations in our model grow stronger as the mean firing level is reduced, accounting for the size dependence of visually evoked gamma rhythms, and suggesting a role for oscillations in improving the signal-to-noise ratio (SNR) of signals in the brain. Empirically testing such predictions is still challenging, and implementing the proposed coding and communication strategies in neuromorphic systems could assist in our understanding of the biological system.

Attentional modulation of neuronal variability in circuit models of cortex

PubMed Central

Kanashiro, Tatjana; Ocker, Gabriel Koch; Cohen, Marlene R; Doiron, Brent

2017-01-01

The circuit mechanisms behind shared neural variability (noise correlation) and its dependence on neural state are poorly understood. Visual attention is well-suited to constrain cortical models of response variability because attention both increases firing rates and their stimulus sensitivity, as well as decreases noise correlations. We provide a novel analysis of population recordings in rhesus primate visual area V4 showing that a single biophysical mechanism may underlie these diverse neural correlates of attention. We explore model cortical networks where top-down mediated increases in excitability, distributed across excitatory and inhibitory targets, capture the key neuronal correlates of attention. Our models predict that top-down signals primarily affect inhibitory neurons, whereas excitatory neurons are more sensitive to stimulus specific bottom-up inputs. Accounting for trial variability in models of state dependent modulation of neuronal activity is a critical step in building a mechanistic theory of neuronal cognition. DOI: http://dx.doi.org/10.7554/eLife.23978.001 PMID:28590902

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.

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.

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

NASA Astrophysics Data System (ADS)

Mikkelsen, Kaare; Imparato, Alberto; Torcini, Alessandro

2013-05-01

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

Role of glutamate and substance P in the amphibian respiratory network during development

PubMed Central

Chen, Anna K.; Hedrick, Michael S.

2008-01-01

This study tested the hypothesis that glutamatergic ionotropic (AMPA/kainate) receptors and neurokinin receptors (NKR) are important in the regulation of respiratory motor output during development in the bullfrog. The roles of these receptors were studied with in vitro brainstem preparations from pre-metamorphic tadpoles and post-metamorphic frogs. Brainstems were superfused with an artificial cerebrospinal fluid at 20–22°C containing CNQX, a selective non-NMDA antagonist, or with substance P (SP), an agonist of NKR. Blockade of glutamate receptors with CNQX in both groups caused a reduction of lung burst frequency that was reversibly abolished at 5 μM (P<0.01). CNQX, but not SP, application produced a significant increase (P<0.05) in gill and buccal frequency in tadpoles and frogs, respectively. SP caused a significant increase (P<0.05) in lung burst frequency at 5 μM in both groups. These results suggest that glutamatergic activation of AMPA/kainate receptors is necessary for generation of lung burst activity and that SP is an excitatory neurotransmitter for lung burst frequency generation. Both glutamate and SP provide excitatory input for lung burst generation throughout the aquatic to terrestrial developmental transition in bullfrogs. PMID:18450524

Role of glutamate and substance P in the amphibian respiratory network during development.

PubMed

Chen, Anna K; Hedrick, Michael S

2008-06-30

This study tested the hypothesis that glutamatergic ionotropic (AMPA/kainate) receptors and neurokinin receptors (NKR) are important in the regulation of respiratory motor output during development in the bullfrog. The roles of these receptors were studied with in vitro brainstem preparations from pre-metamorphic tadpoles and post-metamorphic frogs. Brainstems were superfused with an artificial cerebrospinal fluid at 20-22 degrees C containing CNQX, a selective non-NMDA antagonist, or with substance P (SP), an agonist of NKR. Blockade of glutamate receptors with CNQX in both groups caused a reduction of lung burst frequency that was reversibly abolished at 5 microM (P<0.01). CNQX, but not SP, application produced a significant increase (P<0.05) in gill and buccal frequency in tadpoles and frogs, respectively. SP caused a significant increase (P<0.05) in lung burst frequency at 5 microM in both groups. These results suggest that glutamatergic activation of AMPA/kainate receptors is necessary for generation of lung burst activity and that SP is an excitatory neurotransmitter for lung burst frequency generation. Both glutamate and SP provide excitatory input for lung burst generation throughout the aquatic to terrestrial developmental transition in bullfrogs.

Word Length and Lexical Activation: Longer Is Better

ERIC Educational Resources Information Center

Pitt, Mark A.; Samuel, Arthur G.

2006-01-01

Many models of spoken word recognition posit the existence of lexical and sublexical representations, with excitatory and inhibitory mechanisms used to affect the activation levels of such representations. Bottom-up evidence provides excitatory input, and inhibition from phonetically similar representations leads to lexical competition. In such a…

Pulse-coupled Belousov-Zhabotinsky oscillators with frequency modulation

NASA Astrophysics Data System (ADS)

Horvath, Viktor; Epstein, Irving R.

2018-04-01

Inhibitory perturbations to the ferroin-catalyzed Belousov-Zhabotinsky (BZ) chemical oscillator operated in a continuously fed stirred tank reactor cause long term changes to the limit cycle: the lengths of the cycles subsequent to the perturbation are longer than that of the unperturbed cycle, and the unperturbed limit cycle is recovered only after several cycles. The frequency of the BZ reaction strongly depends on the acid concentration of the medium. By adding strong acid or base to the perturbing solutions, the magnitude and the direction of the frequency changes concomitant to excitatory or inhibitory perturbations can be controlled independently of the coupling strength. The dynamics of two BZ oscillators coupled through perturbations carrying a coupling agent (activator or inhibitor) and a frequency modulator (strong acid or base) was explored using a numerical model of the system. Here, we report new complex temporal patterns: higher order, partially synchronized modes that develop when inhibitory coupling is combined with positive frequency modulation (FM), and complex bursting patterns when excitatory coupling is combined with negative FM. The role of time delay between the peak and perturbation (the analog of synaptic delays in networks of neurons) has also been studied. The complex patterns found under inhibitory coupling and positive FM vanish when the delay is significant, whereas a sufficiently long time delay is required for the complex temporal dynamics to occur when coupling is excitatory and FM is negative.

Electronic neural network for dynamic resource allocation

NASA Technical Reports Server (NTRS)

Thakoor, A. P.; Eberhardt, S. P.; Daud, T.

1991-01-01

A VLSI implementable neural network architecture for dynamic assignment is presented. The resource allocation problems involve assigning members of one set (e.g. resources) to those of another (e.g. consumers) such that the global 'cost' of the associations is minimized. The network consists of a matrix of sigmoidal processing elements (neurons), where the rows of the matrix represent resources and columns represent consumers. Unlike previous neural implementations, however, association costs are applied directly to the neurons, reducing connectivity of the network to VLSI-compatible 0 (number of neurons). Each row (and column) has an additional neuron associated with it to independently oversee activations of all the neurons in each row (and each column), providing a programmable 'k-winner-take-all' function. This function simultaneously enforces blocking (excitatory/inhibitory) constraints during convergence to control the number of active elements in each row and column within desired boundary conditions. Simulations show that the network, when implemented in fully parallel VLSI hardware, offers optimal (or near-optimal) solutions within only a fraction of a millisecond, for problems up to 128 resources and 128 consumers, orders of magnitude faster than conventional computing or heuristic search methods.

Non-Hermitian localization in biological networks.

PubMed

Amir, Ariel; Hatano, Naomichi; Nelson, David R

2016-04-01

We explore the spectra and localization properties of the N-site banded one-dimensional non-Hermitian random matrices that arise naturally in sparse neural networks. Approximately equal numbers of random excitatory and inhibitory connections lead to spatially localized eigenfunctions and an intricate eigenvalue spectrum in the complex plane that controls the spontaneous activity and induced response. A finite fraction of the eigenvalues condense onto the real or imaginary axes. For large N, the spectrum has remarkable symmetries not only with respect to reflections across the real and imaginary axes but also with respect to 90^{∘} rotations, with an unusual anisotropic divergence in the localization length near the origin. When chains with periodic boundary conditions become directed, with a systematic directional bias superimposed on the randomness, a hole centered on the origin opens up in the density-of-states in the complex plane. All states are extended on the rim of this hole, while the localized eigenvalues outside the hole are unchanged. The bias-dependent shape of this hole tracks the bias-independent contours of constant localization length. We treat the large-N limit by a combination of direct numerical diagonalization and using transfer matrices, an approach that allows us to exploit an electrostatic analogy connecting the "charges" embodied in the eigenvalue distribution with the contours of constant localization length. We show that similar results are obtained for more realistic neural networks that obey "Dale's law" (each site is purely excitatory or inhibitory) and conclude with perturbation theory results that describe the limit of large directional bias, when all states are extended. Related problems arise in random ecological networks and in chains of artificial cells with randomly coupled gene expression patterns.

Non-Hermitian localization in biological networks

NASA Astrophysics Data System (ADS)

Amir, Ariel; Hatano, Naomichi; Nelson, David R.

2016-04-01

We explore the spectra and localization properties of the N -site banded one-dimensional non-Hermitian random matrices that arise naturally in sparse neural networks. Approximately equal numbers of random excitatory and inhibitory connections lead to spatially localized eigenfunctions and an intricate eigenvalue spectrum in the complex plane that controls the spontaneous activity and induced response. A finite fraction of the eigenvalues condense onto the real or imaginary axes. For large N , the spectrum has remarkable symmetries not only with respect to reflections across the real and imaginary axes but also with respect to 90∘ rotations, with an unusual anisotropic divergence in the localization length near the origin. When chains with periodic boundary conditions become directed, with a systematic directional bias superimposed on the randomness, a hole centered on the origin opens up in the density-of-states in the complex plane. All states are extended on the rim of this hole, while the localized eigenvalues outside the hole are unchanged. The bias-dependent shape of this hole tracks the bias-independent contours of constant localization length. We treat the large-N limit by a combination of direct numerical diagonalization and using transfer matrices, an approach that allows us to exploit an electrostatic analogy connecting the "charges" embodied in the eigenvalue distribution with the contours of constant localization length. We show that similar results are obtained for more realistic neural networks that obey "Dale's law" (each site is purely excitatory or inhibitory) and conclude with perturbation theory results that describe the limit of large directional bias, when all states are extended. Related problems arise in random ecological networks and in chains of artificial cells with randomly coupled gene expression patterns.

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

The Influence of Cold Temperature on Cellular Excitability of Hippocampal Networks

PubMed Central

Vara, Hugo; Caires, Rebeca; Ballesta, Juan J.; Belmonte, Carlos; Viana, Felix

2012-01-01

The hippocampus plays an important role in short term memory, learning and spatial navigation. A characteristic feature of the hippocampal region is its expression of different electrical population rhythms and activities during different brain states. Physiological fluctuations in brain temperature affect the activity patterns in hippocampus, but the underlying cellular mechanisms are poorly understood. In this work, we investigated the thermal modulation of hippocampal activity at the cellular network level. Primary cell cultures of mouse E17 hippocampus displayed robust network activation upon light cooling of the extracellular solution from baseline physiological temperatures. The activity generated was dependent on action potential firing and excitatory glutamatergic synaptic transmission. Involvement of thermosensitive channels from the transient receptor potential (TRP) family in network activation by temperature changes was ruled out, whereas pharmacological and immunochemical experiments strongly pointed towards the involvement of temperature-sensitive two-pore-domain potassium channels (K2P), TREK/TRAAK family. In hippocampal slices we could show an increase in evoked and spontaneous synaptic activity produced by mild cooling in the physiological range that was prevented by chloroform, a K2P channel opener. We propose that cold-induced closure of background TREK/TRAAK family channels increases the excitability of some hippocampal neurons, acting as a temperature-sensitive gate of network activation. Our findings in the hippocampus open the possibility that small temperature variations in the brain in vivo, associated with metabolism or blood flow oscillations, act as a switch mechanism of neuronal activity and determination of firing patterns through regulation of thermosensitive background potassium channel activity. PMID:23300680

Indistinguishable Synaptic Pharmacodynamics of the N-Methyl-d-Aspartate Receptor Channel Blockers Memantine and Ketamine

PubMed Central

Emnett, Christine M.; Eisenman, Lawrence N.; Taylor, Amanda M.; Izumi, Yukitoshi; Zorumski, Charles F.

2013-01-01

Memantine and ketamine, voltage- and activation-dependent channel blockers of N-methyl-d-aspartate (NMDA) receptors (NMDARs), have enjoyed a recent resurgence in clinical interest. Steady-state pharmacodynamic differences between these blockers have been reported, but it is unclear whether the compounds differentially affect dynamic physiologic signaling. In this study, we explored nonequilibrium conditions relevant to synaptic transmission in hippocampal networks in dissociated culture and hippocampal slices. Equimolar memantine and ketamine had indistinguishable effects on the following measures: steady-state NMDA currents, NMDAR excitatory postsynaptic current (EPSC) decay kinetics, progressive EPSC inhibition during repetitive stimulation, and extrasynaptic NMDAR inhibition. Therapeutic drug efficacy and tolerability of memantine have been attributed to fast kinetics and strong voltage dependence. However, pulse depolarization in drug presence revealed a surprisingly slow and similar time course of equilibration for the two compounds, although memantine produced a more prominent fast component (62% versus 48%) of re-equilibration. Simulations predicted that low gating efficacy underlies the slow voltage–dependent relief from block. This prediction was empirically supported by faster voltage-dependent blocker re-equilibration with several experimental manipulations of gating efficacy. Excitatory postsynaptic potential–like voltage commands produced drug differences only with large, prolonged depolarizations unlikely to be attained physiologically. In fact, we found no difference between drugs on measures of spontaneous network activity or acute effects on plasticity in hippocampal slices. Despite indistinguishable synaptic pharmacodynamics, ketamine provided significantly greater neuroprotection from damage induced by oxygen glucose deprivation, consistent with the idea that under extreme depolarizing conditions, the biophysical difference between drugs becomes detectable. We conclude that despite subtle differences in voltage dependence, during physiologic activity, blocker pharmacodynamics are largely indistinguishable and largely voltage independent. PMID:24101301

Spatiotemporal Dynamics and Reliable Computations in Recurrent Spiking Neural Networks

NASA Astrophysics Data System (ADS)

Pyle, Ryan; Rosenbaum, Robert

2017-01-01

Randomly connected networks of excitatory and inhibitory spiking neurons provide a parsimonious model of neural variability, but are notoriously unreliable for performing computations. We show that this difficulty is overcome by incorporating the well-documented dependence of connection probability on distance. Spatially extended spiking networks exhibit symmetry-breaking bifurcations and generate spatiotemporal patterns that can be trained to perform dynamical computations under a reservoir computing framework.

The spatial extent of excitatory and inhibitory zones in the receptive field of superficial layer hypercomplex cells

PubMed Central

Sillito, A. M.

1977-01-01

1. An investigation has been made of the extent of inhibitory and excitatory components in the receptive field of superficial layer hypercomplex cells in the cat's striate cortex and the relation of the components to the length preference exhibited by these cells. 2. Maximal responses were produced by an optimal length stimulus moving through a restricted region of the receptive field. The length of this receptive field region was less than the total length of the excitatory zone as mapped with a very short slit. Slits of similar length to the excitatory zone produced a smaller response than an optimal length slit. 3. An increase of slit length so that it passed over receptive field regions either side of the excitatory zone resulted in an elimination of the response. When background discharge levels were increased by the iontophoretic application of D, L-homocysteic acid slits of this length were observed to produce a suppression of the resting discharge as they passed over the receptive field. They did not modify the resting discharge level when it was induced by the iontophoretic application of the GABA antagonist bicuculline. This data is taken to indicate that long slits activate a powerful post-synaptic inhibitory input to the cell. 4. Maximal inhibitory effects were only observed if the testing slit passed over the receptive field centre. That is slits with a gap positioned midway along their length so as to exclude the optimal excitatory response region surprisingly tended to produce excitatory effects rather than the expected inhibitory effects. It appears that simultaneous stimulation of the receptive field centre is a precondition for the inhibitory effect of stimulation of regions either side of the excitatory zone to be activated. 5. It is suggested that the interneurones mediating the inhibitory input to the superficial layer hypercomplex cells are driven both by cells in adjacent hypercolumns with receptive fields spatially displaced to either side of the excitatory zone and by cells in the same column, optimal inhibitory effects only being achieved when both sets of input to the interneurone are activated. PMID:604459

Plasticity of cortical inhibition in dystonia is impaired after motor learning and Paired-Associative Stimulation

PubMed Central

Meunier, Sabine; Russmann, Heike; Shamim, Ejaz; Lamy, Jean-Charles; Hallett, Mark

2012-01-01

Summary Artificial induction of plasticity by paired associative stimulation (PAS) in healthy subjects (HV) demonstrates Hebbian-like plasticity in selected inhibitory networks as well as excitatory ones. In a group of 17 patients with focal hand dystonia and a group of 19 HV, we evaluated how PAS and the learning of a simple motor task influence the circuits supporting long interval intracortical inhibition (LICI, reflecting activity of GABAB interneurons) and long latency afferent inhibition (LAI, reflecting activity of somatosensory inputs to the motor cortex). In HV, PAS and motor learning induced LTP-like plasticity of excitatory networks and a lasting decrease of LAI and LICI in the motor representation of the targeted or trained muscle. The better the motor performance, the larger was the decrease of LAI. Although motor performance in the patient group was similar to that of the control group, LAI did not decrease during the motor learning as it did in the control group. In contrast, LICI was normally modulated. In patients the results after PAS did not match those obtained after motor learning: LAI was paradoxically increased and LICI did not exhibit any change. In the normal situation, decreased excitability in inhibitory circuits after induction of LTP-like plasticity may help to shape the cortical maps according to the new sensorimotor task. In patients, the abnormal or absent modulation of afferent and intracortical long-interval inhibition might indicate maladaptive plasticity that possibly contributes to the difficulty that they have to learn a new sensorimotor task.“ PMID:22429246

Distinct Spatiotemporal Activation Patterns of the Perirhinal-Entorhinal Network in Response to Cortical and Amygdala Input

PubMed Central

Willems, Janske G. P.; Wadman, Wytse J.; Cappaert, Natalie L. M.

2016-01-01

The perirhinal (PER) and entorhinal cortex (EC) receive input from the agranular insular cortex (AiP) and the subcortical lateral amygdala (LA) and the main output area is the hippocampus. Information transfer through the PER/EC network however, is not always guaranteed. It is hypothesized that this network actively regulates the (sub)cortical activity transfer to the hippocampal network and that the inhibitory system is involved in this function. This study determined the recruitment by the AiP and LA afferents in PER/EC network with the use of voltage sensitive dye (VSD) imaging in horizontal mouse brain slices. Electrical stimulation (500 μA) of the AiP induced activity that gradually propagated predominantly in the rostro-caudal direction: from the PER to the lateral EC (LEC). In the presence of 1 μM of the competitive γ-aminobutyric acid (GABAA) receptor antagonist bicuculline, AiP stimulation recruited the medial EC (MEC) as well. In contrast, LA stimulation (500 μA) only induced activity in the deep layers of the PER. In the presence of bicuculline, the initial population activity in the PER propagated further towards the superficial layers and the EC after a delay. The latency of evoked responses decreased with increasing stimulus intensities (50–500 μA) for both the AiP and LA stimuli. The stimulation threshold for evoking responses in the PER/EC network was higher for the LA than for the AiP. This study showed that the extent of the PER/EC network activation depends on release of inhibition. When GABAA dependent inhibition is reduced, both the AiP and the LA activate spatially overlapping regions, although in a distinct spatiotemporal fashion. It is therefore hypothesized that the inhibitory network regulates excitatory activity from both cortical and subcortical areas that has to be transmitted through the PER/EC network. PMID:27378860

Role of GABAergic inhibition in hippocampal network oscillations.

PubMed

Mann, Edward O; Paulsen, Ole

2007-07-01

Physiological rhythmic activity in cortical circuits relies on GABAergic inhibition to balance excitation and control spike timing. With a focus on recent experimental progress in the hippocampus, here we review the mechanisms by which synaptic inhibition can control the precise timing of spike generation, by way of effects of GABAergic events on membrane conductance ('shunting' inhibition) and membrane potential ('hyperpolarizing' inhibition). Synaptic inhibition itself can be synchronized by way of interactions within networks of GABAergic neurons, and by excitatory neurons. The importance of GABAergic mechanisms for generation of cortical rhythms is now well established. What remains to be resolved is how such inhibitory control of spike timing can be harnessed for long-range fast synchronization, and the relevance of these mechanisms to network function. This review is part of the INMED/TINS special issue Physiogenic and pathogenic oscillations: the beauty and the beast, based on presentations at the annual INMED/TINS symposium (http://inmednet.com).

Seizures beget seizures in temporal lobe epilepsies: the boomerang effects of newly formed aberrant kainatergic synapses.

PubMed

Ben-Ari, Yehezkel; Crepel, Valérie; Represa, Alfonso

2008-01-01

Do temporal lobe epilepsy (TLE) seizures in adults promote further seizures? Clinical and experimental data suggest that new synapses are formed after an initial episode of status epilepticus, however their contribution to the transformation of a naive network to an epileptogenic one has been debated. Recent experimental data show that newly formed aberrant excitatory synapses on the granule cells of the fascia dentate operate by means of kainate receptor-operated signals that are not present on naive granule cells. Therefore, genuine epileptic networks rely on signaling cascades that differentiate them from naive networks. Recurrent limbic seizures generated by the activation of kainate receptors and synapses in naive animals lead to the formation of novel synapses that facilitate the emergence of further seizures. This negative, vicious cycle illustrates the central role of reactive plasticity in neurological disorders.

Excitatory amino acid transmitters in epilepsy.

PubMed

Meldrum, B S

1991-01-01

For the majority of human epilepsy syndromes, the molecular and cellular basis for the epileptic activity remains largely conjectural. The principal hypotheses currently concern: defects in membrane ionic conductances or transport mechanisms; defects in gamma-aminobutyric acid (GABA)-mediated inhibitory processes; and enhanced or abnormal excitatory synaptic action. Substantial evidence exists in humans and animals for acquired abnormalities in excitatory amino acid neurotransmission that may participate in the abnormal patterns of neuronal discharge, and this could provide the morphological basis for a recurrent excitatory pathway sustaining seizure discharges in temporal lobe epilepsy. In practice, two approaches appear significant in the suppression of seizures. One is to act postsynaptically on receptors to decrease the excitation induced by glutamate, and the other is to decrease synaptic release of glutamate and aspartate. Agents acting upon adenosine or GABAB receptors decrease glutamate release in vitro but do not have significant anticonvulsant activity, probably because of their predominant actions at other sites. Lamotrigine blocks stimulated release of glutamate and shows anticonvulsant activity in a wide range of animal models.

Asynchronous Rate Chaos in Spiking Neuronal Circuits

PubMed Central

Harish, Omri; Hansel, David

2015-01-01

The brain exhibits temporally complex patterns of activity with features similar to those of chaotic systems. Theoretical studies over the last twenty years have described various computational advantages for such regimes in neuronal systems. Nevertheless, it still remains unclear whether chaos requires specific cellular properties or network architectures, or whether it is a generic property of neuronal circuits. We investigate the dynamics of networks of excitatory-inhibitory (EI) spiking neurons with random sparse connectivity operating in the regime of balance of excitation and inhibition. Combining Dynamical Mean-Field Theory with numerical simulations, we show that chaotic, asynchronous firing rate fluctuations emerge generically for sufficiently strong synapses. Two different mechanisms can lead to these chaotic fluctuations. One mechanism relies on slow I-I inhibition which gives rise to slow subthreshold voltage and rate fluctuations. The decorrelation time of these fluctuations is proportional to the time constant of the inhibition. The second mechanism relies on the recurrent E-I-E feedback loop. It requires slow excitation but the inhibition can be fast. In the corresponding dynamical regime all neurons exhibit rate fluctuations on the time scale of the excitation. Another feature of this regime is that the population-averaged firing rate is substantially smaller in the excitatory population than in the inhibitory population. This is not necessarily the case in the I-I mechanism. Finally, we discuss the neurophysiological and computational significance of our results. PMID:26230679

Corticostriatal Divergent Function in Determining the Temporal and Spatial Properties of Motor Tics

PubMed Central

Israelashvili, Michal

2015-01-01

Striatal disinhibition leads to the formation of motor tics resembling those expressed during Tourette syndrome and other tic disorders. The spatial properties of these tics are dependent on the location of the focal disinhibition within the striatum; however, the factors affecting the temporal properties of tic expression are still unknown. Here, we used microstimulation within the motor cortex of freely behaving rats before and after striatal disinhibition to explore the factors underlying the timing of individual tics. Cortical activation determined the timing of individual tics via an accumulation process of inputs that was dependent on the frequency and amplitude of the inputs. The resulting tics and their neuronal representation within the striatum were highly stereotypic and independent of the cortical activity properties. The generation of tics was limited by absolute and relative tic refractory periods that were derived from an internal striatal state. Thus, the precise time of the tic expression depends on the interaction between the summation of incoming excitatory inputs to the striatum and the timing of the previous tic. A data-driven computational model of corticostriatal function closely replicated the temporal properties of tic generation and enabled the prediction of tic timing based on incoming cortical activity and tic history. These converging experimental and computational findings suggest a clear functional dichotomy within the corticostriatal network, pointing to disparate temporal (cortical) versus spatial (striatal) encoding. Thus, the abnormal striatal inhibition typical of Tourette syndrome and other tic disorders results in tics due to cortical activation of the abnormal striatal network. SIGNIFICANCE STATEMENT The factors underlying the temporal properties of tics expressed in Tourette syndrome and other tic disorders have eluded clinicians and scientists for decades. In this study, we highlight the key role of corticostriatal activity in determining the timing of individual tics. We found that cortical activation determined the timing of tics but did not determine their form. A data-driven computational model of the corticostriatal network closely replicated the temporal properties of tic generation and enabled the prediction of tic timing based on incoming cortical activity and tic history. This study thus shows that, although tics originate in the striatum, their timing depends on the interplay between incoming excitatory corticostriatal inputs and the internal striatal state. PMID:26674861

Corticostriatal Divergent Function in Determining the Temporal and Spatial Properties of Motor Tics.

PubMed

Israelashvili, Michal; Bar-Gad, Izhar

2015-12-16

Striatal disinhibition leads to the formation of motor tics resembling those expressed during Tourette syndrome and other tic disorders. The spatial properties of these tics are dependent on the location of the focal disinhibition within the striatum; however, the factors affecting the temporal properties of tic expression are still unknown. Here, we used microstimulation within the motor cortex of freely behaving rats before and after striatal disinhibition to explore the factors underlying the timing of individual tics. Cortical activation determined the timing of individual tics via an accumulation process of inputs that was dependent on the frequency and amplitude of the inputs. The resulting tics and their neuronal representation within the striatum were highly stereotypic and independent of the cortical activity properties. The generation of tics was limited by absolute and relative tic refractory periods that were derived from an internal striatal state. Thus, the precise time of the tic expression depends on the interaction between the summation of incoming excitatory inputs to the striatum and the timing of the previous tic. A data-driven computational model of corticostriatal function closely replicated the temporal properties of tic generation and enabled the prediction of tic timing based on incoming cortical activity and tic history. These converging experimental and computational findings suggest a clear functional dichotomy within the corticostriatal network, pointing to disparate temporal (cortical) versus spatial (striatal) encoding. Thus, the abnormal striatal inhibition typical of Tourette syndrome and other tic disorders results in tics due to cortical activation of the abnormal striatal network. The factors underlying the temporal properties of tics expressed in Tourette syndrome and other tic disorders have eluded clinicians and scientists for decades. In this study, we highlight the key role of corticostriatal activity in determining the timing of individual tics. We found that cortical activation determined the timing of tics but did not determine their form. A data-driven computational model of the corticostriatal network closely replicated the temporal properties of tic generation and enabled the prediction of tic timing based on incoming cortical activity and tic history. This study thus shows that, although tics originate in the striatum, their timing depends on the interplay between incoming excitatory corticostriatal inputs and the internal striatal state. Copyright © 2015 the authors 0270-6474/15/3516340-12$15.00/0.

Selective reduction of excitatory hippocampal sharp waves by docosahexaenoic acid and its methyl ester analog ex-vivo.

PubMed

Taha, Ameer Y; Zahid, Tariq; Epps, Tina; Trepanier, Marc-Olivier; Burnham, W M; Bazinet, Richard P; Zhang, Liang

2013-11-06

Excitatory sharp waves (SPWs) originating from the hippocampus are considered to model the interictal "spikes" that occur in people with temporal lobe epilepsy. Docosahexaenoic acid (DHA) is an omega-3 polyunsaturated fatty acid that has been reported to reduce neuronal excitability in vitro. The effect of DHA on hippocampal SPWs, however, is not known. Our goal was to determine whether DHA suppresses SPWs in thick mouse hippocampal slices, and to compare its effects with those of oleic acid (OA, control) and the standard anticonvulsant carbamazepine (CBZ). Also tested, were DHA's structural PUFA analogs n-3 docosapentaenoic acid (n-3 DPA), n-6 docosapentaenoic acid (n-6 DPA) and DHA-methyl ester (DHA-Me). The possible involvement of GABAergic activity was also examined using GABA receptor blockers. Extracellular recordings from CA1 and CA3 regions in hippocampal slices revealed that DHA reduced the incidence of SPWs. CBZ also reduced the incidence of SPWs and was 5 time more potent than DHA. DHA's effects on SPWs was abolished in the presence of GABA-receptor blockers, suggesting involvement of the GABA system in reducing excitatory SPWs. (14)C-DHA application to the slices confirmed the incorporation of DHA into membrane phospholipids. N-3 DPA and n-6 DPA, however, which also incorporate into phospholipids, had no effect on SPWs, while DHA-Me, a DHA analog that does not incorporate into membrane phospholipids, was effective at reducing them. We conclude that DHA, but not its n-3 and n-6 analogs, reduces network excitability of the recurrent CA3 circuitry in the mouse hippocampus. This reduction may be mediated by DHA in its unesterified form, and is likely related to a modulatory effect of DHA on GABAergic activity. © 2013 Published by Elsevier B.V.

Selective Localization of Shanks to VGLUT1-Positive Excitatory Synapses in the Mouse Hippocampus

PubMed Central

Heise, Christopher; Schroeder, Jan C.; Schoen, Michael; Halbedl, Sonja; Reim, Dominik; Woelfle, Sarah; Kreutz, Michael R.; Schmeisser, Michael J.; Boeckers, Tobias M.

2016-01-01

Members of the Shank family of multidomain proteins (Shank1, Shank2, and Shank3) are core components of the postsynaptic density (PSD) of excitatory synapses. At synaptic sites Shanks serve as scaffolding molecules that cluster neurotransmitter receptors as well as cell adhesion molecules attaching them to the actin cytoskeleton. In this study we investigated the synapse specific localization of Shank1-3 and focused on well-defined synaptic contacts within the hippocampal formation. We found that all three family members are present only at VGLUT1-positive synapses, which is particularly visible at mossy fiber contacts. No costaining was found at VGLUT2-positive contacts indicating that the molecular organization of VGLUT2-associated PSDs diverges from classical VGLUT1-positive excitatory contacts in the hippocampus. In light of SHANK mutations in neuropsychiatric disorders, this study indicates which glutamatergic networks within the hippocampus will be primarily affected by shankopathies. PMID:27199660

Selective Localization of Shanks to VGLUT1-Positive Excitatory Synapses in the Mouse Hippocampus.

PubMed

Heise, Christopher; Schroeder, Jan C; Schoen, Michael; Halbedl, Sonja; Reim, Dominik; Woelfle, Sarah; Kreutz, Michael R; Schmeisser, Michael J; Boeckers, Tobias M

2016-01-01

Members of the Shank family of multidomain proteins (Shank1, Shank2, and Shank3) are core components of the postsynaptic density (PSD) of excitatory synapses. At synaptic sites Shanks serve as scaffolding molecules that cluster neurotransmitter receptors as well as cell adhesion molecules attaching them to the actin cytoskeleton. In this study we investigated the synapse specific localization of Shank1-3 and focused on well-defined synaptic contacts within the hippocampal formation. We found that all three family members are present only at VGLUT1-positive synapses, which is particularly visible at mossy fiber contacts. No costaining was found at VGLUT2-positive contacts indicating that the molecular organization of VGLUT2-associated PSDs diverges from classical VGLUT1-positive excitatory contacts in the hippocampus. In light of SHANK mutations in neuropsychiatric disorders, this study indicates which glutamatergic networks within the hippocampus will be primarily affected by shankopathies.

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

PubMed Central

Endo, Toshiaki; Kiehn, Ole

2008-01-01

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

The Neurona at Home project: Simulating a large-scale cellular automata brain in a distributed computing environment

NASA Astrophysics Data System (ADS)

Acedo, L.; Villanueva-Oller, J.; Moraño, J. A.; Villanueva, R.-J.

2013-01-01

The Berkeley Open Infrastructure for Network Computing (BOINC) has become the standard open source solution for grid computing in the Internet. Volunteers use their computers to complete an small part of the task assigned by a dedicated server. We have developed a BOINC project called Neurona@Home whose objective is to simulate a cellular automata random network with, at least, one million neurons. We consider a cellular automata version of the integrate-and-fire model in which excitatory and inhibitory nodes can activate or deactivate neighbor nodes according to a set of probabilistic rules. Our aim is to determine the phase diagram of the model and its behaviour and to compare it with the electroencephalographic signals measured in real brains.

Low doses of cyclic AMP-phosphodiesterase inhibitors rapidly evoke opioid receptor-mediated thermal hyperalgesia in naïve mice which is converted to prominent analgesia by cotreatment with ultra-low-dose naltrexone.

PubMed

Crain, Stanley M; Shen, Ke-Fei

2008-09-22

Systemic (s.c.) injection in naïve mice of cyclic AMP-phosphodiesterase (cAMP-PDE) inhibitors, e.g. 3-isobutyl-1-methylxanthine [(IBMX) or caffeine, 10 mg/kg] or the more specific cAMP-PDE inhibitor, rolipram (1 mug/kg), rapidly evokes thermal hyperalgesia (lasting >5 h). These effects appear to be mediated by enhanced excitatory opioid receptor signaling, as occurs during withdrawal in opioid-dependent mice. Cotreatment of these mice with ultra-low-dose naltrexone (NTX, 0.1 ng/kg-1 pg/kg, s.c.) results in prominent opioid analgesia (lasting >4 h) even when the dose of rolipram is reduced to 1 pg/kg. Cotreatment of these cAMP-PDE inhibitors in naïve mice with an ultra-low-dose (0.1 ng/kg) of the kappa-opioid receptor antagonist, nor-binaltorphimine (nor-BNI) or the mu-opioid receptor antagonist, beta-funaltrexamine (beta-FNA) also results in opioid analgesia. These excitatory effects of cAMP-PDE inhibitors in naïve mice may be mediated by enhanced release of small amounts of endogenous bimodally-acting (excitatory/inhibitory) opioid agonists by neurons in nociceptive networks. Ultra-low-dose NTX, nor-BNI or beta-FNA selectively antagonizes high-efficacy excitatory (hyperalgesic) Gs-coupled opioid receptor-mediated signaling in naïve mice and results in rapid conversion to inhibitory (analgesic) Gi/Go-coupled opioid receptor-mediated signaling which normally requires activation by much higher doses of opioid agonists. Cotreatment with a low subanalgesic dose of kelatorphan, an inhibitor of multiple endogenous opioid peptide-degrading enzymes, stabilizes endogenous opioid agonists released by cAMP-PDE inhibitors, resulting in conversion of the hyperalgesia to analgesia without requiring selective blockade of excitatory opioid receptor signaling. The present study provides a novel pharmacologic paradigm that may facilitate development of valuable non-narcotic clinical analgesics utilizing cotreatment with ultra-low-dose rolipram plus ultra-low-dose NTX or related agents.

Balance of excitation and inhibition determines 1/f power spectrum in neuronal networks.

PubMed

Lombardi, F; Herrmann, H J; de Arcangelis, L

2017-04-01

The 1/f-like decay observed in the power spectrum of electro-physiological signals, along with scale-free statistics of the so-called neuronal avalanches, constitutes evidence of criticality in neuronal systems. Recent in vitro studies have shown that avalanche dynamics at criticality corresponds to some specific balance of excitation and inhibition, thus suggesting that this is a basic feature of the critical state of neuronal networks. In particular, a lack of inhibition significantly alters the temporal structure of the spontaneous avalanche activity and leads to an anomalous abundance of large avalanches. Here, we study the relationship between network inhibition and the scaling exponent β of the power spectral density (PSD) of avalanche activity in a neuronal network model inspired in Self-Organized Criticality. We find that this scaling exponent depends on the percentage of inhibitory synapses and tends to the value β = 1 for a percentage of about 30%. More specifically, β is close to 2, namely, Brownian noise, for purely excitatory networks and decreases towards values in the interval [1, 1.4] as the percentage of inhibitory synapses ranges between 20% and 30%, in agreement with experimental findings. These results indicate that the level of inhibition affects the frequency spectrum of resting brain activity and suggest the analysis of the PSD scaling behavior as a possible tool to study pathological conditions.

Balance of excitation and inhibition determines 1/f power spectrum in neuronal networks

NASA Astrophysics Data System (ADS)

Lombardi, F.; Herrmann, H. J.; de Arcangelis, L.

2017-04-01

The 1/f-like decay observed in the power spectrum of electro-physiological signals, along with scale-free statistics of the so-called neuronal avalanches, constitutes evidence of criticality in neuronal systems. Recent in vitro studies have shown that avalanche dynamics at criticality corresponds to some specific balance of excitation and inhibition, thus suggesting that this is a basic feature of the critical state of neuronal networks. In particular, a lack of inhibition significantly alters the temporal structure of the spontaneous avalanche activity and leads to an anomalous abundance of large avalanches. Here, we study the relationship between network inhibition and the scaling exponent β of the power spectral density (PSD) of avalanche activity in a neuronal network model inspired in Self-Organized Criticality. We find that this scaling exponent depends on the percentage of inhibitory synapses and tends to the value β = 1 for a percentage of about 30%. More specifically, β is close to 2, namely, Brownian noise, for purely excitatory networks and decreases towards values in the interval [1, 1.4] as the percentage of inhibitory synapses ranges between 20% and 30%, in agreement with experimental findings. These results indicate that the level of inhibition affects the frequency spectrum of resting brain activity and suggest the analysis of the PSD scaling behavior as a possible tool to study pathological conditions.

Erythropoietin attenuates loss of potassium chloride co-transporters following prenatal brain injury.

PubMed

Jantzie, L L; Getsy, P M; Firl, D J; Wilson, C G; Miller, R H; Robinson, S

2014-07-01

Therapeutic agents that restore the inhibitory actions of γ-amino butyric acid (GABA) by modulating intracellular chloride concentrations will provide novel avenues to treat stroke, chronic pain, epilepsy, autism, and neurodegenerative and cognitive disorders. During development, upregulation of the potassium-chloride co-transporter KCC2, and the resultant switch from excitatory to inhibitory responses to GABA guide the formation of essential inhibitory circuits. Importantly, maturation of inhibitory mechanisms is also central to the development of excitatory circuits and proper balance between excitatory and inhibitory networks in the developing brain. Loss of KCC2 expression occurs in postmortem samples from human preterm infant brains with white matter lesions. Here we show that late gestation brain injury in a rat model of extreme prematurity impairs the developmental upregulation of potassium chloride co-transporters during a critical postnatal period of circuit maturation in CA3 hippocampus by inducing a sustained loss of oligomeric KCC2 via a calpain-dependent mechanism. Further, administration of erythropoietin (EPO) in a clinically relevant postnatal dosing regimen following the prenatal injury protects the developing brain by reducing calpain activity, restoring oligomeric KCC2 expression and attenuating KCC2 fragmentation, thus providing the first report of a safe therapy to address deficits in KCC2 expression. Together, these data indicate it is possible to reverse abnormalities in KCC2 expression during the postnatal period, and potentially reverse deficits in inhibitory circuit formation central to cognitive impairment and epileptogenesis. Copyright © 2014 Elsevier Inc. All rights reserved.

Higher-order associative processing in Hermissenda suggests multiple sites of neuronal modulation.

PubMed

Rogers, R F; Matzel, L D

1996-01-01

Two important features of modern accounts of associative learning are (1) the capacity for contextual stimuli to serve as a signal for an unconditioned stimulus (US) and (2) the capacity for a previously conditioned (excitatory) stimulus to "block" learning about a redundant stimulus when both stimuli serve as a signal for the same US. Here, we examined the process of blocking, thought by some to reflect a cognitive aspect of classical conditioning, and its underlying mechanisms in the marine mollusc Hermissenda. In two behavioral experiments, a context defined by chemosensory stimuli was made excitatory by presenting unsignalled USs (rotation) in that context. The excitatory context subsequently blocked overt learning about a discrete conditioned stimulus (CS; light) paired with the US in that context. In a third experiment, the excitability of the B photoreceptors in the Hermissenda eye, which typically increases following light-rotation pairings, was examined in behaviorally blocked animals, as well as in animals that had acquired a normal CS-US association or animals that had been exposed to the CS and US unpaired. Both the behaviorally blocked and the "normal" learning groups exhibited increases in neuronal excitability relative to unpaired animals. However, light-induced multiunit activity in pedal nerves was suppressed following normal conditioning but not in blocked or unpaired control animals, suggesting that the expression of blocking is mediated by neuronal modifications not directly reflected in B-cell excitability, possibly within an extensive network of central light-responsive interneurons.

Interactions between Inhibitory Interneurons and Excitatory Associational Circuitry in Determining Spatio-Temporal Dynamics of Hippocampal Dentate Granule Cells: A Large-Scale Computational Study

PubMed Central

Hendrickson, Phillip J.; Yu, Gene J.; Song, Dong; Berger, Theodore W.

2015-01-01

This paper reports on findings from a million-cell granule cell model of the rat dentate gyrus that was used to explore the contributions of local interneuronal and associational circuits to network-level activity. The model contains experimentally derived morphological parameters for granule cells, which each contain approximately 200 compartments, and biophysical parameters for granule cells, basket cells, and mossy cells that were based both on electrophysiological data and previously published models. Synaptic input to cells in the model consisted of glutamatergic AMPA-like EPSPs and GABAergic-like IPSPs from excitatory and inhibitory neurons, respectively. The main source of input to the model was from layer II entorhinal cortical neurons. Network connectivity was constrained by the topography of the system, and was derived from axonal transport studies, which provided details about the spatial spread of axonal terminal fields, as well as how subregions of the medial and lateral entorhinal cortices project to subregions of the dentate gyrus. Results of this study show that strong feedback inhibition from the basket cell population can cause high-frequency rhythmicity in granule cells, while the strength of feedforward inhibition serves to scale the total amount of granule cell activity. Results furthermore show that the topography of local interneuronal circuits can have just as strong an impact on the development of spatio-temporal clusters in the granule cell population as the perforant path topography does, both sharpening existing clusters and introducing new ones with a greater spatial extent. Finally, results show that the interactions between the inhibitory and associational loops can cause high frequency oscillations that are modulated by a low-frequency oscillatory signal. These results serve to further illustrate the importance of topographical constraints on a global signal processing feature of a neural network, while also illustrating how rich spatio-temporal and oscillatory dynamics can evolve from a relatively small number of interacting local circuits. PMID:26635545

Cationic influences upon synaptic transmission at the hair cell-afferent fiber synapse of the frog

NASA Technical Reports Server (NTRS)

Cochran, S. L.

1995-01-01

The concentrations of inorganic cations (K+, Na+, and Ca2+) bathing the isolated frog labyrinth were varied in order to assess their role in influencing and mediating synaptic transmission at the hair cell-afferent fiber synapse. Experiments employed intracellular recordings of synaptic activity from VIIIth nerve afferents. Recordings were digitized continuously at 50 kHz, and excitatory postsynaptic potentials were detected and parameters quantified by computer algorithms. Particular attention was focused on cationic effects upon excitatory postsynaptic potential frequency of occurrence and excitatory postsynaptic potential amplitude, in order to discriminate between pre- and postsynaptic actions. Because the small size of afferents preclude long term stable recordings, alterations in cationic concentrations were applied transiently and their peak effects on synaptic activity were assessed. Increases in extracellular K+ concentration of a few millimolar produced a large increase in the frequency of occurrence of excitatory postsynaptic potentials with little change in amplitude, indicating that release of transmitter from the hair cell is tightly coupled to its membrane potential. Increasing extracellular Na+ concentration resulted in an increase in excitatory postsynaptic potential amplitude with no significant change in excitatory postsynaptic potential frequency of occurrence, suggesting that the transmitter-gated subsynaptic channel conducts Na+ ions. Decreases in extracellular Ca2+ concentration had little effect upon excitatory postsynaptic potential frequency, but increased excitatory postsynaptic potential frequency and amplitude. These findings suggest that at higher concentrations Ca2+ act presynaptically to prevent transmitter release and postsynaptically to prevent Na+ influx during the generation of the excitatory postsynaptic potential. The influences of these ions on synaptic activity at this synapse are remarkably similar to those reported at the vertebrate neuromuscular junction. The major differences between these two synapses are the neurotransmitters and the higher resting release rate and higher sensitivity of release to increased K+ concentrations of the hair cells over that of motor nerve terminals. These differences reflect the functional roles of the two synapses: the motor nerve terminal response in an all-or-nothing signal consequent from action potential invasion, while the hair cell releases transmitter in a graded fashion, proportionate to the extent of stereocilial deflection. Despite these differences between the two junctions, the similar actions of these elemental cations upon synaptic function at each implies that these ions may participate similarly in the operations of other synapses, independent of the neurotransmitter type.(ABSTRACT TRUNCATED AT 400 WORDS).

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.

Entorhinal Denervation Induces Homeostatic Synaptic Scaling of Excitatory Postsynapses of Dentate Granule Cells in Mouse Organotypic Slice Cultures

PubMed Central

Vlachos, Andreas; Becker, Denise; Jedlicka, Peter; Winkels, Raphael; Roeper, Jochen; Deller, Thomas

2012-01-01

Denervation-induced changes in excitatory synaptic strength were studied following entorhinal deafferentation of hippocampal granule cells in mature (≥3 weeks old) mouse organotypic entorhino-hippocampal slice cultures. Whole-cell patch-clamp recordings revealed an increase in excitatory synaptic strength in response to denervation during the first week after denervation. By the end of the second week synaptic strength had returned to baseline. Because these adaptations occurred in response to the loss of excitatory afferents, they appeared to be in line with a homeostatic adjustment of excitatory synaptic strength. To test whether denervation-induced changes in synaptic strength exploit similar mechanisms as homeostatic synaptic scaling following pharmacological activity blockade, we treated denervated cultures at 2 days post lesion for 2 days with tetrodotoxin. In these cultures, the effects of denervation and activity blockade were not additive, suggesting that similar mechanisms are involved. Finally, we investigated whether entorhinal denervation, which removes afferents from the distal dendrites of granule cells while leaving the associational afferents to the proximal dendrites of granule cells intact, results in a global or a local up-scaling of granule cell synapses. By using computational modeling and local electrical stimulations in Strontium (Sr2+)-containing bath solution, we found evidence for a lamina-specific increase in excitatory synaptic strength in the denervated outer molecular layer at 3–4 days post lesion. Taken together, our data show that entorhinal denervation results in homeostatic functional changes of excitatory postsynapses of denervated dentate granule cells in vitro. PMID:22403720

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

Effects of inhibitory neurons on the quorum percolation model and dynamical extension with the Brette-Gerstner model

NASA Astrophysics Data System (ADS)

Fardet, Tanguy; Bottani, Samuel; Métens, Stéphane; Monceau, Pascal

2018-06-01

The Quorum Percolation model (QP) has been designed in the context of neurobiology to describe the initiation of activity bursts occurring in neuronal cultures from the point of view of statistical physics rather than from a dynamical synchronization approach. This paper aims at investigating an extension of the original QP model by taking into account the presence of inhibitory neurons in the cultures (IQP model). The first part of this paper is focused on an equivalence between the presence of inhibitory neurons and a reduction of the network connectivity. By relying on a simple topological argument, we show that the mean activation behavior of networks containing a fraction η of inhibitory neurons can be mapped onto purely excitatory networks with an appropriately modified wiring, provided that η remains in the range usually observed in neuronal cultures, namely η ⪅ 20%. As a striking result, we show that such a mapping enables to predict the evolution of the critical point of the IQP model with the fraction of inhibitory neurons. In a second part, we bridge the gap between the description of bursts in the framework of percolation and the temporal description of neural networks activity by showing how dynamical simulations of bursts with an adaptive exponential integrate-and-fire model lead to a mean description of bursts activation which is captured by Quorum Percolation.

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.

Inference of topology and the nature of synapses, and the flow of information in neuronal networks

NASA Astrophysics Data System (ADS)

Borges, F. S.; Lameu, E. L.; Iarosz, K. C.; Protachevicz, P. R.; Caldas, I. L.; Viana, R. L.; Macau, E. E. N.; Batista, A. M.; Baptista, M. S.

2018-02-01

The characterization of neuronal connectivity is one of the most important matters in neuroscience. In this work, we show that a recently proposed informational quantity, the causal mutual information, employed with an appropriate methodology, can be used not only to correctly infer the direction of the underlying physical synapses, but also to identify their excitatory or inhibitory nature, considering easy to handle and measure bivariate time series. The success of our approach relies on a surprising property found in neuronal networks by which nonadjacent neurons do "understand" each other (positive mutual information), however, this exchange of information is not capable of causing effect (zero transfer entropy). Remarkably, inhibitory connections, responsible for enhancing synchronization, transfer more information than excitatory connections, known to enhance entropy in the network. We also demonstrate that our methodology can be used to correctly infer directionality of synapses even in the presence of dynamic and observational Gaussian noise, and is also successful in providing the effective directionality of intermodular connectivity, when only mean fields can be measured.

Excitatory and inhibitory synaptic mechanisms at the first stage of integration in the electroreception system of the shark

PubMed Central

Rotem, Naama; Sestieri, Emanuel; Hounsgaard, Jorn; Yarom, Yosef

2014-01-01

High impulse rate in afferent nerves is a common feature in many sensory systems that serve to accommodate a wide dynamic range. However, the first stage of integration should be endowed with specific properties that enable efficient handling of the incoming information. In elasmobranches, the afferent nerve originating from the ampullae of Lorenzini targets specific neurons located at the Dorsal Octavolateral Nucleus (DON), the first stage of integration in the electroreception system. Using intracellular recordings in an isolated brainstem preparation from the shark we analyze the properties of this afferent pathway. We found that stimulating the afferent nerve activates a mixture of excitatory and inhibitory synapses mediated by AMPA-like and GABAA receptors, respectively. The excitatory synapses that are extremely efficient in activating the postsynaptic neurons display unusual voltage dependence, enabling them to operate as a current source. The inhibitory input is powerful enough to completely eliminate the excitatory action of the afferent nerve but is ineffective regarding other excitatory inputs. These observations can be explained by the location and efficiency of the synapses. We conclude that the afferent nerve provides powerful and reliable excitatory input as well as a feed-forward inhibitory input, which is partially presynaptic in origin. These results question the cellular location within the DON where cancelation of expected incoming signals occurs. PMID:24639631

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

Rapid Long-Range Disynaptic Inhibition Explains the Formation of Cortical Orientation Maps

PubMed Central

Antolík, Ján

2017-01-01

Competitive interactions are believed to underlie many types of cortical processing, ranging from memory formation, attention and development of cortical functional organization (e.g., development of orientation maps in primary visual cortex). In the latter case, the competitive interactions happen along the cortical surface, with local populations of neurons reinforcing each other, while competing with those displaced more distally. This specific configuration of lateral interactions is however in stark contrast with the known properties of the anatomical substrate, i.e., excitatory connections (mediating reinforcement) having longer reach than inhibitory ones (mediating competition). No satisfactory biologically plausible resolution of this conflict between anatomical measures, and assumed cortical function has been proposed. Recently a specific pattern of delays between different types of neurons in cat cortex has been discovered, where direct mono-synaptic excitation has approximately the same delay, as the combined delays of the disynaptic inhibitory interactions between excitatory neurons (i.e., the sum of delays from excitatory to inhibitory and from inhibitory to excitatory neurons). Here we show that this specific pattern of delays represents a biologically plausible explanation for how short-range inhibition can support competitive interactions that underlie the development of orientation maps in primary visual cortex. We demonstrate this statement analytically under simplifying conditions, and subsequently show using network simulations that development of orientation maps is preserved when long-range excitation, direct inhibitory to inhibitory interactions, and moderate inequality in the delays between excitatory and inhibitory pathways is added. PMID:28408869

Computer simulations of stimulus dependent state switching in basic circuits of bursting neurons

NASA Astrophysics Data System (ADS)

Rabinovich, Mikhail; Huerta, Ramón; Bazhenov, Maxim; Kozlov, Alexander K.; Abarbanel, Henry D. I.

1998-11-01

We investigate the ability of oscillating neural circuits to switch between different states of oscillation in two basic neural circuits. We model two quite distinct small neural circuits. The first circuit is based on invertebrate central pattern generator (CPG) studies [A. I. Selverston and M. Moulins, The Crustacean Stomatogastric System (Springer-Verlag, Berlin, 1987)] and is composed of two neurons coupled via both gap junction and inhibitory synapses. The second consists of coupled pairs of interconnected thalamocortical relay and thalamic reticular neurons with both inhibitory and excitatory synaptic coupling. The latter is an elementary unit of the thalamic networks passing sensory information to the cerebral cortex [M. Steriade, D. A. McCormick, and T. J. Sejnowski, Science 262, 679 (1993)]. Both circuits have contradictory coupling between symmetric parts. The thalamocortical model has excitatory and inhibitory connections and the CPG has reciprocal inhibitory and electrical coupling. We describe the dynamics of the individual neurons in these circuits by conductance based ordinary differential equations of Hodgkin-Huxley type [J. Physiol. (London) 117, 500 (1952)]. Both model circuits exhibit bistability and hysteresis in a wide region of coupling strengths. The two main modes of behavior are in-phase and out-of-phase oscillations of the symmetric parts of the network. We investigate the response of these circuits, while they are operating in bistable regimes, to externally imposed excitatory spike trains with varying interspike timing and small amplitude pulses. These are meant to represent spike trains received by the basic circuits from sensory neurons. Circuits operating in a bistable region are sensitive to the frequency of these excitatory inputs. Frequency variations lead to changes from in-phase to out-of-phase coordination or vice versa. The signaling information contained in a spike train driving the network can place the circuit into one or another state depending on the interspike interval and this happens within a few spikes. These states are maintained by the basic circuit after the input signal is ended. When a new signal of the correct frequency enters the circuit, it can be switched to another state with the same ease.

Functional Differentiation of a Population of Electrically-Coupled Heterogeneous Elements in a Microcircuit

PubMed Central

Sasaki, Kosei; Cropper, Elizabeth C; Weiss, Klaudiusz R; Jing, Jian

2013-01-01

Although electrical coupling is present in many microcircuits, the extent to which it will determine neuronal firing patterns and network activity remains poorly understood. This is particularly true when the coupling is present in a population of heterogeneous, or intrinsically distinct circuit elements. We examine this question in the Aplysia californica feeding motor network in five electrically-coupled identified cells, B64, B4/5, B70, B51 and a newly-identified interneuron B71. These neurons exhibit distinct activity patterns during the radula retraction phase of motor programs. In a subset of motor programs, retraction can be flexibly extended by adding a phase of network activity (hyper-retraction). This is manifested most prominently as an additional burst in the radula closure motoneuron B8. Two neurons that excite B8 (B51 and B71) and one that inhibits it (B70) are active during hyper-retraction. Consistent with their near synchronous firing, B51 and B71 showed one of the strongest coupling ratios in this group of neurons. Nonetheless, by manipulating their activity, we found that B51 preferentially acted as a driver of B64/B71 activity, whereas B71 played a larger role in driving B8 activity. In contrast, B70 was weakly coupled to other neurons and its inhibition of B8 counter-acted the excitatory drive to B8. Finally, the distinct firing patterns of the electrically-coupled neurons were fine-tuned by their intrinsic properties and the largely chemical cross-inhibition between some of them. Thus, the small microcircuit of Aplysia feeding network is advantageous in understanding how a population of electrically-coupled heterogeneous neurons may fulfill specific network functions. PMID:23283325

A computational model of the respiratory network challenged and optimized by data from optogenetic manipulation of glycinergic neurons.

PubMed

Oku, Yoshitaka; Hülsmann, Swen

2017-04-07

The topology of the respiratory network in the brainstem has been addressed using different computational models, which help to understand the functional properties of the system. We tested a neural mass model by comparing the result of activation and inhibition of inhibitory neurons in silico with recently published results of optogenetic manipulation of glycinergic neurons [Sherman, et al. (2015) Nat Neurosci 18:408]. The comparison revealed that a five-cell type model consisting of three classes of inhibitory neurons [I-DEC, E-AUG, E-DEC (PI)] and two excitatory populations (pre-I/I) and (I-AUG) neurons can be applied to explain experimental observations made by stimulating or inhibiting inhibitory neurons by light sensitive ion channels. Copyright © 2017 IBRO. Published by Elsevier Ltd. All rights reserved.

Ambra1 Shapes Hippocampal Inhibition/Excitation Balance: Role in Neurodevelopmental Disorders.

PubMed

Nobili, Annalisa; Krashia, Paraskevi; Cordella, Alberto; La Barbera, Livia; Dell'Acqua, Maria Concetta; Caruso, Angela; Pignataro, Annabella; Marino, Ramona; Sciarra, Francesca; Biamonte, Filippo; Scattoni, Maria Luisa; Ammassari-Teule, Martine; Cecconi, Francesco; Berretta, Nicola; Keller, Flavio; Mercuri, Nicola Biagio; D'Amelio, Marcello

2018-02-27

Imbalances between excitatory and inhibitory synaptic transmission cause brain network dysfunction and are central to the pathogenesis of neurodevelopmental disorders. Parvalbumin interneurons are highly implicated in this imbalance. Here, we probed the social behavior and hippocampal function of mice carrying a haploinsufficiency for Ambra1, a pro-autophagic gene crucial for brain development. We show that heterozygous Ambra1 mice (Ambra +/- ) are characterized by loss of hippocampal parvalbumin interneurons, decreases in the inhibition/excitation ratio, and altered social behaviors that are solely restricted to the female gender. Loss of parvalbumin interneurons in Ambra1 +/- females is further linked to reductions of the inhibitory drive onto principal neurons and alterations in network oscillatory activity, CA1 synaptic plasticity, and pyramidal neuron spine density. Parvalbumin interneuron loss is underlined by increased apoptosis during the embryonic development of progenitor neurons in the medial ganglionic eminence. Together, these findings identify an Ambra1-dependent mechanism that drives inhibition/excitation imbalance in the hippocampus, contributing to abnormal brain activity reminiscent of neurodevelopmental disorders.

AMPA GluA1-flip targeted oligonucleotide therapy reduces neonatal seizures and hyperexcitability

PubMed Central

Lykens, Nicole M.; Reddi, Jyoti M.

2017-01-01

Glutamate-activated α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptors (AMPA-Rs) mediate the majority of excitatory neurotransmission in brain and thus are major drug targets for diseases associated with hyperexcitability or neurotoxicity. Due to the critical nature of AMPA-Rs in normal brain function, typical AMPA-R antagonists have deleterious effects on cognition and motor function, highlighting the need for more precise modulators. A dramatic increase in the flip isoform of alternatively spliced AMPA-R GluA1 subunits occurs post-seizure in humans and animal models. GluA1-flip produces higher gain AMPA channels than GluA1-flop, increasing network excitability and seizure susceptibility. Splice modulating oligonucleotides (SMOs) bind to pre-mRNA to influence alternative splicing, a strategy that can be exploited to develop more selective drugs across therapeutic areas. We developed a novel SMO, GR1, which potently and specifically decreased GluA1-flip expression throughout the brain of neonatal mice lasting at least 60 days after single intracerebroventricular injection. GR1 treatment reduced AMPA-R mediated excitatory postsynaptic currents at hippocampal CA1 synapses, without affecting long-term potentiation or long-term depression, cellular models of memory, or impairing GluA1-dependent cognition or motor function in mice. Importantly, GR1 demonstrated anti-seizure properties and reduced post-seizure hyperexcitability in neonatal mice, highlighting its drug candidate potential for treating epilepsies and other neurological diseases involving network hyperexcitability. PMID:28178321

Where’s the Noise? Key Features of Spontaneous Activity and Neural Variability Arise through Learning in a Deterministic Network

PubMed Central

Hartmann, Christoph; Lazar, Andreea; Nessler, Bernhard; Triesch, Jochen

2015-01-01

Even in the absence of sensory stimulation the brain is spontaneously active. This background “noise” seems to be the dominant cause of the notoriously high trial-to-trial variability of neural recordings. Recent experimental observations have extended our knowledge of trial-to-trial variability and spontaneous activity in several directions: 1. Trial-to-trial variability systematically decreases following the onset of a sensory stimulus or the start of a motor act. 2. Spontaneous activity states in sensory cortex outline the region of evoked sensory responses. 3. Across development, spontaneous activity aligns itself with typical evoked activity patterns. 4. The spontaneous brain activity prior to the presentation of an ambiguous stimulus predicts how the stimulus will be interpreted. At present it is unclear how these observations relate to each other and how they arise in cortical circuits. Here we demonstrate that all of these phenomena can be accounted for by a deterministic self-organizing recurrent neural network model (SORN), which learns a predictive model of its sensory environment. The SORN comprises recurrently coupled populations of excitatory and inhibitory threshold units and learns via a combination of spike-timing dependent plasticity (STDP) and homeostatic plasticity mechanisms. Similar to balanced network architectures, units in the network show irregular activity and variable responses to inputs. Additionally, however, the SORN exhibits sequence learning abilities matching recent findings from visual cortex and the network’s spontaneous activity reproduces the experimental findings mentioned above. Intriguingly, the network’s behaviour is reminiscent of sampling-based probabilistic inference, suggesting that correlates of sampling-based inference can develop from the interaction of STDP and homeostasis in deterministic networks. We conclude that key observations on spontaneous brain activity and the variability of neural responses can be accounted for by a simple deterministic recurrent neural network which learns a predictive model of its sensory environment via a combination of generic neural plasticity mechanisms. PMID:26714277

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

Differential Modulation of Excitatory and Inhibitory Neurons during Periodic Stimulation

PubMed Central

Mahmud, Mufti; Vassanelli, Stefano

2016-01-01

Non-invasive transcranial neuronal stimulation, in addition to deep brain stimulation, is seen as a promising therapeutic and diagnostic approach for an increasing number of neurological diseases such as epilepsy, cluster headaches, depression, specific type of blindness, and other central nervous system disfunctions. Improving its effectiveness and widening its range of use may strongly rely on development of proper stimulation protocols that are tailored to specific brain circuits and that are based on a deep knowledge of different neuron types response to stimulation. To this aim, we have performed a simulation study on the behavior of excitatory and inhibitory neurons subject to sinusoidal stimulation. Due to the intrinsic difference in membrane conductance properties of excitatory and inhibitory neurons, we show that their firing is differentially modulated by the wave parameters. We analyzed the behavior of the two neuronal types for a broad range of stimulus frequency and amplitude and demonstrated that, within a small-world network prototype, parameters tuning allow for a selective enhancement or suppression of the excitation/inhibition ratio. PMID:26941602

When do correlations increase with firing rates in recurrent networks?

PubMed Central

2017-01-01

A central question in neuroscience is to understand how noisy firing patterns are used to transmit information. Because neural spiking is noisy, spiking patterns are often quantified via pairwise correlations, or the probability that two cells will spike coincidentally, above and beyond their baseline firing rate. One observation frequently made in experiments, is that correlations can increase systematically with firing rate. Theoretical studies have determined that stimulus-dependent correlations that increase with firing rate can have beneficial effects on information coding; however, we still have an incomplete understanding of what circuit mechanisms do, or do not, produce this correlation-firing rate relationship. Here, we studied the relationship between pairwise correlations and firing rates in recurrently coupled excitatory-inhibitory spiking networks with conductance-based synapses. We found that with stronger excitatory coupling, a positive relationship emerged between pairwise correlations and firing rates. To explain these findings, we used linear response theory to predict the full correlation matrix and to decompose correlations in terms of graph motifs. We then used this decomposition to explain why covariation of correlations with firing rate—a relationship previously explained in feedforward networks driven by correlated input—emerges in some recurrent networks but not in others. Furthermore, when correlations covary with firing rate, this relationship is reflected in low-rank structure in the correlation matrix. PMID:28448499

Computational Account of Spontaneous Activity as a Signature of Predictive Coding

PubMed Central

Koren, Veronika

2017-01-01

Spontaneous activity is commonly observed in a variety of cortical states. Experimental evidence suggested that neural assemblies undergo slow oscillations with Up ad Down states even when the network is isolated from the rest of the brain. Here we show that these spontaneous events can be generated by the recurrent connections within the network and understood as signatures of neural circuits that are correcting their internal representation. A noiseless spiking neural network can represent its input signals most accurately when excitatory and inhibitory currents are as strong and as tightly balanced as possible. However, in the presence of realistic neural noise and synaptic delays, this may result in prohibitively large spike counts. An optimal working regime can be found by considering terms that control firing rates in the objective function from which the network is derived and then minimizing simultaneously the coding error and the cost of neural activity. In biological terms, this is equivalent to tuning neural thresholds and after-spike hyperpolarization. In suboptimal working regimes, we observe spontaneous activity even in the absence of feed-forward inputs. In an all-to-all randomly connected network, the entire population is involved in Up states. In spatially organized networks with local connectivity, Up states spread through local connections between neurons of similar selectivity and take the form of a traveling wave. Up states are observed for a wide range of parameters and have similar statistical properties in both active and quiescent state. In the optimal working regime, Up states are vanishing, leaving place to asynchronous activity, suggesting that this working regime is a signature of maximally efficient coding. Although they result in a massive increase in the firing activity, the read-out of spontaneous Up states is in fact orthogonal to the stimulus representation, therefore interfering minimally with the network function. PMID:28114353

A reanalysis of "Two types of asynchronous activity in networks of excitatory and inhibitory spiking neurons".

PubMed

Engelken, Rainer; Farkhooi, Farzad; Hansel, David; van Vreeswijk, Carl; Wolf, Fred

2016-01-01

Neuronal activity in the central nervous system varies strongly in time and across neuronal populations. It is a longstanding proposal that such fluctuations generically arise from chaotic network dynamics. Various theoretical studies predict that the rich dynamics of rate models operating in the chaotic regime can subserve circuit computation and learning. Neurons in the brain, however, communicate via spikes and it is a theoretical challenge to obtain similar rate fluctuations in networks of spiking neuron models. A recent study investigated spiking balanced networks of leaky integrate and fire (LIF) neurons and compared their dynamics to a matched rate network with identical topology, where single unit input-output functions were chosen from isolated LIF neurons receiving Gaussian white noise input. A mathematical analogy between the chaotic instability in networks of rate units and the spiking network dynamics was proposed. Here we revisit the behavior of the spiking LIF networks and these matched rate networks. We find expected hallmarks of a chaotic instability in the rate network: For supercritical coupling strength near the transition point, the autocorrelation time diverges. For subcritical coupling strengths, we observe critical slowing down in response to small external perturbations. In the spiking network, we found in contrast that the timescale of the autocorrelations is insensitive to the coupling strength and that rate deviations resulting from small input perturbations rapidly decay. The decay speed even accelerates for increasing coupling strength. In conclusion, our reanalysis demonstrates fundamental differences between the behavior of pulse-coupled spiking LIF networks and rate networks with matched topology and input-output function. In particular there is no indication of a corresponding chaotic instability in the spiking network.

Analysis of globally connected active rotators with excitatory and inhibitory connections using the Fokker-Planck equation

NASA Astrophysics Data System (ADS)

Kanamaru, Takashi; Sekine, Masatoshi

2003-03-01

The globally connected active rotators with excitatory and inhibitory connections are analyzed using the nonlinear Fokker-Planck equation. The bifurcation diagram of the system is obtained numerically, and both periodic solutions and chaotic solutions are found. By observing the interspike interval, the coefficient of variance, and the correlation coefficient of the system, the relationship of our model to the biological data is discussed.

An excitatory paraventricular nucleus to AgRP neuron circuit that drives hunger.

PubMed

Krashes, Michael J; Shah, Bhavik P; Madara, Joseph C; Olson, David P; Strochlic, David E; Garfield, Alastair S; Vong, Linh; Pei, Hongjuan; Watabe-Uchida, Mitsuko; Uchida, Naoshige; Liberles, Stephen D; Lowell, Bradford B

2014-03-13

Hunger is a hard-wired motivational state essential for survival. Agouti-related peptide (AgRP)-expressing neurons in the arcuate nucleus (ARC) at the base of the hypothalamus are crucial to the control of hunger. They are activated by caloric deficiency and, when naturally or artificially stimulated, they potently induce intense hunger and subsequent food intake. Consistent with their obligatory role in regulating appetite, genetic ablation or chemogenetic inhibition of AgRP neurons decreases feeding. Excitatory input to AgRP neurons is important in caloric-deficiency-induced activation, and is notable for its remarkable degree of caloric-state-dependent synaptic plasticity. Despite the important role of excitatory input, its source(s) has been unknown. Here, through the use of Cre-recombinase-enabled, cell-specific neuron mapping techniques in mice, we have discovered strong excitatory drive that, unexpectedly, emanates from the hypothalamic paraventricular nucleus, specifically from subsets of neurons expressing thyrotropin-releasing hormone (TRH) and pituitary adenylate cyclase-activating polypeptide (PACAP, also known as ADCYAP1). Chemogenetic stimulation of these afferent neurons in sated mice markedly activates AgRP neurons and induces intense feeding. Conversely, acute inhibition in mice with caloric-deficiency-induced hunger decreases feeding. Discovery of these afferent neurons capable of triggering hunger advances understanding of how this intense motivational state is regulated.

Electromyographic reflexes evoked in human flexor carpi radialis by tendon vibration.

PubMed

Cody, F W; Goodwin, C N; Richardson, H C

1990-10-01

The rectified, electromyographic (EMG) reflexes evoked in the voluntarily contracting flexor carpi radialis (FCR) muscle by vibration of its tendon were studied in healthy human subjects. Responses comprised a prominent, transient, short-latency (SL, 20-25 ms) increase in EMG, attributed to Ia mono- and/or oligo-synaptic action, followed by a series of less pronounced troughs and peaks of activity. Evidence of continuing Ia mono- or oligo-synaptic action was indicated by (i) the presence of small subpeaks, at vibration frequency, superimposed upon the excitatory components and (ii) the occurrence of a separate reduction in EMG, of consistent latency (ca. 30 ms), after cessation of stimulation. Progressively shortening the train of vibration from 29 cycles (at 145 Hz) to a single cycle significantly reduced net, excitatory reflex activity. Gradually increasing the level (10-50% maximum) of pre-existing voluntary contraction on top of which reflexes were elicited, by moderately prolonged (29 cycles) trains of vibration, resulted in small increases, in absolute terms, in SL peaks and in later, excitatory EMG activity. Excitatory reflexes, when normalised for pre-stimulus EMG, however, declined in an approximately hyperbolic manner with increasing background activity over this range. Thus, effective "automatic gain compensation" does not operate for vibration reflexes in FCR.

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

PubMed Central

2012-01-01

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

The effects of noise on binocular rivalry waves: a stochastic neural field model

NASA Astrophysics Data System (ADS)

Webber, Matthew A.; Bressloff, Paul C.

2013-03-01

We analyze the effects of extrinsic noise on traveling waves of visual perception in a competitive neural field model of binocular rivalry. The model consists of two one-dimensional excitatory neural fields, whose activity variables represent the responses to left-eye and right-eye stimuli, respectively. The two networks mutually inhibit each other, and slow adaptation is incorporated into the model by taking the network connections to exhibit synaptic depression. We first show how, in the absence of any noise, the system supports a propagating composite wave consisting of an invading activity front in one network co-moving with a retreating front in the other network. Using a separation of time scales and perturbation methods previously developed for stochastic reaction-diffusion equations, we then show how extrinsic noise in the activity variables leads to a diffusive-like displacement (wandering) of the composite wave from its uniformly translating position at long time scales, and fluctuations in the wave profile around its instantaneous position at short time scales. We use our analysis to calculate the first-passage-time distribution for a stochastic rivalry wave to travel a fixed distance, which we find to be given by an inverse Gaussian. Finally, we investigate the effects of noise in the depression variables, which under an adiabatic approximation lead to quenched disorder in the neural fields during propagation of a wave.

EM connectomics reveals axonal target variation in a sequence-generating network

PubMed Central

Narayanan, Rajeevan T; Svara, Fabian; Egger, Robert; Oberlaender, Marcel; Denk, Winfried; Long, Michael A

2017-01-01

The sequential activation of neurons has been observed in various areas of the brain, but in no case is the underlying network structure well understood. Here we examined the circuit anatomy of zebra finch HVC, a cortical region that generates sequences underlying the temporal progression of the song. We combined serial block-face electron microscopy with light microscopy to determine the cell types targeted by HVC(RA) neurons, which control song timing. Close to their soma, axons almost exclusively targeted inhibitory interneurons, consistent with what had been found with electrical recordings from pairs of cells. Conversely, far from the soma the targets were mostly other excitatory neurons, about half of these being other HVC(RA) cells. Both observations are consistent with the notion that the neural sequences that pace the song are generated by global synaptic chains in HVC embedded within local inhibitory networks. DOI: http://dx.doi.org/10.7554/eLife.24364.001 PMID:28346140

The neural circuit and synaptic dynamics underlying perceptual decision-making

NASA Astrophysics Data System (ADS)

Liu, Feng

2015-03-01

Decision-making with several choice options is central to cognition. To elucidate the neural mechanisms of multiple-choice motion discrimination, we built a continuous recurrent network model to represent a local circuit in the lateral intraparietal area (LIP). The network is composed of pyramidal cells and interneurons, which are directionally tuned. All neurons are reciprocally connected, and the synaptic connectivity strength is heterogeneous. Specifically, we assume two types of inhibitory connectivity to pyramidal cells: opposite-feature and similar-feature inhibition. The model accounted for both physiological and behavioral data from monkey experiments. The network is endowed with slow excitatory reverberation, which subserves the buildup and maintenance of persistent neural activity, and predominant feedback inhibition, which underlies the winner-take-all competition and attractor dynamics. The opposite-feature and opposite-feature inhibition have different effects on decision-making, and only their combination allows for a categorical choice among 12 alternatives. Together, our work highlights the importance of structured synaptic inhibition in multiple-choice decision-making processes.

The motor cortex: a network tuned to 7-14 Hz

PubMed Central

Castro-Alamancos, Manuel A.

2013-01-01

The neocortex or six layer cortex consists of at least 52 cytoarchitectonically distinct areas in humans, and similar areas can be distinguished in rodents. Each of these areas has a defining set of extrinsic connections, identifiable functional roles, a distinct laminar arrangement, etc. Thus, neocortex is extensively subdivided into areas of anatomical and functional specialization, but less is known about the specialization of cellular and network physiology across areas. The motor cortex appears to have a distinct propensity to oscillate in the 7–14 Hz frequency range. Augmenting responses, normal mu and beta oscillations, and abnormal oscillations or after discharges caused by enhancing excitation or suppressing inhibition are all expressed around this frequency range. The substrate for this activity may be an excitatory network that is unique to the motor cortex or that is more strongly suppressed in other areas, such as somatosensory cortex. Interestingly, augmenting responses are dependent on behavioral state. They are abolished during behavioral arousal. Here, I briefly review this evidence. PMID:23439785

Delayed excitatory and inhibitory feedback shape neural information transmission

NASA Astrophysics Data System (ADS)

Chacron, Maurice J.; Longtin, André; Maler, Leonard

2005-11-01

Feedback circuitry with conduction and synaptic delays is ubiquitous in the nervous system. Yet the effects of delayed feedback on sensory processing of natural signals are poorly understood. This study explores the consequences of delayed excitatory and inhibitory feedback inputs on the processing of sensory information. We show, through numerical simulations and theory, that excitatory and inhibitory feedback can alter the firing frequency response of stochastic neurons in opposite ways by creating dynamical resonances, which in turn lead to information resonances (i.e., increased information transfer for specific ranges of input frequencies). The resonances are created at the expense of decreased information transfer in other frequency ranges. Using linear response theory for stochastically firing neurons, we explain how feedback signals shape the neural transfer function for a single neuron as a function of network size. We also find that balanced excitatory and inhibitory feedback can further enhance information tuning while maintaining a constant mean firing rate. Finally, we apply this theory to in vivo experimental data from weakly electric fish in which the feedback loop can be opened. We show that it qualitatively predicts the observed effects of inhibitory feedback. Our study of feedback excitation and inhibition reveals a possible mechanism by which optimal processing may be achieved over selected frequency ranges.

Activity-dependent regulation of release probability at excitatory hippocampal synapses: a crucial role of FMRP in neurotransmission

PubMed Central

Wang, Xiao-Sheng; Peng, Chun-Zi; Cai, Wei-Jun; Xia, Jian; Jin, Daozhong; Dai, Yuqiao; Luo, Xue-Gang; Klyachko, Vitaly A.; Deng, Pan-Yue

2014-01-01

Transcriptional silencing of the Fmr1 gene encoding fragile X mental retardation protein (FMRP) causes Fragile X Syndrome (FXS), the most common form of inherited intellectual disability and the leading genetic cause of autism. FMRP has been suggested to play important roles in regulating neurotransmission and short-term synaptic plasticity at excitatory hippocampal and cortical synapses. However, the origins and the mechanisms of these FMRP actions remain incompletely understood, and the role of FMRP in regulating synaptic release probability and presynaptic function remains debated. Here we used variance-mean analysis and peak scaled nonstationary variance analysis to examine changes in both pre- and postsynaptic parameters during repetitive activity at excitatory CA3-CA1 hippocampal synapses in a mouse model of FXS. Our analyses revealed that loss of FMRP did not affect the basal release probability or basal synaptic transmission, but caused an abnormally elevated release probability specifically during repetitive activity. These abnormalities were not accompanied by changes in EPSC kinetics, quantal size or postsynaptic AMPA receptor conductance. Our results thus indicate that FMRP regulates neurotransmission at excitatory hippocampal synapses specifically during repetitive activity via modulation of release probability in a presynaptic manner. Our study suggests that FMRP function in regulating neurotransmitter release is an activity-dependent phenomenon that may contribute to the pathophysiology of FXS. PMID:24646437

Connectivity, excitability and activity patterns in neuronal networks

NASA Astrophysics Data System (ADS)

le Feber, Joost; Stoyanova, Irina I.; Chiappalone, Michela

2014-06-01

Extremely synchronized firing patterns such as those observed in brain diseases like epilepsy may result from excessive network excitability. Although network excitability is closely related to (excitatory) connectivity, a direct measure for network excitability remains unavailable. Several methods currently exist for estimating network connectivity, most of which are related to cross-correlation. An example is the conditional firing probability (CFP) analysis which calculates the pairwise probability (CFPi,j) that electrode j records an action potential at time t = τ, given that electrode i recorded a spike at t = 0. However, electrode i often records multiple spikes within the analysis interval, and CFP values are biased by the on-going dynamic state of the network. Here we show that in a linear approximation this bias may be removed by deconvoluting CFPi,j with the autocorrelation of i (i.e. CFPi,i), to obtain the single pulse response (SPRi,j)—the average response at electrode j to a single spike at electrode i. Thus, in a linear system SPRs would be independent of the dynamic network state. Nonlinear components of synaptic transmission, such as facilitation and short term depression, will however still affect SPRs. Therefore SPRs provide a clean measure of network excitability. We used carbachol and ghrelin to moderately activate cultured cortical networks to affect their dynamic state. Both neuromodulators transformed the bursting firing patterns of the isolated networks into more dispersed firing. We show that the influence of the dynamic state on SPRs is much smaller than the effect on CFPs, but not zero. The remaining difference reflects the alteration in network excitability. We conclude that SPRs are less contaminated by the dynamic network state and that mild excitation may decrease network excitability, possibly through short term synaptic depression.

Coordination of locomotor and cardiorespiratory networks of Lymnaea stagnalis by a pair of identified interneurones.

PubMed

Syed, N I; Winlow, W

1991-07-01

1. The morphology and electrophysiology of a newly identified bilateral pair of interneurones in the central nervous system of the pulmonate pond snail Lymnaea stagnalis is described. 2. These interneurones, identified as left and right pedal dorsal 11 (L/RPeD11), are electrically coupled to each other as well as to a large number of foot and body wall motoneurones, forming a fast-acting neural network which coordinates the activities of foot and body wall muscles. 3. The left and right sides of the body wall of Lymnaea are innervated by left and right cerebral A cluster neurones. Although these motoneurones have only ipsilateral projections, they are indirectly electrically coupled to their contralateral homologues via their connections with L/RPeD11. Similarly, the activities of left and right pedal G cluster neurones, which are known to be involved in locomotion, are also coordinated by L/RPeD11. 4. Selective ablation of both neurones PeD11 results in the loss of coordination between the bilateral cerebral A clusters. 5. Interneurones L/RPeD11 are multifunctional. In addition to coordinating motoneuronal activity, they make chemical excitatory connections with heart motoneurones. They also synapse upon respiratory motoneurones, hyperpolarizing those involved in pneumostome opening (expiration) and depolarizing those involved in pneumostome closure (inspiration). 6. An identified respiratory interneurone involved in pneumostome closure (visceral dorsal 4) inhibits L/RPeD11 together with all their electrically coupled follower cells. 7. Both L/RPeD11 have strong excitatory effects on another pair of electrically coupled neurones, visceral dorsal 1 and right parietal dorsal 2, which have previously been shown to be sensitive to changes in the partial pressure of environmental oxygen (PO2). 8. Although L/RPeD11 participate in whole-body withdrawal responses, electrical stimulation applied directly to these neurones was not sufficient to induce this behaviour.

Understanding the Implications of Neural Population Activity on Behavior

NASA Astrophysics Data System (ADS)

Briguglio, John

Learning how neural activity in the brain leads to the behavior we exhibit is one of the fundamental questions in Neuroscience. In this dissertation, several lines of work are presented to that use principles of neural coding to understand behavior. In one line of work, we formulate the efficient coding hypothesis in a non-traditional manner in order to test human perceptual sensitivity to complex visual textures. We find a striking agreement between how variable a particular texture signal is and how sensitive humans are to its presence. This reveals that the efficient coding hypothesis is still a guiding principle for neural organization beyond the sensory periphery, and that the nature of cortical constraints differs from the peripheral counterpart. In another line of work, we relate frequency discrimination acuity to neural responses from auditory cortex in mice. It has been previously observed that optogenetic manipulation of auditory cortex, in addition to changing neural responses, evokes changes in behavioral frequency discrimination. We are able to account for changes in frequency discrimination acuity on an individual basis by examining the Fisher information from the neural population with and without optogenetic manipulation. In the third line of work, we address the question of what a neural population should encode given that its inputs are responses from another group of neurons. Drawing inspiration from techniques in machine learning, we train Deep Belief Networks on fake retinal data and show the emergence of Garbor-like filters, reminiscent of responses in primary visual cortex. In the last line of work, we model the state of a cortical excitatory-inhibitory network during complex adaptive stimuli. Using a rate model with Wilson-Cowan dynamics, we demonstrate that simple non-linearities in the signal transferred from inhibitory to excitatory neurons can account for real neural recordings taken from auditory cortex. This work establishes and tests a variety of hypotheses that will be useful in helping to understand the relationship between neural activity and behavior as recorded neural populations continue to grow.

From Synaptic Transmission to Cognition: An Intermediary Role for Dendritic Spines

ERIC Educational Resources Information Center

Gonzalez-Burgos, Ignacio

2012-01-01

Dendritic spines are cytoplasmic protrusions that develop directly or indirectly from the filopodia of neurons. Dendritic spines mediate excitatory neurotransmission and they can isolate the electrical activity generated by synaptic impulses, enabling them to translate excitatory afferent information via several types of plastic changes, including…

The excitatory/inhibitory input to orexin/hypocretin neuron soma undergoes day/night reorganization.

PubMed

Laperchia, Claudia; Imperatore, Roberta; Azeez, Idris A; Del Gallo, Federico; Bertini, Giuseppe; Grassi-Zucconi, Gigliola; Cristino, Luigia; Bentivoglio, Marina

2017-11-01

Orexin (OX)/hypocretin-containing neurons are main regulators of wakefulness stability, arousal, and energy homeostasis. Their activity varies in relation to the animal's behavioral state. We here tested whether such variation is subserved by synaptic plasticity phenomena in basal conditions. Mice were sacrificed during day or night, at times when sleep or wake, respectively, predominates, as assessed by electroencephalography in matched mice. Triple immunofluorescence was used to visualize OX-A perikarya and varicosities containing the vesicular glutamate transporter (VGluT)2 or the vesicular GABA transporter (VGAT) combined with synaptophysin (Syn) as a presynaptic marker. Appositions on OX-A + somata were quantitatively analyzed in pairs of sections in epifluorescence and confocal microscopy. The combined total number of glutamatergic (Syn + /VGluT2 + ) and GABAergic (Syn + /VGAT + ) varicosities apposed to OX-A somata was similar during day and night. However, glutamatergic varicosities were significantly more numerous at night, whereas GABAergic varicosities prevailed in the day. Triple immunofluorescence in confocal microscopy was employed to visualize synapse scaffold proteins as postsynaptic markers and confirmed the nighttime prevalence of VGluT2 + together with postsynaptic density protein 95 + excitatory contacts, and daytime prevalence of VGAT + together with gephyrin + inhibitory contacts, while also showing that they formed synapses on OX-A + cell bodies. The findings reveal a daily reorganization of axosomatic synapses in orexinergic neurons, with a switch from a prevalence of excitatory innervation at a time corresponding to wakefulness to a prevalence of inhibitory innervations in the antiphase, at a time corresponding to sleep. This reorganization could represent a key mechanism of plasticity of the orexinergic network in basal conditions.

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.

A Theory of How Columns in the Neocortex Enable Learning the Structure of the World

PubMed Central

Hawkins, Jeff; Ahmad, Subutai; Cui, Yuwei

2017-01-01

Neocortical regions are organized into columns and layers. Connections between layers run mostly perpendicular to the surface suggesting a columnar functional organization. Some layers have long-range excitatory lateral connections suggesting interactions between columns. Similar patterns of connectivity exist in all regions but their exact role remain a mystery. In this paper, we propose a network model composed of columns and layers that performs robust object learning and recognition. Each column integrates its changing input over time to learn complete predictive models of observed objects. Excitatory lateral connections across columns allow the network to more rapidly infer objects based on the partial knowledge of adjacent columns. Because columns integrate input over time and space, the network learns models of complex objects that extend well beyond the receptive field of individual cells. Our network model introduces a new feature to cortical columns. We propose that a representation of location relative to the object being sensed is calculated within the sub-granular layers of each column. The location signal is provided as an input to the network, where it is combined with sensory data. Our model contains two layers and one or more columns. Simulations show that using Hebbian-like learning rules small single-column networks can learn to recognize hundreds of objects, with each object containing tens of features. Multi-column networks recognize objects with significantly fewer movements of the sensory receptors. Given the ubiquity of columnar and laminar connectivity patterns throughout the neocortex, we propose that columns and regions have more powerful recognition and modeling capabilities than previously assumed. PMID:29118696

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

Serotonergic Modulation Differentially Targets Distinct Network Elements within the Antennal Lobe of Drosophila melanogaster

PubMed Central

Sizemore, Tyler R.; Dacks, Andrew M.

2016-01-01

Neuromodulation confers flexibility to anatomically-restricted neural networks so that animals are able to properly respond to complex internal and external demands. However, determining the mechanisms underlying neuromodulation is challenging without knowledge of the functional class and spatial organization of neurons that express individual neuromodulatory receptors. Here, we describe the number and functional identities of neurons in the antennal lobe of Drosophila melanogaster that express each of the receptors for one such neuromodulator, serotonin (5-HT). Although 5-HT enhances odor-evoked responses of antennal lobe projection neurons (PNs) and local interneurons (LNs), the receptor basis for this enhancement is unknown. We used endogenous reporters of transcription and translation for each of the five 5-HT receptors (5-HTRs) to identify neurons, based on cell class and transmitter content, that express each receptor. We find that specific receptor types are expressed by distinct combinations of functional neuronal classes. For instance, the excitatory PNs express the excitatory 5-HTRs, while distinct classes of LNs each express different 5-HTRs. This study therefore provides a detailed atlas of 5-HT receptor expression within a well-characterized neural network, and enables future dissection of the role of serotonergic modulation of olfactory processing. PMID:27845422

Our Selections and Decisions: Inherent Features of the Nervous System?

NASA Astrophysics Data System (ADS)

Rösler, Frank

The chapter summarizes findings on the neuronal bases of decisionmaking. Taking the phenomenon of selection it will be explained that systems built only from excitatory and inhibitory neuron (populations) have the emergent property of selecting between different alternatives. These considerations suggest that there exists a hierarchical architecture with central selection switches. However, in such a system, functions of selection and decision-making are not localized, but rather emerge from an interaction of several participating networks. These are, on the one hand, networks that process specific input and output representations and, on the other hand, networks that regulate the relative activation/inhibition of the specific input and output networks. These ideas are supported by recent empirical evidence. Moreover, other studies show that rather complex psychological variables, like subjective probability estimates, expected gains and losses, prediction errors, etc., do have biological correlates, i.e., they can be localized in time and space as activation states of neural networks and single cells. These findings suggest that selections and decisions are consequences of an architecture which, seen from a biological perspective, is fully deterministic. However, a transposition of such nomothetic functional principles into the idiographic domain, i.e., using them as elements for comprehensive 'mechanistic' explanations of individual decisions, seems not to be possible because of principle limitations. Therefore, individual decisions will remain predictable by means of probabilistic models alone.

Exact distinction of excitatory and inhibitory neurons in neural networks: a study with GFP-GAD67 neurons optically and electrophysiologically recognized on multielectrode arrays

PubMed Central

Becchetti, Andrea; Gullo, Francesca; Bruno, Giuseppe; Dossi, Elena; Lecchi, Marzia; Wanke, Enzo

2012-01-01

Distinguishing excitatory from inhibitory neurons with multielectrode array (MEA) recordings is a serious experimental challenge. The current methods, developed in vitro, mostly rely on spike waveform analysis. These however often display poor resolution and may produce errors caused by the variability of spike amplitudes and neuron shapes. Recent recordings in human brain suggest that the spike waveform features correlate with time-domain statistics such as spiking rate, autocorrelation, and coefficient of variation. However, no precise criteria are available to exactly assign identified units to specific neuronal types, either in vivo or in vitro. To solve this problem, we combined MEA recording with fluorescence imaging of neocortical cultures from mice expressing green fluorescent protein (GFP) in GABAergic cells. In this way, we could sort out “authentic excitatory neurons” (AENs) and “authentic inhibitory neurons” (AINs). We thus characterized 1275 units (from 405 electrodes, n = 10 experiments), based on autocorrelation, burst length, spike number (SN), spiking rate, squared coefficient of variation, and Fano factor (FF) (the ratio between spike-count variance and mean). These metrics differed by about one order of magnitude between AINs and AENs. In particular, the FF turned out to provide a firing code which exactly (no overlap) recognizes excitatory and inhibitory units. The difference in FF between all of the identified AEN and AIN groups was highly significant (p < 10−8, ANOVA post-hoc Tukey test). Our results indicate a statistical metric-based approach to distinguish excitatory from inhibitory neurons independently from the spike width. PMID:22973197

From homeostasis to behavior: Balanced activity in an exploration of embodied dynamic environmental-neural interaction.

PubMed

Hellyer, Peter John; Clopath, Claudia; Kehagia, Angie A; Turkheimer, Federico E; Leech, Robert

2017-08-01

In recent years, there have been many computational simulations of spontaneous neural dynamics. Here, we describe a simple model of spontaneous neural dynamics that controls an agent moving in a simple virtual environment. These dynamics generate interesting brain-environment feedback interactions that rapidly destabilize neural and behavioral dynamics demonstrating the need for homeostatic mechanisms. We investigate roles for homeostatic plasticity both locally (local inhibition adjusting to balance excitatory input) as well as more globally (regional "task negative" activity that compensates for "task positive", sensory input in another region) balancing neural activity and leading to more stable behavior (trajectories through the environment). Our results suggest complementary functional roles for both local and macroscale mechanisms in maintaining neural and behavioral dynamics and a novel functional role for macroscopic "task-negative" patterns of activity (e.g., the default mode network).

Contralesional homotopic activity negatively influences functional recovery after stroke (Conference Presentation)

NASA Astrophysics Data System (ADS)

Bauer, Adam Q.; Kraft, Andrew; Baxter, Grant A.; Bruchas, Michael R.; Lee, Jin-Moo; Culver, Joseph P.

2017-02-01

Recent fcMRI studies examining spontaneous brain activity after stoke have revealed disrupted global patterns of functional connectivity (FC). Interestingly, acute interhemispheric homotopic FC has been shown to be predictive of recovery potential. While substantial indirect evidence also suggests that homotopic brain activity may directly impact recovery, results in humans are extremely varied. A better understanding of how activity within networks functionally-connected to lesioned tissue influences brain plasticity might improve therapeutic strategies. We combine cell-type specific optogenetic targeting with optical intrinsic signal (OIS) imaging to assess the effects of homotopic contralesional activity (specifically in excitatory CamKIIa pyramidal neurons) on FC, cortical remapping, and behavior after stroke. Thirty-one mice were housed in enriched cages for the experiment. OIS imaging was performed before, 1, and 4 weeks after photothrombosis of left forepaw somatosensory cortex (S1fp). On day 1 after stroke, 17 mice were subjected to chronic, intermittent optical stimulation of right S1fp for 10 min, 5 days/week for 4 weeks. New cortical representations of left S1fp appeared in non-stimulated mice at week 1, but not in stimulated mice (p=0.005). Evoked responses were comparable in both groups at week 4 (p=0.57). Homotopic FC between left and right S1fp regions was equally reduced in both groups (p=0.012) at week 1. However, in non-stimulated mice, behavioral performance and FC between right S1fp and left perilesional S1 cortex was significantly higher by 4 weeks compared to stimulated mice (p=0.009). Our results suggest that increased homotopic, contralesional activity in excitatory neurons negatively influences spontaneous recovery following ischemic stroke.

Olfactory bulb short axon cell release of GABA and dopamine produces a temporally biphasic inhibition-excitation response in external tufted cells.

PubMed

Liu, Shaolin; Plachez, Celine; Shao, Zuoyi; Puche, Adam; Shipley, Michael T

2013-02-13

Evidence for coexpression of two or more classic neurotransmitters in neurons has increased, but less is known about cotransmission. Ventral tegmental area (VTA) neurons corelease dopamine (DA), the excitatory transmitter glutamate, and the inhibitory transmitter GABA onto target cells in the striatum. Olfactory bulb (OB) short axon cells (SACs) form interglomerular connections and coexpress markers for DA and GABA. Using an optogenetic approach, we provide evidence that mouse OB SACs release both GABA and DA onto external tufted cells (ETCs) in other glomeruli. Optical activation of channelrhodopsin specifically expressed in DAergic SACs produced a GABA(A) receptor-mediated monosynaptic inhibitory response, followed by DA-D(1)-like receptor-mediated excitatory response in ETCs. The GABA(A) receptor-mediated hyperpolarization activates I(h) current in ETCs; synaptically released DA increases I(h), which enhances postinhibitory rebound spiking. Thus, the opposing actions of synaptically released GABA and DA are functionally integrated by I(h) to generate an inhibition-to-excitation "switch" in ETCs. Consistent with the established role of I(h) in ETC burst firing, we show that endogenous DA release increases ETC spontaneous bursting frequency. ETCs transmit sensory signals to mitral/tufted output neurons and drive intraglomerular inhibition to shape glomerulus output to downstream olfactory networks. GABA and DA cotransmission from SACs to ETCs may play a key role in regulating output coding across the glomerular array.

Mapping Horizontal Spread of Activity in Monkey Motor Cortex Using Single Pulse Microstimulation

PubMed Central

Riehle, Alexa; Brochier, Thomas G.

2016-01-01

Anatomical studies have demonstrated that distant cortical points are interconnected through long range axon collaterals of pyramidal cells. However, the functional properties of these intrinsic synaptic connections, especially their relationship with the cortical representations of body movements, have not been systematically investigated. To address this issue, we used multielectrode arrays chronically implanted in the motor cortex of two rhesus monkeys to analyze the effects of single-pulse intracortical microstimulation (sICMS) applied at one electrode on the neuronal activities recorded at all other electrodes. The temporal and spatial distribution of the evoked responses of single and multiunit activities was quantified to determine the properties of horizontal propagation. The typical responses were characterized by a brief excitatory peak followed by inhibition of longer duration. Significant excitatory responses to sICMS could be evoked up to 4 mm away from the stimulation site, but the strength of the response decreased exponentially and its latency increased linearly with the distance. We then quantified the direction and strength of the propagation in relation to the somatotopic organization of the motor cortex. We observed that following sICMS the propagation of neural activity is mainly directed rostro-caudally near the central sulcus but follows medio-lateral direction at the most anterior electrodes. The fact that these interactions are not entirely symmetrical may characterize a critical functional property of the motor cortex for the control of upper limb movements. Overall, these results support the assumption that the motor cortex is not functionally homogeneous but forms a complex network of interacting subregions. PMID:28018182

Development of spiral wave in a regular network of excitatory neurons due to stochastic poisoning of ion channels

NASA Astrophysics Data System (ADS)

Wu, Xinyi; Ma, Jun; Li, Fan; Jia, Ya

2013-12-01

Some experimental evidences show that spiral wave could be observed in the cortex of brain, and the propagation of this spiral wave plays an important role in signal communication as a pacemaker. The profile of spiral wave generated in a numerical way is often perfect while the observed profile in experiments is not perfect and smooth. In this paper, formation and development of spiral wave in a regular network of Morris-Lecar neurons, which neurons are placed on nodes uniformly in a two-dimensional array and each node is coupled with nearest-neighbor type, are investigated by considering the effect of stochastic ion channels poisoning and channel noise. The formation and selection of spiral wave could be detected as follows. (1) External forcing currents with diversity are imposed on neurons in the network of excitatory neurons with nearest-neighbor connection, a target-like wave emerges and its potential mechanism is discussed; (2) artificial defects and local poisoned area are selected in the network to induce new wave to interact with the target wave; (3) spiral wave can be induced to occupy the network when the target wave is blocked by the artificial defects or poisoned area with regular border lines; (4) the stochastic poisoning effect is introduced by randomly modifying the border lines (areas) of specific regions in the network. It is found that spiral wave can be also developed to occupy the network under appropriate poisoning ratio. The process of growth for the poisoned area of ion channels poisoning is measured, the effect of channels noise is also investigated. It is confirmed that perfect spiral wave emerges in the network under gradient poisoning even if the channel noise is considered.

Controlling Synfire Chain by Inhibitory Synaptic Input

NASA Astrophysics Data System (ADS)

Shinozaki, Takashi; Câteau, Hideyuki; Urakubo, Hidetoshi; Okada, Masato

2007-04-01

The propagation of highly synchronous firings across neuronal networks, called the synfire chain, has been actively studied both theoretically and experimentally. The temporal accuracy and remarkable stability of the propagation have been repeatedly examined in previous studies. However, for such a mode of signal transduction to play a major role in processing information in the brain, the propagation should also be controlled dynamically and flexibly. Here, we show that inhibitory but not excitatory input can bidirectionally modulate the propagation, i.e., enhance or suppress the synchronous firings depending on the timing of the input. Our simulations based on the Hodgkin-Huxley neuron model demonstrate this bidirectional modulation and suggest that it should be achieved with any biologically inspired modeling. Our finding may help describe a concrete scenario of how multiple synfire chains lying in a neuronal network are appropriately controlled to perform significant information processing.

Fast voltage-sensitive dye imaging of excitatory and inhibitory synaptic transmission in the rat granular retrosplenial cortex.

PubMed

Nixima, Ken'ichi; Okanoya, Kazuo; Ichinohe, Noritaka; Kurotani, Tohru

2017-09-01

Rodent granular retrosplenial cortex (GRS) has dense connections between the anterior thalamic nuclei (ATN) and hippocampal formation. GRS superficial pyramidal neurons exhibit distinctive late spiking (LS) firing property and form patchy clusters with prominent apical dendritic bundles. The aim of this study was to investigate spatiotemporal dynamics of signal transduction in the GRS induced by ATN afferent stimulation by using fast voltage-sensitive dye imaging in rat brain slices. In coronal slices, layer 1a stimulation, which presumably activated thalamic fibers, evoked propagation of excitatory synaptic signals from layers 2-4 to layers 5-6 in a direction perpendicular to the layer axis, followed by transverse signal propagation within each layer. In the presence of ionotropic glutamate receptor antagonists, inhibitory responses were observed in superficial layers, induced by direct activation of inhibitory interneurons in layer 1. In horizontal slices, excitatory signals in deep layers propagated transversely mainly from posterior to anterior via superficial layers. Cortical inhibitory responses upon layer 1a stimulation in horizontal slices were weaker than those in the coronal slices. Observed differences between coronal and horizontal planes suggest anisotropy of the intracortical circuitry. In conclusion, ATN inputs are processed differently in coronal and horizontal planes of the GRS and then conveyed to other cortical areas. In both planes, GRS superficial layers play an important role in signal propagation, which suggests that superficial neuronal cascade is crucial in the integration of multiple information sources. NEW & NOTEWORTHY Superficial neurons in the rat granular retrosplenial cortex (GRS) show distinctive late-spiking (LS) firing property. However, little is known about spatiotemporal dynamics of signal transduction in the GRS. We demonstrated LS neuron network relaying thalamic inputs to deep layers and anisotropic distribution of inhibition between coronal and horizontal planes. Since deep layers of the GRS receive inputs from the subiculum, GRS circuits may work as an integrator of multiple sources such as sensory and memory information. Copyright © 2017 the American Physiological Society.

Bidirectional global spontaneous network activity precedes the canonical unidirectional circuit organization in the developing hippocampus.

PubMed

Shi, Yulin; Ikrar, Taruna; Olivas, Nicholas D; Xu, Xiangmin

2014-06-15

Spontaneous network activity is believed to sculpt developing neural circuits. Spontaneous giant depolarizing potentials (GDPs) were first identified with single-cell recordings from rat CA3 pyramidal neurons, but here we identify and characterize a large-scale spontaneous network activity we term global network activation (GNA) in the developing mouse hippocampal slices, which is measured macroscopically by fast voltage-sensitive dye imaging. The initiation and propagation of GNA in the mouse is largely GABA-independent and dominated by glutamatergic transmission via AMPA receptors. Despite the fact that signal propagation in the adult hippocampus is strongly unidirectional through the canonical trisynaptic circuit (dentate gyrus [DG] to CA3 to CA1), spontaneous GNA in the developing hippocampus originates in distal CA3 and propagates both forward to CA1 and backward to DG. Photostimulation-evoked GNA also shows prominent backward propagation in the developing hippocampus from CA3 to DG. Mouse GNA is strongly correlated to electrophysiological recordings of highly localized single-cell and local field potential events. Photostimulation mapping of neural circuitry demonstrates that the enhancement of local circuit connections to excitatory pyramidal neurons occurs over the same time course as GNA and reveals the underlying pathways accounting for GNA backward propagation from CA3 to DG. The disappearance of GNA coincides with a transition to the adult-like unidirectional circuit organization at about 2 weeks of age. Taken together, our findings strongly suggest a critical link between GNA activity and maturation of functional circuit connections in the developing hippocampus. Copyright © 2013 Wiley Periodicals, Inc.

Activity propagation in an avian basal ganglia-thalamo-cortical circuit essential for vocal learning

PubMed Central

Kojima, Satoshi; Doupe, Allison J.

2009-01-01

In mammalian basal ganglia-thalamo-cortical circuits, GABAergic pallidal neurons are thought to ‘gate’ or modulate excitation in thalamus with their strong inhibitory inputs, and thus signal to cortex by pausing and permitting thalamic neurons to fire in response to excitatory drive. In contrast, in a homologous circuit specialized for vocal learning in songbirds, evidence suggests that pallidal neurons signal by eliciting postinhibitory rebound spikes in thalamus, which could occur even without any excitatory drive to thalamic neurons. To test whether songbird pallidal neurons can also communicate with thalamus by gating excitatory drive, as well as by postinhibitory rebound, we examined the activity of thalamic relay neurons in response to acute inactivation of the basal ganglia structure Area X; Area X contains the pallidal neurons that project to thalamus. Although inactivation of Area X should eliminate rebound-mediated spiking in thalamus, this manipulation tonically increases the firing rate of thalamic relay neurons, providing evidence that songbird pallidal neurons can gate tonic thalamic excitatory drive. We also found that the increased thalamic activity was fed forward to its target in the avian equivalent of cortex, which includes neurons that project to the vocal premotor area. These data raise the possibility that basal ganglia circuits can signal to cortex through thalamus both by generating postinhibitory rebound and by gating excitatory drive, and may switch between these modes depending on the statistics of pallidal firing. Moreover, these findings provide insight into the strikingly different disruptive effects of basal ganglia and ‘cortical’ lesions on songbird vocal learning. PMID:19369547

Common mechanisms of excitatory and inhibitory imbalance in schizophrenia and autism spectrum disorders.

PubMed

Gao, R; Penzes, P

2015-01-01

Autism Spectrum Disorders (ASD) and Schizophrenia (SCZ) are cognitive disorders with complex genetic architectures but overlapping behavioral phenotypes, which suggests common pathway perturbations. Multiple lines of evidence implicate imbalances in excitatory and inhibitory activity (E/I imbalance) as a shared pathophysiological mechanism. Thus, understanding the molecular underpinnings of E/I imbalance may provide essential insight into the etiology of these disorders and may uncover novel targets for future drug discovery. Here, we review key genetic, physiological, neuropathological, functional, and pathway studies that suggest alterations to excitatory/inhibitory circuits are keys to ASD and SCZ pathogenesis.

A Markovian event-based framework for stochastic spiking neural networks.

PubMed

Touboul, Jonathan D; Faugeras, Olivier D

2011-11-01

In spiking neural networks, the information is conveyed by the spike times, that depend on the intrinsic dynamics of each neuron, the input they receive and on the connections between neurons. In this article we study the Markovian nature of the sequence of spike times in stochastic neural networks, and in particular the ability to deduce from a spike train the next spike time, and therefore produce a description of the network activity only based on the spike times regardless of the membrane potential process. To study this question in a rigorous manner, we introduce and study an event-based description of networks of noisy integrate-and-fire neurons, i.e. that is based on the computation of the spike times. We show that the firing times of the neurons in the networks constitute a Markov chain, whose transition probability is related to the probability distribution of the interspike interval of the neurons in the network. In the cases where the Markovian model can be developed, the transition probability is explicitly derived in such classical cases of neural networks as the linear integrate-and-fire neuron models with excitatory and inhibitory interactions, for different types of synapses, possibly featuring noisy synaptic integration, transmission delays and absolute and relative refractory period. This covers most of the cases that have been investigated in the event-based description of spiking deterministic neural networks.

FPGA implementation of a biological neural network based on the Hodgkin-Huxley neuron model.

PubMed

Yaghini Bonabi, Safa; Asgharian, Hassan; Safari, Saeed; Nili Ahmadabadi, Majid

2014-01-01

A set of techniques for efficient implementation of Hodgkin-Huxley-based (H-H) model of a neural network on FPGA (Field Programmable Gate Array) is presented. The central implementation challenge is H-H model complexity that puts limits on the network size and on the execution speed. However, basics of the original model cannot be compromised when effect of synaptic specifications on the network behavior is the subject of study. To solve the problem, we used computational techniques such as CORDIC (Coordinate Rotation Digital Computer) algorithm and step-by-step integration in the implementation of arithmetic circuits. In addition, we employed different techniques such as sharing resources to preserve the details of model as well as increasing the network size in addition to keeping the network execution speed close to real time while having high precision. Implementation of a two mini-columns network with 120/30 excitatory/inhibitory neurons is provided to investigate the characteristic of our method in practice. The implementation techniques provide an opportunity to construct large FPGA-based network models to investigate the effect of different neurophysiological mechanisms, like voltage-gated channels and synaptic activities, on the behavior of a neural network in an appropriate execution time. Additional to inherent properties of FPGA, like parallelism and re-configurability, our approach makes the FPGA-based system a proper candidate for study on neural control of cognitive robots and systems as well.

Specific excitatory connectivity for feature integration in mouse primary visual cortex

PubMed Central

Molina-Luna, Patricia; Roth, Morgane M.

2017-01-01

Local excitatory connections in mouse primary visual cortex (V1) are stronger and more prevalent between neurons that share similar functional response features. However, the details of how functional rules for local connectivity shape neuronal responses in V1 remain unknown. We hypothesised that complex responses to visual stimuli may arise as a consequence of rules for selective excitatory connectivity within the local network in the superficial layers of mouse V1. In mouse V1 many neurons respond to overlapping grating stimuli (plaid stimuli) with highly selective and facilitatory responses, which are not simply predicted by responses to single gratings presented alone. This complexity is surprising, since excitatory neurons in V1 are considered to be mainly tuned to single preferred orientations. Here we examined the consequences for visual processing of two alternative connectivity schemes: in the first case, local connections are aligned with visual properties inherited from feedforward input (a ‘like-to-like’ scheme specifically connecting neurons that share similar preferred orientations); in the second case, local connections group neurons into excitatory subnetworks that combine and amplify multiple feedforward visual properties (a ‘feature binding’ scheme). By comparing predictions from large scale computational models with in vivo recordings of visual representations in mouse V1, we found that responses to plaid stimuli were best explained by assuming feature binding connectivity. Unlike under the like-to-like scheme, selective amplification within feature-binding excitatory subnetworks replicated experimentally observed facilitatory responses to plaid stimuli; explained selective plaid responses not predicted by grating selectivity; and was consistent with broad anatomical selectivity observed in mouse V1. Our results show that visual feature binding can occur through local recurrent mechanisms without requiring feedforward convergence, and that such a mechanism is consistent with visual responses and cortical anatomy in mouse V1. PMID:29240769

Synaptic reorganization of inhibitory hilar interneuron circuitry after traumatic brain injury in mice

PubMed Central

Hunt, Robert F.; Scheff, Stephen W.; Smith, Bret N.

2011-01-01

Functional plasticity of synaptic networks in the dentate gyrus has been implicated in the development of posttraumatic epilepsy and in cognitive dysfunction after traumatic brain injury, but little is known about potentially pathogenic changes in inhibitory circuits. We examined synaptic inhibition of dentate granule cells and excitability of surviving GABAergic hilar interneurons 8–13 weeks after cortical contusion brain injury in transgenic mice that express enhanced green fluorescent protein in a subpopulation of inhibitory neurons. Whole-cell voltage-clamp recordings in granule cells revealed a reduction in spontaneous and miniature IPSC frequency after head injury; no concurrent change in paired-pulse ratio was found in granule cells after paired electrical stimulation of the hilus. Despite reduced inhibitory input to granule cells, action potential and EPSC frequencies were increased in hilar GABA neurons from slices ipsilateral to the injury, versus those from control or contralateral slices. Further, increased excitatory synaptic activity was detected in hilar GABA neurons ipsilateral to the injury after glutamate photostimulation of either the granule cell or CA3 pyramidal cell layers. Together, these findings suggest that excitatory drive to surviving hilar GABA neurons is enhanced by convergent input from both pyramidal and granule cells, but synaptic inhibition of granule cells is not fully restored after injury. This rewiring of circuitry regulating hilar inhibitory neurons may reflect an important compensatory mechanism, but it may also contribute to network destabilization by increasing the relative impact of surviving individual interneurons in controlling granule cell excitability in the posttraumatic dentate gyrus. PMID:21543618

Cracking Down on Inhibition: Selective Removal of GABAergic Interneurons from Hippocampal Networks

PubMed Central

Antonucci, Flavia; Alpár, Alán; Kacza, Johannes; Caleo, Matteo; Verderio, Claudia; Giani, Alice; Martens, Henrik; Chaudhry, Farrukh A.; Allegra, Manuela; Grosche, Jens; Michalski, Dominik; Erck, Christian; Hoffmann, Anke; Härtig, Wolfgang

2012-01-01

Inhibitory (GABAergic) interneurons entrain assemblies of excitatory principal neurons to orchestrate information processing in the hippocampus. Disrupting the dynamic recruitment as well as the temporally precise activity of interneurons in hippocampal circuitries can manifest in epileptiform seizures, and impact specific behavioral traits. Despite the importance of GABAergic interneurons during information encoding in the brain, experimental tools to selectively manipulate GABAergic neurotransmission are limited. Here, we report the selective elimination of GABAergic interneurons by a ribosome inactivation approach through delivery of saporin-conjugated anti-vesicular GABA transporter antibodies (SAVAs) in vitro as well as in the mouse and rat hippocampus in vivo. We demonstrate the selective loss of GABAergic—but not glutamatergic—synapses, reduced GABA release, and a shift in excitation/inhibition balance in mixed cultures of hippocampal neurons exposed to SAVAs. We also show the focal and indiscriminate loss of calbindin+, calretinin+, parvalbumin/system A transporter 1+, somatostatin+, vesicular glutamate transporter 3 (VGLUT3)/cholecystokinin/CB1 cannabinoid receptor+ and neuropeptide Y+ local-circuit interneurons upon SAVA microlesions to the CA1 subfield of the rodent hippocampus, with interneuron debris phagocytosed by infiltrating microglia. SAVA microlesions did not affect VGLUT1+ excitatory afferents. Yet SAVA-induced rearrangement of the hippocampal circuitry triggered network hyperexcitability associated with the progressive loss of CA1 pyramidal cells and the dispersion of dentate granule cells. Overall, our data identify SAVAs as an effective tool to eliminate GABAergic neurons from neuronal circuits underpinning high-order behaviors and cognition, and whose manipulation can recapitulate pathogenic cascades of epilepsy and other neuropsychiatric illnesses. PMID:22323713

Sensory-driven and spontaneous gamma oscillations engage distinct cortical circuitry

PubMed Central

2015-01-01

Gamma oscillations are a robust component of sensory responses but are also part of the background spontaneous activity of the brain. To determine whether the properties of gamma oscillations in cortex are specific to their mechanism of generation, we compared in mouse visual cortex in vivo the laminar geometry and single-neuron rhythmicity of oscillations produced during sensory representation with those occurring spontaneously in the absence of stimulation. In mouse visual cortex under anesthesia (isoflurane and xylazine), visual stimulation triggered oscillations mainly between 20 and 50 Hz, which, because of their similar functional significance to gamma oscillations in higher mammals, we define here as gamma range. Sensory representation in visual cortex specifically increased gamma oscillation amplitude in the supragranular (L2/3) and granular (L4) layers and strongly entrained putative excitatory and inhibitory neurons in infragranular layers, while spontaneous gamma oscillations were distributed evenly through the cortical depth and primarily entrained putative inhibitory neurons in the infragranular (L5/6) cortical layers. The difference in laminar distribution of gamma oscillations during the two different conditions may result from differences in the source of excitatory input to the cortex. In addition, modulation of superficial gamma oscillation amplitude did not result in a corresponding change in deep-layer oscillations, suggesting that superficial and deep layers of cortex may utilize independent but related networks for gamma generation. These results demonstrate that stimulus-driven gamma oscillations engage cortical circuitry in a manner distinct from spontaneous oscillations and suggest multiple networks for the generation of gamma oscillations in cortex. PMID:26719085

Reducing Neuronal Networks to Discrete Dynamics

PubMed Central

Terman, David; Ahn, Sungwoo; Wang, Xueying; Just, Winfried

2008-01-01

We consider a general class of purely inhibitory and excitatory-inhibitory neuronal networks, with a general class of network architectures, and characterize the complex firing patterns that emerge. Our strategy for studying these networks is to first reduce them to a discrete model. In the discrete model, each neuron is represented as a finite number of states and there are rules for how a neuron transitions from one state to another. In this paper, we rigorously demonstrate that the continuous neuronal model can be reduced to the discrete model if the intrinsic and synaptic properties of the cells are chosen appropriately. In a companion paper [1], we analyze the discrete model. PMID:18443649

Impaired neurogenesis of the dentate gyrus is associated with pattern separation deficits: A computational study.

PubMed

Faghihi, Faramarz; Moustafa, Ahmed A

2016-09-01

The separation of input patterns received from the entorhinal cortex (EC) by the dentate gyrus (DG) is a well-known critical step of information processing in the hippocampus. Although the role of interneurons in separation pattern efficiency of the DG has been theoretically known, the balance of neurogenesis of excitatory neurons and interneurons as well as its potential role in information processing in the DG is not fully understood. In this work, we study separation efficiency of the DG for different rates of neurogenesis of interneurons and excitatory neurons using a novel computational model in which we assume an increase in the synaptic efficacy between excitatory neurons and interneurons and then its decay over time. Information processing in the EC and DG was simulated as information flow in a two layer feed-forward neural network. The neurogenesis rate was modeled as the percentage of new born neurons added to the neuronal population in each time bin. The results show an important role of an optimal neurogenesis rate of interneurons and excitatory neurons in the DG in efficient separation of inputs from the EC in pattern separation tasks. The model predicts that any deviation of the optimal values of neurogenesis rates leads to different decreased levels of the separation deficits of the DG which influences its function to encode memory.

Mechanisms of Left-Right Coordination in Mammalian Locomotor Pattern Generation Circuits: A Mathematical Modeling View

PubMed Central

Talpalar, Adolfo E.; Rybak, Ilya A.

2015-01-01

The locomotor gait in limbed animals is defined by the left-right leg coordination and locomotor speed. Coordination between left and right neural activities in the spinal cord controlling left and right legs is provided by commissural interneurons (CINs). Several CIN types have been genetically identified, including the excitatory V3 and excitatory and inhibitory V0 types. Recent studies demonstrated that genetic elimination of all V0 CINs caused switching from a normal left-right alternating activity to a left-right synchronized “hopping” pattern. Furthermore, ablation of only the inhibitory V0 CINs (V0D subtype) resulted in a lack of left-right alternation at low locomotor frequencies and retaining this alternation at high frequencies, whereas selective ablation of the excitatory V0 neurons (V0V subtype) maintained the left–right alternation at low frequencies and switched to a hopping pattern at high frequencies. To analyze these findings, we developed a simplified mathematical model of neural circuits consisting of four pacemaker neurons representing left and right, flexor and extensor rhythm-generating centers interacting via commissural pathways representing V3, V0D, and V0V CINs. The locomotor frequency was controlled by a parameter defining the excitation of neurons and commissural pathways mimicking the effects of N-methyl-D-aspartate on locomotor frequency in isolated rodent spinal cord preparations. The model demonstrated a typical left-right alternating pattern under control conditions, switching to a hopping activity at any frequency after removing both V0 connections, a synchronized pattern at low frequencies with alternation at high frequencies after removing only V0D connections, and an alternating pattern at low frequencies with hopping at high frequencies after removing only V0V connections. We used bifurcation theory and fast-slow decomposition methods to analyze network behavior in the above regimes and transitions between them. The model reproduced, and suggested explanation for, a series of experimental phenomena and generated predictions available for experimental testing. PMID:25970489

Self-Consistent Scheme for Spike-Train Power Spectra in Heterogeneous Sparse Networks.

PubMed

Pena, Rodrigo F O; Vellmer, Sebastian; Bernardi, Davide; Roque, Antonio C; Lindner, Benjamin

2018-01-01

Recurrent networks of spiking neurons can be in an asynchronous state characterized by low or absent cross-correlations and spike statistics which resemble those of cortical neurons. Although spatial correlations are negligible in this state, neurons can show pronounced temporal correlations in their spike trains that can be quantified by the autocorrelation function or the spike-train power spectrum. Depending on cellular and network parameters, correlations display diverse patterns (ranging from simple refractory-period effects and stochastic oscillations to slow fluctuations) and it is generally not well-understood how these dependencies come about. Previous work has explored how the single-cell correlations in a homogeneous network (excitatory and inhibitory integrate-and-fire neurons with nearly balanced mean recurrent input) can be determined numerically from an iterative single-neuron simulation. Such a scheme is based on the fact that every neuron is driven by the network noise (i.e., the input currents from all its presynaptic partners) but also contributes to the network noise, leading to a self-consistency condition for the input and output spectra. Here we first extend this scheme to homogeneous networks with strong recurrent inhibition and a synaptic filter, in which instabilities of the previous scheme are avoided by an averaging procedure. We then extend the scheme to heterogeneous networks in which (i) different neural subpopulations (e.g., excitatory and inhibitory neurons) have different cellular or connectivity parameters; (ii) the number and strength of the input connections are random (Erdős-Rényi topology) and thus different among neurons. In all heterogeneous cases, neurons are lumped in different classes each of which is represented by a single neuron in the iterative scheme; in addition, we make a Gaussian approximation of the input current to the neuron. These approximations seem to be justified over a broad range of parameters as indicated by comparison with simulation results of large recurrent networks. Our method can help to elucidate how network heterogeneity shapes the asynchronous state in recurrent neural networks.

Enhancement by citral of glutamatergic spontaneous excitatory transmission in adult rat substantia gelatinosa neurons.

PubMed

Zhu, Lan; Fujita, Tsugumi; Jiang, Chang-Yu; Kumamoto, Eiichi

2016-02-10

Although citral, which is abundantly present in lemongrass, has various actions including antinociception, how citral affects synaptic transmission has not been examined as yet. Citral activates in heterologous cells transient receptor potential vanilloid-1, ankyrin-1, and melastatin-8 (TRPV1, TRPA1, and TRPM8, respectively) channels, the activation of which in the spinal lamina II [substantia gelatinosa (SG)] increases the spontaneous release of L-glutamate from nerve terminals. It remains to be examined what types of transient receptor potential channel in native neurons are activated by citral. With a focus on transient receptor potential activation, we examined the effect of citral on glutamatergic spontaneous excitatory transmission using the whole-cell patch-clamp technique to SG neurons in adult rat spinal cord slices. Bath-applied citral for 3 min increased the frequency of spontaneous excitatory postsynaptic current in a concentration-dependent manner (half-maximal effective concentration=0.58 mM), with a small increase in its amplitude. The spontaneous excitatory postsynaptic current frequency increase produced by citral was repeated at a time interval of 30 min, albeit this action recovered with a slow time course after washout. The presynaptic effect of citral was inhibited by TRPA1 antagonist HC-030031, but not by voltage-gated Na-channel blocker tetrodotoxin, TRPV1 antagonist capsazepine, and TRPM8 antagonist BCTC. It is concluded that citral increases spontaneous L-glutamate release in SG neurons by activating TRPA1 channels. Considering that the SG plays a pivotal role in modulating nociceptive transmission from the periphery, the citral activity could contribute toward at least a part of the modulation.

Mechanisms of perceptual organization provide auto-zoom and auto-localization for attention to objects

PubMed Central

Mihalas, Stefan; Dong, Yi; von der Heydt, Rüdiger; Niebur, Ernst

2011-01-01

Visual attention is often understood as a modulatory field acting at early stages of processing, but the mechanisms that direct and fit the field to the attended object are not known. We show that a purely spatial attention field propagating downward in the neuronal network responsible for perceptual organization will be reshaped, repositioned, and sharpened to match the object's shape and scale. Key features of the model are grouping neurons integrating local features into coherent tentative objects, excitatory feedback to the same local feature neurons that caused grouping neuron activation, and inhibition between incompatible interpretations both at the local feature level and at the object representation level. PMID:21502489

Epigenetic regulation of female puberty.

PubMed

Lomniczi, Alejandro; Wright, Hollis; Ojeda, Sergio R

2015-01-01

Substantial progress has been made in recent years toward deciphering the molecular and genetic underpinnings of the pubertal process. The availability of powerful new methods to interrogate the human genome has led to the identification of genes that are essential for puberty to occur. Evidence has also emerged suggesting that the initiation of puberty requires the coordinated activity of gene sets organized into functional networks. At a cellular level, it is currently thought that loss of transsynaptic inhibition, accompanied by an increase in excitatory inputs, results in the pubertal activation of GnRH release. This concept notwithstanding, a mechanism of epigenetic repression targeting genes required for the pubertal activation of GnRH neurons was recently identified as a core component of the molecular machinery underlying the central restraint of puberty. In this chapter we will discuss the potential contribution of various mechanisms of epigenetic regulation to the hypothalamic control of female puberty. Copyright © 2014 Elsevier Inc. All rights reserved.

Balanced Cortical Microcircuitry for Spatial Working Memory Based on Corrective Feedback Control

PubMed Central

2014-01-01

A hallmark of working memory is the ability to maintain graded representations of both the spatial location and amplitude of a memorized stimulus. Previous work has identified a neural correlate of spatial working memory in the persistent maintenance of spatially specific patterns of neural activity. How such activity is maintained by neocortical circuits remains unknown. Traditional models of working memory maintain analog representations of either the spatial location or the amplitude of a stimulus, but not both. Furthermore, although most previous models require local excitation and lateral inhibition to maintain spatially localized persistent activity stably, the substrate for lateral inhibitory feedback pathways is unclear. Here, we suggest an alternative model for spatial working memory that is capable of maintaining analog representations of both the spatial location and amplitude of a stimulus, and that does not rely on long-range feedback inhibition. The model consists of a functionally columnar network of recurrently connected excitatory and inhibitory neural populations. When excitation and inhibition are balanced in strength but offset in time, drifts in activity trigger spatially specific negative feedback that corrects memory decay. The resulting networks can temporally integrate inputs at any spatial location, are robust against many commonly considered perturbations in network parameters, and, when implemented in a spiking model, generate irregular neural firing characteristic of that observed experimentally during persistent activity. This work suggests balanced excitatory–inhibitory memory circuits implementing corrective negative feedback as a substrate for spatial working memory. PMID:24828633

The contribution of raised intraneuronal chloride to epileptic network activity.

PubMed

Alfonsa, Hannah; Merricks, Edward M; Codadu, Neela K; Cunningham, Mark O; Deisseroth, Karl; Racca, Claudia; Trevelyan, Andrew J

2015-05-20

Altered inhibitory function is an important facet of epileptic pathology. A key concept is that GABAergic activity can become excitatory if intraneuronal chloride rises. However, it has proved difficult to separate the role of raised chloride from other contributory factors in complex network phenomena, such as epileptic pathology. Therefore, we asked what patterns of activity are associated with chloride dysregulation by making novel use of Halorhodopsin to load clusters of mouse pyramidal cells artificially with Cl(-). Brief (1-10 s) activation of Halorhodopsin caused substantial positive shifts in the GABAergic reversal potential that were proportional to the charge transfer during the illumination and in adult neocortical pyramidal neurons decayed with a time constant of τ = 8.0 ± 2.8s. At the network level, these positive shifts in EGABA produced a transient rise in network excitability, with many distinctive features of epileptic foci, including high-frequency oscillations with evidence of out-of-phase firing (Ibarz et al., 2010). We show how such firing patterns can arise from quite small shifts in the mean intracellular Cl(-) level, within heterogeneous neuronal populations. Notably, however, chloride loading by itself did not trigger full ictal events, even with additional electrical stimulation to the underlying white matter. In contrast, when performed in combination with low, subepileptic levels of 4-aminopyridine, Halorhodopsin activation rapidly induced full ictal activity. These results suggest that chloride loading has at most an adjunctive role in ictogenesis. Our simulations also show how chloride loading can affect the jitter of action potential timing associated with imminent recruitment to an ictal event (Netoff and Schiff, 2002). Copyright © 2015 Alfonsa et al.

Top-Down Modulation on Perceptual Decision with Balanced Inhibition through Feedforward and Feedback Inhibitory Neurons

PubMed Central

Wang, Cheng-Te; Lee, Chung-Ting; Wang, Xiao-Jing; Lo, Chung-Chuan

2013-01-01

Recent physiological studies have shown that neurons in various regions of the central nervous systems continuously receive noisy excitatory and inhibitory synaptic inputs in a balanced and covaried fashion. While this balanced synaptic input (BSI) is typically described in terms of maintaining the stability of neural circuits, a number of experimental and theoretical studies have suggested that BSI plays a proactive role in brain functions such as top-down modulation for executive control. Two issues have remained unclear in this picture. First, given the noisy nature of neuronal activities in neural circuits, how do the modulatory effects change if the top-down control implements BSI with different ratios between inhibition and excitation? Second, how is a top-down BSI realized via only excitatory long-range projections in the neocortex? To address the first issue, we systematically tested how the inhibition/excitation ratio affects the accuracy and reaction times of a spiking neural circuit model of perceptual decision. We defined an energy function to characterize the network dynamics, and found that different ratios modulate the energy function of the circuit differently and form two distinct functional modes. To address the second issue, we tested BSI with long-distance projection to inhibitory neurons that are either feedforward or feedback, depending on whether these inhibitory neurons do or do not receive inputs from local excitatory cells, respectively. We found that BSI occurs in both cases. Furthermore, when relying on feedback inhibitory neurons, through the recurrent interactions inside the circuit, BSI dynamically and automatically speeds up the decision by gradually reducing its inhibitory component in the course of a trial when a decision process takes too long. PMID:23626812

Top-down modulation on perceptual decision with balanced inhibition through feedforward and feedback inhibitory neurons.

PubMed

Wang, Cheng-Te; Lee, Chung-Ting; Wang, Xiao-Jing; Lo, Chung-Chuan

2013-01-01

Recent physiological studies have shown that neurons in various regions of the central nervous systems continuously receive noisy excitatory and inhibitory synaptic inputs in a balanced and covaried fashion. While this balanced synaptic input (BSI) is typically described in terms of maintaining the stability of neural circuits, a number of experimental and theoretical studies have suggested that BSI plays a proactive role in brain functions such as top-down modulation for executive control. Two issues have remained unclear in this picture. First, given the noisy nature of neuronal activities in neural circuits, how do the modulatory effects change if the top-down control implements BSI with different ratios between inhibition and excitation? Second, how is a top-down BSI realized via only excitatory long-range projections in the neocortex? To address the first issue, we systematically tested how the inhibition/excitation ratio affects the accuracy and reaction times of a spiking neural circuit model of perceptual decision. We defined an energy function to characterize the network dynamics, and found that different ratios modulate the energy function of the circuit differently and form two distinct functional modes. To address the second issue, we tested BSI with long-distance projection to inhibitory neurons that are either feedforward or feedback, depending on whether these inhibitory neurons do or do not receive inputs from local excitatory cells, respectively. We found that BSI occurs in both cases. Furthermore, when relying on feedback inhibitory neurons, through the recurrent interactions inside the circuit, BSI dynamically and automatically speeds up the decision by gradually reducing its inhibitory component in the course of a trial when a decision process takes too long.

Impaired inhibitory control of cortical synchronization in fragile X syndrome.

PubMed

Paluszkiewicz, Scott M; Olmos-Serrano, Jose Luis; Corbin, Joshua G; Huntsman, Molly M

2011-11-01

Fragile X syndrome (FXS) is a neurodevelopmental disorder characterized by severe cognitive impairments, sensory hypersensitivity, and comorbidities with autism and epilepsy. Fmr1 knockout (KO) mouse models of FXS exhibit alterations in excitatory and inhibitory neurotransmission, but it is largely unknown how aberrant function of specific neuronal subtypes contributes to these deficits. In this study we show specific inhibitory circuit dysfunction in layer II/III of somatosensory cortex of Fmr1 KO mice. We demonstrate reduced activation of somatostatin-expressing low-threshold-spiking (LTS) interneurons in response to the group I metabotropic glutamate receptor (mGluR) agonist 3,5-dihydroxyphenylglycine (DHPG) in Fmr1 KO mice, resulting in impaired synaptic inhibition. Paired recordings from pyramidal neurons revealed reductions in synchronized synaptic inhibition and coordinated spike synchrony in response to DHPG, indicating a weakened LTS interneuron network in Fmr1 KO mice. Together, these findings reveal a functional defect in a single subtype of cortical interneuron in Fmr1 KO mice. This defect is linked to altered activity of the cortical network in line with the FXS phenotype.

TRPV1 regulates excitatory innervation of OLM neurons in the hippocampus

PubMed Central

Hurtado-Zavala, Joaquin I.; Ramachandran, Binu; Ahmed, Saheeb; Halder, Rashi; Bolleyer, Christiane; Awasthi, Ankit; Stahlberg, Markus A.; Wagener, Robin J.; Anderson, Kristin; Drenan, Ryan M.; Lester, Henry A.; Miwa, Julie M.; Staiger, Jochen F.; Fischer, Andre; Dean, Camin

2017-01-01

TRPV1 is an ion channel activated by heat and pungent agents including capsaicin, and has been extensively studied in nociception of sensory neurons. However, the location and function of TRPV1 in the hippocampus is debated. We found that TRPV1 is expressed in oriens-lacunosum-moleculare (OLM) interneurons in the hippocampus, and promotes excitatory innervation. TRPV1 knockout mice have reduced glutamatergic innervation of OLM neurons. When activated by capsaicin, TRPV1 recruits more glutamatergic, but not GABAergic, terminals to OLM neurons in vitro. When TRPV1 is blocked, glutamatergic input to OLM neurons is dramatically reduced. Heterologous expression of TRPV1 also increases excitatory innervation. Moreover, TRPV1 knockouts have reduced Schaffer collateral LTP, which is rescued by activating OLM neurons with nicotine—via α2β2-containing nicotinic receptors—to bypass innervation defects. Our results reveal a synaptogenic function of TRPV1 in a specific interneuron population in the hippocampus, where it is important for gating hippocampal plasticity. PMID:28722015

Presynaptic LRP4 promotes synapse number and function of excitatory CNS neurons

PubMed Central

Mosca, Timothy J; Luginbuhl, David J; Wang, Irving E; Luo, Liqun

2017-01-01

Precise coordination of synaptic connections ensures proper information flow within circuits. The activity of presynaptic organizing molecules signaling to downstream pathways is essential for such coordination, though such entities remain incompletely known. We show that LRP4, a conserved transmembrane protein known for its postsynaptic roles, functions presynaptically as an organizing molecule. In the Drosophila brain, LRP4 localizes to the nerve terminals at or near active zones. Loss of presynaptic LRP4 reduces excitatory (not inhibitory) synapse number, impairs active zone architecture, and abolishes olfactory attraction - the latter of which can be suppressed by reducing presynaptic GABAB receptors. LRP4 overexpression increases synapse number in excitatory and inhibitory neurons, suggesting an instructive role and a common downstream synapse addition pathway. Mechanistically, LRP4 functions via the conserved kinase SRPK79D to ensure normal synapse number and behavior. This highlights a presynaptic function for LRP4, enabling deeper understanding of how synapse organization is coordinated. DOI: http://dx.doi.org/10.7554/eLife.27347.001 PMID:28606304

Directed functional connectivity matures with motor learning in a cortical pattern generator.

PubMed

Day, Nancy F; Terleski, Kyle L; Nykamp, Duane Q; Nick, Teresa A

2013-02-01

Sequential motor skills may be encoded by feedforward networks that consist of groups of neurons that fire in sequence (Abeles 1991; Long et al. 2010). However, there has been no evidence of an anatomic map of activation sequence in motor control circuits, which would be potentially detectable as directed functional connectivity of coactive neuron groups. The proposed pattern generator for birdsong, the HVC (Long and Fee 2008; Vu et al. 1994), contains axons that are preferentially oriented in the rostrocaudal axis (Nottebohm et al. 1982; Stauffer et al. 2012). We used four-tetrode recordings to assess the activity of ensembles of single neurons along the rostrocaudal HVC axis in anesthetized zebra finches. We found an axial, polarized neural network in which sequential activity is directionally organized along the rostrocaudal axis in adult males, who produce a stereotyped song. Principal neurons fired in rostrocaudal order and with interneurons that were rostral to them, suggesting that groups of excitatory neurons fire at the leading edge of travelling waves of inhibition. Consistent with the synchronization of neurons by caudally travelling waves of inhibition, the activity of interneurons was more coherent in the orthogonal mediolateral axis than in the rostrocaudal axis. If directed functional connectivity within the HVC is important for stereotyped, learned song, then it may be lacking in juveniles, which sing a highly variable song. Indeed, we found little evidence for network directionality in juveniles. These data indicate that a functionally directed network within the HVC matures during sensorimotor learning and may underlie vocal patterning.

Directed functional connectivity matures with motor learning in a cortical pattern generator

PubMed Central

Day, Nancy F.; Terleski, Kyle L.; Nykamp, Duane Q.

2013-01-01

Sequential motor skills may be encoded by feedforward networks that consist of groups of neurons that fire in sequence (Abeles 1991; Long et al. 2010). However, there has been no evidence of an anatomic map of activation sequence in motor control circuits, which would be potentially detectable as directed functional connectivity of coactive neuron groups. The proposed pattern generator for birdsong, the HVC (Long and Fee 2008; Vu et al. 1994), contains axons that are preferentially oriented in the rostrocaudal axis (Nottebohm et al. 1982; Stauffer et al. 2012). We used four-tetrode recordings to assess the activity of ensembles of single neurons along the rostrocaudal HVC axis in anesthetized zebra finches. We found an axial, polarized neural network in which sequential activity is directionally organized along the rostrocaudal axis in adult males, who produce a stereotyped song. Principal neurons fired in rostrocaudal order and with interneurons that were rostral to them, suggesting that groups of excitatory neurons fire at the leading edge of travelling waves of inhibition. Consistent with the synchronization of neurons by caudally travelling waves of inhibition, the activity of interneurons was more coherent in the orthogonal mediolateral axis than in the rostrocaudal axis. If directed functional connectivity within the HVC is important for stereotyped, learned song, then it may be lacking in juveniles, which sing a highly variable song. Indeed, we found little evidence for network directionality in juveniles. These data indicate that a functionally directed network within the HVC matures during sensorimotor learning and may underlie vocal patterning. PMID:23175804

[Mechanism of action of antiepileptic drugs].

PubMed

Saidón, Patricia

2003-01-01

Antiepileptic drugs (DAEs) act through different mechanisms of action: increase in central inhibition, inhibition of excitatorios mechanisms and modification of the excitability through their action on the ionic channels. Epilepsy is characterized by an abnormal and hypersynchronic unloading of a neuronal population. The activity of numerous drugs is associated to increase in gabaergic activity. Another group of drugs decreases excitatory mechanisms, through the inhibition of ionic channels, or through a decrease in the activity of the excitatory neurotransmitters. There are some of antiepileptic drugs, especially within the group of drugs of recent appearance, for wich the mechanism of action remains unknown.

Excitatory amino acid neurotoxicity and neurodegenerative disease.

PubMed

Meldrum, B; Garthwaite, J

1990-09-01

The progress over the last 30 years in defining the role of excitatory amino acids in normal physiological function and in the abnormal neuronal activity of epilepsy has been reviewed in earlier articles in this series. In the last five years it has become clear that excitatory amino acids also play a role in a wide range of neurodegenerative processes. The evidence is clearest where the degenerative process is acute, but is more controversial for slow degenerative processes. In this article Brian Meldrum and John Garthwaite review in vivo and in vitro studies of the cytotoxicity of amino acids and summarize the contribution of such toxicity to acute and chronic neurodegenerative disorders.

Modulation of short-term plasticity in the corticothalamic circuit by group III metabotropic glutamate receptors.

PubMed

Kyuyoung, Christine L; Huguenard, John R

2014-01-08

Recurrent connections in the corticothalamic circuit underlie oscillatory behavior in this network and range from normal sleep rhythms to the abnormal spike-wave discharges seen in absence epilepsy. The propensity of thalamic neurons to fire postinhibitory rebound bursts mediated by low-threshold calcium spikes renders the circuit vulnerable to both increased excitation and increased inhibition, such as excessive excitatory cortical drive to thalamic reticular (RT) neurons or heightened inhibition of thalamocortical relay (TC) neurons by RT. In this context, a protective role may be played by group III metabotropic receptors (mGluRs), which are uniquely located in the presynaptic active zone and typically act as autoreceptors or heteroceptors to depress synaptic release. Here, we report that these receptors regulate short-term plasticity at two loci in the corticothalamic circuit in rats: glutamatergic cortical synapses onto RT neurons and GABAergic synapses onto TC neurons in somatosensory ventrobasal thalamus. The net effect of group III mGluR activation at these synapses is to suppress thalamic oscillations as assayed in vitro. These findings suggest a functional role of these receptors to modulate corticothalamic transmission and protect against prolonged activity in the network.

Hippocampal CA1 Ripples as Inhibitory Transients

PubMed Central

Krishnan, Giri P; Fellous, Jean-Marc; Bazhenov, Maxim

2016-01-01

Memories are stored and consolidated as a result of a dialogue between the hippocampus and cortex during sleep. Neurons active during behavior reactivate in both structures during sleep, in conjunction with characteristic brain oscillations that may form the neural substrate of memory consolidation. In the hippocampus, replay occurs within sharp wave-ripples: short bouts of high-frequency activity in area CA1 caused by excitatory activation from area CA3. In this work, we develop a computational model of ripple generation, motivated by in vivo rat data showing that ripples have a broad frequency distribution, exponential inter-arrival times and yet highly non-variable durations. Our study predicts that ripples are not persistent oscillations but result from a transient network behavior, induced by input from CA3, in which the high frequency synchronous firing of perisomatic interneurons does not depend on the time scale of synaptic inhibition. We found that noise-induced loss of synchrony among CA1 interneurons dynamically constrains individual ripple duration. Our study proposes a novel mechanism of hippocampal ripple generation consistent with a broad range of experimental data, and highlights the role of noise in regulating the duration of input-driven oscillatory spiking in an inhibitory network. PMID:27093059

The reducing agent dithiothreitol (DTT) does not abolish the inhibitory nicotinic response recorded from rat dorsolateral septal neurons

NASA Technical Reports Server (NTRS)

Sorenson, E. M.; Gallagher, J. P.

1993-01-01

Previous intracellular recordings have demonstrated that dorsolateral septal nucleus (DLSN) neurons express a novel nicotinic receptor which produces a direct membrane hyperpolarization when activated by nicotinic agonists. Activation of the classical excitatory nicotinic receptors has been shown to require a disulfide bond involving the cysteines at positions 192 and 193 of the alpha subunits of the receptor. Reduction of this cystine bond with dithiothreitol (DTT) abolishes agonist activation of excitatory nicotinic receptors. We have now examined whether DTT treatment of the inhibitory nicotinic receptor on DLSN neurons also abolishes the inhibitory nicotinic response. We find that the inhibitory response persists after treatment of the neurons with 1 mM DTT, even if the reduction is followed by alkylation of the receptor with bromoacetylcholine to prevent possible reformation of disulfide bonds. This result suggests that the agonist binding site on the inhibitory nicotinic receptor does not require an intact disulfide bond, similar to the bond on the alpha subunit of the excitatory nicotinic receptor, for agonist activation of the receptor. Some of these results have been previously reported in abstract form.

High frequency stimulation abolishes thalamic network oscillations: an electrophysiological and computational analysis

NASA Astrophysics Data System (ADS)

Lee, Kendall H.; Hitti, Frederick L.; Chang, Su-Youne; Lee, Dongchul C.; Roberts, David W.; McIntyre, Cameron C.; Leiter, James C.

2011-08-01

Deep brain stimulation (DBS) of the thalamus has been demonstrated to be effective for the treatment of epilepsy. To investigate the mechanism of action of thalamic DBS, we examined the effects of high frequency stimulation (HFS) on spindle oscillations in thalamic brain slices from ferrets. We recorded intracellular and extracellular electrophysiological activity in the nucleus reticularis thalami (nRt) and in thalamocortical relay (TC) neurons in the lateral geniculate nucleus, stimulated the slice using a concentric bipolar electrode, and recorded the level of glutamate within the slice. HFS (100 Hz) of TC neurons generated excitatory post-synaptic potentials, increased the number of action potentials in both TC and nRt neurons, reduced the input resistance, increased the extracellular glutamate concentration, and abolished spindle wave oscillations. HFS of the nRt also suppressed spindle oscillations. In both locations, HFS was associated with significant and persistent elevation in extracellular glutamate levels and suppressed spindle oscillations for many seconds after the cessation of stimulation. We simulated HFS within a computational model of the thalamic network, and HFS also disrupted spindle wave activity, but the suppression of spindle activity was short-lived. Simulated HFS disrupted spindle activity for prolonged periods of time only after glutamate release and glutamate-mediated activation of a hyperpolarization-activated current (Ih) was incorporated into the model. Our results suggest that the mechanism of action of thalamic DBS as used in epilepsy may involve the prolonged release of glutamate, which in turn modulates specific ion channels such as Ih, decreases neuronal input resistance, and abolishes thalamic network oscillatory activity.

Oscillations and Synchrony in Large-scale Cortical Network Models

DTIC Science & Technology

2008-06-17

synaptic current is computed as In = −gn(xpostn − xrp ), (7) where gsyn is the strength of the synaptic coupling and the indices pre and post stand... xrp defines the reversal potential and, therefore, the type of synapse: excitatory ( xrp = 0) or inhibitory ( xrp = −1.1). To include the effects of short

Epilepsy and optogenetics: can seizures be controlled by light?

PubMed

Tønnesen, Jan; Kokaia, Merab

2017-07-15

Over the past decade, 'optogenetics' has been consolidated as a game-changing tool in the neuroscience field, by allowing optical control of neuronal activity with high cell-type specificity. The ability to activate or inhibit targeted neurons at millisecond resolution not only offers an investigative tool, but potentially also provides a therapeutic intervention strategy for acute correction of aberrant neuronal activity. As efficient therapeutic tools are in short supply for neurological disorders, optogenetic technology has therefore spurred considerable enthusiasm and fostered a new wave of translational studies in neuroscience. Epilepsy is among the disorders that have been widely explored. Partial epilepsies are characterized by seizures arising from excessive excitatory neuronal activity that emerges from a focal area. Based on the constricted seizure focus, it appears feasible to intercept partial seizures by acutely shutting down excitatory neurons by means of optogenetics. The availability of both inhibitory and excitatory optogenetic probes, along with the available targeting strategies for respective excitatory or inhibitory neurons, allows multiple conceivable scenarios for controlling abnormal circuit activity. Several such scenarios have been explored in the settings of experimental epilepsy and have provided encouraging translational findings and revealed interesting and unexpected new aspects of epileptogenesis. However, it has also emerged that considerable challenges persist before clinical translation becomes feasible. This review provides a general introduction to optogenetics, and an overview of findings that are relevant for understanding how optogenetics may be utilized therapeutically as a highly innovative treatment for epilepsy. © 2017 The Author(s). Published by Portland Press Limited on behalf of the Biochemical Society.

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

Asynchronous Cholinergic Drive Correlates with Excitation-Inhibition Imbalance via a Neuronal Ca2+ Sensor Protein.

PubMed

Zhou, Keming; Cherra, Salvatore J; Goncharov, Alexandr; Jin, Yishi

2017-05-09

Excitation-inhibition imbalance in neural networks is widely linked to neurological and neuropsychiatric disorders. However, how genetic factors alter neuronal activity, leading to excitation-inhibition imbalance, remains unclear. Here, using the C. elegans locomotor circuit, we examine how altering neuronal activity for varying time periods affects synaptic release pattern and animal behavior. We show that while short-duration activation of excitatory cholinergic neurons elicits a reversible enhancement of presynaptic strength, persistent activation results to asynchronous and reduced cholinergic drive, inducing imbalance between endogenous excitation and inhibition. We find that the neuronal calcium sensor protein NCS-2 is required for asynchronous cholinergic release in an activity-dependent manner and dampens excitability of inhibitory neurons non-cell autonomously. The function of NCS-2 requires its Ca 2+ binding and membrane association domains. These results reveal a synaptic mechanism implicating asynchronous release in regulation of excitation-inhibition balance. Copyright © 2017 The Author(s). Published by Elsevier Inc. All rights reserved.

Interictal to Ictal Phase Transition in a Small-World Network

NASA Astrophysics Data System (ADS)

Nemzer, Louis; Cravens, Gary; Worth, Robert

Real-time detection and prediction of seizures in patients with epilepsy is essential for rapid intervention. Here, we perform a full Hodgkin-Huxley calculation using n 50 in silico neurons configured in a small-world network topology to generate simulated EEG signals. The connectivity matrix, constructed using a Watts-Strogatz algorithm, admits randomized or deterministic entries. We find that situations corresponding to interictal (non-seizure) and ictal (seizure) states are separated by a phase transition that can be influenced by congenital channelopathies, anticonvulsant drugs, and connectome plasticity. The interictal phase exhibits scale-free phenomena, as characterized by a power law form of the spectral power density, while the ictal state suffers from pathological synchronization. We compare the results with intracranial EEG data and show how these findings may be used to detect or even predict seizure onset. Along with the balance of excitatory and inhibitory factors, the network topology plays a large role in determining the overall characteristics of brain activity. We have developed a new platform for testing the conditions that contribute to the phase transition between non-seizure and seizure states.

Towards a theory of cortical columns: From spiking neurons to interacting neural populations of finite size.

PubMed

Schwalger, Tilo; Deger, Moritz; Gerstner, Wulfram

2017-04-01

Neural population equations such as neural mass or field models are widely used to study brain activity on a large scale. However, the relation of these models to the properties of single neurons is unclear. Here we derive an equation for several interacting populations at the mesoscopic scale starting from a microscopic model of randomly connected generalized integrate-and-fire neuron models. Each population consists of 50-2000 neurons of the same type but different populations account for different neuron types. The stochastic population equations that we find reveal how spike-history effects in single-neuron dynamics such as refractoriness and adaptation interact with finite-size fluctuations on the population level. Efficient integration of the stochastic mesoscopic equations reproduces the statistical behavior of the population activities obtained from microscopic simulations of a full spiking neural network model. The theory describes nonlinear emergent dynamics such as finite-size-induced stochastic transitions in multistable networks and synchronization in balanced networks of excitatory and inhibitory neurons. The mesoscopic equations are employed to rapidly integrate a model of a cortical microcircuit consisting of eight neuron types, which allows us to predict spontaneous population activities as well as evoked responses to thalamic input. Our theory establishes a general framework for modeling finite-size neural population dynamics based on single cell and synapse parameters and offers an efficient approach to analyzing cortical circuits and computations.

Task-dependent activity and connectivity predict episodic memory network-based responses to brain stimulation in healthy aging

PubMed Central

Vidal-Piñeiro, Dídac; Martin-Trias, Pablo; Arenaza-Urquijo, Eider M.; Sala-Llonch, Roser; Mena-Sánchez, Isaias; Bargalló, Núria; Falcón, Carles; Pascual-Leone, Álvaro; Bartrés-Faz, David

2015-01-01

Background Transcranial Magnetic Stimulation (TMS) can affect episodic memory, one of the main cognitive hallmarks of aging, but the mechanisms of action remain unclear. Objectives To evaluate the behavioral and functional impact of excitatory TMS in a group of healthy elders. Methods We applied a paradigm of repetitive TMS -intermittent theta-burst stimulation- over left inferior frontal gyrus in healthy elders (n=24) and evaluated its impact on the performance of an episodic memory task with two levels of processing and the associated brain activity as captured by a pre and post fMRI scans. Results In the post-TMS fMRI we found TMS-related activity increases in left prefrontal and cerebellum-occipital areas specifically during deep encoding but not during shallow encoding or at rest. Furthermore, we found a task-dependent change in connectivity during the encoding task between cerebellum-occipital areas and the TMS-targeted left inferior frontal region. This connectivity change correlated with the TMS effects over brain networks. Conclusions The results suggest that the aged brain responds to brain stimulation in a state-dependent manner as engaged by different tasks components and that TMS effect is related to inter-individual connectivity changes measures. These findings reveal fundamental insights into brain network dynamics in aging and the capacity to probe them with combined behavioral and stimulation approaches. PMID:24485466

Task-dependent activity and connectivity predict episodic memory network-based responses to brain stimulation in healthy aging.

PubMed

Vidal-Piñeiro, Dídac; Martin-Trias, Pablo; Arenaza-Urquijo, Eider M; Sala-Llonch, Roser; Clemente, Imma C; Mena-Sánchez, Isaias; Bargalló, Núria; Falcón, Carles; Pascual-Leone, Álvaro; Bartrés-Faz, David

2014-01-01

Transcranial magnetic stimulation (TMS) can affect episodic memory, one of the main cognitive hallmarks of aging, but the mechanisms of action remain unclear. To evaluate the behavioral and functional impact of excitatory TMS in a group of healthy elders. We applied a paradigm of repetitive TMS - intermittent theta-burst stimulation - over left inferior frontal gyrus in healthy elders (n = 24) and evaluated its impact on the performance of an episodic memory task with two levels of processing and the associated brain activity as captured by a pre and post fMRI scans. In the post-TMS fMRI we found TMS-related activity increases in left prefrontal and cerebellum-occipital areas specifically during deep encoding but not during shallow encoding or at rest. Furthermore, we found a task-dependent change in connectivity during the encoding task between cerebellum-occipital areas and the TMS-targeted left inferior frontal region. This connectivity change correlated with the TMS effects over brain networks. The results suggest that the aged brain responds to brain stimulation in a state-dependent manner as engaged by different tasks components and that TMS effect is related to inter-individual connectivity changes measures. These findings reveal fundamental insights into brain network dynamics in aging and the capacity to probe them with combined behavioral and stimulation approaches. Copyright © 2014 Elsevier Inc. All rights reserved.

Neurotransmitter activity is linked to outcome following subthalamic deep brain stimulation in Parkinson's disease.

PubMed

O'Gorman Tuura, Ruth L; Baumann, Christian R; Baumann-Vogel, Heide

2018-05-01

While the mechanisms underlying the therapeutic effects of deep brain stimulation (DBS) in Parkinson's Disease (PD) are not yet fully understood, DBS appears to exert a wide range of neurochemical effects on the network level, thought to arise from activation of inhibitory and excitatory pathways. The activity within the primary inhibitory (GABAergic) and excitatory (glutamatergic) neurotransmitter systems may therefore play an important role in the therapeutic efficacy of DBS in PD. The purpose of this study was to investigate abnormalities in GABA-ergic and glutamatergic neurotransmission in PD, and to examine the link between neurotransmitter levels and outcome following DBS. Magnetic resonance spectra were acquired from the pons and basal ganglia in sixteen patients with PD and sixteen matched control participants. GABA and glutamate levels were quantified with LCModel, an automated spectral fitting package. Fourteen patients subsequently underwent DBS, and PD symptoms were evaluated with the MDS-UPDRS at baseline and six months after surgery. The efficacy of DBS treatment was evaluated from the percentage improvement in MDS-UPDRS scores. Basal ganglia GABA levels were significantly higher in PD patients relative to control participants (p < 0.01), while pontine glutamate + glutamine (Glx) levels were significantly lower in patients with PD (p < 0.05). While GABA levels were not significantly related to outcome post-surgery, basal ganglia glutamate levels emerged as a significant predictor of outcome, suggesting a possible role for glutamatergic neurotransmission in the therapeutic mechanism of DBS. GABAergic and glutamatergic neurotransmission is altered in PD, and glutamatergic activity in particular may influence outcome post-surgery. Copyright © 2018 Elsevier Ltd. All rights reserved.

Excitatory innervation of caudal hypoglossal nucleus from nucleus reticularis gigantocellularis in the rat.

PubMed

Yang, C C; Chan, J Y; Chan, S H

1995-03-01

We examined the possible innervation of the caudal hypoglossal nucleus by the nucleus reticularis gigantocellularis of the medulla oblongata, based on single-neuron recording and retrograde tracing experiments in Sprague-Dawley rats. Under pentobarbital sodium (50 mg/kg, i.p.) anesthesia, electrical stimulation of the caudal portion of the nucleus reticularis gigantocellularis with repetitive 0.5-ms rectangular pulses increased (46 of 51 neurons) the basal discharge frequency of spontaneously active cells, or evoked spike activity in silent, hypoglossal neurons located at the level of the obex. This excitatory effect was related to the intensity (25-100 microA) and/or frequency (0.5-20 Hz) of the stimulating pulses to the nucleus reticularis gigantocellularis. Perikaryal activation of neurons by microinjection of L-glutamate (0.5 nmol, 25 nl) into the caudal portion of the nucleus reticularis gigantocellularis similarly produced an excitatory action on eight of 14 hypoglossal neurons. Retrogradely labeled neurons were found bilaterally within the confines of the nucleus reticularis gigantocellularis following unilateral microinjection of wheatgerm agglutinin-conjugated horseradish peroxidase or Fast Blue into the corresponding hypoglossal recording sites. Furthermore, the distribution of labeled neurons in the nucleus reticularis gigantocellularis substantially overlapped with the loci of electrical or chemical stimulation. These complementary electrophysiological and neuroanatomical results support the conclusion that an excitatory link exists between the nucleus reticularis gigantocellularis and at least the caudal portion of the hypoglossal nucleus in the rat.

Olfactory bulb short axon cell release of GABA and dopamine produces a temporally biphasic inhibition-excitation response in external tufted cells

PubMed Central

Liu, Shaolin; Plachez, Celine; Shao, Zuoyi; Puche, Adam; Shipley, Michael T.

2013-01-01

Evidence for co-expression of two or more classic neurotransmitters in neurons has increased but less is known about co-transmission. Ventral tegmental area (VTA) neurons, co-release dopamine (DA), the excitatory transmitter glutamate and the inhibitory transmitter GABA onto target cells in the striatum. Olfactory bulb (OB) short axon cells (SACs) form interglomerular connections and co-express markers for dopamine (DA) and GABA. Using an optogenetic approach we provide evidence that mouse OB SACs release both GABA and DA onto external tufted cells (ETCs) in other glomeruli. Optical activation of channelrhodopsin specifically expressed in DAergic SACs produced a GABAA receptor-mediated monosynaptic inhibitory response followed by DA-D1-like receptor-mediated excitatory response in ETCs. The GABAA receptor-mediated hyperpolarization activates Ih current in ETCs; synaptically released DA increases Ih, which enhances post-inhibitory rebound spiking. Thus, the opposing actions of synaptically released GABA and DA are functionally integrated by Ih to generate an inhibition-to-excitation “switch” in ETCs. Consistent with the established role of Ih in ETC burst firing, we show that endogenous DA release increases ETC spontaneous bursting frequency. ETCs transmit sensory signals to mitral/tufted output neurons and drive intraglomerular inhibition to shape glomerulus output to downstream olfactory networks. GABA and DA co-transmission from SACs to ETCs may play a key role in regulating output coding across the glomerular array. PMID:23407950

Optimizing one-shot learning with binary synapses.

PubMed

Romani, Sandro; Amit, Daniel J; Amit, Yali

2008-08-01

A network of excitatory synapses trained with a conservative version of Hebbian learning is used as a model for recognizing the familiarity of thousands of once-seen stimuli from those never seen before. Such networks were initially proposed for modeling memory retrieval (selective delay activity). We show that the same framework allows the incorporation of both familiarity recognition and memory retrieval, and estimate the network's capacity. In the case of binary neurons, we extend the analysis of Amit and Fusi (1994) to obtain capacity limits based on computations of signal-to-noise ratio of the field difference between selective and non-selective neurons of learned signals. We show that with fast learning (potentiation probability approximately 1), the most recently learned patterns can be retrieved in working memory (selective delay activity). A much higher number of once-seen learned patterns elicit a realistic familiarity signal in the presence of an external field. With potentiation probability much less than 1 (slow learning), memory retrieval disappears, whereas familiarity recognition capacity is maintained at a similarly high level. This analysis is corroborated in simulations. For analog neurons, where such analysis is more difficult, we simplify the capacity analysis by studying the excess number of potentiated synapses above the steady-state distribution. In this framework, we derive the optimal constraint between potentiation and depression probabilities that maximizes the capacity.

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.

Bidirectional Regulation of Innate and Learned Behaviors That Rely on Frequency Discrimination by Cortical Inhibitory Neurons

PubMed Central

Aizenberg, Mark; Mwilambwe-Tshilobo, Laetitia; Briguglio, John J.; Natan, Ryan G.; Geffen, Maria N.

2015-01-01

The ability to discriminate tones of different frequencies is fundamentally important for everyday hearing. While neurons in the primary auditory cortex (AC) respond differentially to tones of different frequencies, whether and how AC regulates auditory behaviors that rely on frequency discrimination remains poorly understood. Here, we find that the level of activity of inhibitory neurons in AC controls frequency specificity in innate and learned auditory behaviors that rely on frequency discrimination. Photoactivation of parvalbumin-positive interneurons (PVs) improved the ability of the mouse to detect a shift in tone frequency, whereas photosuppression of PVs impaired the performance. Furthermore, photosuppression of PVs during discriminative auditory fear conditioning increased generalization of conditioned response across tone frequencies, whereas PV photoactivation preserved normal specificity of learning. The observed changes in behavioral performance were correlated with bidirectional changes in the magnitude of tone-evoked responses, consistent with predictions of a model of a coupled excitatory-inhibitory cortical network. Direct photoactivation of excitatory neurons, which did not change tone-evoked response magnitude, did not affect behavioral performance in either task. Our results identify a new function for inhibition in the auditory cortex, demonstrating that it can improve or impair acuity of innate and learned auditory behaviors that rely on frequency discrimination. PMID:26629746

Complexity in neuronal noise depends on network interconnectivity.

PubMed

Serletis, Demitre; Zalay, Osbert C; Valiante, Taufik A; Bardakjian, Berj L; Carlen, Peter L

2011-06-01

"Noise," or noise-like activity (NLA), defines background electrical membrane potential fluctuations at the cellular level of the nervous system, comprising an important aspect of brain dynamics. Using whole-cell voltage recordings from fast-spiking stratum oriens interneurons and stratum pyramidale neurons located in the CA3 region of the intact mouse hippocampus, we applied complexity measures from dynamical systems theory (i.e., 1/f(γ) noise and correlation dimension) and found evidence for complexity in neuronal NLA, ranging from high- to low-complexity dynamics. Importantly, these high- and low-complexity signal features were largely dependent on gap junction and chemical synaptic transmission. Progressive neuronal isolation from the surrounding local network via gap junction blockade (abolishing gap junction-dependent spikelets) and then chemical synaptic blockade (abolishing excitatory and inhibitory post-synaptic potentials), or the reverse order of these treatments, resulted in emergence of high-complexity NLA dynamics. Restoring local network interconnectivity via blockade washout resulted in resolution to low-complexity behavior. These results suggest that the observed increase in background NLA complexity is the result of reduced network interconnectivity, thereby highlighting the potential importance of the NLA signal to the study of network state transitions arising in normal and abnormal brain dynamics (such as in epilepsy, for example).

A Simple Network Architecture Accounts for Diverse Reward Time Responses in Primary Visual Cortex

PubMed Central

Hussain Shuler, Marshall G.; Shouval, Harel Z.

2015-01-01

Many actions performed by animals and humans depend on an ability to learn, estimate, and produce temporal intervals of behavioral relevance. Exemplifying such learning of cued expectancies is the observation of reward-timing activity in the primary visual cortex (V1) of rodents, wherein neural responses to visual cues come to predict the time of future reward as behaviorally experienced in the past. These reward-timing responses exhibit significant heterogeneity in at least three qualitatively distinct classes: sustained increase or sustained decrease in firing rate until the time of expected reward, and a class of cells that reach a peak in firing at the expected delay. We elaborate upon our existing model by including inhibitory and excitatory units while imposing simple connectivity rules to demonstrate what role these inhibitory elements and the simple architectures play in sculpting the response dynamics of the network. We find that simply adding inhibition is not sufficient for obtaining the different distinct response classes, and that a broad distribution of inhibitory projections is necessary for obtaining peak-type responses. Furthermore, although changes in connection strength that modulate the effects of inhibition onto excitatory units have a strong impact on the firing rate profile of these peaked responses, the network exhibits robustness in its overall ability to predict the expected time of reward. Finally, we demonstrate how the magnitude of expected reward can be encoded at the expected delay in the network and how peaked responses express this reward expectancy. SIGNIFICANCE STATEMENT Heterogeneity in single-neuron responses is a common feature of neuronal systems, although sometimes, in theoretical approaches, it is treated as a nuisance and seldom considered as conveying a different aspect of a signal. In this study, we focus on the heterogeneous responses in the primary visual cortex of rodents trained with a predictable delayed reward time. We describe under what conditions this heterogeneity can arise by self-organization, and what information it can convey. This study, while focusing on a specific system, provides insight onto how heterogeneity can arise in general while also shedding light onto mechanisms of reinforcement learning using realistic biological assumptions. PMID:26377457

Early Correlated Network Activity in the Hippocampus: Its Putative Role in Shaping Neuronal Circuits.

PubMed

Griguoli, Marilena; Cherubini, Enrico

2017-01-01

Synchronized neuronal activity occurring at different developmental stages in various brain structures represents a hallmark of developmental circuits. This activity, which differs in its specific patterns among animal species may play a crucial role in de novo formation and in shaping neuronal networks. In the rodent hippocampus in vitro , the so-called giant depolarizing potentials (GDPs) constitute a primordial form of neuronal synchrony preceding more organized forms of activity such as oscillations in the theta and gamma frequency range. GDPs are generated at the network level by the interaction of the neurotransmitters glutamate and GABA which, immediately after birth, exert both a depolarizing and excitatory action on their targets. GDPs are triggered by GABAergic interneurons, which in virtue of their extensive axonal branching operate as functional hubs to synchronize large ensembles of cells. Intrinsic bursting activity, driven by a persistent sodium conductance and facilitated by the low expression of Kv7.2 and Kv7.3 channel subunits, responsible for I M , exerts a permissive role in GDP generation. Here, we discuss how GDPs are generated in a probabilistic way when neuronal excitability within a local circuit reaches a certain threshold and how GDP-associated calcium transients act as coincident detectors for enhancing synaptic strength at emerging GABAergic and glutamatergic synapses. We discuss the possible in vivo correlate of this activity. Finally, we debate recent data showing how, in several animal models of neuropsychiatric disorders including autism, a GDPs dysfunction is associated to morphological alterations of neuronal circuits and behavioral deficits reminiscent of those observed in patients.

FPGA implementation of a biological neural network based on the Hodgkin-Huxley neuron model

PubMed Central

Yaghini Bonabi, Safa; Asgharian, Hassan; Safari, Saeed; Nili Ahmadabadi, Majid

2014-01-01

A set of techniques for efficient implementation of Hodgkin-Huxley-based (H-H) model of a neural network on FPGA (Field Programmable Gate Array) is presented. The central implementation challenge is H-H model complexity that puts limits on the network size and on the execution speed. However, basics of the original model cannot be compromised when effect of synaptic specifications on the network behavior is the subject of study. To solve the problem, we used computational techniques such as CORDIC (Coordinate Rotation Digital Computer) algorithm and step-by-step integration in the implementation of arithmetic circuits. In addition, we employed different techniques such as sharing resources to preserve the details of model as well as increasing the network size in addition to keeping the network execution speed close to real time while having high precision. Implementation of a two mini-columns network with 120/30 excitatory/inhibitory neurons is provided to investigate the characteristic of our method in practice. The implementation techniques provide an opportunity to construct large FPGA-based network models to investigate the effect of different neurophysiological mechanisms, like voltage-gated channels and synaptic activities, on the behavior of a neural network in an appropriate execution time. Additional to inherent properties of FPGA, like parallelism and re-configurability, our approach makes the FPGA-based system a proper candidate for study on neural control of cognitive robots and systems as well. PMID:25484854

The Complexity of Dynamics in Small Neural Circuits

PubMed Central

Panzeri, Stefano

2016-01-01

Mean-field approximations are a powerful tool for studying large neural networks. However, they do not describe well the behavior of networks composed of a small number of neurons. In this case, major differences between the mean-field approximation and the real behavior of the network can arise. Yet, many interesting problems in neuroscience involve the study of mesoscopic networks composed of a few tens of neurons. Nonetheless, mathematical methods that correctly describe networks of small size are still rare, and this prevents us to make progress in understanding neural dynamics at these intermediate scales. Here we develop a novel systematic analysis of the dynamics of arbitrarily small networks composed of homogeneous populations of excitatory and inhibitory firing-rate neurons. We study the local bifurcations of their neural activity with an approach that is largely analytically tractable, and we numerically determine the global bifurcations. We find that for strong inhibition these networks give rise to very complex dynamics, caused by the formation of multiple branching solutions of the neural dynamics equations that emerge through spontaneous symmetry-breaking. This qualitative change of the neural dynamics is a finite-size effect of the network, that reveals qualitative and previously unexplored differences between mesoscopic cortical circuits and their mean-field approximation. The most important consequence of spontaneous symmetry-breaking is the ability of mesoscopic networks to regulate their degree of functional heterogeneity, which is thought to help reducing the detrimental effect of noise correlations on cortical information processing. PMID:27494737

Differential regulation of NMDA receptors by d-serine and glycine in mammalian spinal locomotor networks

PubMed Central

Acton, David

2017-01-01

Activation of N-methyl-d-aspartate receptors (NMDARs) requires the binding of a coagonist, either d-serine or glycine, in addition to glutamate. Changes in occupancy of the coagonist binding site are proposed to modulate neural networks including those controlling swimming in frog tadpoles. Here, we characterize regulation of the NMDAR coagonist binding site in mammalian spinal locomotor networks. Blockade of NMDARs by d(−)-2-amino-5-phosphonopentanoic acid (d-APV) or 5,7-dichlorokynurenic acid reduced the frequency and amplitude of pharmacologically induced locomotor-related activity recorded from the ventral roots of spinal-cord preparations from neonatal mice. Furthermore, d-APV abolished synchronous activity induced by blockade of inhibitory transmission. These results demonstrate an important role for NMDARs in murine locomotor networks. Bath-applied d-serine enhanced the frequency of locomotor-related but not disinhibited bursting, indicating that coagonist binding sites are saturated during the latter but not the former mode of activity. Depletion of endogenous d-serine by d-amino acid oxidase or the serine-racemase inhibitor erythro-β-hydroxy-l-aspartic acid (HOAsp) increased the frequency of locomotor-related activity, whereas application of l-serine to enhance endogenous d-serine synthesis reduced burst frequency, suggesting a requirement for d-serine at a subset of synapses onto inhibitory interneurons. Consistent with this, HOAsp was ineffective during disinhibited activity. Bath-applied glycine (1–100 µM) failed to alter locomotor-related activity, whereas ALX 5407, a selective inhibitor of glycine transporter-1 (GlyT1), enhanced burst frequency, supporting a role for GlyT1 in NMDAR regulation. Together these findings indicate activity-dependent and synapse-specific regulation of the coagonist binding site within spinal locomotor networks, illustrating the importance of NMDAR regulation in shaping motor output. NEW & NOTEWORTHY We provide evidence that NMDARs within murine spinal locomotor networks determine the frequency and amplitude of ongoing locomotor-related activity in vitro and that NMDARs are regulated by d-serine and glycine in a synapse-specific and activity-dependent manner. In addition, glycine transporter-1 is shown to be an important regulator of NMDARs during locomotor-related activity. These results show how excitatory transmission can be tuned to diversify the output repertoire of spinal locomotor networks in mammals. PMID:28202572

NO-producing compounds transform neuron responses to glutamate.

PubMed

D'yakonova, T L

2000-01-01

We have previously shown that NO increases the excitatory effects of glutamate and blocks the desensitization of neurons to glutamate in the brain of the common snail. The aim of the present work was to identify the possible effect of NO on inhibitory responses to glutamate in the neurons of this mollusk. Electrophysiological investigations were performed on three identified neurons. The results showed that glutamate (0.05-0.1 mM) initially induced hyperpolarization and blocked the spike activity of these neurons. Simultaneous exposure to glutamate and the NO donor nitroprusside or preincubation with an NO donor had the effect that cells again responded to glutamate with depolarization and excitation. The transformed excitatory response lasted several minutes and could be reproduced even after 24 h of washing. The NO synthase blocker monomethylarginine blocked the excitatory response to glutamate. Another agonist of glutamate receptors, N-methyl-D-aspartate (NMDA, 0.1-1 mM), initially had excitatory effects on these neurons; this effect was significantly enhanced after transformation of the response to glutamate by NO donors. The results obtained here show that NO is involved in transforming the inhibitory responses to glutamate to excitatory responses, and that this effect may be mediated by NMDA-type receptors.

Rhythmogenic neuronal networks, emergent leaders, and k-cores.

PubMed

Schwab, David J; Bruinsma, Robijn F; Feldman, Jack L; Levine, Alex J

2010-11-01

Neuronal network behavior results from a combination of the dynamics of individual neurons and the connectivity of the network that links them together. We study a simplified model, based on the proposal of Feldman and Del Negro (FDN) [Nat. Rev. Neurosci. 7, 232 (2006)], of the preBötzinger Complex, a small neuronal network that participates in the control of the mammalian breathing rhythm through periodic firing bursts. The dynamics of this randomly connected network of identical excitatory neurons differ from those of a uniformly connected one. Specifically, network connectivity determines the identity of emergent leader neurons that trigger the firing bursts. When neuronal desensitization is controlled by the number of input signals to the neurons (as proposed by FDN), the network's collective desensitization--required for successful burst termination--is mediated by k-core clusters of neurons.

Retinal co-mediator acetylcholine evokes muscarinic inhibition of recurrent excitation in frog tectum column.

PubMed

Baginskas, Armantas; Kuras, Antanas

2016-08-26

Acetylcholine receptors contribute to the control of neuronal and neuronal network activity from insects to humans. We have investigated the action of acetylcholine receptors in the optic tectum of Rana temporaria (common frog). Our previous studies have demonstrated that acetylcholine activates presynaptic nicotinic receptors, when released into the frog optic tectum as a co-mediator during firing of a single retinal ganglion cell, and causes: a) potentiation of retinotectal synaptic transmission, and b) facilitation of transition of the tectum column to a higher level of activity. In the present study we have shown that endogenous acetylcholine also activates muscarinic receptors, leading to a delayed inhibition of recurrent excitatory synaptic transmission in the tectum column. The delay of muscarinic inhibition was evaluated to be of ∼80ms, with an extent of inhibition of ∼2 times. The inhibition of the recurrent excitation determines transition of the tectum column back to its resting state, giving a functional sense for the inhibition. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Involvement of Mossy Cells in Sharp Wave-Ripple Activity In Vitro.

PubMed

Swaminathan, Aarti; Wichert, Ines; Schmitz, Dietmar; Maier, Nikolaus

2018-05-29

The role of mossy cells (MCs) of the hippocampal dentate area has long remained mysterious. Recent research has begun to unveil their significance in spatial computation of the hippocampus. Here, we used an in vitro model of sharp wave-ripple complexes (SWRs), which contribute to hippocampal memory formation, to investigate MC involvement in this fundamental population activity. We find that a significant fraction of MCs (∼47%) is recruited into the active neuronal network during SWRs in the CA3 area. Moreover, MCs receive pronounced, ripple-coherent, excitatory and inhibitory synaptic input. Finally, we find evidence for SWR-related synaptic activity in granule cells that is mediated by MCs. Given the widespread connectivity of MCs within and between hippocampi, our data suggest a role for MCs as a hub functionally coupling the CA3 and the DG during ripple-associated computations. Copyright © 2018 The Author(s). Published by Elsevier Inc. All rights reserved.

Regulation of Cerebral Cortical Size and Neuron Number by Fibroblast Growth Factors: Implications for Autism

ERIC Educational Resources Information Center

Vaccarino, Flora M.; Grigorenko, Elena L.; Smith, Karen Muller; Stevens, Hanna E.

2009-01-01

Increased brain size is common in children with autism spectrum disorders. Here we propose that an increased number of cortical excitatory neurons may underlie the increased brain volume, minicolumn pathology and excessive network excitability, leading to sensory hyper-reactivity and seizures, which are often found in autism. We suggest that…

Ex vivo dissection of optogenetically activated mPFC and hippocampal inputs to neurons in the basolateral amygdala: implications for fear and emotional memory

PubMed Central

Hübner, Cora; Bosch, Daniel; Gall, Andrea; Lüthi, Andreas; Ehrlich, Ingrid

2014-01-01

Many lines of evidence suggest that a reciprocally interconnected network comprising the amygdala, ventral hippocampus (vHC), and medial prefrontal cortex (mPFC) participates in different aspects of the acquisition and extinction of conditioned fear responses and fear behavior. This could at least in part be mediated by direct connections from mPFC or vHC to amygdala to control amygdala activity and output. However, currently the interactions between mPFC and vHC afferents and their specific targets in the amygdala are still poorly understood. Here, we use an ex-vivo optogenetic approach to dissect synaptic properties of inputs from mPFC and vHC to defined neuronal populations in the basal amygdala (BA), the area that we identify as a major target of these projections. We find that BA principal neurons (PNs) and local BA interneurons (INs) receive monosynaptic excitatory inputs from mPFC and vHC. In addition, both these inputs also recruit GABAergic feedforward inhibition in a substantial fraction of PNs, in some neurons this also comprises a slow GABAB-component. Amongst the innervated PNs we identify neurons that project back to subregions of the mPFC, indicating a loop between neurons in mPFC and BA, and a pathway from vHC to mPFC via BA. Interestingly, mPFC inputs also recruit feedforward inhibition in a fraction of INs, suggesting that these inputs can activate dis-inhibitory circuits in the BA. A general feature of both mPFC and vHC inputs to local INs is that excitatory inputs display faster rise and decay kinetics than in PNs, which would enable temporally precise signaling. However, mPFC and vHC inputs to both PNs and INs differ in their presynaptic release properties, in that vHC inputs are more depressing. In summary, our data describe novel wiring, and features of synaptic connections from mPFC and vHC to amygdala that could help to interpret functions of these interconnected brain areas at the network level. PMID:24634648

Spatial features of synaptic adaptation affecting learning performance.

PubMed

Berger, Damian L; de Arcangelis, Lucilla; Herrmann, Hans J

2017-09-08

Recent studies have proposed that the diffusion of messenger molecules, such as monoamines, can mediate the plastic adaptation of synapses in supervised learning of neural networks. Based on these findings we developed a model for neural learning, where the signal for plastic adaptation is assumed to propagate through the extracellular space. We investigate the conditions allowing learning of Boolean rules in a neural network. Even fully excitatory networks show very good learning performances. Moreover, the investigation of the plastic adaptation features optimizing the performance suggests that learning is very sensitive to the extent of the plastic adaptation and the spatial range of synaptic connections.

Mechanisms of Seizure Propagation in 2-Dimensional Centre-Surround Recurrent Networks

PubMed Central

Hall, David; Kuhlmann, Levin

2013-01-01

Understanding how seizures spread throughout the brain is an important problem in the treatment of epilepsy, especially for implantable devices that aim to avert focal seizures before they spread to, and overwhelm, the rest of the brain. This paper presents an analysis of the speed of propagation in a computational model of seizure-like activity in a 2-dimensional recurrent network of integrate-and-fire neurons containing both excitatory and inhibitory populations and having a difference of Gaussians connectivity structure, an approximation to that observed in cerebral cortex. In the same computational model network, alternative mechanisms are explored in order to simulate the range of seizure-like activity propagation speeds (0.1–100 mm/s) observed in two animal-slice-based models of epilepsy: (1) low extracellular , which creates excess excitation and (2) introduction of gamma-aminobutyric acid (GABA) antagonists, which reduce inhibition. Moreover, two alternative connection topologies are considered: excitation broader than inhibition, and inhibition broader than excitation. It was found that the empirically observed range of propagation velocities can be obtained for both connection topologies. For the case of the GABA antagonist model simulation, consistent with other studies, it was found that there is an effective threshold in the degree of inhibition below which waves begin to propagate. For the case of the low extracellular model simulation, it was found that activity-dependent reductions in inhibition provide a potential explanation for the emergence of slowly propagating waves. This was simulated as a depression of inhibitory synapses, but it may also be achieved by other mechanisms. This work provides a localised network understanding of the propagation of seizures in 2-dimensional centre-surround networks that can be tested empirically. PMID:23967201

Menin: A Tumor Suppressor That Mediates Postsynaptic Receptor Expression and Synaptogenesis between Central Neurons of Lymnaea stagnalis

PubMed Central

Flynn, Nichole; Getz, Angela; Visser, Frank; Janes, Tara A.; Syed, Naweed I.

2014-01-01

Neurotrophic factors (NTFs) support neuronal survival, differentiation, and even synaptic plasticity both during development and throughout the life of an organism. However, their precise roles in central synapse formation remain unknown. Previously, we demonstrated that excitatory synapse formation in Lymnaea stagnalis requires a source of extrinsic NTFs and receptor tyrosine kinase (RTK) activation. Here we show that NTFs such as Lymnaea epidermal growth factor (L-EGF) act through RTKs to trigger a specific subset of intracellular signalling events in the postsynaptic neuron, which lead to the activation of the tumor suppressor menin, encoded by Lymnaea MEN1 (L-MEN1) and the expression of excitatory nicotinic acetylcholine receptors (nAChRs). We provide direct evidence that the activation of the MAPK/ERK cascade is required for the expression of nAChRs, and subsequent synapse formation between pairs of neurons in vitro. Furthermore, we show that L-menin activation is sufficient for the expression of postsynaptic excitatory nAChRs and subsequent synapse formation in media devoid of NTFs. By extending our findings in situ, we reveal the necessity of EGFRs in mediating synapse formation between a single transplanted neuron and its intact presynaptic partner. Moreover, deficits in excitatory synapse formation following EGFR knock-down can be rescued by injecting synthetic L-MEN1 mRNA in the intact central nervous system. Taken together, this study provides the first direct evidence that NTFs functioning via RTKs activate the MEN1 gene, which appears sufficient to regulate synapse formation between central neurons. Our study also offers a novel developmental role for menin beyond tumour suppression in adult humans. PMID:25347295

Neuroligin-1 overexpression in newborn granule cells in vivo.

PubMed

Schnell, Eric; Bensen, Aesoon L; Washburn, Eric K; Westbrook, Gary L

2012-01-01

Adult-born dentate granule cells integrate into the hippocampal network, extend neurites and form synapses in otherwise mature tissue. Excitatory and inhibitory inputs innervate these new granule cells in a stereotyped, temporally segregated manner, which presents a unique opportunity to study synapse development in the adult brain. To examine the role of neuroligins as synapse-inducing molecules in vivo, we infected dividing neural precursors in adult mice with a retroviral construct that increased neuroligin-1 levels during granule cell differentiation. By 21 days post-mitosis, exogenous neuroligin-1 was expressed at the tips of dendritic spines and increased the number of dendritic spines. Neuroligin-1-overexpressing cells showed a selective increase in functional excitatory synapses and connection multiplicity by single afferent fibers, as well as an increase in the synaptic AMPA/NMDA receptor ratio. In contrast to its synapse-inducing ability in vitro, neuroligin-1 overexpression did not induce precocious synapse formation in adult-born neurons. However, the dendrites of neuroligin-1-overexpressing cells did have more thin protrusions during an early period of dendritic outgrowth, suggesting enhanced filopodium formation or stabilization. Our results indicate that neuroligin-1 expression selectively increases the degree, but not the onset, of excitatory synapse formation in adult-born neurons.

Fine and distributed subcellular retinotopy of excitatory inputs to the dendritic tree of a collision-detecting neuron

PubMed Central

Zhu, Ying

2016-01-01

Individual neurons in several sensory systems receive synaptic inputs organized according to subcellular topographic maps, yet the fine structure of this topographic organization and its relation to dendritic morphology have not been studied in detail. Subcellular topography is expected to play a role in dendritic integration, particularly when dendrites are extended and active. The lobula giant movement detector (LGMD) neuron in the locust visual system is known to receive topographic excitatory inputs on part of its dendritic tree. The LGMD responds preferentially to objects approaching on a collision course and is thought to implement several interesting dendritic computations. To study the fine retinotopic mapping of visual inputs onto the excitatory dendrites of the LGMD, we designed a custom microscope allowing visual stimulation at the native sampling resolution of the locust compound eye while simultaneously performing two-photon calcium imaging on excitatory dendrites. We show that the LGMD receives a distributed, fine retinotopic projection from the eye facets and that adjacent facets activate overlapping portions of the same dendritic branches. We also demonstrate that adjacent retinal inputs most likely make independent synapses on the excitatory dendrites of the LGMD. Finally, we show that the fine topographic mapping can be studied using dynamic visual stimuli. Our results reveal the detailed structure of the dendritic input originating from individual facets on the eye and their relation to that of adjacent facets. The mapping of visual space onto the LGMD's dendrites is expected to have implications for dendritic computation. PMID:27009157

Synaptic control of the shape of the motoneuron pool input-output function

PubMed Central

Heckman, Charles J.

2017-01-01

Although motoneurons have often been considered to be fairly linear transducers of synaptic input, recent evidence suggests that strong persistent inward currents (PICs) in motoneurons allow neuromodulatory and inhibitory synaptic inputs to induce large nonlinearities in the relation between the level of excitatory input and motor output. To try to estimate the possible extent of this nonlinearity, we developed a pool of model motoneurons designed to replicate the characteristics of motoneuron input-output properties measured in medial gastrocnemius motoneurons in the decerebrate cat with voltage-clamp and current-clamp techniques. We drove the model pool with a range of synaptic inputs consisting of various mixtures of excitation, inhibition, and neuromodulation. We then looked at the relation between excitatory drive and total pool output. Our results revealed that the PICs not only enhance gain but also induce a strong nonlinearity in the relation between the average firing rate of the motoneuron pool and the level of excitatory input. The relation between the total simulated force output and input was somewhat more linear because of higher force outputs in later-recruited units. We also found that the nonlinearity can be increased by increasing neuromodulatory input and/or balanced inhibitory input and minimized by a reciprocal, push-pull pattern of inhibition. We consider the possibility that a flexible input-output function may allow motor output to be tuned to match the widely varying demands of the normal motor repertoire. NEW & NOTEWORTHY Motoneuron activity is generally considered to reflect the level of excitatory drive. However, the activation of voltage-dependent intrinsic conductances can distort the relation between excitatory drive and the total output of a pool of motoneurons. Using a pool of realistic motoneuron models, we show that pool output can be a highly nonlinear function of synaptic input but linearity can be achieved through adjusting the time course of excitatory and inhibitory synaptic inputs. PMID:28053245

Plasticity of spontaneous excitatory and inhibitory synaptic activity in morphologically defined vestibular nuclei neurons during early vestibular compensation

PubMed Central

Shao, Mei; Hirsch, June C.

2012-01-01

After unilateral peripheral vestibular lesions, the brain plasticity underlying early recovery from the static symptoms is not fully understood. Principal cells of the chick tangential nucleus offer a subset of morphologically defined vestibular nuclei neurons to study functional changes after vestibular lesions. Chickens show posture and balance deficits immediately after unilateral vestibular ganglionectomy (UVG), but by 3 days most subjects begin to recover, although some remain uncompensated. With the use of whole cell voltage-clamp, spontaneous excitatory and inhibitory postsynaptic currents (sEPSCs and sIPSCs) and miniature excitatory and inhibitory postsynaptic currents (mEPSCs and mIPSCs) were recorded from principal cells in brain slices 1 and 3 days after UVG. One day after UVG, sEPSC frequency increased on the lesion side and remained elevated at 3 days in uncompensated chickens only. Also by 3 days, sIPSC frequency increased on the lesion side in all operated chickens due to major increases in GABAergic events. Significant change also occurred in decay time of the events. To determine whether fluctuations in frequency and kinetics influenced overall excitatory or inhibitory synaptic drive, synaptic charge transfer was calculated. Principal cells showed significant increase in excitatory synaptic charge transfer only on the lesion side of uncompensated chickens. Thus compensation continues when synaptic charge transfer is in balance bilaterally. Furthermore, excessive excitatory drive in principal cells on the lesion side may prevent vestibular compensation. Altogether, this work is important for it defines the time course and excitatory and inhibitory nature of changing spontaneous synaptic inputs to a morphologically defined subset of vestibular nuclei neurons during critical early stages of recovery after UVG. PMID:21957228

Distinct retrosplenial cortex cell populations and their spike dynamics during ketamine-induced unconscious state

PubMed Central

Zhao, Fang; Tsien, Joe Z.

2017-01-01

Ketamine is known to induce psychotic-like symptoms, including delirium and visual hallucinations. It also causes neuronal damage and cell death in the retrosplenial cortex (RSC), an area that is thought to be a part of high visual cortical pathways and at least partially responsible for ketamine’s psychotomimetic activities. However, the basic physiological properties of RSC cells as well as their response to ketamine in vivo remained largely unexplored. Here, we combine a computational method, the Inter-Spike Interval Classification Analysis (ISICA), and in vivo recordings to uncover and profile excitatory cell subtypes within layers 2&3 and 5&6 of the RSC in mice within both conscious, sleep, and ketamine-induced unconscious states. We demonstrate two distinct excitatory principal cell sub-populations, namely, high-bursting excitatory principal cells and low-bursting excitatory principal cells, within layers 2&3, and show that this classification is robust over the conscious states, namely quiet awake, and natural unconscious sleep periods. Similarly, we provide evidence of high-bursting and low-bursting excitatory principal cell sub-populations within layers 5&6 that remained distinct during quiet awake and sleep states. We further examined how these subtypes are dynamically altered by ketamine. During ketamine-induced unconscious state, these distinct excitatory principal cell subtypes in both layer 2&3 and layer 5&6 exhibited distinct dynamics. We also uncovered different dynamics of local field potential under various brain states in layer 2&3 and layer 5&6. Interestingly, ketamine administration induced high gamma oscillations in layer 2&3 of the RSC, but not layer 5&6. Our results show that excitatory principal cells within RSC layers 2&3 and 5&6 contain multiple physiologically distinct sub-populations, and they are differentially affected by ketamine. PMID:29073221

Distinct retrosplenial cortex cell populations and their spike dynamics during ketamine-induced unconscious state.

PubMed

Fox, Grace E; Li, Meng; Zhao, Fang; Tsien, Joe Z

2017-01-01

Ketamine is known to induce psychotic-like symptoms, including delirium and visual hallucinations. It also causes neuronal damage and cell death in the retrosplenial cortex (RSC), an area that is thought to be a part of high visual cortical pathways and at least partially responsible for ketamine's psychotomimetic activities. However, the basic physiological properties of RSC cells as well as their response to ketamine in vivo remained largely unexplored. Here, we combine a computational method, the Inter-Spike Interval Classification Analysis (ISICA), and in vivo recordings to uncover and profile excitatory cell subtypes within layers 2&3 and 5&6 of the RSC in mice within both conscious, sleep, and ketamine-induced unconscious states. We demonstrate two distinct excitatory principal cell sub-populations, namely, high-bursting excitatory principal cells and low-bursting excitatory principal cells, within layers 2&3, and show that this classification is robust over the conscious states, namely quiet awake, and natural unconscious sleep periods. Similarly, we provide evidence of high-bursting and low-bursting excitatory principal cell sub-populations within layers 5&6 that remained distinct during quiet awake and sleep states. We further examined how these subtypes are dynamically altered by ketamine. During ketamine-induced unconscious state, these distinct excitatory principal cell subtypes in both layer 2&3 and layer 5&6 exhibited distinct dynamics. We also uncovered different dynamics of local field potential under various brain states in layer 2&3 and layer 5&6. Interestingly, ketamine administration induced high gamma oscillations in layer 2&3 of the RSC, but not layer 5&6. Our results show that excitatory principal cells within RSC layers 2&3 and 5&6 contain multiple physiologically distinct sub-populations, and they are differentially affected by ketamine.

Structural-Functional Properties of Identified Excitatory and Inhibitory Interneurons within Pre-Bötzinger Complex Respiratory Microcircuits

PubMed Central

Koizumi, Hidehiko; Koshiya, Naohiro; Chia, Justine X.; Cao, Fang; Nugent, Joseph; Zhang, Ruli

2013-01-01

We comparatively analyzed cellular and circuit properties of identified rhythmic excitatory and inhibitory interneurons within respiratory microcircuits of the neonatal rodent pre-Bötzinger complex (pre-BötC), the structure generating inspiratory rhythm in the brainstem. We combined high-resolution structural–functional imaging, molecular assays for neurotransmitter phenotype identification in conjunction with electrophysiological property phenotyping, and morphological reconstruction of interneurons in neonatal rat and mouse slices in vitro. This approach revealed previously undifferentiated structural–functional features that distinguish excitatory and inhibitory interneuronal populations. We identified distinct subpopulations of pre-BötC glutamatergic, glycinergic, GABAergic, and glycine-GABA coexpressing interneurons. Most commissural pre-BötC inspiratory interneurons were glutamatergic, with a substantial subset exhibiting intrinsic oscillatory bursting properties. Commissural excitatory interneurons projected with nearly planar trajectories to the contralateral pre-BötC, many also with axon collaterals to areas containing inspiratory hypoglossal (XII) premotoneurons and motoneurons. Inhibitory neurons as characterized in the present study did not exhibit intrinsic oscillatory bursting properties, but were electrophysiologically distinguished by more pronounced spike frequency adaptation properties. Axons of many inhibitory neurons projected ipsilaterally also to regions containing inspiratory XII premotoneurons and motoneurons, whereas a minority of inhibitory neurons had commissural axonal projections. Dendrites of both excitatory and inhibitory interneurons were arborized asymmetrically, primarily in the coronal plane. The dendritic fields of inhibitory neurons were more spatially compact than those of excitatory interneurons. Our results are consistent with the concepts of a compartmental circuit organization, a bilaterally coupled excitatory rhythmogenic kernel, and a role of pre-BötC inhibitory neurons in shaping inspiratory pattern as well as coordinating inspiratory and expiratory activity. PMID:23407957

Functional evidence for a direct excitatory projection from the lateral habenula to the ventral tegmental area in the rat

PubMed Central

Shepard, Paul D.

2016-01-01

The lateral habenula, a phylogenetically conserved epithalamic structure, is activated by aversive stimuli and reward omission. Excitatory efferents from the lateral habenula predominately inhibit midbrain dopamine neuronal firing through a disynaptic, feedforward inhibitory mechanism involving the rostromedial tegmental nucleus. However, the lateral habenula also directly targets dopamine neurons within the ventral tegmental area, suggesting that opposing actions may result from increased lateral habenula activity. In the present study, we tested the effect of habenular efferent stimulation on dopamine and nondopamine neurons in the ventral tegmental area of Sprague-Dawley rats using a parasagittal brain slice preparation. Single pulse stimulation of the fasciculus retroflexus excited 48% of dopamine neurons and 51% of nondopamine neurons in the ventral tegmental area of rat pups. These proportions were not altered by excision of the rostromedial tegmental nucleus and were evident in both cortical- and striatal-projecting dopamine neurons. Glutamate receptor antagonists blocked this excitation, and fasciculus retroflexus stimulation elicited evoked excitatory postsynaptic potentials with a nearly constant onset latency, indicative of a monosynaptic, glutamatergic connection. Comparison of responses in rat pups and young adults showed no significant difference in the proportion of neurons excited by fasciculus retroflexus stimulation. Our data indicate that the well-known, indirect inhibitory effect of lateral habenula activation on midbrain dopamine neurons is complemented by a significant, direct excitatory effect. This pathway may contribute to the role of midbrain dopamine neurons in processing aversive stimuli and salience. PMID:27358317

Functional evidence for a direct excitatory projection from the lateral habenula to the ventral tegmental area in the rat.

PubMed

Brown, P Leon; Shepard, Paul D

2016-09-01

The lateral habenula, a phylogenetically conserved epithalamic structure, is activated by aversive stimuli and reward omission. Excitatory efferents from the lateral habenula predominately inhibit midbrain dopamine neuronal firing through a disynaptic, feedforward inhibitory mechanism involving the rostromedial tegmental nucleus. However, the lateral habenula also directly targets dopamine neurons within the ventral tegmental area, suggesting that opposing actions may result from increased lateral habenula activity. In the present study, we tested the effect of habenular efferent stimulation on dopamine and nondopamine neurons in the ventral tegmental area of Sprague-Dawley rats using a parasagittal brain slice preparation. Single pulse stimulation of the fasciculus retroflexus excited 48% of dopamine neurons and 51% of nondopamine neurons in the ventral tegmental area of rat pups. These proportions were not altered by excision of the rostromedial tegmental nucleus and were evident in both cortical- and striatal-projecting dopamine neurons. Glutamate receptor antagonists blocked this excitation, and fasciculus retroflexus stimulation elicited evoked excitatory postsynaptic potentials with a nearly constant onset latency, indicative of a monosynaptic, glutamatergic connection. Comparison of responses in rat pups and young adults showed no significant difference in the proportion of neurons excited by fasciculus retroflexus stimulation. Our data indicate that the well-known, indirect inhibitory effect of lateral habenula activation on midbrain dopamine neurons is complemented by a significant, direct excitatory effect. This pathway may contribute to the role of midbrain dopamine neurons in processing aversive stimuli and salience. Copyright © 2016 the American Physiological Society.

Self-Consistent Scheme for Spike-Train Power Spectra in Heterogeneous Sparse Networks

PubMed Central

Pena, Rodrigo F. O.; Vellmer, Sebastian; Bernardi, Davide; Roque, Antonio C.; Lindner, Benjamin

2018-01-01

Recurrent networks of spiking neurons can be in an asynchronous state characterized by low or absent cross-correlations and spike statistics which resemble those of cortical neurons. Although spatial correlations are negligible in this state, neurons can show pronounced temporal correlations in their spike trains that can be quantified by the autocorrelation function or the spike-train power spectrum. Depending on cellular and network parameters, correlations display diverse patterns (ranging from simple refractory-period effects and stochastic oscillations to slow fluctuations) and it is generally not well-understood how these dependencies come about. Previous work has explored how the single-cell correlations in a homogeneous network (excitatory and inhibitory integrate-and-fire neurons with nearly balanced mean recurrent input) can be determined numerically from an iterative single-neuron simulation. Such a scheme is based on the fact that every neuron is driven by the network noise (i.e., the input currents from all its presynaptic partners) but also contributes to the network noise, leading to a self-consistency condition for the input and output spectra. Here we first extend this scheme to homogeneous networks with strong recurrent inhibition and a synaptic filter, in which instabilities of the previous scheme are avoided by an averaging procedure. We then extend the scheme to heterogeneous networks in which (i) different neural subpopulations (e.g., excitatory and inhibitory neurons) have different cellular or connectivity parameters; (ii) the number and strength of the input connections are random (Erdős-Rényi topology) and thus different among neurons. In all heterogeneous cases, neurons are lumped in different classes each of which is represented by a single neuron in the iterative scheme; in addition, we make a Gaussian approximation of the input current to the neuron. These approximations seem to be justified over a broad range of parameters as indicated by comparison with simulation results of large recurrent networks. Our method can help to elucidate how network heterogeneity shapes the asynchronous state in recurrent neural networks. PMID:29551968

Spinal Hb9::Cre-derived excitatory interneurons contribute to rhythm generation in the mouse

PubMed Central

Caldeira, Vanessa; Dougherty, Kimberly J.; Borgius, Lotta; Kiehn, Ole

2017-01-01

Rhythm generating neurons are thought to be ipsilaterally-projecting excitatory neurons in the thoracolumbar mammalian spinal cord. Recently, a subset of Shox2 interneurons (Shox2 non-V2a INs) was found to fulfill these criteria and make up a fraction of the rhythm-generating population. Here we use Hb9::Cre mice to genetically manipulate Hb9::Cre-derived excitatory interneurons (INs) in order to determine the role of these INs in rhythm generation. We demonstrate that this line captures a consistent population of spinal INs which is mixed with respect to neurotransmitter phenotype and progenitor domain, but does not overlap with the Shox2 non-V2a population. We also show that Hb9::Cre-derived INs include the comparatively small medial population of INs which continues to express Hb9 postnatally. When excitatory neurotransmission is selectively blocked by deleting Vglut2 from Hb9::Cre-derived INs, there is no difference in left-right and/or flexor-extensor phasing between these cords and controls, suggesting that excitatory Hb9::Cre-derived INs do not affect pattern generation. In contrast, the frequencies of locomotor activity are significantly lower in cords from Hb9::Cre-Vglut2Δ/Δ mice than in cords from controls. Collectively, our findings indicate that excitatory Hb9::Cre-derived INs constitute a distinct population of neurons that participates in the rhythm generating kernel for spinal locomotion. PMID:28128321

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.

Low-noise encoding of active touch by layer 4 in the somatosensory cortex.

PubMed

Hires, Samuel Andrew; Gutnisky, Diego A; Yu, Jianing; O'Connor, Daniel H; Svoboda, Karel

2015-08-06

Cortical spike trains often appear noisy, with the timing and number of spikes varying across repetitions of stimuli. Spiking variability can arise from internal (behavioral state, unreliable neurons, or chaotic dynamics in neural circuits) and external (uncontrolled behavior or sensory stimuli) sources. The amount of irreducible internal noise in spike trains, an important constraint on models of cortical networks, has been difficult to estimate, since behavior and brain state must be precisely controlled or tracked. We recorded from excitatory barrel cortex neurons in layer 4 during active behavior, where mice control tactile input through learned whisker movements. Touch was the dominant sensorimotor feature, with >70% spikes occurring in millisecond timescale epochs after touch onset. The variance of touch responses was smaller than expected from Poisson processes, often reaching the theoretical minimum. Layer 4 spike trains thus reflect the millisecond-timescale structure of tactile input with little noise.

Pyramidal cell-interneuron interactions underlie hippocampal ripple oscillations.

PubMed

Stark, Eran; Roux, Lisa; Eichler, Ronny; Senzai, Yuta; Royer, Sebastien; Buzsáki, György

2014-07-16

High-frequency ripple oscillations, observed most prominently in the hippocampal CA1 pyramidal layer, are associated with memory consolidation. The cellular and network mechanisms underlying the generation, frequency control, and spatial coherence of the rhythm are poorly understood. Using multisite optogenetic manipulations in freely behaving rodents, we found that depolarization of a small group of nearby pyramidal cells was sufficient to induce high-frequency oscillations, whereas closed-loop silencing of pyramidal cells or activation of parvalbumin- (PV) or somatostatin-immunoreactive interneurons aborted spontaneously occurring ripples. Focal pharmacological blockade of GABAA receptors abolished ripples. Localized PV interneuron activation paced ensemble spiking, and simultaneous induction of high-frequency oscillations at multiple locations resulted in a temporally coherent pattern mediated by phase-locked interneuron spiking. These results constrain competing models of ripple generation and indicate that temporally precise local interactions between excitatory and inhibitory neurons support ripple generation in the intact hippocampus. Copyright © 2014 Elsevier Inc. All rights reserved.

Pyramidal Cell-Interneuron Interactions Underlie Hippocampal Ripple Oscillations

PubMed Central

Stark, Eran; Roux, Lisa; Eichler, Ronny; Senzai, Yuta; Royer, Sebastien; Buzsáki, György

2015-01-01

SUMMARY High-frequency ripple oscillations, observed most prominently in the hippocampal CA1 pyramidal layer, are associated with memory consolidation. The cellular and network mechanisms underlying the generation, frequency control, and spatial coherence of the rhythm are poorly understood. Using multisite optogenetic manipulations in freely behaving rodents, we found that depolarization of a small group of nearby pyramidal cells was sufficient to induce high-frequency oscillations, whereas closed-loop silencing of pyramidal cells or activation of parvalbumin-(PV) or somatostatin-immunoreactive interneurons aborted spontaneously occurring ripples. Focal pharmacological blockade of GABAA receptors abolished ripples. Localized PV inter-neuron activation paced ensemble spiking, and simultaneous induction of high-frequency oscillations at multiple locations resulted in a temporally coherent pattern mediated by phase-locked inter-neuron spiking. These results constrain competing models of ripple generation and indicate that temporally precise local interactions between excitatory and inhibitory neurons support ripple generation in the intact hippocampus. PMID:25033186

Modulation of excitatory amino acids pathway: a possible therapeutic approach to chronic daily headache associated with analgesic drugs abuse.

PubMed

Nicolodi, M; Del Bianco, P L; Sicuteri, F

1997-01-01

The use of antagonists of N-methyl-D-aspartate (NMDA) receptors, or the administration of inhibitors of the synthesis or of the release of excitatory amino acids, enables the analgesic drug-dependence associated with chronic daily migraine to be overcome without any physical abstinence sign. Follow-up period indicates that negative modulators of excitatory amino-acid function can induce a stable benefit. The persistent benefit is seemingly due to an inhibitory effect on the process underlying the hyperalgesia state which is a crucial feature of migraine. It can also be suggested that the antagonist activity at NMDA receptor might play a role in very severe non-opioid analgesic drug dependence.

The extended fronto-striatal model of obsessive compulsive disorder: convergence from event-related potentials, neuropsychology and neuroimaging

PubMed Central

Melloni, Margherita; Urbistondo, Claudia; Sedeño, Lucas; Gelormini, Carlos; Kichic, Rafael; Ibanez, Agustin

2012-01-01

In this work, we explored convergent evidence supporting the fronto-striatal model of obsessive-compulsive disorder (FSMOCD) and the contribution of event-related potential (ERP) studies to this model. First, we considered minor modifications to the FSMOCD model based on neuroimaging and neuropsychological data. We noted the brain areas most affected in this disorder -anterior cingulate cortex (ACC), basal ganglia (BG), and orbito-frontal cortex (OFC) and their related cognitive functions, such as monitoring and inhibition. Then, we assessed the ERPs that are directly related to the FSMOCD, including the error-related negativity (ERN), N200, and P600. Several OCD studies present enhanced ERN and N2 responses during conflict tasks as well as an enhanced P600 during working memory (WM) tasks. Evidence from ERP studies (especially regarding ERN and N200 amplitude enhancement), neuroimaging and neuropsychological findings suggests abnormal activity in the OFC, ACC, and BG in OCD patients. Moreover, additional findings from these analyses suggest dorsolateral prefrontal and parietal cortex involvement, which might be related to executive function (EF) deficits. Thus, these convergent results suggest the existence of a self-monitoring imbalance involving inhibitory deficits and executive dysfunctions. OCD patients present an impaired ability to monitor, control, and inhibit intrusive thoughts, urges, feelings, and behaviors. In the current model, this imbalance is triggered by an excitatory role of the BG (associated with cognitive or motor actions without volitional control) and inhibitory activity of the OFC as well as excessive monitoring of the ACC to block excitatory impulses. This imbalance would interact with the reduced activation of the parietal-DLPC network, leading to executive dysfunction. ERP research may provide further insight regarding the temporal dynamics of action monitoring and executive functioning in OCD. PMID:23015786

Nutritional State-Dependent Ghrelin Activation of Vasopressin Neurons via Retrograde Trans-Neuronal–Glial Stimulation of Excitatory GABA Circuits

PubMed Central

Haam, Juhee; Halmos, Katalin C.; Di, Shi

2014-01-01

Behavioral and physiological coupling between energy balance and fluid homeostasis is critical for survival. The orexigenic hormone ghrelin has been shown to stimulate the secretion of the osmoregulatory hormone vasopressin (VP), linking nutritional status to the control of blood osmolality, although the mechanism of this systemic crosstalk is unknown. Here, we show using electrophysiological recordings and calcium imaging in rat brain slices that ghrelin stimulates VP neurons in the hypothalamic paraventricular nucleus (PVN) in a nutritional state-dependent manner by activating an excitatory GABAergic synaptic input via a retrograde neuronal–glial circuit. In slices from fasted rats, ghrelin activation of a postsynaptic ghrelin receptor, the growth hormone secretagogue receptor type 1a (GHS-R1a), in VP neurons caused the dendritic release of VP, which stimulated astrocytes to release the gliotransmitter adenosine triphosphate (ATP). ATP activation of P2X receptors excited presynaptic GABA neurons to increase GABA release, which was excitatory to the VP neurons. This trans-neuronal–glial retrograde circuit activated by ghrelin provides an alternative means of stimulation of VP release and represents a novel mechanism of neuronal control by local neuronal–glial circuits. It also provides a potential cellular mechanism for the physiological integration of energy and fluid homeostasis. PMID:24790191

Evx1 and Evx2 specify excitatory neurotransmitter fates and suppress inhibitory fates through a Pax2-independent mechanism.

PubMed

Juárez-Morales, José L; Schulte, Claus J; Pezoa, Sofia A; Vallejo, Grace K; Hilinski, William C; England, Samantha J; de Jager, Sarah; Lewis, Katharine E

2016-02-19

For neurons to function correctly in neuronal circuitry they must utilize appropriate neurotransmitters. However, even though neurotransmitter specificity is one of the most important and defining properties of a neuron we still do not fully understand how neurotransmitter fates are specified during development. Most neuronal properties are determined by the transcription factors that neurons express as they start to differentiate. While we know a few transcription factors that specify the neurotransmitter fates of particular neurons, there are still many spinal neurons for which the transcription factors specifying this critical phenotype are unknown. Strikingly, all of the transcription factors that have been identified so far as specifying inhibitory fates in the spinal cord act through Pax2. Even Tlx1 and Tlx3, which specify the excitatory fates of dI3 and dI5 spinal neurons work at least in part by down-regulating Pax2. In this paper we use single and double mutant zebrafish embryos to identify the spinal cord functions of Evx1 and Evx2. We demonstrate that Evx1 and Evx2 are expressed by spinal cord V0v cells and we show that these cells develop into excitatory (glutamatergic) Commissural Ascending (CoSA) interneurons. In the absence of both Evx1 and Evx2, V0v cells still form and develop a CoSA morphology. However, they lose their excitatory fate and instead express markers of a glycinergic fate. Interestingly, they do not express Pax2, suggesting that they are acquiring their inhibitory fate through a novel Pax2-independent mechanism. Evx1 and Evx2 are required, partially redundantly, for spinal cord V0v cells to become excitatory (glutamatergic) interneurons. These results significantly increase our understanding of the mechanisms of neuronal specification and the genetic networks involved in these processes.

Phase-locked cluster oscillations in periodically forced integrate-and-fire-or-burst neuronal populations.

PubMed

Langdon, Angela J; Breakspear, Michael; Coombes, Stephen

2012-12-01

The minimal integrate-and-fire-or-burst neuron model succinctly describes both tonic firing and postinhibitory rebound bursting of thalamocortical cells in the sensory relay. Networks of integrate-and-fire-or-burst (IFB) neurons with slow inhibitory synaptic interactions have been shown to support stable rhythmic states, including globally synchronous and cluster oscillations, in which network-mediated inhibition cyclically generates bursting in coherent subgroups of neurons. In this paper, we introduce a reduced IFB neuronal population model to study synchronization of inhibition-mediated oscillatory bursting states to periodic excitatory input. Using numeric methods, we demonstrate the existence and stability of 1:1 phase-locked bursting oscillations in the sinusoidally forced IFB neuronal population model. Phase locking is shown to arise when periodic excitation is sufficient to pace the onset of bursting in an IFB cluster without counteracting the inhibitory interactions necessary for burst generation. Phase-locked bursting states are thus found to destabilize when periodic excitation increases in strength or frequency. Further study of the IFB neuronal population model with pulse-like periodic excitatory input illustrates that this synchronization mechanism generalizes to a broad range of n:m phase-locked bursting states across both globally synchronous and clustered oscillatory regimes.

Goal-seeking neural net for recall and recognition

NASA Astrophysics Data System (ADS)

Omidvar, Omid M.

1990-07-01

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

Differential Activation of Fast-Spiking and Regular-Firing Neuron Populations During Movement and Reward in the Dorsal Medial Frontal Cortex

PubMed Central

Insel, Nathan; Barnes, Carol A.

2015-01-01

The medial prefrontal cortex is thought to be important for guiding behavior according to an animal's expectations. Efforts to decode the region have focused not only on the question of what information it computes, but also how distinct circuit components become engaged during behavior. We find that the activity of regular-firing, putative projection neurons contains rich information about behavioral context and firing fields cluster around reward sites, while activity among putative inhibitory and fast-spiking neurons is most associated with movement and accompanying sensory stimulation. These dissociations were observed even between adjacent neurons with apparently reciprocal, inhibitory–excitatory connections. A smaller population of projection neurons with burst-firing patterns did not show clustered firing fields around rewards; these neurons, although heterogeneous, were generally less selective for behavioral context than regular-firing cells. The data suggest a network that tracks an animal's behavioral situation while, at the same time, regulating excitation levels to emphasize high valued positions. In this scenario, the function of fast-spiking inhibitory neurons is to constrain network output relative to incoming sensory flow. This scheme could serve as a bridge between abstract sensorimotor information and single-dimensional codes for value, providing a neural framework to generate expectations from behavioral state. PMID:24700585

A neuronal model of predictive coding accounting for the mismatch negativity.

PubMed

Wacongne, Catherine; Changeux, Jean-Pierre; Dehaene, Stanislas

2012-03-14

The mismatch negativity (MMN) is thought to index the activation of specialized neural networks for active prediction and deviance detection. However, a detailed neuronal model of the neurobiological mechanisms underlying the MMN is still lacking, and its computational foundations remain debated. We propose here a detailed neuronal model of auditory cortex, based on predictive coding, that accounts for the critical features of MMN. The model is entirely composed of spiking excitatory and inhibitory neurons interconnected in a layered cortical architecture with distinct input, predictive, and prediction error units. A spike-timing dependent learning rule, relying upon NMDA receptor synaptic transmission, allows the network to adjust its internal predictions and use a memory of the recent past inputs to anticipate on future stimuli based on transition statistics. We demonstrate that this simple architecture can account for the major empirical properties of the MMN. These include a frequency-dependent response to rare deviants, a response to unexpected repeats in alternating sequences (ABABAA…), a lack of consideration of the global sequence context, a response to sound omission, and a sensitivity of the MMN to NMDA receptor antagonists. Novel predictions are presented, and a new magnetoencephalography experiment in healthy human subjects is presented that validates our key hypothesis: the MMN results from active cortical prediction rather than passive synaptic habituation.

Intrinsic bursting of AII amacrine cells underlies oscillations in the rd1 mouse retina.

PubMed

Choi, Hannah; Zhang, Lei; Cembrowski, Mark S; Sabottke, Carl F; Markowitz, Alexander L; Butts, Daniel A; Kath, William L; Singer, Joshua H; Riecke, Hermann

2014-09-15

In many forms of retinal degeneration, photoreceptors die but inner retinal circuits remain intact. In the rd1 mouse, an established model for blinding retinal diseases, spontaneous activity in the coupled network of AII amacrine and ON cone bipolar cells leads to rhythmic bursting of ganglion cells. Since such activity could impair retinal and/or cortical responses to restored photoreceptor function, understanding its nature is important for developing treatments of retinal pathologies. Here we analyzed a compartmental model of the wild-type mouse AII amacrine cell to predict that the cell's intrinsic membrane properties, specifically, interacting fast Na and slow, M-type K conductances, would allow its membrane potential to oscillate when light-evoked excitatory synaptic inputs were withdrawn following photoreceptor degeneration. We tested and confirmed this hypothesis experimentally by recording from AIIs in a slice preparation of rd1 retina. Additionally, recordings from ganglion cells in a whole mount preparation of rd1 retina demonstrated that activity in AIIs was propagated unchanged to elicit bursts of action potentials in ganglion cells. We conclude that oscillations are not an emergent property of a degenerated retinal network. Rather, they arise largely from the intrinsic properties of a single retinal interneuron, the AII amacrine cell. Copyright © 2014 the American Physiological Society.

Towards a theory of cortical columns: From spiking neurons to interacting neural populations of finite size

PubMed Central

Gerstner, Wulfram

2017-01-01

Neural population equations such as neural mass or field models are widely used to study brain activity on a large scale. However, the relation of these models to the properties of single neurons is unclear. Here we derive an equation for several interacting populations at the mesoscopic scale starting from a microscopic model of randomly connected generalized integrate-and-fire neuron models. Each population consists of 50–2000 neurons of the same type but different populations account for different neuron types. The stochastic population equations that we find reveal how spike-history effects in single-neuron dynamics such as refractoriness and adaptation interact with finite-size fluctuations on the population level. Efficient integration of the stochastic mesoscopic equations reproduces the statistical behavior of the population activities obtained from microscopic simulations of a full spiking neural network model. The theory describes nonlinear emergent dynamics such as finite-size-induced stochastic transitions in multistable networks and synchronization in balanced networks of excitatory and inhibitory neurons. The mesoscopic equations are employed to rapidly integrate a model of a cortical microcircuit consisting of eight neuron types, which allows us to predict spontaneous population activities as well as evoked responses to thalamic input. Our theory establishes a general framework for modeling finite-size neural population dynamics based on single cell and synapse parameters and offers an efficient approach to analyzing cortical circuits and computations. PMID:28422957

Quantitative analysis of sex-pheromone coding in the antennal lobe of the moth Agrotis ipsilon: a tool to study network plasticity.

PubMed

Jarriault, David; Gadenne, Christophe; Rospars, Jean-Pierre; Anton, Sylvia

2009-04-01

To find a mating partner, moths rely on pheromone communication. Released in very low amounts, female sex pheromones are used by males to identify and localize females. Depending on the physiological state (i.e. age, reproductive state), the olfactory system of the males of the noctuid moth Agrotis ipsilon is 'switched on or off'. To understand the neural basis of this behavioural plasticity, we performed a detailed characterization of the qualitative, quantitative and temporal aspects of pheromone coding in the primary centre of integration of pheromonal information, the macroglomerular complex (MGC) of the antennal lobe. MGC neurons were intracellularly recorded and stained in sexually mature virgin males. When stimulating antennae of males with the three main components of the female pheromone blend, most of the neurons showed a biphasic excitatory-inhibitory response. Although they showed different preferences, 80% of the neurons responded at least to the main pheromone component (Z-7-dodecenyl acetate). Six stained neurons responding to this component had their dendrites in the largest MGC glomerulus. Changes in the stimulus intensity and duration affected the excitatory phase but not the inhibitory phase properties. The stimulus intensity was shown to be encoded in the firing frequency, the number of spikes and the latency of the excitatory phase, whereas the stimulus duration only changed its duration. We conclude that the inhibitory input provided by local interneurons following the excitatory phase might not contribute directly to the encoding of stimulus characteristics. The data presented will serve as a basis for comparison with those of immature and mated males.

The Ising Decision Maker: a binary stochastic network for choice response time.

PubMed

Verdonck, Stijn; Tuerlinckx, Francis

2014-07-01

The Ising Decision Maker (IDM) is a new formal model for speeded two-choice decision making derived from the stochastic Hopfield network or dynamic Ising model. On a microscopic level, it consists of 2 pools of binary stochastic neurons with pairwise interactions. Inside each pool, neurons excite each other, whereas between pools, neurons inhibit each other. The perceptual input is represented by an external excitatory field. Using methods from statistical mechanics, the high-dimensional network of neurons (microscopic level) is reduced to a two-dimensional stochastic process, describing the evolution of the mean neural activity per pool (macroscopic level). The IDM can be seen as an abstract, analytically tractable multiple attractor network model of information accumulation. In this article, the properties of the IDM are studied, the relations to existing models are discussed, and it is shown that the most important basic aspects of two-choice response time data can be reproduced. In addition, the IDM is shown to predict a variety of observed psychophysical relations such as Piéron's law, the van der Molen-Keuss effect, and Weber's law. Using Bayesian methods, the model is fitted to both simulated and real data, and its performance is compared to the Ratcliff diffusion model. (c) 2014 APA, all rights reserved.

Network models of frequency modulated sweep detection.

PubMed

Skorheim, Steven; Razak, Khaleel; Bazhenov, Maxim

2014-01-01

Frequency modulated (FM) sweeps are common in species-specific vocalizations, including human speech. Auditory neurons selective for the direction and rate of frequency change in FM sweeps are present across species, but the synaptic mechanisms underlying such selectivity are only beginning to be understood. Even less is known about mechanisms of experience-dependent changes in FM sweep selectivity. We present three network models of synaptic mechanisms of FM sweep direction and rate selectivity that explains experimental data: (1) The 'facilitation' model contains frequency selective cells operating as coincidence detectors, summing up multiple excitatory inputs with different time delays. (2) The 'duration tuned' model depends on interactions between delayed excitation and early inhibition. The strength of delayed excitation determines the preferred duration. Inhibitory rebound can reinforce the delayed excitation. (3) The 'inhibitory sideband' model uses frequency selective inputs to a network of excitatory and inhibitory cells. The strength and asymmetry of these connections results in neurons responsive to sweeps in a single direction of sufficient sweep rate. Variations of these properties, can explain the diversity of rate-dependent direction selectivity seen across species. We show that the inhibitory sideband model can be trained using spike timing dependent plasticity (STDP) to develop direction selectivity from a non-selective network. These models provide a means to compare the proposed synaptic and spectrotemporal mechanisms of FM sweep processing and can be utilized to explore cellular mechanisms underlying experience- or training-dependent changes in spectrotemporal processing across animal models. Given the analogy between FM sweeps and visual motion, these models can serve a broader function in studying stimulus movement across sensory epithelia.

A convergent and essential interneuron pathway for Mauthner-cell-mediated escapes.

PubMed

Lacoste, Alix M B; Schoppik, David; Robson, Drew N; Haesemeyer, Martin; Portugues, Ruben; Li, Jennifer M; Randlett, Owen; Wee, Caroline L; Engert, Florian; Schier, Alexander F

2015-06-01

The Mauthner cell (M-cell) is a command-like neuron in teleost fish whose firing in response to aversive stimuli is correlated with short-latency escapes [1-3]. M-cells have been proposed as evolutionary ancestors of startle response neurons of the mammalian reticular formation [4], and studies of this circuit have uncovered important principles in neurobiology that generalize to more complex vertebrate models [3]. The main excitatory input was thought to originate from multisensory afferents synapsing directly onto the M-cell dendrites [3]. Here, we describe an additional, convergent pathway that is essential for the M-cell-mediated startle behavior in larval zebrafish. It is composed of excitatory interneurons called spiral fiber neurons, which project to the M-cell axon hillock. By in vivo calcium imaging, we found that spiral fiber neurons are active in response to aversive stimuli capable of eliciting escapes. Like M-cell ablations, bilateral ablations of spiral fiber neurons largely eliminate short-latency escapes. Unilateral spiral fiber neuron ablations shift the directionality of escapes and indicate that spiral fiber neurons excite the M-cell in a lateralized manner. Their optogenetic activation increases the probability of short-latency escapes, supporting the notion that spiral fiber neurons help activate M-cell-mediated startle behavior. These results reveal that spiral fiber neurons are essential for the function of the M-cell in response to sensory cues and suggest that convergent excitatory inputs that differ in their input location and timing ensure reliable activation of the M-cell, a feedforward excitatory motif that may extend to other neural circuits. Copyright © 2015 Elsevier Ltd. All rights reserved.

Contribution of NMDA receptor hypofunction in prefrontal and cortical excitatory neurons to schizophrenia-like phenotypes.

PubMed

Rompala, Gregory R; Zsiros, Veronika; Zhang, Shuqin; Kolata, Stefan M; Nakazawa, Kazu

2013-01-01

Pharmacological and genetic studies support a role for NMDA receptor (NMDAR) hypofunction in the etiology of schizophrenia. We have previously demonstrated that NMDAR obligatory subunit 1 (GluN1) deletion in corticolimbic interneurons during early postnatal development is sufficient to confer schizophrenia-like phenotypes in mice. However, the consequence of NMDAR hypofunction in cortical excitatory neurons is not well delineated. Here, we characterize a conditional knockout mouse strain (CtxGluN1 KO mice), in which postnatal GluN1 deletion is largely confined to the excitatory neurons in layer II/III of the medial prefrontal cortex and sensory cortices, as evidenced by the lack of GluN1 mRNA expression in in situ hybridization immunocytochemistry as well as the lack of NMDA currents with in vitro recordings. Mutants were impaired in prepulse inhibition of the auditory startle reflex as well as object-based short-term memory. However, they did not exhibit impairments in additional hallmarks of schizophrenia-like phenotypes (e.g. spatial working memory, social behavior, saccharine preference, novelty and amphetamine-induced hyperlocomotion, and anxiety-related behavior). Furthermore, upon administration of the NMDA receptor antagonist, MK-801, there were no differences in locomotor activity versus controls. The mutant mice also showed negligible levels of reactive oxygen species production following chronic social isolation, and recording of miniature-EPSC/IPSCs from layer II/III excitatory neurons in medial prefrontal cortex suggested no alteration in GABAergic activity. All together, the mutant mice displayed cognitive deficits in the absence of additional behavioral or cellular phenotypes reflecting schizophrenia pathophysiology. Thus, NMDAR hypofunction in prefrontal and cortical excitatory neurons may recapitulate only a cognitive aspect of human schizophrenia symptoms.

Correction of respiratory disorders in a mouse model of Rett syndrome

PubMed Central

Abdala, Ana P. L.; Dutschmann, Mathias; Bissonnette, John M.; Paton, Julian F. R.

2010-01-01

Rett syndrome (RTT) is an autism spectrum disorder caused by mutations in the X-linked gene that encodes the transcription factor methyl-CpG-binding protein 2 (MeCP2). A major debilitating phenotype in affected females is frequent apneas, and heterozygous Mecp2-deficient female mice mimic the human respiratory disorder. GABA defects have been demonstrated in the brainstem of Mecp2-deficient mice. Here, using an intact respiratory network, we show that apnea in RTT mice is characterized by excessive excitatory activity in expiratory cranial and spinal nerves. Augmenting GABA markedly improves the respiratory phenotype. In addition, a serotonin 1a receptor agonist that depresses expiratory neuron activity also reduces apnea, corrects the irregular breathing pattern, and prolongs survival in MeCP2 null males. Combining a GABA reuptake blocker with a serotonin 1a agonist in heterozygous females completely corrects their respiratory defects. The results indicate that GABA and serotonin 1a receptor activity are candidates for treatment of the respiratory disorders in Rett syndrome. PMID:20921395

Linear summation of outputs in a balanced network model of motor cortex.

PubMed

Capaday, Charles; van Vreeswijk, Carl

2015-01-01

Given the non-linearities of the neural circuitry's elements, we would expect cortical circuits to respond non-linearly when activated. Surprisingly, when two points in the motor cortex are activated simultaneously, the EMG responses are the linear sum of the responses evoked by each of the points activated separately. Additionally, the corticospinal transfer function is close to linear, implying that the synaptic interactions in motor cortex must be effectively linear. To account for this, here we develop a model of motor cortex composed of multiple interconnected points, each comprised of reciprocally connected excitatory and inhibitory neurons. We show how non-linearities in neuronal transfer functions are eschewed by strong synaptic interactions within each point. Consequently, the simultaneous activation of multiple points results in a linear summation of their respective outputs. We also consider the effects of reduction of inhibition at a cortical point when one or more surrounding points are active. The network response in this condition is linear over an approximately two- to three-fold decrease of inhibitory feedback strength. This result supports the idea that focal disinhibition allows linear coupling of motor cortical points to generate movement related muscle activation patterns; albeit with a limitation on gain control. The model also explains why neural activity does not spread as far out as the axonal connectivity allows, whilst also explaining why distant cortical points can be, nonetheless, functionally coupled by focal disinhibition. Finally, we discuss the advantages that linear interactions at the cortical level afford to motor command synthesis.

Primary afferent activity, putative excitatory transmitters and extracellular potassium levels in frog spinal cord.

PubMed Central

Davidoff, R A; Hackman, J C; Holohean, A M; Vega, J L; Zhang, D X

1988-01-01

1. Changes in extracellular K+ activity were measured with ion-selective microelectrodes in the grey matter of the isolated hemisected frog spinal cord. The magnitude of the elevation of [K+]o (delta[K+]o) produced by repetitive stimulation (25 Hz, 10 s) of afferent fibres in the sciatic nerve was monotonically related to the strength of the electrical stimuli applied to the sciatic nerve. Repetitive stimulation of the largest diameter A alpha and A beta fibres, which were found histologically to comprise only 11% of the afferent axons in the dorsal root, elevated [K+]o to approximately 60% of the maximum level seen when all afferent fibres were stimulated. 2. Addition of Mg2+ (20 mM) to Ringer solution devoid of Mg2+ reduced delta[K+]o by over 85% suggesting that about 15% of delta[K+]o results from action potentials in presynaptic primary afferents. When 20 mM-Mg2+ was added to spinal cords bathed in Ringer solution containing a physiological (i.e. 1.0 mM) concentration of Mg2+, delta[K+]o was reduced by ca. 65-75% indicating that in spinal cords bathed in medium containing 'physiological' concentrations of Mg2+ about 25-35% of the K+ is released from primary afferent fibres. 3. Application of excitatory amino acids and agonists increased [K+]o with the following potency pattern: quisqualate greater than kainate greater than NMDA (N-methyl-D-aspartate) greater than glutamate greater than aspartate. 4. D(-)-2-Amino-5-phosphonovalerate (APV), an NMDA antagonist, reduced [K+]o by only about 50%, but kynurenate, an NMDA and non-NMDA antagonist, reduced [K+]o by approximately 85%; i.e. the same levels observed when synaptic transmission was blocked with 20 mM-Mg2+. These findings support the idea that synaptic release of excitatory amino acids such as L-glutamate and/or L-aspartate and subsequent activation of specific receptors by these putative transmitters are necessary for the postsynaptic component of delta[K+]o. 5. Addition of tachykinins elevated [K+]o but the effect appeared to require the participation of excitatory amino acids because it was blocked by APV and by kynurenate. 6. The finding that tetrodotoxin substantially reduced the ability of excitatory amino acid agonists and tachykinins to elevate [K+]o suggests that discharges in interneurones as a result of excitatory amino acid receptor activation are responsible for the postsynaptic component of delta[K+]o. PMID:3261795

Primary afferent activity, putative excitatory transmitters and extracellular potassium levels in frog spinal cord.

PubMed

Davidoff, R A; Hackman, J C; Holohean, A M; Vega, J L; Zhang, D X

1988-03-01

1. Changes in extracellular K+ activity were measured with ion-selective microelectrodes in the grey matter of the isolated hemisected frog spinal cord. The magnitude of the elevation of [K+]o (delta[K+]o) produced by repetitive stimulation (25 Hz, 10 s) of afferent fibres in the sciatic nerve was monotonically related to the strength of the electrical stimuli applied to the sciatic nerve. Repetitive stimulation of the largest diameter A alpha and A beta fibres, which were found histologically to comprise only 11% of the afferent axons in the dorsal root, elevated [K+]o to approximately 60% of the maximum level seen when all afferent fibres were stimulated. 2. Addition of Mg2+ (20 mM) to Ringer solution devoid of Mg2+ reduced delta[K+]o by over 85% suggesting that about 15% of delta[K+]o results from action potentials in presynaptic primary afferents. When 20 mM-Mg2+ was added to spinal cords bathed in Ringer solution containing a physiological (i.e. 1.0 mM) concentration of Mg2+, delta[K+]o was reduced by ca. 65-75% indicating that in spinal cords bathed in medium containing 'physiological' concentrations of Mg2+ about 25-35% of the K+ is released from primary afferent fibres. 3. Application of excitatory amino acids and agonists increased [K+]o with the following potency pattern: quisqualate greater than kainate greater than NMDA (N-methyl-D-aspartate) greater than glutamate greater than aspartate. 4. D(-)-2-Amino-5-phosphonovalerate (APV), an NMDA antagonist, reduced [K+]o by only about 50%, but kynurenate, an NMDA and non-NMDA antagonist, reduced [K+]o by approximately 85%; i.e. the same levels observed when synaptic transmission was blocked with 20 mM-Mg2+. These findings support the idea that synaptic release of excitatory amino acids such as L-glutamate and/or L-aspartate and subsequent activation of specific receptors by these putative transmitters are necessary for the postsynaptic component of delta[K+]o. 5. Addition of tachykinins elevated [K+]o but the effect appeared to require the participation of excitatory amino acids because it was blocked by APV and by kynurenate. 6. The finding that tetrodotoxin substantially reduced the ability of excitatory amino acid agonists and tachykinins to elevate [K+]o suggests that discharges in interneurones as a result of excitatory amino acid receptor activation are responsible for the postsynaptic component of delta[K+]o.

Effects of intrinsic aerobic capacity and ovariectomy on voluntary wheel running and nucleus accumbens dopamine receptor gene expression.

PubMed

Park, Young-Min; Kanaley, Jill A; Padilla, Jaume; Zidon, Terese; Welly, Rebecca J; Will, Matthew J; Britton, Steven L; Koch, Lauren G; Ruegsegger, Gregory N; Booth, Frank W; Thyfault, John P; Vieira-Potter, Victoria J

2016-10-01

Rats selectively bred for high (HCR) and low (LCR) aerobic capacity show a stark divergence in wheel running behavior, which may be associated with the dopamine (DA) system in the brain. HCR possess greater motivation for voluntary running along with greater brain DA activity compared to LCR. We recently demonstrated that HCR are not immune to ovariectomy (OVX)-associated reductions in spontaneous cage (i.e. locomotor) activity. Whether HCR and LCR rats differ in their OVX-mediated voluntary wheel running response is unknown. To determine whether HCR are protected from OVX-associated reduction in voluntary wheel running. Forty female HCR and LCR rats (age ~27weeks) had either SHM or OVX operations, and given access to a running wheel for 11weeks. Weekly wheel running distance was monitored throughout the intervention. Nucleus accumbens (NAc) was assessed for mRNA expression of DA receptors at sacrifice. Compared to LCR, HCR ran greater distance and had greater ratio of excitatory/inhibitory DA mRNA expression (both line main effects, P<0.05). Wheel running distance was significantly, positively correlated with the ratio of excitatory/inhibitory DA mRNA expression across animals. In both lines, OVX reduced wheel running (P<0.05). Unexpectedly, although HCR started with significantly greater voluntary wheel running, they had greater OVX-induced reduction in wheel running than LCR such that no differences were found 11weeks after OVX between HCROVX and LCROVX (interaction, P<0.05). This significant reduction in wheel running in HCR was associated with an OVX-mediated reduction in the ratio of excitatory/inhibitory DA mRNA expression. The DA system in the NAc region may play a significant role in motivation to run in female rats. Compared to LCR, HCR rats run significantly more, which associates with greater ratio of excitatory/inhibitory DA mRNA expression. However, despite greater inherent motivation to run and an associated brain DA mRNA expression profile, HCR rats are not protected against OVX-induced reduction in wheel running or OVX-mediated reduction in the ratio of excitatory/inhibitory DA receptor mRNA expression. OVX-mediated reduction in motivated physical activity may be partially explained by a reduced ratio of excitatory/inhibitory DA receptor mRNA expression for which intrinsic fitness does not confer protection. Copyright © 2016 Elsevier Inc. All rights reserved.

Voltage Gated Calcium Channel Activation by Backpropagating Action Potentials Downregulates NMDAR Function.

PubMed

Theis, Anne-Kathrin; Rózsa, Balázs; Katona, Gergely; Schmitz, Dietmar; Johenning, Friedrich W

2018-01-01

The majority of excitatory synapses are located on dendritic spines of cortical glutamatergic neurons. In spines, compartmentalized Ca 2+ signals transduce electrical activity into specific long-term biochemical and structural changes. Action potentials (APs) propagate back into the dendritic tree and activate voltage gated Ca 2+ channels (VGCCs). For spines, this global mode of spine Ca 2+ signaling is a direct biochemical feedback of suprathreshold neuronal activity. We previously demonstrated that backpropagating action potentials (bAPs) result in long-term enhancement of spine VGCCs. This activity-dependent VGCC plasticity results in a large interspine variability of VGCC Ca 2+ influx. Here, we investigate how spine VGCCs affect glutamatergic synaptic transmission. We combined electrophysiology, two-photon Ca 2+ imaging and two-photon glutamate uncaging in acute brain slices from rats. T- and R-type VGCCs were the dominant depolarization-associated Ca 2+ conductances in dendritic spines of excitatory layer 2 neurons and do not affect synaptic excitatory postsynaptic potentials (EPSPs) measured at the soma. Using two-photon glutamate uncaging, we compared the properties of glutamatergic synapses of single spines that express different levels of VGCCs. While VGCCs contributed to EPSP mediated Ca 2+ influx, the amount of EPSP mediated Ca 2+ influx is not determined by spine VGCC expression. On a longer timescale, the activation of VGCCs by bAP bursts results in downregulation of spine NMDAR function.

Laminar- and Target-Specific Amygdalar Inputs in Rat Primary Gustatory Cortex.

PubMed

Haley, Melissa S; Fontanini, Alfredo; Maffei, Arianna

2016-03-02

The primary gustatory cortex (GC) receives projections from the basolateral nucleus of the amygdala (BLA). Behavioral and electrophysiological studies demonstrated that this projection is involved in encoding the hedonic value of taste and is a source of anticipatory activity in GC. Anatomically, this projection is largest in the agranular portion of GC; however, its synaptic targets and synaptic properties are currently unknown. In vivo electrophysiological recordings report conflicting evidence about BLA afferents either selectively activating excitatory neurons or driving a compound response consistent with the activation of inhibitory circuits. Here we demonstrate that BLA afferents directly activate excitatory neurons and two distinct populations of inhibitory neurons in both superficial and deep layers of rat GC. BLA afferents recruit different proportions of excitatory and inhibitory neurons and show distinct patterns of circuit activation in the superficial and deep layers of GC. These results provide the first circuit-level analysis of BLA inputs to a sensory area. Laminar- and target-specific differences of BLA inputs likely explain the complexity of amygdalocortical interactions during sensory processing. Projections from the basolateral nucleus of the amygdala (BLA) to the cortex convey information about the emotional value and the expectation of a sensory stimulus. Although much work has been done to establish the behavioral role of BLA inputs to sensory cortices, very little is known about the circuit organization of BLA projections. Here we provide the first in-depth analysis of connectivity and synaptic properties of the BLA input to the gustatory cortex. We show that BLA afferents activate excitatory and inhibitory circuits in a layer-specific and pattern-specific manner. Our results provide important new information about how neural circuits establishing the hedonic value of sensory stimuli and driving anticipatory behaviors are organized at the synaptic level. Copyright © 2016 the authors 0270-6474/16/362623-15$15.00/0.

AMYGDALA MICROCIRCUITS CONTROLLING LEARNED FEAR

PubMed Central

Duvarci, Sevil; Pare, Denis

2014-01-01

We review recent work on the role of intrinsic amygdala networks in the regulation of classically conditioned defensive behaviors, commonly known as conditioned fear. These new developments highlight how conditioned fear depends on far more complex networks than initially envisioned. Indeed, multiple parallel inhibitory and excitatory circuits are differentially recruited during the expression versus extinction of conditioned fear. Moreover, shifts between expression and extinction circuits involve coordinated interactions with different regions of the medial prefrontal cortex. However, key areas of uncertainty remain, particularly with respect to the connectivity of the different cell types. Filling these gaps in our knowledge is important because much evidence indicates that human anxiety disorders results from an abnormal regulation of the networks supporting fear learning. PMID:24908482

Inhibitory Network Interactions Shape the Auditory Processing of Natural Communication Signals in the Songbird Auditory Forebrain

PubMed Central

Pinaud, Raphael; Terleph, Thomas A.; Tremere, Liisa A.; Phan, Mimi L.; Dagostin, André A.; Leão, Ricardo M.; Mello, Claudio V.; Vicario, David S.

2008-01-01

The role of GABA in the central processing of complex auditory signals is not fully understood. We have studied the involvement of GABAA-mediated inhibition in the processing of birdsong, a learned vocal communication signal requiring intact hearing for its development and maintenance. We focused on caudomedial nidopallium (NCM), an area analogous to parts of the mammalian auditory cortex with selective responses to birdsong. We present evidence that GABAA-mediated inhibition plays a pronounced role in NCM's auditory processing of birdsong. Using immunocytochemistry, we show that approximately half of NCM's neurons are GABAergic. Whole cell patch-clamp recordings in a slice preparation demonstrate that, at rest, spontaneously active GABAergic synapses inhibit excitatory inputs onto NCM neurons via GABAA receptors. Multi-electrode electrophysiological recordings in awake birds show that local blockade of GABAA-mediated inhibition in NCM markedly affects the temporal pattern of song-evoked responses in NCM without modifications in frequency tuning. Surprisingly, this blockade increases the phasic and largely suppresses the tonic response component, reflecting dynamic relationships of inhibitory networks that could include disinhibition. Thus processing of learned natural communication sounds in songbirds, and possibly other vocal learners, may depend on complex interactions of inhibitory networks. PMID:18480371

Extrinsic and Intrinsic Brain Network Connectivity Maintains Cognition across the Lifespan Despite Accelerated Decay of Regional Brain Activation.

PubMed

Tsvetanov, Kamen A; Henson, Richard N A; Tyler, Lorraine K; Razi, Adeel; Geerligs, Linda; Ham, Timothy E; Rowe, James B

2016-03-16

The maintenance of wellbeing across the lifespan depends on the preservation of cognitive function. We propose that successful cognitive aging is determined by interactions both within and between large-scale functional brain networks. Such connectivity can be estimated from task-free functional magnetic resonance imaging (fMRI), also known as resting-state fMRI (rs-fMRI). However, common correlational methods are confounded by age-related changes in the neurovascular signaling. To estimate network interactions at the neuronal rather than vascular level, we used generative models that specified both the neural interactions and a flexible neurovascular forward model. The networks' parameters were optimized to explain the spectral dynamics of rs-fMRI data in 602 healthy human adults from population-based cohorts who were approximately uniformly distributed between 18 and 88 years (www.cam-can.com). We assessed directed connectivity within and between three key large-scale networks: the salience network, dorsal attention network, and default mode network. We found that age influences connectivity both within and between these networks, over and above the effects on neurovascular coupling. Canonical correlation analysis revealed that the relationship between network connectivity and cognitive function was age-dependent: cognitive performance relied on neural dynamics more strongly in older adults. These effects were driven partly by reduced stability of neural activity within all networks, as expressed by an accelerated decay of neural information. Our findings suggest that the balance of excitatory connectivity between networks, and the stability of intrinsic neural representations within networks, changes with age. The cognitive function of older adults becomes increasingly dependent on these factors. Maintaining cognitive function is critical to successful aging. To study the neural basis of cognitive function across the lifespan, we studied a large population-based cohort (n = 602, 18-88 years), separating neural connectivity from vascular components of fMRI signals. Cognitive ability was influenced by the strength of connection within and between functional brain networks, and this positive relationship increased with age. In older adults, there was more rapid decay of intrinsic neuronal activity in multiple regions of the brain networks, which related to cognitive performance. Our data demonstrate increased reliance on network flexibility to maintain cognitive function, in the presence of more rapid decay of neural activity. These insights will facilitate the development of new strategies to maintain cognitive ability. Copyright © 2016 Tsvetanov et al.

Extrinsic and Intrinsic Brain Network Connectivity Maintains Cognition across the Lifespan Despite Accelerated Decay of Regional Brain Activation

PubMed Central

Henson, Richard N.A.; Tyler, Lorraine K.; Razi, Adeel; Geerligs, Linda; Ham, Timothy E.; Rowe, James B.

2016-01-01

The maintenance of wellbeing across the lifespan depends on the preservation of cognitive function. We propose that successful cognitive aging is determined by interactions both within and between large-scale functional brain networks. Such connectivity can be estimated from task-free functional magnetic resonance imaging (fMRI), also known as resting-state fMRI (rs-fMRI). However, common correlational methods are confounded by age-related changes in the neurovascular signaling. To estimate network interactions at the neuronal rather than vascular level, we used generative models that specified both the neural interactions and a flexible neurovascular forward model. The networks' parameters were optimized to explain the spectral dynamics of rs-fMRI data in 602 healthy human adults from population-based cohorts who were approximately uniformly distributed between 18 and 88 years (www.cam-can.com). We assessed directed connectivity within and between three key large-scale networks: the salience network, dorsal attention network, and default mode network. We found that age influences connectivity both within and between these networks, over and above the effects on neurovascular coupling. Canonical correlation analysis revealed that the relationship between network connectivity and cognitive function was age-dependent: cognitive performance relied on neural dynamics more strongly in older adults. These effects were driven partly by reduced stability of neural activity within all networks, as expressed by an accelerated decay of neural information. Our findings suggest that the balance of excitatory connectivity between networks, and the stability of intrinsic neural representations within networks, changes with age. The cognitive function of older adults becomes increasingly dependent on these factors. SIGNIFICANCE STATEMENT Maintaining cognitive function is critical to successful aging. To study the neural basis of cognitive function across the lifespan, we studied a large population-based cohort (n = 602, 18–88 years), separating neural connectivity from vascular components of fMRI signals. Cognitive ability was influenced by the strength of connection within and between functional brain networks, and this positive relationship increased with age. In older adults, there was more rapid decay of intrinsic neuronal activity in multiple regions of the brain networks, which related to cognitive performance. Our data demonstrate increased reliance on network flexibility to maintain cognitive function, in the presence of more rapid decay of neural activity. These insights will facilitate the development of new strategies to maintain cognitive ability. PMID:26985024

When is an Inhibitory Synapse Effective?

NASA Astrophysics Data System (ADS)

Qian, Ning; Sejnowski, Terrence J.

1990-10-01

Interactions between excitatory and inhibitory synaptic inputs on dendrites determine the level of activity in neurons. Models based on the cable equation predict that silent shunting inhibition can strongly veto the effect of an excitatory input. The cable model assumes that ionic concentrations do not change during the electrical activity, which may not be a valid assumption, especially for small structures such as dendritic spines. We present here an analysis and computer simulations to show that for large Cl^- conductance changes, the more general Nernst-Planck electrodiffusion model predicts that shunting inhibition on spines should be much less effective than that predicted by the cable model. This is a consequence of the large changes in the intracellular ionic concentration of Cl^- that can occur in small structures, which would alter the reversal potential and reduce the driving force for Cl^-. Shunting inhibition should therefore not be effective on spines, but it could be significantly more effective on the dendritic shaft at the base of the spine. In contrast to shunting inhibition, hyperpolarizing synaptic inhibition mediated by K^+ currents can be very effective in reducing the excitatory synaptic potentials on the same spine if the excitatory conductance change is less than 10 nS. We predict that if the inhibitory synapses found on cortical spines are to be effective, then they should be mediated by K^+ through GABA_B receptors.

Distinct Physiological Maturation of Parvalbumin-Positive Neuron Subtypes in Mouse Prefrontal Cortex.

PubMed

Miyamae, Takeaki; Chen, Kehui; Lewis, David A; Gonzalez-Burgos, Guillermo

2017-05-10

Parvalbumin-positive (PV + ) neurons control the timing of pyramidal cell output in cortical neuron networks. In the prefrontal cortex (PFC), PV + neuron activity is involved in cognitive function, suggesting that PV + neuron maturation is critical for cognitive development. The two major PV + neuron subtypes found in the PFC, chandelier cells (ChCs) and basket cells (BCs), are thought to play different roles in cortical circuits, but the trajectories of their physiological maturation have not been compared. Using two separate mouse lines, we found that in the mature PFC, both ChCs and BCs are abundant in superficial layer 2, but only BCs are present in deeper laminar locations. This distinctive laminar distribution was observed by postnatal day 12 (P12), when we first identified ChCs by the presence of axon cartridges. Electrophysiology analysis of excitatory synapse development, starting at P12, showed that excitatory drive remains low throughout development in ChCs, but increases rapidly before puberty in BCs, with an earlier time course in deeper-layer BCs. Consistent with a role of excitatory synaptic drive in the maturation of PV + neuron firing properties, the fast-spiking phenotype showed different maturation trajectories between ChCs and BCs, and between superficial versus deep-layer BCs. ChC and BC maturation was nearly completed, via different trajectories, before the onset of puberty. These findings suggest that ChC and BC maturation may contribute differentially to the emergence of cognitive function, primarily during prepubertal development. SIGNIFICANCE STATEMENT Parvalbumin-positive (PV + ) neurons tightly control pyramidal cell output. Thus PV + neuron maturation in the prefrontal cortex (PFC) is crucial for cognitive development. However, the relative physiological maturation of the two major subtypes of PV + neurons, chandelier cells (ChCs) and basket cells (BCs), has not been determined. We assessed the maturation of ChCs and BCs in different layers of the mouse PFC, and found that, from early postnatal age, ChCs and BCs differ in laminar location. Excitatory synapses and fast-spiking properties matured before the onset of puberty in both cell types, but following cell type-specific developmental trajectories. Hence, the physiological maturation of ChCs and BCs may contribute to the emergence of cognitive function differentially, and predominantly during prepubertal development. Copyright © 2017 the authors 0270-6474/17/374883-20$15.00/0.

Prefrontal NMDA receptors expressed in excitatory neurons control fear discrimination and fear extinction.

PubMed

Vieira, Philip A; Corches, Alex; Lovelace, Jonathan W; Westbrook, Kevin B; Mendoza, Michael; Korzus, Edward

2015-03-01

N-methyl-D-aspartate receptors (NMDARs) are critically involved in various learning mechanisms including modulation of fear memory, brain development and brain disorders. While NMDARs mediate opposite effects on medial prefrontal cortex (mPFC) interneurons and excitatory neurons, NMDAR antagonists trigger profound cortical activation. The objectives of the present study were to determine the involvement of NMDARs expressed specifically in excitatory neurons in mPFC-dependent adaptive behaviors, specifically fear discrimination and fear extinction. To achieve this, we tested mice with locally deleted Grin1 gene encoding the obligatory NR1 subunit of the NMDAR from prefrontal CamKIIα positive neurons for their ability to distinguish frequency modulated (FM) tones in fear discrimination test. We demonstrated that NMDAR-dependent signaling in the mPFC is critical for effective fear discrimination following initial generalization of conditioned fear. While mice with deficient NMDARs in prefrontal excitatory neurons maintain normal responses to a dangerous fear-conditioned stimulus, they exhibit abnormal generalization decrement. These studies provide evidence that NMDAR-dependent neural signaling in the mPFC is a component of a neural mechanism for disambiguating the meaning of fear signals and supports discriminative fear learning by retaining proper gating information, viz. both dangerous and harmless cues. We also found that selective deletion of NMDARs from excitatory neurons in the mPFC leads to a deficit in fear extinction of auditory conditioned stimuli. These studies suggest that prefrontal NMDARs expressed in excitatory neurons are involved in adaptive behavior. Copyright © 2015 Elsevier Inc. All rights reserved.

Spectral integration in primary auditory cortex attributable to temporally precise convergence of thalamocortical and intracortical input.

PubMed

Happel, Max F K; Jeschke, Marcus; Ohl, Frank W

2010-08-18

Primary sensory cortex integrates sensory information from afferent feedforward thalamocortical projection systems and convergent intracortical microcircuits. Both input systems have been demonstrated to provide different aspects of sensory information. Here we have used high-density recordings of laminar current source density (CSD) distributions in primary auditory cortex of Mongolian gerbils in combination with pharmacological silencing of cortical activity and analysis of the residual CSD, to dissociate the feedforward thalamocortical contribution and the intracortical contribution to spectral integration. We found a temporally highly precise integration of both types of inputs when the stimulation frequency was in close spectral neighborhood of the best frequency of the measurement site, in which the overlap between both inputs is maximal. Local intracortical connections provide both directly feedforward excitatory and modulatory input from adjacent cortical sites, which determine how concurrent afferent inputs are integrated. Through separate excitatory horizontal projections, terminating in cortical layers II/III, information about stimulus energy in greater spectral distance is provided even over long cortical distances. These projections effectively broaden spectral tuning width. Based on these data, we suggest a mechanism of spectral integration in primary auditory cortex that is based on temporally precise interactions of afferent thalamocortical inputs and different short- and long-range intracortical networks. The proposed conceptual framework allows integration of different and partly controversial anatomical and physiological models of spectral integration in the literature.

RECURRENT NEONATAL SEIZURES RESULT IN LONG-TERM INCREASE OF NEURONAL NETWORK EXCITABILITY IN THE RAT NEOCORTEX

PubMed Central

Isaeva, Elena; Isaev, Dmytro; Savrasova, Alina; Khazipov, Rustem; Holmes, Gregory L.

2011-01-01

Neonatal seizures are associated with a high likelihood of adverse neurological outcomes, including mental retardation, behavioral disorders, and epilepsy. Early seizures typically involve the neocortex, and post-neonatal epilepsy is often of neocortical origin. However, our understanding of the consequences of neonatal seizures for neocortical function is limited. In the present study, we show that neonatal seizures induced by flurothyl result in markedly enhanced susceptibility of the neocortex to seizure-like activity. This change occurs in young rats studied weeks after the last induced seizure and in adult rats studied months after the initial seizures. Neonatal seizures resulted in reductions in the amplitude of spontaneous inhibitory postsynaptic currents and the frequency of miniature inhibitory postsynaptic currents, and significant increases in the amplitude and frequency of spontaneous excitatory postsynaptic currents (sEPSCs) and in the frequency of miniature excitatory postsynaptic currents (mEPSCs) in pyramidal cells of layer 2/3 of the somatosensory cortex. The selective N-methyl-d-aspartate (NMDA) receptor antagonist d-2-amino-5-phosphon-ovalerate eliminated the differences in amplitude and frequency of sEPSCs and mEPSCs in the control and flurothyl groups, suggesting that NMDA receptors contribute significantly to the enhanced excitability seen in slices from rats that experienced recurrent neonatal seizures. Taken together, our results suggest that recurrent seizures in infancy result in a persistent enhancement of neocortical excitability. PMID:20384780

Hippocampal sharp wave-ripple: A cognitive biomarker for episodic memory and planning.

PubMed

Buzsáki, György

2015-10-01

Sharp wave ripples (SPW-Rs) represent the most synchronous population pattern in the mammalian brain. Their excitatory output affects a wide area of the cortex and several subcortical nuclei. SPW-Rs occur during "off-line" states of the brain, associated with consummatory behaviors and non-REM sleep, and are influenced by numerous neurotransmitters and neuromodulators. They arise from the excitatory recurrent system of the CA3 region and the SPW-induced excitation brings about a fast network oscillation (ripple) in CA1. The spike content of SPW-Rs is temporally and spatially coordinated by a consortium of interneurons to replay fragments of waking neuronal sequences in a compressed format. SPW-Rs assist in transferring this compressed hippocampal representation to distributed circuits to support memory consolidation; selective disruption of SPW-Rs interferes with memory. Recently acquired and pre-existing information are combined during SPW-R replay to influence decisions, plan actions and, potentially, allow for creative thoughts. In addition to the widely studied contribution to memory, SPW-Rs may also affect endocrine function via activation of hypothalamic circuits. Alteration of the physiological mechanisms supporting SPW-Rs leads to their pathological conversion, "p-ripples," which are a marker of epileptogenic tissue and can be observed in rodent models of schizophrenia and Alzheimer's Disease. Mechanisms for SPW-R genesis and function are discussed in this review. © 2015 The Authors Hippocampus Published by Wiley Periodicals, Inc.

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

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 Edge of Stability: Response Times and Delta Oscillations in Balanced Networks

PubMed Central

Gillary, Grant; Niebur, Ernst

2016-01-01

The standard architecture of neocortex is a network with excitation and inhibition in closely maintained balance. These networks respond fast and with high precision to their inputs and they allow selective amplification of patterned signals. The stability of such networks is known to depend on balancing the strengths of positive and negative feedback. We here show that a second condition is required for stability which depends on the relative strengths and time courses of fast (AMPA) and slow (NMDA) currents in the excitatory projections. This condition also determines the response time of the network. We show that networks which respond quickly to an input are necessarily close to an oscillatory instability which resonates in the delta range. This instability explains the existence of neocortical delta oscillations and the emergence of absence epilepsy. Although cortical delta oscillations are a network-level phenomenon, we show that in non-pathological networks, individual neurons receive sufficient information to keep the network in the fast-response regime without sliding into the instability. PMID:27689361

Aspects of the homeostaic plasticity of GABAA receptor-mediated inhibition

PubMed Central

Mody, Istvan

2005-01-01

Plasticity of ligand-gated ion channels plays a critical role in nervous system development, circuit formation and refinement, and pathological processes. Recent advances have mainly focused on the plasticity of channels gated by excitatory amino acids, including their acclaimed role in learning and memory. These receptors, together with voltage-gated ion channels, have also been known to be subjected to a homeostatic form of plasticity that prevents destabilization of the neurone's function and that of the network during various physiological processes. To date, the plasticity of GABAA receptors has been examined mainly from a developmental and a pathological point of view. Little is known about homeostatic mechanisms governing their plasticity. This review summarizes some of the findings on the homeostatic plasticity of tonic and phasic inhibitory activity. PMID:15528237

Excitatory amino acids in epilepsy and potential novel therapies.

PubMed

Meldrum, B S

1992-07-01

Evidence that an abnormality of excitatory neurotransmission may contribute to the epileptic phenomena in various animal and human syndromes is reviewed. Altered glutamate transport or metabolism may be a contributory factor in some genetic syndromes and enhanced responsiveness to activation of NMDA receptors may be significant in various acquired forms of epilepsy. Decreasing glutamatergic neurotransmission provides a rational therapeutic approach to epilepsy. Potent anticonvulsant effects are seen with the acute administration of NMDA antagonists in a wide range of animal models. Some competitive antagonists acting at the NMDA/glutamate site show prolonged anticonvulsant activity following oral administration at doses free of motor side effects and appear suitable for clinical trial.

Glutamate receptor activation in the kindled dentate gyrus.

PubMed

Behr, J; Heinemann, U; Mody, I

2000-01-01

The contribution of alpha-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA), N-methyl-D-aspartate (NMDA), and kainate receptor activation to the enhanced seizure susceptibility of the dentate gyrus was investigated in an experimental model of temporal lobe epilepsy. Using the specific NMDA and AMPA receptor antagonists D-APV and SYM 2206, we examined alterations in glutamate receptor-dependent synaptic currents 48 hours and 28 days after kindling in field-potential and voltage-clamp recordings. Forty-eight hours after kindling, the fractions of AMPA and NMDA receptor-mediated excitatory postsynaptic current components shifted dramatically in favor of the NMDA receptor-mediated response. Four weeks after kindling, however, AMPA and NMDA receptor-mediated excitatory postsynaptic currents reverted to control-like values. Neither single nor repetitive perforant path stimuli evoked kainate receptor-mediated excitatory postsynaptic currents in dentate gyrus granule cells of control or kindled rats. The enhanced excitability of the kindled dentate gyrus 48 hours after the last seizure most likely results from transiently enhanced NMDA receptor activation. The NMDA receptor seems to play a critical role in the induction of the kindled state rather than in the persistence of the enhanced seizure susceptibility.

Cholinergic interneurons in the feeding system of the pond snail Lymnaea stagnalis. II. N1 interneurons make cholinergic synapses with feeding motoneurons.

PubMed

Elliott, C J; Kemenes, G

1992-05-29

The N1 neurons are a population of interneurons active during the protraction phase of the feeding rhythm. All the N1 neurons are coupled by electrical synapses which persist in a high Mg/low Ca saline which blocks chemical synapses. Individual N1 spikes produce discrete electrotonic postsynaptic potentials (PSPS) in other N1 cells, but the coupling is not strong enough to ensure 1:1 firing. Bursts of N1 spikes generate compound PSPS in the feeding motoneurons. The sign (excitation or inhibition) of the N1 input corresponds with the synaptic barrage recorded during the protraction phase. Discrete PSPS are only resolved in a Hi-Di saline. Their variation in latency and number can be explained by variation in electrotonic propagation within the electrically coupled network of N1 cells. The excitatory postsynaptic potentials (ESPS) in the 1 cell are reduced by 0.5 mM antagonists hexamethonium (HMT), atropine (ATR), curare (d-TC) and by methylxylocholine (MeXCh), all of which block the excitatory cholinergic receptor (Elliott et al. (Phil. Trans. R. Soc. Lond. 336, 157-166 (Preceding paper.) (1992)). The 1 cell EPSPS were transiently blocked by phenyltrimethylammonium (PTMA), which is both an agonist and antagonist at the 1 cell excitatory acetylcholine (ACh) receptor (Elliott et al. 1992). The inhibitory postsynaptic potential (IPSP) in the 3 cell is blocked by bath applications of MeXCh and PTMA, which both abolish the response of the 3 cell to ACh (Elliott et. al. 1992). The effects of the cholinergic antagonists on the response of 4 cluster and 5 cells to N1 stimulation matches their response to ACh (Elliott et al. 1992). It is concluded that the population of N1 cells are multiaction, premotor cholinergic interneurons.

Nothing can be coincidence: synaptic inhibition and plasticity in the cerebellar nuclei

PubMed Central

Pugh, Jason R.; Raman, Indira M.

2009-01-01

Many cerebellar neurons fire spontaneously, generating 10–100 action potentials per second even without synaptic input. This high basal activity correlates with information-coding mechanisms that differ from those of cells that are quiescent until excited synaptically. For example, in the deep cerebellar nuclei, Hebbian patterns of coincident synaptic excitation and postsynaptic firing fail to induce long-term increases in the strength of excitatory inputs. Instead, excitatory synaptic currents are potentiated by combinations of inhibition and excitation that resemble the activity of Purkinje and mossy fiber afferents that is predicted to occur during cerebellar associative learning tasks. Such results indicate that circuits with intrinsically active neurons have rules for information transfer and storage that distinguish them from other brain regions. PMID:19178955

New Patterns of Activity in a Pair of Interacting Excitatory-Inhibitory Neural Fields

NASA Astrophysics Data System (ADS)

Folias, S. E.; Ermentrout, G. B.

2011-11-01

In this Letter, we study stationary bump solutions in a pair of interacting excitatory-inhibitory (E-I) neural fields in one dimension. We demonstrate the existence of localized bump solutions of persistent activity that can be maintained by the pair of interacting layers when a stationary bump is not supported by either layer in isolation—a scenario which may be relevant as a mechanism for the persistent activity associated with working memory in the prefrontal cortex and may explain why bumps are not seen in in vitro slice preparations. Furthermore, we describe a new type of stationary bump solution arising from a pitchfork bifurcation which produces a stationary bump in each layer with a spatial offset that increases with the bifurcation parameter.

Average activity of excitatory and inhibitory neural populations

NASA Astrophysics Data System (ADS)

Roulet, Javier; Mindlin, Gabriel B.

2016-09-01

We develop an extension of the Ott-Antonsen method [E. Ott and T. M. Antonsen, Chaos 18(3), 037113 (2008)] that allows obtaining the mean activity (spiking rate) of a population of excitable units. By means of the Ott-Antonsen method, equations for the dynamics of the order parameters of coupled excitatory and inhibitory populations of excitable units are obtained, and their mean activities are computed. Two different excitable systems are studied: Adler units and theta neurons. The resulting bifurcation diagrams are compared with those obtained from studying the phenomenological Wilson-Cowan model in some regions of the parameter space. Compatible behaviors, as well as higher dimensional chaotic solutions, are observed. We study numerical simulations to further validate the equations.

Average activity of excitatory and inhibitory neural populations

PubMed Central

Mindlin, Gabriel B.

2016-01-01

We develop an extension of the Ott-Antonsen method [E. Ott and T. M. Antonsen, Chaos 18(3), 037113 (2008)] that allows obtaining the mean activity (spiking rate) of a population of excitable units. By means of the Ott-Antonsen method, equations for the dynamics of the order parameters of coupled excitatory and inhibitory populations of excitable units are obtained, and their mean activities are computed. Two different excitable systems are studied: Adler units and theta neurons. The resulting bifurcation diagrams are compared with those obtained from studying the phenomenological Wilson-Cowan model in some regions of the parameter space. Compatible behaviors, as well as higher dimensional chaotic solutions, are observed. We study numerical simulations to further validate the equations. PMID:27781447

YADCLAN: yet another digitally-controlled linear artificial neuron.

PubMed

Frenger, Paul

2003-01-01

This paper updates the author's 1999 RMBS presentation on digitally controlled linear artificial neuron design. Each neuron is based on a standard operational amplifier having excitatory and inhibitory inputs, variable gain, an amplified linear analog output and an adjustable threshold comparator for digital output. This design employs a 1-wire serial network of digitally controlled potentiometers and resistors whose resistance values are set and read back under microprocessor supervision. This system embodies several unique and useful features, including: enhanced neuronal stability, dynamic reconfigurability and network extensibility. This artificial neuronal is being employed for feature extraction and pattern recognition in an advanced robotic application.

Information processing occurs via critical avalanches in a model of the primary visual cortex

NASA Astrophysics Data System (ADS)

Bortolotto, G. S.; Girardi-Schappo, M.; Gonsalves, J. J.; Pinto, L. T.; Tragtenberg, M. H. R.

2016-01-01

We study a new biologically motivated model for the Macaque monkey primary visual cortex which presents power-law avalanches after a visual stimulus. The signal propagates through all the layers of the model via avalanches that depend on network structure and synaptic parameter. We identify four different avalanche profiles as a function of the excitatory postsynaptic potential. The avalanches follow a size-duration scaling relation and present critical exponents that match experiments. The structure of the network gives rise to a regime of two characteristic spatial scales, one of which vanishes in the thermodynamic limit.

Information entropy-based fitting of the disease trajectory of brain ischemia-induced vascular cognitive impairment.

PubMed

Liu, Lin; Huo, Ju; Zhao, Ying; Tian, Yu

2012-03-25

The present study investigated the disease trajectory of vascular cognitive impairment using the entropy of information in a neural network mathematical simulation based on the free radical and excitatory amino acids theories. Glutamate, malondialdehyde, and inducible nitric oxide synthase content was significantly elevated, but acetylcholine, catalase, superoxide dismutase, glutathione peroxidase and constitutive nitric oxide synthase content was significantly decreased in our vascular cognitive impairment model. The fitting curves for each factor were obtained using Matlab software. Nineteen, 30 and 49 days post ischemia were the main output time frames of the influence of these seven factors. Our results demonstrated that vascular cognitive impairment involves multiple factors. These factors include excitatory amino acid toxicity and nitric oxide toxicity. These toxicities disrupt the dynamic equilibrium of the production and removal of oxygen free radicals after cerebral ischemia, reducing the ability to clear oxygen free radicals and worsening brain injury.

Sequentially switching cell assemblies in random inhibitory networks of spiking neurons in the striatum.

PubMed

Ponzi, Adam; Wickens, Jeff

2010-04-28

The striatum is composed of GABAergic medium spiny neurons with inhibitory collaterals forming a sparse random asymmetric network and receiving an excitatory glutamatergic cortical projection. Because the inhibitory collaterals are sparse and weak, their role in striatal network dynamics is puzzling. However, here we show by simulation of a striatal inhibitory network model composed of spiking neurons that cells form assemblies that fire in sequential coherent episodes and display complex identity-temporal spiking patterns even when cortical excitation is simply constant or fluctuating noisily. Strongly correlated large-scale firing rate fluctuations on slow behaviorally relevant timescales of hundreds of milliseconds are shown by members of the same assembly whereas members of different assemblies show strong negative correlation, and we show how randomly connected spiking networks can generate this activity. Cells display highly irregular spiking with high coefficients of variation, broadly distributed low firing rates, and interspike interval distributions that are consistent with exponentially tailed power laws. Although firing rates vary coherently on slow timescales, precise spiking synchronization is absent in general. Our model only requires the minimal but striatally realistic assumptions of sparse to intermediate random connectivity, weak inhibitory synapses, and sufficient cortical excitation so that some cells are depolarized above the firing threshold during up states. Our results are in good qualitative agreement with experimental studies, consistent with recently determined striatal anatomy and physiology, and support a new view of endogenously generated metastable state switching dynamics of the striatal network underlying its information processing operations.

Modeling mesoscopic cortical dynamics using a mean-field model of conductance-based networks of adaptive exponential integrate-and-fire neurons.

PubMed

Zerlaut, Yann; Chemla, Sandrine; Chavane, Frederic; Destexhe, Alain

2018-02-01

Voltage-sensitive dye imaging (VSDi) has revealed fundamental properties of neocortical processing at macroscopic scales. Since for each pixel VSDi signals report the average membrane potential over hundreds of neurons, it seems natural to use a mean-field formalism to model such signals. Here, we present a mean-field model of networks of Adaptive Exponential (AdEx) integrate-and-fire neurons, with conductance-based synaptic interactions. We study a network of regular-spiking (RS) excitatory neurons and fast-spiking (FS) inhibitory neurons. We use a Master Equation formalism, together with a semi-analytic approach to the transfer function of AdEx neurons to describe the average dynamics of the coupled populations. We compare the predictions of this mean-field model to simulated networks of RS-FS cells, first at the level of the spontaneous activity of the network, which is well predicted by the analytical description. Second, we investigate the response of the network to time-varying external input, and show that the mean-field model predicts the response time course of the population. Finally, to model VSDi signals, we consider a one-dimensional ring model made of interconnected RS-FS mean-field units. We found that this model can reproduce the spatio-temporal patterns seen in VSDi of awake monkey visual cortex as a response to local and transient visual stimuli. Conversely, we show that the model allows one to infer physiological parameters from the experimentally-recorded spatio-temporal patterns.

Molsidomine potentiates the protective activity of GYKI 52466, a non-NMDA antagonist, MK-801, a non-competitive NMDA antagonist, and riluzole against electroconvulsions in mice.

PubMed

Tutka, Piotr; Olszewski, Krzysztof; Woźniak, Małgorzata; Kleinrok, Zdzisław; Czuczwar, Stanisław J; Wielosz, Marian

2002-08-01

The influence of molsidomine, a donor of nitric oxide (NO), L-arginine, a substrate for NO synthesis, and N(G)-nitro-L-arginine (NNA), an inhibitor of NO synthase, on the protective activity of CGP 40116, GYKI 52466, MK-801, and riluzole against electroconvulsions was studied in mice. Molsidomine (100 mg kg(-1); i.p.) potentiated the protective activity of GYKI 52466, MK-801, and riluzole but did not influence the protection offered by CGP 40116. In contrast to molsidomine, L-arginine (500 mg kg(-1); i.p.) did not impair the protective activity of any anticonvulsant. In a dose of 40 mg kg(-1), NNA administered i.p. did not affect the protection offered by any excitatory amino acid antagonists and riluzole. Combinations of molsidomine with either GYKI 52466 or MK-801 as well as riluzole did not cause a memory deficit in the passive avoidance task. However, the combined treatment of molsidomine with these anticonvulsants resulted in a motor impairment quantified by the chimney test. The lack of effect of L-arginine and NNA on the protective activity of excitatory amino acid antagonists suggests that molsidomine-evoked alterations in the protection provided by some excitatory amino acid antagonists against electroconvulsions are independent of the NO pathway.

Astrocytes Modulate a Postsynaptic NMDA–GABAA-Receptor Crosstalk in Hypothalamic Neurosecretory Neurons

PubMed Central

Potapenko, Evgeniy S.; Biancardi, Vinicia C.; Zhou, Yiqiang

2013-01-01

A dynamic balance between the excitatory and inhibitory neurotransmitters glutamate and GABA is critical for maintaining proper neuronal activity in the brain. This balance is partly achieved via presynaptic interactions between glutamatergic and GABAAergic synapses converging into the same targets. Here, we show that in hypothalamic magnocellular neurosecretory neurons (MNCs), a direct crosstalk between postsynaptic NMDA receptors (NMDARs) and GABAA receptors (GABAARs) contributes to the excitatory/inhibitory balance in this system. We found that activation of NMDARs by endogenous glutamate levels controlled by astrocyte glutamate transporters, evokes a transient and reversible potentiation of postsynaptic GABAARs. This inter-receptor crosstalk is calcium-dependent and involves a kinase-dependent phosphorylation mechanism, but does not require nitric oxide as an intermediary signal. Finally, we found the NMDAR–GABAAR crosstalk to be blunted in rats with heart failure, a pathological condition in which the hypothalamic glutamate–GABA balance is tipped toward an excitatory predominance. Together, our findings support a novel form of glutamate–GABA interactions in MNCs, which involves crosstalk between NMDA and GABAA postsynaptic receptors, whose strength is controlled by the activity of local astrocytes. We propose this inter-receptor crosstalk to act as a compensatory, counterbalancing mechanism to dampen glutamate-mediated overexcitation. Finally, we propose that an uncoupling between NMDARs and GABAARs may contribute to exacerbated neuronal activity and, consequently, sympathohumoral activation in such disease conditions as heart failure. PMID:23303942

Active integration of glutamatergic input to the inferior olive generates bidirectional postsynaptic potentials

PubMed Central

Garden, Derek L. F.; Rinaldi, Arianna

2016-01-01

Key points We establish experimental preparations for optogenetic investigation of glutamatergic input to the inferior olive.Neurones in the principal olivary nucleus receive monosynaptic extra‐somatic glutamatergic input from the neocortex.Glutamatergic inputs to neurones in the inferior olive generate bidirectional postsynaptic potentials (PSPs), with a fast excitatory component followed by a slower inhibitory component.Small conductance calcium‐activated potassium (SK) channels are required for the slow inhibitory component of glutamatergic PSPs and oppose temporal summation of inputs at intervals ≤ 20 ms.Active integration of synaptic input within the inferior olive may play a central role in control of olivo‐cerebellar climbing fibre signals. Abstract The inferior olive plays a critical role in motor coordination and learning by integrating diverse afferent signals to generate climbing fibre inputs to the cerebellar cortex. While it is well established that climbing fibre signals are important for motor coordination, the mechanisms by which neurones in the inferior olive integrate synaptic inputs and the roles of particular ion channels are unclear. Here, we test the hypothesis that neurones in the inferior olive actively integrate glutamatergic synaptic inputs. We demonstrate that optogenetically activated long‐range synaptic inputs to the inferior olive, including projections from the motor cortex, generate rapid excitatory potentials followed by slower inhibitory potentials. Synaptic projections from the motor cortex preferentially target the principal olivary nucleus. We show that inhibitory and excitatory components of the bidirectional synaptic potentials are dependent upon AMPA (GluA) receptors, are GABAA independent, and originate from the same presynaptic axons. Consistent with models that predict active integration of synaptic inputs by inferior olive neurones, we find that the inhibitory component is reduced by blocking large conductance calcium‐activated potassium channels with iberiotoxin, and is abolished by blocking small conductance calcium‐activated potassium channels with apamin. Summation of excitatory components of synaptic responses to inputs at intervals ≤ 20 ms is increased by apamin, suggesting a role for the inhibitory component of glutamatergic responses in temporal integration. Our results indicate that neurones in the inferior olive implement novel rules for synaptic integration and suggest new principles for the contribution of inferior olive neurones to coordinated motor behaviours. PMID:27767209

On-demand activation of the endocannabinoid system in the control of neuronal excitability and epileptiform seizures.

PubMed

Lutz, Beat

2004-11-01

Neurons intensively exchange information among each other using both inhibitory and excitatory neurotransmitters. However, if the balance of excitation and inhibition is perturbed, the intensity of excitatory transmission may exceed a certain threshold and epileptic seizures can occur. As the occurrence of epilepsy in the human population is about 1%, the search for therapeutic targets to alleviate seizures is warranted. Extracts of Cannabis sativa have a long history in the treatment of various neurological diseases, including epilepsy. However, cannabinoids have been reported to exert both pro- and anti-convulsive activities. The recent progress in understanding the endogenous cannabinoid system has allowed new insights into these opposing effects of cannabinoids. When excessive neuronal activity occurs, endocannabinoids are generated on demand and activate cannabinoid type 1 (CB1) receptors. Using mice lacking CB1 receptors in principal forebrain neurons in a model of epileptiform seizures, it was shown that CB1 receptors expressed on excitatory glutamatergic neurons mediate the anti-convulsive activity of endocannabinoids. Systemic activation of CB1 receptors by exogenous cannabinoids, however, are anti- or pro-convulsive, depending on the seizure model used. The pro-convulsive activity of exogenous cannabinoids might be explained by the notion that CB1 receptors expressed on inhibitory GABAergic neurons are also activated, leading to a decreased release of GABA, and to a concomitant increase in seizure susceptibility. The concept that the endogenous cannabinoid system is activated on demand suggests that a promising strategy to alleviate seizure frequency is the enhancement of endocannabinoid levels by inhibiting the cellular uptake and the degradation of these endogenous compounds.

A Simple Network Architecture Accounts for Diverse Reward Time Responses in Primary Visual Cortex.

PubMed

Huertas, Marco A; Hussain Shuler, Marshall G; Shouval, Harel Z

2015-09-16

Many actions performed by animals and humans depend on an ability to learn, estimate, and produce temporal intervals of behavioral relevance. Exemplifying such learning of cued expectancies is the observation of reward-timing activity in the primary visual cortex (V1) of rodents, wherein neural responses to visual cues come to predict the time of future reward as behaviorally experienced in the past. These reward-timing responses exhibit significant heterogeneity in at least three qualitatively distinct classes: sustained increase or sustained decrease in firing rate until the time of expected reward, and a class of cells that reach a peak in firing at the expected delay. We elaborate upon our existing model by including inhibitory and excitatory units while imposing simple connectivity rules to demonstrate what role these inhibitory elements and the simple architectures play in sculpting the response dynamics of the network. We find that simply adding inhibition is not sufficient for obtaining the different distinct response classes, and that a broad distribution of inhibitory projections is necessary for obtaining peak-type responses. Furthermore, although changes in connection strength that modulate the effects of inhibition onto excitatory units have a strong impact on the firing rate profile of these peaked responses, the network exhibits robustness in its overall ability to predict the expected time of reward. Finally, we demonstrate how the magnitude of expected reward can be encoded at the expected delay in the network and how peaked responses express this reward expectancy. Heterogeneity in single-neuron responses is a common feature of neuronal systems, although sometimes, in theoretical approaches, it is treated as a nuisance and seldom considered as conveying a different aspect of a signal. In this study, we focus on the heterogeneous responses in the primary visual cortex of rodents trained with a predictable delayed reward time. We describe under what conditions this heterogeneity can arise by self-organization, and what information it can convey. This study, while focusing on a specific system, provides insight onto how heterogeneity can arise in general while also shedding light onto mechanisms of reinforcement learning using realistic biological assumptions. Copyright © 2015 the authors 0270-6474/15/3512659-14$15.00/0.

Firing-rate based network modeling of the dLGN circuit: Effects of cortical feedback on spatiotemporal response properties of relay cells.

PubMed

Mobarhan, Milad Hobbi; Halnes, Geir; Martínez-Cañada, Pablo; Hafting, Torkel; Fyhn, Marianne; Einevoll, Gaute T

2018-05-01

Visually evoked signals in the retina pass through the dorsal geniculate nucleus (dLGN) on the way to the visual cortex. This is however not a simple feedforward flow of information: there is a significant feedback from cortical cells back to both relay cells and interneurons in the dLGN. Despite four decades of experimental and theoretical studies, the functional role of this feedback is still debated. Here we use a firing-rate model, the extended difference-of-Gaussians (eDOG) model, to explore cortical feedback effects on visual responses of dLGN relay cells. For this model the responses are found by direct evaluation of two- or three-dimensional integrals allowing for fast and comprehensive studies of putative effects of different candidate organizations of the cortical feedback. Our analysis identifies a special mixed configuration of excitatory and inhibitory cortical feedback which seems to best account for available experimental data. This configuration consists of (i) a slow (long-delay) and spatially widespread inhibitory feedback, combined with (ii) a fast (short-delayed) and spatially narrow excitatory feedback, where (iii) the excitatory/inhibitory ON-ON connections are accompanied respectively by inhibitory/excitatory OFF-ON connections, i.e. following a phase-reversed arrangement. The recent development of optogenetic and pharmacogenetic methods has provided new tools for more precise manipulation and investigation of the thalamocortical circuit, in particular for mice. Such data will expectedly allow the eDOG model to be better constrained by data from specific animal model systems than has been possible until now for cat. We have therefore made the Python tool pyLGN which allows for easy adaptation of the eDOG model to new situations.

Excitation-transcription coupling in parvalbumin-positive interneurons employs a novel CaM Kinase-dependent pathway distinct from excitatory neurons

PubMed Central

Cohen, Samuel M.; Ma, Huan; Kuchibhotla, Kishore V.; Watson, Brendon O.; Buzsáki, György; Froemke, Robert C.; Tsien, Richard W.

2016-01-01

Properly functional CNS circuits depend on inhibitory interneurons that in turn rely upon activity-dependent gene expression for morphological development, connectivity and excitatory-inhibitory coordination. Despite its importance, excitation-transcription coupling in inhibitory interneurons is poorly understood. Here, we report that PV+ interneurons employ a novel CaMK-dependent pathway to trigger CREB phosphorylation and gene expression. As in excitatory neurons, voltage-gated Ca2+ influx through CaV1 channels triggers CaM nuclear translocation via local Ca2+ signaling. However, PV+ interneurons are distinct in that nuclear signaling is mediated by γCaMKI, not γCaMKII. CREB phosphorylation also proceeds with slow, sigmoid kinetics, rate-limited by paucity of CaMKIV, protecting against saturation of phospho-CREB in the face of higher firing rates and bigger Ca2+ transients. Our findings support the generality of CaM shuttling to drive nuclear CaMK activity, and are relevant to disease pathophysiology, insofar as dysfunction of PV+ interneurons and molecules underpinning their excitation-transcription coupling both relate to neuropsychiatric disease. PMID:27041500

[Effect of trimebutine on cholinergic transmission in neurons of the inferior mesenteric ganglion of the rabbit].

PubMed

Julé, Y

1987-01-01

We analyzed the effects of trimebutine on the synaptic activity of neurons of the rabbit inferior mesenteric ganglion, using intracellular recording techniques. The synaptic activity was produced by subthreshold stimuli (0.5 Hz) applied individually, on lumbar splanchnic and lumbar colonic nerves. These stimuli triggered cholinergic responses corresponding to fast excitatory postsynaptic potentials. In 8 of 20 neurones tested trimebutine (10(-6) g/ml) produced an inhibition of excitatory postsynaptic potentials, without any change in the resting membrane potential. In 6 of 20 neurons tested, trimebutine produced, successively, an early facilitation followed by a late inhibition of excitatory postsynaptic potentials. Both effects occurred without change in the resting membrane potential. The inhibitory and facilitatory effects of trimebutine were accompanied, by an increase and a decrease in the number of failures of nerve stimulation respectively. These results indicate that inhibitory and facilitatory effects of trimebutine correspond respectively to a decrease and an increase in the amount of acetylcholine released from presynaptic nerve terminals originating from the spinal cord and the distal colon.

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.

Time-course of changes in neuronal activity markers following iTBS-TMS of the rat neocortex.

PubMed

Hoppenrath, Kathrin; Funke, Klaus

2013-03-01

In a rat model of transcranial magnetic stimulation we could recently show that intermittent theta-burst stimulation (iTBS) affects the neocortical expression of the immediate early gene products c-Fos and zif268 as well as that of the two glutamic acid decarboxylase isoforms GAD65 and GAD67 and that of the calcium-binding proteins calbindin (CB) and parvalbumin (PV), known as markers of excitatory and inhibitory activity. We now analyzed in more detail the time course of changes in the expression of these proteins at 10, 20, 40, 80 and 160min following a single block of iTBS consisting of 600 stimuli. Initial increase in c-Fos, zif268 and GAD65 (20min) signals transient activation of excitatory and inhibitory neurons, thereafter first followed by a decrease in markers of activity of inhibitory neurons (GAD67, PV, CB: 20-80min) and then by a late decrease in c-Fos and GAD65 expression (160min). The results demonstrate that one iTBS block may have an after-effect of at least two different phases, an early phase with increased neuronal activity (c-Fos, zif268) but also the likelihood of increased GABA-release (GAD65), followed by a late phase (>40min) of reduced neuronal activity in excitatory and inhibitory systems which may indicate a state of reduced excitability. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Structural connectivity in schizophrenia and its impact on the dynamics of spontaneous functional networks

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

Cabral, Joana; Department of Psychiatry, University of Oxford, Oxford OX3 7JX; Fernandes, Henrique M.

The neuropathology of schizophrenia remains unclear. Some insight has come from modern neuroimaging techniques, which offer an unparalleled opportunity to explore in vivo the structure and function of the brain. Using functional magnetic resonance imaging, it has been found that the large-scale resting-state functional connectivity (rsFC) in schizophrenia — measured as the temporal correlations of the blood-oxygen-level-dependent (BOLD) signal — exhibit altered network topology, with lower small-world index. The origin of these rsFC alterations and link with the underlying structural connectivity remain unclear. In this work, we used a computational model of spontaneous large-scale brain activity to explore the rolemore » of the structural connectivity in the large-scale dynamics of the brain in health and schizophrenia. The structural connectomes from 15 adolescent patients with early-onset schizophrenia and 15 age- and gender-matched controls were built from diffusion tensor imaging data to detect the white matter tracts between 90 brain areas. Brain areas, simulated using a reduced dynamic mean-field model, receive excitatory input from other areas in proportion to the number of fibre tracts between them. The simulated mean field activity was transformed into BOLD signal, and the properties of the simulated functional networks were analyzed. Our results suggest that the functional alterations observed in schizophrenia are not directly linked to alterations in the structural topology. Instead, subtly randomized and less small-world functional networks appear when the brain operates with lower global coupling, which shifts the dynamics from the optimal healthy regime.« less

Structural connectivity in schizophrenia and its impact on the dynamics of spontaneous functional networks

NASA Astrophysics Data System (ADS)

Cabral, Joana; Fernandes, Henrique M.; Van Hartevelt, Tim J.; James, Anthony C.; Kringelbach, Morten L.; Deco, Gustavo

2013-12-01

The neuropathology of schizophrenia remains unclear. Some insight has come from modern neuroimaging techniques, which offer an unparalleled opportunity to explore in vivo the structure and function of the brain. Using functional magnetic resonance imaging, it has been found that the large-scale resting-state functional connectivity (rsFC) in schizophrenia — measured as the temporal correlations of the blood-oxygen-level-dependent (BOLD) signal — exhibit altered network topology, with lower small-world index. The origin of these rsFC alterations and link with the underlying structural connectivity remain unclear. In this work, we used a computational model of spontaneous large-scale brain activity to explore the role of the structural connectivity in the large-scale dynamics of the brain in health and schizophrenia. The structural connectomes from 15 adolescent patients with early-onset schizophrenia and 15 age- and gender-matched controls were built from diffusion tensor imaging data to detect the white matter tracts between 90 brain areas. Brain areas, simulated using a reduced dynamic mean-field model, receive excitatory input from other areas in proportion to the number of fibre tracts between them. The simulated mean field activity was transformed into BOLD signal, and the properties of the simulated functional networks were analyzed. Our results suggest that the functional alterations observed in schizophrenia are not directly linked to alterations in the structural topology. Instead, subtly randomized and less small-world functional networks appear when the brain operates with lower global coupling, which shifts the dynamics from the optimal healthy regime.

Modulation of hippocampal rhythms by subthreshold electric fields and network topology

PubMed Central

Berzhanskaya, Julia; Chernyy, Nick; Gluckman, Bruce J.; Schiff, Steven J.; Ascoli, Giorgio A.

2012-01-01

Theta (4–12 Hz) and gamma (30–80 Hz) rhythms are considered important for cortical and hippocampal function. Although several neuron types are implicated in rhythmogenesis, the exact cellular mechanisms remain unknown. Subthreshold electric fields provide a flexible, area-specific tool to modulate neural activity and directly test functional hypotheses. Here we present experimental and computational evidence of the interplay among hippocampal synaptic circuitry, neuronal morphology, external electric fields, and network activity. Electrophysiological data are used to constrain and validate an anatomically and biophysically realistic model of area CA1 containing pyramidal cells and two interneuron types: dendritic- and perisomatic-targeting. We report two lines of results: addressing the network structure capable of generating theta-modulated gamma rhythms, and demonstrating electric field effects on those rhythms. First, theta-modulated gamma rhythms require specific inhibitory connectivity. In one configuration, GABAergic axo-dendritic feedback on pyramidal cells is only effective in proximal but not distal layers. An alternative configuration requires two distinct perisomatic interneuron classes, one exclusively receiving excitatory contacts, the other additionally targeted by inhibition. These observations suggest novel roles for particular classes of oriens and basket cells. The second major finding is that subthreshold electric fields robustly alter the balance between different rhythms. Independent of network configuration, positive electric fields decrease, while negative fields increase the theta/gamma ratio. Moreover, electric fields differentially affect average theta frequency depending on specific synaptic connectivity. These results support the testable prediction that subthreshold electric fields can alter hippocampal rhythms, suggesting new approaches to explore their cognitive functions and underlying circuitry. PMID:23053863

Theta phase precession and phase selectivity: a cognitive device description of neural coding

NASA Astrophysics Data System (ADS)

Zalay, Osbert C.; Bardakjian, Berj L.

2009-06-01

Information in neural systems is carried by way of phase and rate codes. Neuronal signals are processed through transformative biophysical mechanisms at the cellular and network levels. Neural coding transformations can be represented mathematically in a device called the cognitive rhythm generator (CRG). Incoming signals to the CRG are parsed through a bank of neuronal modes that orchestrate proportional, integrative and derivative transformations associated with neural coding. Mode outputs are then mixed through static nonlinearities to encode (spatio) temporal phase relationships. The static nonlinear outputs feed and modulate a ring device (limit cycle) encoding output dynamics. Small coupled CRG networks were created to investigate coding functionality associated with neuronal phase preference and theta precession in the hippocampus. Phase selectivity was found to be dependent on mode shape and polarity, while phase precession was a product of modal mixing (i.e. changes in the relative contribution or amplitude of mode outputs resulted in shifting phase preference). Nonlinear system identification was implemented to help validate the model and explain response characteristics associated with modal mixing; in particular, principal dynamic modes experimentally derived from a hippocampal neuron were inserted into a CRG and the neuron's dynamic response was successfully cloned. From our results, small CRG networks possessing disynaptic feedforward inhibition in combination with feedforward excitation exhibited frequency-dependent inhibitory-to-excitatory and excitatory-to-inhibitory transitions that were similar to transitions seen in a single CRG with quadratic modal mixing. This suggests nonlinear modal mixing to be a coding manifestation of the effect of network connectivity in shaping system dynamic behavior. We hypothesize that circuits containing disynaptic feedforward inhibition in the nervous system may be candidates for interpreting upstream rate codes to guide downstream processes such as phase precession, because of their demonstrated frequency-selective properties.

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.

Calcium-permeable α-Amino-3-hydroxy-5-methyl-4-isoxazolepropionic Acid Receptors Trigger Neuronal Nitric-oxide Synthase Activation to Promote Nerve Cell Death in an Src Kinase-dependent Fashion*

PubMed Central

Socodato, Renato; Santiago, Felipe N.; Portugal, Camila C.; Domingues, Ana F.; Santiago, Ana R.; Relvas, João B.; Ambrósio, António F.; Paes-de-Carvalho, Roberto

2012-01-01

In the retina information decoding is dependent on excitatory neurotransmission and is critically modulated by AMPA glutamate receptors. The Src-tyrosine kinase has been implicated in modulating neurotransmission in CNS. Thus, our main goal was to correlate AMPA-mediated excitatory neurotransmission with the modulation of Src activity in retinal neurons. Cultured retinal cells were used to access the effects of AMPA stimulation on nitric oxide (NO) production and Src phosphorylation. 4-Amino-5-methylamino-2′,7′-difluorofluorescein diacetate fluorescence mainly determined NO production, and immunocytochemistry and Western blotting evaluated Src activation. AMPA receptors activation rapidly up-regulated Src phosphorylation at tyrosine 416 (stimulatory site) and down-regulated phosphotyrosine 527 (inhibitory site) in retinal cells, an effect mainly mediated by calcium-permeable AMPA receptors. Interestingly, experiments confirmed that neuronal NOS was activated in response to calcium-permeable AMPA receptor stimulation. Moreover, data suggest NO pathway as a key regulatory signaling in AMPA-induced Src activation in neurons but not in glial cells. The NO donor SNAP (S-nitroso-N-acetyl-dl-penicillamine) and a soluble guanylyl cyclase agonist (YC-1) mimicked AMPA effect in Src Tyr-416 phosphorylation, reinforcing that Src activation is indeed modulated by the NO pathway. Gain and loss-of-function data demonstrated that ERK is a downstream target of AMPA-induced Src activation and NO signaling. Furthermore, AMPA stimulated NO production in organotypic retinal cultures and increased Src activity in the in vivo retina. Additionally, AMPA-induced apoptotic retinal cell death was regulated by both NOS and Src activity. Because Src activity is pivotal in several CNS regions, the data presented herein highlight that Src modulation is a critical step in excitatory retinal cell death. PMID:22992730

Calcium-permeable α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptors trigger neuronal nitric-oxide synthase activation to promote nerve cell death in an Src kinase-dependent fashion.

PubMed

Socodato, Renato; Santiago, Felipe N; Portugal, Camila C; Domingues, Ana F; Santiago, Ana R; Relvas, João B; Ambrósio, António F; Paes-de-Carvalho, Roberto

2012-11-09

In the retina information decoding is dependent on excitatory neurotransmission and is critically modulated by AMPA glutamate receptors. The Src-tyrosine kinase has been implicated in modulating neurotransmission in CNS. Thus, our main goal was to correlate AMPA-mediated excitatory neurotransmission with the modulation of Src activity in retinal neurons. Cultured retinal cells were used to access the effects of AMPA stimulation on nitric oxide (NO) production and Src phosphorylation. 4-Amino-5-methylamino-2',7'-difluorofluorescein diacetate fluorescence mainly determined NO production, and immunocytochemistry and Western blotting evaluated Src activation. AMPA receptors activation rapidly up-regulated Src phosphorylation at tyrosine 416 (stimulatory site) and down-regulated phosphotyrosine 527 (inhibitory site) in retinal cells, an effect mainly mediated by calcium-permeable AMPA receptors. Interestingly, experiments confirmed that neuronal NOS was activated in response to calcium-permeable AMPA receptor stimulation. Moreover, data suggest NO pathway as a key regulatory signaling in AMPA-induced Src activation in neurons but not in glial cells. The NO donor SNAP (S-nitroso-N-acetyl-DL-penicillamine) and a soluble guanylyl cyclase agonist (YC-1) mimicked AMPA effect in Src Tyr-416 phosphorylation, reinforcing that Src activation is indeed modulated by the NO pathway. Gain and loss-of-function data demonstrated that ERK is a downstream target of AMPA-induced Src activation and NO signaling. Furthermore, AMPA stimulated NO production in organotypic retinal cultures and increased Src activity in the in vivo retina. Additionally, AMPA-induced apoptotic retinal cell death was regulated by both NOS and Src activity. Because Src activity is pivotal in several CNS regions, the data presented herein highlight that Src modulation is a critical step in excitatory retinal cell death.

A Biophysical Neural Model To Describe Spatial Visual Attention

NASA Astrophysics Data System (ADS)

Hugues, Etienne; José, Jorge V.

2008-02-01

Visual scenes have enormous spatial and temporal information that are transduced into neural spike trains. Psychophysical experiments indicate that only a small portion of a spatial image is consciously accessible. Electrophysiological experiments in behaving monkeys have revealed a number of modulations of the neural activity in special visual area known as V4, when the animal is paying attention directly towards a particular stimulus location. The nature of the attentional input to V4, however, remains unknown as well as to the mechanisms responsible for these modulations. We use a biophysical neural network model of V4 to address these issues. We first constrain our model to reproduce the experimental results obtained for different external stimulus configurations and without paying attention. To reproduce the known neuronal response variability, we found that the neurons should receive about equal, or balanced, levels of excitatory and inhibitory inputs and whose levels are high as they are in in vivo conditions. Next we consider attentional inputs that can induce and reproduce the observed spiking modulations. We also elucidate the role played by the neural network to generate these modulations.

A Biophysical Neural Model To Describe Spatial Visual Attention

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

Hugues, Etienne; Jose, Jorge V.

2008-02-14

Visual scenes have enormous spatial and temporal information that are transduced into neural spike trains. Psychophysical experiments indicate that only a small portion of a spatial image is consciously accessible. Electrophysiological experiments in behaving monkeys have revealed a number of modulations of the neural activity in special visual area known as V4, when the animal is paying attention directly towards a particular stimulus location. The nature of the attentional input to V4, however, remains unknown as well as to the mechanisms responsible for these modulations. We use a biophysical neural network model of V4 to address these issues. We firstmore » constrain our model to reproduce the experimental results obtained for different external stimulus configurations and without paying attention. To reproduce the known neuronal response variability, we found that the neurons should receive about equal, or balanced, levels of excitatory and inhibitory inputs and whose levels are high as they are in in vivo conditions. Next we consider attentional inputs that can induce and reproduce the observed spiking modulations. We also elucidate the role played by the neural network to generate these modulations.« less

Mixed-mode oscillations and population bursting in the pre-Bötzinger complex

PubMed Central

Bacak, Bartholomew J; Kim, Taegyo; Smith, Jeffrey C; Rubin, Jonathan E; Rybak, Ilya A

2016-01-01

This study focuses on computational and theoretical investigations of neuronal activity arising in the pre-Bötzinger complex (pre-BötC), a medullary region generating the inspiratory phase of breathing in mammals. A progressive increase of neuronal excitability in medullary slices containing the pre-BötC produces mixed-mode oscillations (MMOs) characterized by large amplitude population bursts alternating with a series of small amplitude bursts. Using two different computational models, we demonstrate that MMOs emerge within a heterogeneous excitatory neural network because of progressive neuronal recruitment and synchronization. The MMO pattern depends on the distributed neuronal excitability, the density and weights of network interconnections, and the cellular properties underlying endogenous bursting. Critically, the latter should provide a reduction of spiking frequency within neuronal bursts with increasing burst frequency and a dependence of the after-burst recovery period on burst amplitude. Our study highlights a novel mechanism by which heterogeneity naturally leads to complex dynamics in rhythmic neuronal populations. DOI: http://dx.doi.org/10.7554/eLife.13403.001 PMID:26974345

The perforant path projection to hippocampal area CA1 in the rat hippocampal-entorhinal cortex combined slice.

PubMed

Empson, R M; Heinemann, U

1995-05-01

1. The perforant path projection from layer III of the entorhinal cortex to CA1 of the hippocampus was studied within a hippocampal-entorhinal combined slice preparation. We prevented contamination from the other main hippocampal pathways by removal of CA3 and the dentate gyrus. 2. Initially the projection was mapped using field potential recordings that suggested an excitatory sink in stratum lacunosum moleculare with an associated source in stratum pyramidale. 3. However, recording intracellularly from CA1 cells, stimulation of the perforant path produced prominent fast GABAA and slow GABAB IPSPs often preceded by small EPSPs. In a small number of cells we observed EPSPs only. 4. CNQX blocked excitatory and inhibitory responses. This indicated the presence of an intervening excitatory synapse between the inhibitory interneurone and the pyramidal cell. 5. Focal bicuculline applications revealed that the major site of GABAA inhibitory input was to stratum radiatum of CA1. 6. The inhibition activated by the perforant path was very effective at reducing simultaneously activated Schaffer collateral mediated EPSPs and suprathreshold-stimulated action potentials. 7. Blockade of fast inhibition increased excitability and enhanced slow inhibition. Both increases relied upon the activation of NMDA receptors. 8. Perforant path inputs activated prominent and effective disynaptic inhibition of CA1 cells. This has significance for the output of hippocampal processing during normal behaviour and also under pathological conditions.

Phenytoin attenuates the hyper-exciting neurotransmission in cultured embryonic cortical neurons.

PubMed

Chou, Ming-Yi; Lee, Chun-Yao; Liou, Horng-Huei; Pan, Chien-Yuan

2014-08-01

Phenytoin is an effective anti-epileptic drug that inhibits Na(+) channel activities; however, how phenytoin modulates synaptic transmission to soothe epileptic symptoms is not clear. To characterize the effects of phenytoin regulation on neurotransmission, we studied the electrophysical properties of cultured embryonic cortical neurons. Phenytoin inhibited the inward Na(+) current in a dose-dependent manner with an IC50 of 16.8 μM, and at 100 μM, the inhibitory effect of phenytoin on the Na(+) current was proportional to the frequency applied. In cultured neurons, phenytoin significantly decreased the action potential firing rate and the peak potential. To study the effect of phenytoin in neurotransmission, we measured the Ca(2+) responses from stimulated target neurons and their neighboring neurons. Phenytoin significantly suppressed the Ca(2+) responses evoked by strong stimulations in the target and neighboring neurons, and exerted a decreased inhibitory effect under moderate stimulation. Picrotoxin, a GABAA receptor antagonist, enhanced the recorded spontaneous excitatory postsynaptic current activities. After picrotoxin-induced enhancement, phenytoin had a more pronounced effect on the suppression of the spontaneous hyper-exciting excitatory postsynaptic current (>100 pA), but it only mildly inhibited the general excitatory postsynaptic current. Our results demonstrate that phenytoin suppresses the efficacy of neurotransmission especially for the high-frequency stimulation by reducing the Na(+) channel activity and can potentially alleviate epileptiform activity. Copyright © 2014 Elsevier Ltd. All rights reserved.

Linear summation of outputs in a balanced network model of motor cortex

PubMed Central

Capaday, Charles; van Vreeswijk, Carl

2015-01-01

Given the non-linearities of the neural circuitry's elements, we would expect cortical circuits to respond non-linearly when activated. Surprisingly, when two points in the motor cortex are activated simultaneously, the EMG responses are the linear sum of the responses evoked by each of the points activated separately. Additionally, the corticospinal transfer function is close to linear, implying that the synaptic interactions in motor cortex must be effectively linear. To account for this, here we develop a model of motor cortex composed of multiple interconnected points, each comprised of reciprocally connected excitatory and inhibitory neurons. We show how non-linearities in neuronal transfer functions are eschewed by strong synaptic interactions within each point. Consequently, the simultaneous activation of multiple points results in a linear summation of their respective outputs. We also consider the effects of reduction of inhibition at a cortical point when one or more surrounding points are active. The network response in this condition is linear over an approximately two- to three-fold decrease of inhibitory feedback strength. This result supports the idea that focal disinhibition allows linear coupling of motor cortical points to generate movement related muscle activation patterns; albeit with a limitation on gain control. The model also explains why neural activity does not spread as far out as the axonal connectivity allows, whilst also explaining why distant cortical points can be, nonetheless, functionally coupled by focal disinhibition. Finally, we discuss the advantages that linear interactions at the cortical level afford to motor command synthesis. PMID:26097452

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

Sleep Impairment and Reduced Interneuron Excitability in a Mouse Model of Dravet Syndrome

PubMed Central

Kalume, Franck; Oakley, John C.; Westenbroek, Ruth E.; Gile, Jennifer; de la Iglesia, Horacio O.; Scheuer, Todd; Catterall, William A.

2015-01-01

Dravet Syndrome (DS) is caused by heterozygous loss-of-function mutations in voltage-gated sodium channel NaV1.1. Our genetic mouse model of DS recapitulates its severe seizures and premature death. Sleep disturbance is common in DS, but its mechanism is unknown. Electroencephalographic studies revealed abnormal sleep in DS mice, including reduced delta wave power, reduced sleep spindles, increased brief wakes, and numerous interictal spikes in Non-Rapid-Eye-Movement sleep. Theta power was reduced in Rapid-Eye-Movement sleep. Mice with NaV1.1 deleted specifically in forebrain interneurons exhibited similar sleep pathology to DS mice, but without changes in circadian rhythm. Sleep architecture depends on oscillatory activity in the thalamocortical network generated by excitatory neurons in the ventrobasal nucleus (VBN) of the thalamus and inhibitory GABAergic neurons in the reticular nucleus of the thalamus (RNT). Whole-cell NaV current was reduced in GABAergic RNT neurons but not in VBN neurons. Rebound firing of action potentials following hyperpolarization, the signature firing pattern of RNT neurons during sleep, was also reduced. These results demonstrate imbalance of excitatory vs. inhibitory neurons in this circuit. As predicted from this functional impairment, we found substantial deficit in homeostatic rebound of slow wave activity following sleep deprivation. Although sleep disorders in epilepsies have been attributed to anti-epileptic drugs, our results show that sleep disorder in DS mice arises from loss of NaV1.1 channels in forebrain GABAergic interneurons without drug treatment. Impairment of NaV currents and excitability of GABAergic RNT neurons are correlated with impaired sleep quality and homeostasis in these mice. PMID:25766678

Human Brain-Derived Aβ Oligomers Bind to Synapses and Disrupt Synaptic Activity in a Manner That Requires APP.

PubMed

Wang, Zemin; Jackson, Rosemary J; Hong, Wei; Taylor, Walter M; Corbett, Grant T; Moreno, Arturo; Liu, Wen; Li, Shaomin; Frosch, Matthew P; Slutsky, Inna; Young-Pearse, Tracy L; Spires-Jones, Tara L; Walsh, Dominic M

2017-12-06

Compelling genetic evidence links the amyloid precursor protein (APP) to Alzheimer's disease (AD) and several theories have been advanced to explain the relationship. A leading hypothesis proposes that a small amphipathic fragment of APP, the amyloid β-protein (Aβ), self-associates to form soluble aggregates that impair synaptic and network activity. Here, we used the most disease-relevant form of Aβ, protein isolated from AD brain. Using this material, we show that the synaptotoxic effects of Aβ depend on expression of APP and that the Aβ-mediated impairment of synaptic plasticity is accompanied by presynaptic effects that disrupt the excitatory/inhibitory (E/I) balance. The net increase in the E/I ratio and inhibition of plasticity are associated with Aβ localizing to synapses and binding of soluble Aβ aggregates to synapses requires the expression of APP. Our findings indicate a role for APP in AD pathogenesis beyond the generation of Aβ and suggest modulation of APP expression as a therapy for AD. SIGNIFICANCE STATEMENT Here, we report on the plasticity-disrupting effects of amyloid β-protein (Aβ) isolated from Alzheimer's disease (AD) brain and the requirement of amyloid precursor protein (APP) for these effects. We show that Aβ-containing AD brain extracts block hippocampal LTP, augment glutamate release probability, and disrupt the excitatory/inhibitory balance. These effects are associated with Aβ localizing to synapses and genetic ablation of APP prevents both Aβ binding and Aβ-mediated synaptic dysfunctions. Our results emphasize the importance of APP in AD and should stimulate new studies to elucidate APP-related targets suitable for pharmacological manipulation. Copyright © 2017 the authors 0270-6474/17/3711947-20$15.00/0.

Altered Modulation of Silent Period in Tongue Motor Cortex of Persistent Developmental Stuttering in Relation to Stuttering Severity.

PubMed

Busan, Pierpaolo; Del Ben, Giovanni; Bernardini, Simona; Natarelli, Giulia; Bencich, Marco; Monti, Fabrizio; Manganotti, Paolo; Battaglini, Piero Paolo

2016-01-01

Motor balance in developmental stuttering (DS) was investigated with Transcranial Magnetic Stimulation (TMS), with the aim to define novel neural markers of persistent DS in adulthood. Eleven DS adult males were evaluated with TMS on tongue primary motor cortex, compared to 15 matched fluent speakers, in a "state" condition (i.e. stutterers vs. fluent speakers, no overt stuttering). Motor and silent period thresholds (SPT), recruitment curves, and silent period durations were acquired by recording tongue motor evoked potentials. Tongue silent period duration was increased in DS, especially in the left hemisphere (P<0.05; Hedge's g or Cohen's dunbiased = 1.054, i.e. large effect size), suggesting a "state" condition of higher intracortical inhibition in left motor cortex networks. Differences in motor thresholds (different excitatory/inhibitory ratios in DS) were evident, as well as significant differences in SPT. In fluent speakers, the left hemisphere may be marginally more excitable than the right one in motor thresholds at lower muscular activation, while active motor thresholds and SPT were higher in the left hemisphere of DS with respect to the right one, resulting also in a positive correlation with stuttering severity. Pre-TMS electromyography data gave overlapping evidence. Findings suggest the existence of a complex intracortical balance in DS tongue primary motor cortex, with a particular interplay between excitatory and inhibitory mechanisms, also in neural substrates related to silent periods. Findings are discussed with respect to functional and structural impairments in stuttering, and are also proposed as novel neural markers of a stuttering "state" in persistent DS, helping to define more focused treatments (e.g. neuro-modulation).

Altered Modulation of Silent Period in Tongue Motor Cortex of Persistent Developmental Stuttering in Relation to Stuttering Severity

PubMed Central

Busan, Pierpaolo; Del Ben, Giovanni; Bernardini, Simona; Natarelli, Giulia; Bencich, Marco; Monti, Fabrizio; Manganotti, Paolo; Battaglini, Piero Paolo

2016-01-01

Motor balance in developmental stuttering (DS) was investigated with Transcranial Magnetic Stimulation (TMS), with the aim to define novel neural markers of persistent DS in adulthood. Eleven DS adult males were evaluated with TMS on tongue primary motor cortex, compared to 15 matched fluent speakers, in a “state” condition (i.e. stutterers vs. fluent speakers, no overt stuttering). Motor and silent period thresholds (SPT), recruitment curves, and silent period durations were acquired by recording tongue motor evoked potentials. Tongue silent period duration was increased in DS, especially in the left hemisphere (P<0.05; Hedge’s g or Cohen’s dunbiased = 1.054, i.e. large effect size), suggesting a “state” condition of higher intracortical inhibition in left motor cortex networks. Differences in motor thresholds (different excitatory/inhibitory ratios in DS) were evident, as well as significant differences in SPT. In fluent speakers, the left hemisphere may be marginally more excitable than the right one in motor thresholds at lower muscular activation, while active motor thresholds and SPT were higher in the left hemisphere of DS with respect to the right one, resulting also in a positive correlation with stuttering severity. Pre-TMS electromyography data gave overlapping evidence. Findings suggest the existence of a complex intracortical balance in DS tongue primary motor cortex, with a particular interplay between excitatory and inhibitory mechanisms, also in neural substrates related to silent periods. Findings are discussed with respect to functional and structural impairments in stuttering, and are also proposed as novel neural markers of a stuttering “state” in persistent DS, helping to define more focused treatments (e.g. neuro-modulation). PMID:27711148

Effects of third trimester-equivalent ethanol exposure on Cl(-) co-transporter expression, network activity, and GABAergic transmission in the CA3 hippocampal region of neonatal rats.

PubMed

Everett, Julie C; Licón-Muñoz, Yamhilette; Valenzuela, C Fernando

2012-09-01

Fetal alcohol spectrum disorders are often associated with structural and functional hippocampal abnormalities, leading to long-lasting learning and memory deficits. The mechanisms underlying these abnormalities are not fully understood. Here, we investigated whether ethanol exposure during the 3rd trimester-equivalent period alters spontaneous network activity that is involved in neuronal circuit development in the CA3 hippocampal region. This activity is driven by GABA(A) receptors, which can have excitatory actions in developing neurons as a consequence of greater expression of the Cl(-) importer, NKCC1, with respect to expression of the Cl(-) exporter, KCC2, resulting in high [Cl(-)](i). Rat pups were exposed to ethanol vapor from postnatal day (P) 2-16 (4 h/day). Weight gain was significantly reduced in pups exposed to ethanol compared to control at P15 and 16. Brain slices were prepared immediately after the end of the 4-h exposure on P4-16 and experiments were also performed under ethanol-free conditions at the end of the exposure paradigm (P17-22). Ethanol exposure did not significantly affect expression of KCC2 or NKCC1, nor did it affect network activity in the CA3 hippocampal region. Ethanol exposure significantly decreased the frequency (at P9-11) and increased the amplitude (at P5-8 and P17-21) of GABA(A) receptor-mediated miniature postsynaptic currents. These data suggest that repeated in vivo exposure to ethanol during the 3rd trimester-equivalent period alters GABAergic transmission in the CA3 hippocampal region, an effect that could lead to abnormal circuit maturation and perhaps contribute to the pathophysiology of fetal alcohol spectrum disorders. Copyright © 2012 Elsevier Inc. All rights reserved.

Pulvinar thalamic nucleus allows for asynchronous spike propagation through the cortex

PubMed Central

Cortes, Nelson; van Vreeswijk, Carl

2015-01-01

We create two multilayered feedforward networks composed of excitatory and inhibitory integrate-and-fire neurons in the balanced state to investigate the role of cortico-pulvino-cortical connections. The first network consists of ten feedforward levels where a Poisson spike train with varying firing rate is applied as an input in layer one. Although the balanced state partially avoids spike synchronization during the transmission, the average firing-rate in the last layer either decays or saturates depending on the feedforward pathway gain. The last layer activity is almost independent of the input even for a carefully chosen intermediate gain. Adding connections to the feedforward pathway by a nine areas Pulvinar structure improves the firing-rate propagation to become almost linear among layers. Incoming strong pulvinar spikes balance the low feedforward gain to have a unit input-output relation in the last layer. Pulvinar neurons evoke a bimodal activity depending on the magnitude input: synchronized spike bursts between 20 and 80 Hz and an asynchronous activity for very both low and high frequency inputs. In the first regime, spikes of last feedforward layer neurons are asynchronous with weak, low frequency, oscillations in the rate. Here, the uncorrelated incoming feedforward pathway washes out the synchronized thalamic bursts. In the second regime, spikes in the whole network are asynchronous. As the number of cortical layers increases, long-range pulvinar connections can link directly two or more cortical stages avoiding their either saturation or gradual activity falling. The Pulvinar acts as a shortcut that supplies the input-output firing-rate relationship of two separated cortical areas without changing the strength of connections in the feedforward pathway. PMID:26042026

Metastable neural dynamics mediates expectation

NASA Astrophysics Data System (ADS)

Mazzucato, Luca; La Camera, Giancarlo; Fontanini, Alfredo

Sensory stimuli are processed faster when their presentation is expected compared to when they come as a surprise. We previously showed that, in multiple single-unit recordings from alert rat gustatory cortex, taste stimuli can be decoded faster from neural activity if preceded by a stimulus-predicting cue. However, the specific computational process mediating this anticipatory neural activity is unknown. Here, we propose a biologically plausible model based on a recurrent network of spiking neurons with clustered architecture. In the absence of stimulation, the model neural activity unfolds through sequences of metastable states, each state being a population vector of firing rates. We modeled taste stimuli and cue (the same for all stimuli) as two inputs targeting subsets of excitatory neurons. As observed in experiment, stimuli evoked specific state sequences, characterized in terms of `coding states', i.e., states occurring significantly more often for a particular stimulus. When stimulus presentation is preceded by a cue, coding states show a faster and more reliable onset, and expected stimuli can be decoded more quickly than unexpected ones. This anticipatory effect is unrelated to changes of firing rates in stimulus-selective neurons and is absent in homogeneous balanced networks, suggesting that a clustered organization is necessary to mediate the expectation of relevant events. Our results demonstrate a novel mechanism for speeding up sensory coding in cortical circuits. NIDCD K25-DC013557 (LM); NIDCD R01-DC010389 (AF); NSF IIS-1161852 (GL).

Recognition of abstract objects via neural oscillators: interaction among topological organization, associative memory and gamma band synchronization.

PubMed

Ursino, Mauro; Magosso, Elisa; Cuppini, Cristiano

2009-02-01

Synchronization of neural activity in the gamma band is assumed to play a significant role not only in perceptual processing, but also in higher cognitive functions. Here, we propose a neural network of Wilson-Cowan oscillators to simulate recognition of abstract objects, each represented as a collection of four features. Features are ordered in topological maps of oscillators connected via excitatory lateral synapses, to implement a similarity principle. Experience on previous objects is stored in long-range synapses connecting the different topological maps, and trained via timing dependent Hebbian learning (previous knowledge principle). Finally, a downstream decision network detects the presence of a reliable object representation, when all features are oscillating in synchrony. Simulations performed giving various simultaneous objects to the network (from 1 to 4), with some missing and/or modified properties suggest that the network can reconstruct objects, and segment them from the other simultaneously present objects, even in case of deteriorated information, noise, and moderate correlation among the inputs (one common feature). The balance between sensitivity and specificity depends on the strength of the Hebbian learning. Achieving a correct reconstruction in all cases, however, requires ad hoc selection of the oscillation frequency. The model represents an attempt to investigate the interactions among topological maps, autoassociative memory, and gamma-band synchronization, for recognition of abstract objects.

Short-term field stimulation mimics synaptic maturation of hippocampal synapses

PubMed Central

Bagley, Elena E; Westbrook, Gary L

2012-01-01

Many aspects of synaptic transmission are modified during development, reflecting not only the consequence of developmental programmes of gene expression, but also the effects of ongoing neural activity. We investigated the role of synaptic activity in the maturation of Schaffer collateral (SC)–CA1 synapses using sustained low frequency field stimulation of acute brain slices. Between postnatal days 4–6 and 14–16, mouse SC–CA1 synapses in naïve slices showed a developmental decrease in the probability of transmitter release (Pr) and an increase in the contribution of GluN2A (NR2A) subunits to the NMDA receptor-mediated excitatory postsynaptic current (EPSC). Surprisingly, these developmental changes could be mimicked by short term (4 h) in vitro synaptic activity in slices taken from postnatal days (PND) 4–6 mice. However, different activity levels were required to alter release probability compared to the NMDA receptor subunit composition. Spontaneous synaptic activity was sufficient to alter the NMDA receptor subunit composition, but sustained low-frequency field stimulation of the brain slice (0.1 Hz, 4 h) was necessary to reduce release probability, as assessed 1 h following the cessation of stimulation. The protein synthesis inhibitor anisomycin blocked the effect of field stimulation on release probability. These results indicate that features of mature excitatory synapses can be rapidly induced in immature neurons. The activity dependence of the Pr and NMDA receptor subunit composition serves as a sensitive indicator of prior neural activity, and provides dual mechanisms for homeostatic control of excitatory synaptic efficacy. PMID:22351628

Short-term field stimulation mimics synaptic maturation of hippocampal synapses.

PubMed

Bagley, Elena E; Westbrook, Gary L

2012-04-01

Many aspects of synaptic transmission are modified during development, reflecting not only the consequence of developmental programmes of gene expression, but also the effects of ongoing neural activity. We investigated the role of synaptic activity in the maturation of Schaffer collateral (SC)-CA1 synapses using sustained low frequency field stimulation of acute brain slices. Between postnatal days 4-6 and 14-16, mouse SC-CA1 synapses in naïve slices showed a developmental decrease in the probability of transmitter release (P(r)) and an increase in the contribution of GluN2A (NR2A) subunits to the NMDA receptor-mediated excitatory postsynaptic current (EPSC). Surprisingly, these developmental changes could be mimicked by short term (4 h) in vitro synaptic activity in slices taken from postnatal days (PND) 4-6 mice. However, different activity levels were required to alter release probability compared to the NMDA receptor subunit composition. Spontaneous synaptic activity was sufficient to alter the NMDA receptor subunit composition, but sustained low-frequency field stimulation of the brain slice (0.1 Hz, 4 h) was necessary to reduce release probability, as assessed 1 h following the cessation of stimulation. The protein synthesis inhibitor anisomycin blocked the effect of field stimulation on release probability. These results indicate that features of mature excitatory synapses can be rapidly induced in immature neurons. The activity dependence of the P(r) and NMDA receptor subunit composition serves as a sensitive indicator of prior neural activity, and provides dual mechanisms for homeostatic control of excitatory synaptic efficacy.

Pubertal development and regulation

PubMed Central

Abreu, Ana Paula; Kaiser, Ursula B

2016-01-01

Puberty marks the end of childhood and is a period when individuals undergo physiological and psychological changes to achieve sexual maturation and fertility. The hypothalamic-pituitary-gonadal axis controls puberty and reproduction and is tightly regulated by a complex network of excitatory and inhibitory factors. This axis is active in the embryonic and early postnatal stages of life and is subsequently restrained during childhood, and its reactivation culminates in puberty initiation. The mechanisms underlying this reactivation are not completely known. The age of puberty onset varies between individuals and the timing of puberty initiation is associated with several health outcomes in adult life. In this Series paper, we discuss pubertal markers, epidemiological trends of puberty initiation over time, and the mechanisms whereby genetic, metabolic, and other factors control secretion of gonadotropin-releasing hormone to determine initiation of puberty. PMID:26852256

Dopamine-dependent effects on basal and glutamate stimulated network dynamics in cultured hippocampal neurons.

PubMed

Li, Yan; Chen, Xin; Dzakpasu, Rhonda; Conant, Katherine

2017-02-01

Oscillatory activity occurs in cortical and hippocampal networks with specific frequency ranges thought to be critical to working memory, attention, differentiation of neuronal precursors, and memory trace replay. Synchronized activity within relatively large neuronal populations is influenced by firing and bursting frequency within individual cells, and the latter is modulated by changes in intrinsic membrane excitability and synaptic transmission. Published work suggests that dopamine, a potent modulator of learning and memory, acts on dopamine receptor 1-like dopamine receptors to influence the phosphorylation and trafficking of glutamate receptor subunits, along with long-term potentiation of excitatory synaptic transmission in striatum and prefrontal cortex. Prior studies also suggest that dopamine can influence voltage gated ion channel function and membrane excitability in these regions. Fewer studies have examined dopamine's effect on related endpoints in hippocampus, or potential consequences in terms of network burst dynamics. In this study, we record action potential activity using a microelectrode array system to examine the ability of dopamine to modulate baseline and glutamate-stimulated bursting activity in an in vitro network of cultured murine hippocampal neurons. We show that dopamine stimulates a dopamine type-1 receptor-dependent increase in number of overall bursts within minutes of its application. Notably, however, at the concentration used herein, dopamine did not increase the overall synchrony of bursts between electrodes. Although the number of bursts normalizes by 40 min, bursting in response to a subsequent glutamate challenge is enhanced by dopamine pretreatment. Dopamine-dependent potentiation of glutamate-stimulated bursting was not observed when the two modulators were administered concurrently. In parallel, pretreatment of murine hippocampal cultures with dopamine stimulated lasting increases in the phosphorylation of the glutamate receptor subunit GluA1 at serine 845. This effect is consistent with the possibility that enhanced membrane insertion of GluAs may contribute to a more slowly evolving dopamine-dependent potentiation of glutamate-stimulated bursting. Together, these results are consistent with the possibility that dopamine can influence hippocampal bursting by at least two temporally distinct mechanisms, contributing to an emerging appreciation of dopamine-dependent effects on network activity in the hippocampus. © 2016 International Society for Neurochemistry.

Physiology of Normal Esophageal Motility

PubMed Central

Goyal, Raj K; Chaudhury, Arun

2009-01-01

The esophagus consists of two different parts. In humans, the cervical esophagus is composed of striated muscles and the thoracic esophagus is composed of phasic smooth muscles. The striated muscle esophagus is innervated by the lower motor neurons and peristalsis in this segment is due to sequential activation of the motor neurons in the nucleus ambiguus. Both primary and secondary peristaltic contractions are centrally mediated. The smooth muscle of esophagus is phasic in nature and is innervated by intramural inhibitory (nitric oxide releasing) and excitatory (acetylcholine releasing) neurons that receive inputs from separate sets of preganglionic neurons located in the dorsal motor nucleus of vagus. The primary peristalsis in this segment involves both central and peripheral mechanisms. The primary peristalsis consist of inhibition (called deglutitive inhibition) followed by excitation. The secondary peristalsis is entirely due to peripheral mechanisms and also involves inhibition followed by excitation. The lower esophageal sphincter (LES) is characterized by tonic muscle that is different from the muscle of the esophageal body. The LES, like the esophageal body smooth muscle, is also innervated by the inhibitory and excitatory neurons. The LES maintains tonic closure due to its myogenic property. The LES tone is modulated by the inhibitory and the excitatory nerves. Inhibitory nerves mediate LES relaxation and the excitatory nerves mediate reflex contraction or rebound contraction of the LES. Clinical disorders of esophageal motility can be classified on the basis of disorders of the inhibitory and excitatory innervations and the smooth muscles. PMID:18364578

Neural Oscillations and Synchrony in Brain Dysfunction and Neuropsychiatric Disorders: It's About Time.

PubMed

Mathalon, Daniel H; Sohal, Vikaas S

2015-08-01

Neural oscillations are rhythmic fluctuations over time in the activity or excitability of single neurons, local neuronal populations or "assemblies," and/or multiple regionally distributed neuronal assemblies. Synchronized oscillations among large numbers of neurons are evident in electrocorticographic, electroencephalographic, magnetoencephalographic, and local field potential recordings and are generally understood to depend on inhibition that paces assemblies of excitatory neurons to produce alternating temporal windows of reduced and increased excitability. Synchronization of neural oscillations is supported by the extensive networks of local and long-range feedforward and feedback bidirectional connections between neurons. Here, we review some of the major methods and measures used to characterize neural oscillations, with a focus on gamma oscillations. Distinctions are drawn between stimulus-independent oscillations recorded during resting states or intervals between task events, stimulus-induced oscillations that are time locked but not phase locked to stimuli, and stimulus-evoked oscillations that are both time and phase locked to stimuli. Synchrony of oscillations between recording sites, and between the amplitudes and phases of oscillations of different frequencies (cross-frequency coupling), is described and illustrated. Molecular mechanisms underlying gamma oscillations are also reviewed. Ultimately, understanding the temporal organization of neuronal network activity, including interactions between neural oscillations, is critical for elucidating brain dysfunction in neuropsychiatric disorders.

Circuit mechanisms of hippocampal reactivation during sleep.

PubMed

Malerba, Paola; Bazhenov, Maxim

2018-05-01

The hippocampus is important for memory and learning, being a brain site where initial memories are formed and where sharp wave - ripples (SWR) are found, which are responsible for mapping recent memories to long-term storage during sleep-related memory replay. While this conceptual schema is well established, specific intrinsic and network-level mechanisms driving spatio-temporal patterns of hippocampal activity during sleep, and specifically controlling off-line memory reactivation are unknown. In this study, we discuss a model of hippocampal CA1-CA3 network generating spontaneous characteristic SWR activity. Our study predicts the properties of CA3 input which are necessary for successful CA1 ripple generation and the role of synaptic interactions and intrinsic excitability in spike sequence replay during SWRs. Specifically, we found that excitatory synaptic connections promote reactivation in both CA3 and CA1, but the different dynamics of sharp waves in CA3 and ripples in CA1 result in a differential role for synaptic inhibition in modulating replay: promoting spike sequence specificity in CA3 but not in CA1 areas. Finally, we describe how awake learning of spatial trajectories leads to synaptic changes sufficient to drive hippocampal cells' reactivation during sleep, as required for sleep-related memory consolidation. Copyright © 2018 Elsevier Inc. All rights reserved.

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

Rare excitatory amino acid from flowers of zonal geranium responsible for paralyzing the Japanese beetle.

PubMed

Ranger, Christopher M; Winter, Rudolph E; Singh, Ajay P; Reding, Michael E; Frantz, Jonathan M; Locke, James C; Krause, Charles R

2011-01-25

The Japanese beetle (JB), Popillia japonica, exhibits rapid paralysis after consuming flower petals of zonal geranium, Pelargonium x hortorum. Activity-guided fractionations were conducted with polar flower petal extracts from P. x hortorum cv. Nittany Lion Red, which led to the isolation of a paralysis-inducing compound. High-resolution-MS and NMR ((1)H, (13)C, COSY, heteronuclear sequential quantum correlation, heteronuclear multiple bond correlation) analysis identified the paralytic compound as quisqualic acid (C(5)H(7)N(3)O(5)), a known but rare agonist of excitatory amino acid receptors. Optical rotation measurements and chiral HPLC analysis determined an L-configuration. Geranium-derived and synthetic L-quisqualic acid demonstrated the same positive paralytic dose-response. Isolation of a neurotoxic, excitatory amino acid from zonal geranium establishes the phytochemical basis for induced paralysis of the JB, which had remained uncharacterized since the phenomenon was first described in 1920.

A recurrent network mechanism of time integration in perceptual decisions.

PubMed

Wong, Kong-Fatt; Wang, Xiao-Jing

2006-01-25

Recent physiological studies using behaving monkeys revealed that, in a two-alternative forced-choice visual motion discrimination task, reaction time was correlated with ramping of spike activity of lateral intraparietal cortical neurons. The ramping activity appears to reflect temporal accumulation, on a timescale of hundreds of milliseconds, of sensory evidence before a decision is reached. To elucidate the cellular and circuit basis of such integration times, we developed and investigated a simplified two-variable version of a biophysically realistic cortical network model of decision making. In this model, slow time integration can be achieved robustly if excitatory reverberation is primarily mediated by NMDA receptors; our model with only fast AMPA receptors at recurrent synapses produces decision times that are not comparable with experimental observations. Moreover, we found two distinct modes of network behavior, in which decision computation by winner-take-all competition is instantiated with or without attractor states for working memory. Decision process is closely linked to the local dynamics, in the "decision space" of the system, in the vicinity of an unstable saddle steady state that separates the basins of attraction for the two alternative choices. This picture provides a rigorous and quantitative explanation for the dependence of performance and response time on the degree of task difficulty, and the reason for which reaction times are longer in error trials than in correct trials as observed in the monkey experiment. Our reduced two-variable neural model offers a simple yet biophysically plausible framework for studying perceptual decision making in general.

Computational modeling of spiking neural network with learning rules from STDP and intrinsic plasticity

NASA Astrophysics Data System (ADS)

Li, Xiumin; Wang, Wei; Xue, Fangzheng; Song, Yongduan

2018-02-01

Recently there has been continuously increasing interest in building up computational models of spiking neural networks (SNN), such as the Liquid State Machine (LSM). The biologically inspired self-organized neural networks with neural plasticity can enhance the capability of computational performance, with the characteristic features of dynamical memory and recurrent connection cycles which distinguish them from the more widely used feedforward neural networks. Despite a variety of computational models for brain-like learning and information processing have been proposed, the modeling of self-organized neural networks with multi-neural plasticity is still an important open challenge. The main difficulties lie in the interplay among different forms of neural plasticity rules and understanding how structures and dynamics of neural networks shape the computational performance. In this paper, we propose a novel approach to develop the models of LSM with a biologically inspired self-organizing network based on two neural plasticity learning rules. The connectivity among excitatory neurons is adapted by spike-timing-dependent plasticity (STDP) learning; meanwhile, the degrees of neuronal excitability are regulated to maintain a moderate average activity level by another learning rule: intrinsic plasticity (IP). Our study shows that LSM with STDP+IP performs better than LSM with a random SNN or SNN obtained by STDP alone. The noticeable improvement with the proposed method is due to the better reflected competition among different neurons in the developed SNN model, as well as the more effectively encoded and processed relevant dynamic information with its learning and self-organizing mechanism. This result gives insights to the optimization of computational models of spiking neural networks with neural plasticity.

Calcium dynamics in cardiac excitatory and non-excitatory cells and the role of gap junction.

PubMed

Das, Phonindra Nath; Mehrotra, Parul; Mishra, Aseem; Bairagi, Nandadulal; Chatterjee, Samrat

2017-07-01

Calcium ions aid in the generation of action potential in myocytes and are responsible for the excitation-contraction coupling of heart. The heart muscle has specialized patches of cells, called excitatory cells (EC) such as the Sino-atrial node cells capable of auto-generation of action potential and cells which receive signals from the excitatory cells, called non-excitatory cells (NEC) such as cells of the ventricular and auricular walls. In order to understand cardiac calcium homeostasis, it is, therefore, important to study the calcium dynamics taking into account both types of cardiac cells. Here we have developed a model to capture the calcium dynamics in excitatory and non-excitatory cells taking into consideration the gap junction mediated calcium ion transfer from excitatory cell to non-excitatory cell. Our study revealed that the gap junctional coupling between excitatory and non-excitatory cells plays important role in the calcium dynamics. It is observed that any reduction in the functioning of gap junction may result in abnormal calcium oscillations in NEC, even when the calcium dynamics is normal in EC cell. Sensitivity of gap junction is observed to be independent of the pacing rate and hence a careful monitoring is required to maintain normal cardiomyocyte condition. It also highlights that sarcoplasmic reticulum may not be always able to control the amount of cytoplasmic calcium under the condition of calcium overload. Copyright © 2017 Elsevier Inc. All rights reserved.

Group II and III metabotropic glutamate receptors and the control of the nucleus reticularis thalami input to rat thalamocortical neurones in vitro.

PubMed

Turner, J P; Salt, T E

2003-01-01

Intracellular recordings were made from neurones in the thalamic reticular nucleus (TRN) and ventro-basal (VB) thalamus in slices of rat midbrain in vitro. Electrical stimulation of the medial lemniscus or TRN resulted in the generation of complex synaptic potentials containing disynaptic inhibitory post-synaptic potentials (IPSPs) in VB thalamocortical neurones. Analysis of the excitatory synaptic responses in TRN neurones indicates they can produce burst output response irrespective of the level of sub-threshold membrane potential. This suggests that network-evoked IPSPs in VB thalamocortical neurones occur following a burst of TRN action potentials. Using ionotropic glutamate receptor antagonists, the activation of these disynaptic events was blocked, and the monosynaptic IPSPs that resulted from the direct activation of the TRN could be isolated. The selective Group II agonists LY354740 (1-10 microM) and N-acetyl-aspartyl-glutamate (NAAG; 100-500 microM) both caused a reversible depression of these monosynaptic TRN IPSPs without any effect on membrane potential or input resistance. Likewise, the specific Group III agonist L-2-amino-4-phosphonobutanoate (10-500 microM), but not (RS)-4-phosphonophenylglycine (1 and 30 microM) also caused a reversible depression of these IPSPs, again without any effect on membrane potential or input resistance.Thus, the IPSPs recorded in VB thalamocortical neurones, evoked by TRN activation, can be depressed by the activation of either Group II or III metabotropic glutamate receptors. This is consistent with the location of these receptor types on the presynaptic terminals of TRN axons in the VB thalamus. This raises the possibility that, during periods of intense excitatory activity, glutamate release could influence the release of GABA from TRN axon terminals in the thalamus. In addition, as NAAG is located in the axons and terminals arising from the TRN, there is the possibility that this dipeptide is also released by these terminals to control the release of GABA during periods of high activity in the TRN.

Loss of Balance between Striatal Feedforward Inhibition and Corticostriatal Excitation Leads to Tremor.

PubMed

Oran, Yael; Bar-Gad, Izhar

2018-02-14

Fast-spiking interneurons (FSIs) exert powerful inhibitory control over the striatum and are hypothesized to balance the massive excitatory cortical and thalamic input to this structure. We recorded neuronal activity in the dorsolateral striatum and globus pallidus (GP) concurrently with the detailed movement kinematics of freely behaving female rats before and after selective inhibition of FSI activity using IEM-1460 microinjections. The inhibition led to the appearance of episodic rest tremor in the body part that depended on the somatotopic location of the injection within the striatum. The tremor was accompanied by coherent oscillations in the local field potential (LFP). Individual neuron activity patterns became oscillatory and coherent in the tremor frequency. Striatal neurons, but not GP neurons, displayed additional temporal, nonoscillatory correlations. The subsequent reduction in the corticostriatal input following muscimol injection to the corresponding somatotopic location in the primary motor cortex led to disruption of the tremor and a reduction of the LFP oscillations and individual neuron's phase-locked activity. The breakdown of the normal balance of excitation and inhibition in the striatum has been shown previously to be related to different motor abnormalities. Our results further indicate that the balance between excitatory corticostriatal input and feedforward FSI inhibition is sufficient to break down the striatal decorrelation process and generate oscillations resulting in rest tremor typical of multiple basal ganglia disorders. SIGNIFICANCE STATEMENT Fast-spiking interneurons (FSIs) play a key role in normal striatal processing by exerting powerful inhibitory control over the network. FSI malfunctions have been associated with abnormal processing of information within the striatum that leads to multiple movement disorders. Here, we study the changes in neuronal activity and movement kinematics following selective inhibition of these neurons. The injections led to the appearance of episodic rest tremor, accompanied by coherent oscillations in neuronal activity, which was reversed following corticostriatal inhibition. These results suggest that the balance between corticostriatal excitation and feedforward FSI inhibition is crucial for maintaining the striatal decorrelation process, and that its breakdown leads to the formation of oscillations resulting in rest tremor typical of multiple basal ganglia disorders. Copyright © 2018 the authors 0270-6474/18/381699-12$15.00/0.

Paraflocculus plays a role in salicylate-induced tinnitus.

PubMed

Du, Yali; Liu, Junxiu; Jiang, Qin; Duan, Qingchuan; Mao, Lanqun; Ma, Furong

2017-09-01

Tinnitus impairs quality of life of about 1-2% of the whole population. In most severe situation, tinnitus may cause social isolation, depression and suicide. Drug treatments for tinnitus are generally ineffective, and the mechanisms of tinnitus are still undetermined. Accumulating evidence suggests that tinnitus is related to changes of widespread brain networks. Recent studies propose that paraflocculus (PFL), which is indirectly connected to various cortical regions, may be a gating zone of tinnitus. So we examined the electrophysiological changes and neurotransmitter alterations of the PFL in a rat model of sodium salicylate (SS)-induced tinnitus. We found that spontaneous firing rate (SFR) of the putative excitatory interneurons of the PFL was significantly increased. The level of glutamic acid, which is the main excitatory neurotransmitter in the nervous system, was also dramatically increased in the PFL after SS treatment. These results confirmed the hyperactivity of PFL in the rats with SS-treatment, which might be due to the increased glutamic acid. Then we examined the SFR of the auditory cortex (AC), the center for auditory perception, before and after electrical stimulation of the PFL. 71.4% (105/147) of the recorded neurons showed a response to the stimulation of the PFL. The result demonstrated that stimulation of the PFL could modulate the activity of the AC. Our study suggests a role of PFL in SS-induced tinnitus and AC as a potential target of PFL in the process of tinnitus. Copyright © 2017 Elsevier B.V. All rights reserved.

Hippocampal sharp wave‐ripple: A cognitive biomarker for episodic memory and planning

PubMed Central

2015-01-01

ABSTRACT Sharp wave ripples (SPW‐Rs) represent the most synchronous population pattern in the mammalian brain. Their excitatory output affects a wide area of the cortex and several subcortical nuclei. SPW‐Rs occur during “off‐line” states of the brain, associated with consummatory behaviors and non‐REM sleep, and are influenced by numerous neurotransmitters and neuromodulators. They arise from the excitatory recurrent system of the CA3 region and the SPW‐induced excitation brings about a fast network oscillation (ripple) in CA1. The spike content of SPW‐Rs is temporally and spatially coordinated by a consortium of interneurons to replay fragments of waking neuronal sequences in a compressed format. SPW‐Rs assist in transferring this compressed hippocampal representation to distributed circuits to support memory consolidation; selective disruption of SPW‐Rs interferes with memory. Recently acquired and pre‐existing information are combined during SPW‐R replay to influence decisions, plan actions and, potentially, allow for creative thoughts. In addition to the widely studied contribution to memory, SPW‐Rs may also affect endocrine function via activation of hypothalamic circuits. Alteration of the physiological mechanisms supporting SPW‐Rs leads to their pathological conversion, “p‐ripples,” which are a marker of epileptogenic tissue and can be observed in rodent models of schizophrenia and Alzheimer's Disease. Mechanisms for SPW‐R genesis and function are discussed in this review. © 2015 The Authors Hippocampus Published by Wiley Periodicals, Inc. PMID:26135716

Morpho-physiological Characteristics of Dorsal Subicular Network in Mice after Pilocarpine Induced Status Epilepticus

PubMed Central

He, De Fu; Ma, Dong Liang; Tang, Yong Cheng; Engel, Jerome; Bragin, Anatol; Tang, Feng Ru

2010-01-01

The goal of this study was to examine morpho-physiological changes in the dorsal subiculum network in the mouse model of temporal lobe epilepsy using extracellular recording, juxtacellular and immunofluorescence double labeling, and anterograde tracing methods. A significant loss of total dorsal subicular neurons, particularly calbindin, parvalbumin (PV), and immunopositive interneurons, was found at 2 months after pilocarpine-induced status epilepticus (SE). However, the sprouting of axons from lateral entorhinal cortex (LEnt) was observed to contact with surviving subicular neurons. These neurons had two predominant discharge patterns: bursting and fast irregular discharges. The bursting neurons were mainly pyramidal cells, and their dendritic spine density and bursting discharge rates were increased significantly in SE mice compared to the control group. Fast irregular discharge neurons were PV-immunopositive interneurons, and had less dendritic spines in SE mice when compared to control mice. When LEnt was stimulated, bursting and fast irregular discharge neurons had much shorter latency and stronger excitatory response in SE mice compared to the control group. Our results illustrate that morpho-physiological changes in the dorsal subiculum could be part of a multilevel pathological network that occurs simultaneously in many brain areas to contribute to the generation of epileptiform activity. PMID:19298597

Locally induced neuronal synchrony precisely propagates to specific cortical areas without rhythm distortion.

PubMed

Toda, Haruo; Kawasaki, Keisuke; Sato, Sho; Horie, Masao; Nakahara, Kiyoshi; Bepari, Asim K; Sawahata, Hirohito; Suzuki, Takafumi; Okado, Haruo; Takebayashi, Hirohide; Hasegawa, Isao

2018-05-16

Propagation of oscillatory spike firing activity at specific frequencies plays an important role in distributed cortical networks. However, there is limited evidence for how such frequency-specific signals are induced or how the signal spectra of the propagating signals are modulated during across-layer (radial) and inter-areal (tangential) neuronal interactions. To directly evaluate the direction specificity of spectral changes in a spiking cortical network, we selectively photostimulated infragranular excitatory neurons in the rat primary visual cortex (V1) at a supra-threshold level with various frequencies, and recorded local field potentials (LFPs) at the infragranular stimulation site, the cortical surface site immediately above the stimulation site in V1, and cortical surface sites outside V1. We found a significant reduction of LFP powers during radial propagation, especially at high-frequency stimulation conditions. Moreover, low-gamma-band dominant rhythms were transiently induced during radial propagation. Contrastingly, inter-areal LFP propagation, directed to specific cortical sites, accompanied no significant signal reduction nor gamma-band power induction. We propose an anisotropic mechanism for signal processing in the spiking cortical network, in which the neuronal rhythms are locally induced/modulated along the radial direction, and then propagate without distortion via intrinsic horizontal connections for spatiotemporally precise, inter-areal communication.

Central Control of Brown Adipose Tissue Thermogenesis

PubMed Central

Morrison, Shaun F.; Madden, Christopher J.; Tupone, Domenico

2011-01-01

Thermogenesis, the production of heat energy, is an essential component of the homeostatic repertoire to maintain body temperature during the challenge of low environmental temperature and plays a key role in elevating body temperature during the febrile response to infection. Mitochondrial oxidation in brown adipose tissue (BAT) is a significant source of neurally regulated metabolic heat production in many species from mouse to man. BAT thermogenesis is regulated by neural networks in the central nervous system which responds to feedforward afferent signals from cutaneous and core body thermoreceptors and to feedback signals from brain thermosensitive neurons to activate BAT sympathetic nerve activity. This review summarizes the research leading to a model of the feedforward reflex pathway through which environmental cold stimulates BAT thermogenesis and includes the influence on this thermoregulatory network of the pyrogenic mediator, prostaglandin E2, to increase body temperature during fever. The cold thermal afferent circuit from cutaneous thermal receptors, through second-order thermosensory neurons in the dorsal horn of the spinal cord ascends to activate neurons in the lateral parabrachial nucleus which drive GABAergic interneurons in the preoptic area (POA) to inhibit warm-sensitive, inhibitory output neurons of the POA. The resulting disinhibition of BAT thermogenesis-promoting neurons in the dorsomedial hypothalamus activates BAT sympathetic premotor neurons in the rostral ventromedial medulla, including the rostral raphe pallidus, which provide excitatory, and possibly disinhibitory, inputs to spinal sympathetic circuits to drive BAT thermogenesis. Other recently recognized central sites influencing BAT thermogenesis and energy expenditure are also described. PMID:22389645

Early dynamics of the semantic priming shift

PubMed Central

Lavigne, Frédéric; Chanquoy, Lucile; Dumercy, Laurent; Vitu, Françoise

2013-01-01

Semantic processing of sequences of words requires the cognitive system to keep several word meanings simultaneously activated in working memory with limited capacity. The real- time updating of the sequence of word meanings relies on dynamic changes in the associates to the words that are activated. Protocols involving two sequential primes report a semantic priming shift from larger priming of associates to the first prime to larger priming of associates to the second prime, in a range of long SOAs (stimulus-onset asynchronies) between the second prime and the target. However, the possibility for an early semantic priming shift is still to be tested, and its dynamics as a function of association strength remain unknown. Three multiple priming experiments are proposed that cross-manipulate association strength between each of two successive primes and a target, for different values of short SOAs and prime durations. Results show an early priming shift ranging from priming of associates to the first prime only to priming of strong associates to the first prime and all of the associates to the second prime. We investigated the neural basis of the early priming shift by using a network model of spike frequency adaptive cortical neurons (e.g., Deco & Rolls, 2005), able to code different association strengths between the primes and the target. The cortical network model provides a description of the early dynamics of the priming shift in terms of pro-active and retro-active interferences within populations of excitatory neurons regulated by fast and unselective inhibitory feedback. PMID:23717346

Synchronization properties of networks of electrically coupled neurons in the presence of noise and heterogeneities.

PubMed

Ostojic, Srdjan; Brunel, Nicolas; Hakim, Vincent

2009-06-01

We investigate how synchrony can be generated or induced in networks of electrically coupled integrate-and-fire neurons subject to noisy and heterogeneous inputs. Using analytical tools, we find that in a network under constant external inputs, synchrony can appear via a Hopf bifurcation from the asynchronous state to an oscillatory state. In a homogeneous net work, in the oscillatory state all neurons fire in synchrony, while in a heterogeneous network synchrony is looser, many neurons skipping cycles of the oscillation. If the transmission of action potentials via the electrical synapses is effectively excitatory, the Hopf bifurcation is supercritical, while effectively inhibitory transmission due to pronounced hyperpolarization leads to a subcritical bifurcation. In the latter case, the network exhibits bistability between an asynchronous state and an oscillatory state where all the neurons fire in synchrony. Finally we show that for time-varying external inputs, electrical coupling enhances the synchronization in an asynchronous network via a resonance at the firing-rate frequency.

Common molecular basis of the sentence comprehension network revealed by neurotransmitter receptor fingerprints.

PubMed

Zilles, Karl; Bacha-Trams, Maraike; Palomero-Gallagher, Nicola; Amunts, Katrin; Friederici, Angela D

2015-02-01

The language network is a well-defined large-scale neural network of anatomically and functionally interacting cortical areas. The successful language process requires the transmission of information between these areas. Since neurotransmitter receptors are key molecules of information processing, we hypothesized that cortical areas which are part of the same functional language network may show highly similar multireceptor expression pattern ("receptor fingerprint"), whereas those that are not part of this network should have different fingerprints. Here we demonstrate that the relation between the densities of 15 different excitatory, inhibitory and modulatory receptors in eight language-related areas are highly similar and differ considerably from those of 18 other brain regions not directly involved in language processing. Thus, the fingerprints of all cortical areas underlying a large-scale cognitive domain such as language is a characteristic, functionally relevant feature of this network and an important prerequisite for the underlying neuronal processes of language functions. Copyright © 2014 Elsevier Ltd. All rights reserved.

Common molecular basis of the sentence comprehension network revealed by neurotransmitter receptor fingerprints

PubMed Central

Zilles, Karl; Bacha-Trams, Maraike; Palomero-Gallagher, Nicola; Amunts, Katrin; Friederici, Angela D.

2015-01-01

The language network is a well-defined large-scale neural network of anatomically and functionally interacting cortical areas. The successful language process requires the transmission of information between these areas. Since neurotransmitter receptors are key molecules of information processing, we hypothesized that cortical areas which are part of the same functional language network may show highly similar multireceptor expression pattern (“receptor fingerprint”), whereas those that are not part of this network should have different fingerprints. Here we demonstrate that the relation between the densities of 15 different excitatory, inhibitory and modulatory receptors in eight language-related areas are highly similar and differ considerably from those of 18 other brain regions not directly involved in language processing. Thus, the fingerprints of all cortical areas underlying a large-scale cognitive domain such as language is a characteristic, functionally relevant feature of this network and an important prerequisite for the underlying neuronal processes of language functions. PMID:25243991

Mean-field equations for neuronal networks with arbitrary degree distributions.

PubMed

Nykamp, Duane Q; Friedman, Daniel; Shaker, Sammy; Shinn, Maxwell; Vella, Michael; Compte, Albert; Roxin, Alex

2017-04-01

The emergent dynamics in networks of recurrently coupled spiking neurons depends on the interplay between single-cell dynamics and network topology. Most theoretical studies on network dynamics have assumed simple topologies, such as connections that are made randomly and independently with a fixed probability (Erdös-Rényi network) (ER) or all-to-all connected networks. However, recent findings from slice experiments suggest that the actual patterns of connectivity between cortical neurons are more structured than in the ER random network. Here we explore how introducing additional higher-order statistical structure into the connectivity can affect the dynamics in neuronal networks. Specifically, we consider networks in which the number of presynaptic and postsynaptic contacts for each neuron, the degrees, are drawn from a joint degree distribution. We derive mean-field equations for a single population of homogeneous neurons and for a network of excitatory and inhibitory neurons, where the neurons can have arbitrary degree distributions. Through analysis of the mean-field equations and simulation of networks of integrate-and-fire neurons, we show that such networks have potentially much richer dynamics than an equivalent ER network. Finally, we relate the degree distributions to so-called cortical motifs.

Mean-field equations for neuronal networks with arbitrary degree distributions

NASA Astrophysics Data System (ADS)

Nykamp, Duane Q.; Friedman, Daniel; Shaker, Sammy; Shinn, Maxwell; Vella, Michael; Compte, Albert; Roxin, Alex

2017-04-01

The emergent dynamics in networks of recurrently coupled spiking neurons depends on the interplay between single-cell dynamics and network topology. Most theoretical studies on network dynamics have assumed simple topologies, such as connections that are made randomly and independently with a fixed probability (Erdös-Rényi network) (ER) or all-to-all connected networks. However, recent findings from slice experiments suggest that the actual patterns of connectivity between cortical neurons are more structured than in the ER random network. Here we explore how introducing additional higher-order statistical structure into the connectivity can affect the dynamics in neuronal networks. Specifically, we consider networks in which the number of presynaptic and postsynaptic contacts for each neuron, the degrees, are drawn from a joint degree distribution. We derive mean-field equations for a single population of homogeneous neurons and for a network of excitatory and inhibitory neurons, where the neurons can have arbitrary degree distributions. Through analysis of the mean-field equations and simulation of networks of integrate-and-fire neurons, we show that such networks have potentially much richer dynamics than an equivalent ER network. Finally, we relate the degree distributions to so-called cortical motifs.

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

NASA Astrophysics Data System (ADS)

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

2006-02-01

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

Mechanism of the 5-hydroxytryptamine 2A receptor-mediated facilitation of synaptic activity in prefrontal cortex

PubMed Central

Béïque, Jean-Claude; Imad, Mays; Mladenovic, Ljiljana; Gingrich, Jay A.; Andrade, Rodrigo

2007-01-01

Classic hallucinogens such as lysergic acid diethylamide are thought to elicit their psychotropic actions via serotonin receptors of the 5-hydroxytryptamine 2A subtype (5-HT2AR). One likely site for these effects is the prefrontal cortex (PFC). Previous studies have shown that activation of 5-HT2ARs in this region results in a robust increase in spontaneous glutamatergic synaptic activity, and these results have led to the widely held idea that hallucinogens elicit their effect by modulating synaptic transmission within the PFC. Here, we combine cellular and molecular biological approaches, including single-cell 5-HT2ARs inactivation and 5-HT2AR rescue over a 5-HT2AR knockout genetic background, to distinguish between competing hypotheses accounting for these effects. The results from these experiments do not support the idea that 5-HT2ARs elicit the release of an excitatory retrograde messenger nor that they activate thalamocortical afferents, the two dominant hypotheses. Rather, they suggest that 5-HT2ARs facilitate intrinsic networks within the PFC. Consistent with this idea, we locate a discrete subpopulation of pyramidal cells that is strongly excited by 5-HT2AR activation. PMID:17535909

The median preoptic nucleus reciprocally modulates activity of arousal-related and sleep-related neurons in the perifornical lateral hypothalamus.

PubMed

Suntsova, Natalia; Guzman-Marin, Ruben; Kumar, Sunil; Alam, Md Noor; Szymusiak, Ronald; McGinty, Dennis

2007-02-14

The perifornical-lateral hypothalamic area (PF/LH) contains neuronal groups playing an important role in control of waking and sleep. Among the brain regions that regulate behavioral states, one of the strongest sources of projections to the PF/LH is the median preoptic nucleus (MnPN) containing a sleep-active neuronal population. To evaluate the role of MnPN afferents in the control of PF/LH neuronal activity, we studied the responses of PF/LH cells to electrical stimulation or local chemical manipulation of the MnPN in freely moving rats. Single-pulse electrical stimulation evoked responses in 79% of recorded PF/LH neurons. No cells were activated antidromically. Direct and indirect transsynaptic effects depended on sleep-wake discharge pattern of PF/LH cells. The majority of arousal-related neurons, that is, cells discharging at maximal rates during active waking (AW) or during AW and rapid eye movement (REM) sleep, exhibited exclusively or initially inhibitory responses to stimulation. Sleep-related neurons, the cells with elevated discharge during non-REM and REM sleep or selectively active in REM sleep, exhibited exclusively or initially excitatory responses. Activation of the MnPN via microdialytic application of L-glutamate or bicuculline resulted in reduced discharge of arousal-related and in excitation of sleep-related PF/LH neurons. Deactivation of the MnPN with muscimol caused opposite effects. The results indicate that the MnPN contains subset(s) of neurons, which exert inhibitory control over arousal-related and excitatory control over sleep-related PF/LH neurons. We hypothesize that MnPN sleep-active neuronal group has both inhibitory and excitatory outputs that participate in the inhibitory control of arousal-promoting PF/LH mechanisms.

Exact solutions for rate and synchrony in recurrent networks of coincidence detectors.

PubMed

Mikula, Shawn; Niebur, Ernst

2008-11-01

We provide analytical solutions for mean firing rates and cross-correlations of coincidence detector neurons in recurrent networks with excitatory or inhibitory connectivity, with rate-modulated steady-state spiking inputs. We use discrete-time finite-state Markov chains to represent network state transition probabilities, which are subsequently used to derive exact analytical solutions for mean firing rates and cross-correlations. As illustrated in several examples, the method can be used for modeling cortical microcircuits and clarifying single-neuron and population coding mechanisms. We also demonstrate that increasing firing rates do not necessarily translate into increasing cross-correlations, though our results do support the contention that firing rates and cross-correlations are likely to be coupled. Our analytical solutions underscore the complexity of the relationship between firing rates and cross-correlations.

Heterogeneity of Intrinsic and Synaptic Properties of Neurons in the Ventral and Dorsal Parts of the Ventral Nucleus of the Lateral Lemniscus

PubMed Central

Caspari, Franziska; Baumann, Veronika J.; Garcia-Pino, Elisabet; Koch, Ursula

2015-01-01

The ventral nucleus of the lateral lemniscus (VNLL) provides a major inhibitory projection to the inferior colliculus (IC). Neurons in the VNLL respond with various firing patterns and different temporal precision to acoustic stimulation. The present study investigates the underlying intrinsic and synaptic properties of various cell types in different regions of the VNLL, using in vitro electrophysiological recordings from acute brain slices of mice and immunohistochemistry. We show that the biophysical membrane properties and excitatory input characteristics differed between dorsal and ventral VNLL neurons. Neurons in the ventral VNLL displayed an onset-type firing pattern and little hyperpolarization-activated current (Ih). Stimulation of lemniscal inputs evoked a large all-or-none excitatory response similar to Calyx of Held synapses in neurons in the lateral part of the ventral VNLL. Neurons that were located within the fiber tract of the lateral lemniscus, received several and weak excitatory input fibers. In the dorsal VNLL onset-type and sustained firing neurons were intermingled. These neurons showed large Ih and were strongly immunopositive for the hyperpolarization-activated cyclic nucleotide-gated channel 1 (HCN1) subunit. Both neuron types received several excitatory inputs that were weaker and slower compared to ventrolateral VNLL neurons. Using a mouse model that expresses channelrhodopsin under the promotor of the vesicular GABA transporter (VGAT) suggests that dorsal and ventral neurons were inhibitory since they were all depolarized by light stimulation. The diverse membrane and input properties in dorsal and ventral VNLL neurons suggest differential roles of these neurons for sound processing. PMID:26635535

Structure-activity studies with carboxy- and amino-terminal fragments of neurotensin on hypothalamic neurons in vitro.

PubMed

Baldino, F; Davis, L G; Wolfson, B

1985-09-09

The purpose of this study was to determine the structural requirements for the activity of neurotensin (NT1-13) on preoptic/anterior hypothalamic (POAH) neurons in vitro. Standard explant culture electrophysiological techniques were employed. NT was administered to POAH cultures through the superfusion fluid, or, to the vicinity of individual neurons by pressure ejection (0.5-10 psi) from micropipettes. Computer-generated, peri-event histograms were used to quantitate neuronal responses. Pressure ejection of NT1-13 (50 pM to 1 microM) consistently produced an excitatory effect on 30 of 42 neurons. The remaining cells were either inhibited or unaffected. Application of the C-terminal hexapeptide, NT8-13, but not the N-terminal octapeptide, NT1-8 (less than or equal to 1 mM), produced an excitatory response in 21 of 30 neurons, but was less potent than NT1-13. Application of an N-acetylated NT8-13 fragment (NTAC8-13) produced a response that was similar to that produced by NT8-13. The excitatory effects of NT1-13 and NT8-13 were maintained in medium which effectively blocked synaptic transmission (0 mM Ca2+/12 mM Mg2+ 1 mM EGTA). These data indicate that the C-terminal hexapeptide, but not the N-terminal octapeptide, produces a dose-related, excitatory effect on single neurons in the POAH in vitro. The persistence of these effects in Ca2+-free medium supports a postsynaptic site of action for these peptides.

Results on a binding neuron model and their implications for modified hourglass model for neuronal network.

PubMed

Arunachalam, Viswanathan; Akhavan-Tabatabaei, Raha; Lopez, Cristina

2013-01-01

The classical models of single neuron like Hodgkin-Huxley point neuron or leaky integrate and fire neuron assume the influence of postsynaptic potentials to last till the neuron fires. Vidybida (2008) in a refreshing departure has proposed models for binding neurons in which the trace of an input is remembered only for a finite fixed period of time after which it is forgotten. The binding neurons conform to the behaviour of real neurons and are applicable in constructing fast recurrent networks for computer modeling. This paper develops explicitly several useful results for a binding neuron like the firing time distribution and other statistical characteristics. We also discuss the applicability of the developed results in constructing a modified hourglass network model in which there are interconnected neurons with excitatory as well as inhibitory inputs. Limited simulation results of the hourglass network are presented.

A new bio-inspired stimulator to suppress hyper-synchronized neural firing in a cortical network.

PubMed

Amiri, Masoud; Amiri, Mahmood; Nazari, Soheila; Faez, Karim

2016-12-07

Hyper-synchronous neural oscillations are the character of several neurological diseases such as epilepsy. On the other hand, glial cells and particularly astrocytes can influence neural synchronization. Therefore, based on the recent researches, a new bio-inspired stimulator is proposed which basically is a dynamical model of the astrocyte biophysical model. The performance of the new stimulator is investigated on a large-scale, cortical network. Both excitatory and inhibitory synapses are also considered in the simulated spiking neural network. The simulation results show that the new stimulator has a good performance and is able to reduce recurrent abnormal excitability which in turn avoids the hyper-synchronous neural firing in the spiking neural network. In this way, the proposed stimulator has a demand controlled characteristic and is a good candidate for deep brain stimulation (DBS) technique to successfully suppress the neural hyper-synchronization. Copyright © 2016 Elsevier Ltd. All rights reserved.

A Postsynaptic AMPK→p21-Activated Kinase Pathway Drives Fasting-Induced Synaptic Plasticity in AgRP Neurons.

PubMed

Kong, Dong; Dagon, Yossi; Campbell, John N; Guo, Yikun; Yang, Zongfang; Yi, Xinchi; Aryal, Pratik; Wellenstein, Kerry; Kahn, Barbara B; Sabatini, Bernardo L; Lowell, Bradford B

2016-07-06

AMP-activated protein kinase (AMPK) plays an important role in regulating food intake. The downstream AMPK substrates and neurobiological mechanisms responsible for this, however, are ill defined. Agouti-related peptide (AgRP)-expressing neurons in the arcuate nucleus regulate hunger. Their firing increases with fasting, and once engaged they cause feeding. AgRP neuron activity is regulated by state-dependent synaptic plasticity: fasting increases dendritic spines and excitatory synaptic activity; feeding does the opposite. The signaling mechanisms underlying this, however, are also unknown. Using neuron-specific approaches to measure and manipulate kinase activity specifically within AgRP neurons, we establish that fasting increases AMPK activity in AgRP neurons, that increased AMPK activity in AgRP neurons is both necessary and sufficient for fasting-induced spinogenesis and excitatory synaptic activity, and that the AMPK phosphorylation target mediating this plasticity is p21-activated kinase. This provides a signaling and neurobiological basis for both AMPK regulation of energy balance and AgRP neuron state-dependent plasticity. Copyright © 2016 Elsevier Inc. All rights reserved.

Cortical inhibition and excitation by bilateral transcranial alternating current stimulation.

PubMed

Cancelli, Andrea; Cottone, Carlo; Zito, Giancarlo; Di Giorgio, Marina; Pasqualetti, Patrizio; Tecchio, Franca

2015-01-01

Transcranial electric stimulations (tES) with amplitude-modulated currents are promising tools to enhance neuromodulation effects. It is essential to select the correct cortical targets and inhibitory/excitatory protocols to reverse changes in specific networks. We aimed at assessing the dependence of cortical excitability changes on the current amplitude of 20 Hz transcranial alternating current stimulation (tACS) over the bilateral primary motor cortex. We chose two amplitude ranges of the stimulations, around 25 μA/cm2 and 63 μA/cm2 from peak to peak, with three values (at steps of about 2.5%) around each, to generate, respectively, inhibitory and excitatory effects of the primary motor cortex. We checked such changes online through transcranial magnetic stimulation (TMS)-induced motor evoked potentials (MEPs). Cortical excitability changes depended upon current density (p = 0.001). Low current densities decreased MEP amplitudes (inhibition) while high current densities increased them (excitation). tACS targeting bilateral homologous cortical areas can induce online inhibition or excitation as a function of the current density.

Automata network models of galaxy evolution

NASA Technical Reports Server (NTRS)

Chappell, David; Scalo, John

1993-01-01

Two ideas appear frequently in theories of star formation and galaxy evolution: (1) star formation is nonlocally excitatory, stimulating star formation in neighboring regions by propagation of a dense fragmenting shell or the compression of preexisting clouds; and (2) star formation is nonlocally inhibitory, making H2 regions and explosions which can create low-density and/or high temperature regions and increase the macroscopic velocity dispersion of the cloudy gas. Since it is not possible, given the present state of hydrodynamic modeling, to estimate whether one of these effects greatly dominates the other, it is of interest to investigate the predicted spatial pattern of star formation and its temporal behavior in simple models which incorporate both effects in a controlled manner. The present work presents preliminary results of such a study which is based on lattice galaxy models with various types of nonlocal inhibitory and excitatory couplings of the local SFR to the gas density, temperature, and velocity field meant to model a number of theoretical suggestions.

Activation of NMDA receptors reduces metabotropic glutamate receptor-induced long-term depression in the nucleus accumbens via a CaMKII-dependent mechanism.

PubMed

Huang, Chiung-Chun; Hsu, Kuei-Sen

2012-12-01

Glutamate is the major excitatory neurotransmitter in the brain and exerts its actions through two distinct types of receptors, ionotropic and metabotropic glutamate receptors (mGluR). Although functional interplay between ionotropic N-methyl-d-aspartate receptors (NMDAR) and mGluR has been convincingly demonstrated in native and recombinant systems, the mechanism by which NMDAR activation leads to modulation of mGluR function has yet to be elucidated. Using whole-cell patch-clamp recordings in mouse nucleus accumbens (NAc) slices, we found that tetanic stimulation (TS) of excitatory afferents with a naturally occurring frequency (10 min at 13 Hz) reliably induces a mGluR1/5-dependent long-term depression (mGluR1/5-LTD) of excitatory synaptic transmission. Blockade of NMDAR during but not after TS showed enhanced mGluR1/5-LTD induction, which is associated with its antagonism of TS-induced calcium/calmodulin-dependent protein kinase II (CaMKII) activation. The ability of NMDAR antagonists to promote mGluR1/5-LTD induction was mimicked by a selective CaMKII inhibitor KN-62. However, the induction of mGluR1/5-LTD by bath-applied agonist (S)-3,5-dihydrophenylglycine was not affected by NMDAR blockade. We also observed that NMDAR or CaMKII blockade during TS significantly blunted TS-induced increased serine/threonine phosphorylation of the scaffold protein Homer1b/c and resulted in an increased interaction of mGluR5 with the Homer1b/c. These results indicate that synaptically released glutamate during TS of excitatory afferents can activate both NMDAR and mGluR1/5 in NAc neurons concomitantly and that activation of NMDAR may stimulate CaMKII-mediated phosphorylation of Homer1b/c and impair the interaction between mGluR5 and Homer1b/c, thereby attenuating mGluR1/5-LTD induction. This study provides a novel molecular mechanism by which NMDAR could regulate mGluR5 function. Copyright © 2012 Elsevier Ltd. All rights reserved.

Insulin growth factor-1 (IGF-1) enhances hippocampal excitatory and seizure activity through IGF-1 receptor-mediated mechanisms in the epileptic brain.

PubMed

Jiang, Guohui; Wang, Wei; Cao, Qingqing; Gu, Juan; Mi, Xiujuan; Wang, Kewei; Chen, Guojun; Wang, Xuefeng

2015-12-01

Insulin-like growth factor-1 (IGF-1) is known to promote neurogenesis and survival. However, recent studies have suggested that IGF-1 regulates neuronal firing and excitatory neurotransmission. In the present study, focusing on temporal lobe epilepsy, we found that IGF-1 levels and IGF-1 receptor activation are increased in human epileptogenic tissues, and pilocarpine- and pentylenetetrazole-treated rat models. Using an acute model of seizures, we showed that lateral cerebroventricular infusion of IGF-1 elevates IGF-1 receptor (IGF-1R) signalling before pilocarpine application had proconvulsant effects. In vivo electroencephalogram recordings and power spectrogram analysis of local field potential revealed that IGF-1 promotes epileptiform activities. This effect is diminished by co-application of an IGF-1R inhibitor. In an in vitro electrophysiological study, we demonstrated that IGF-1 enhancement of excitatory neurotransmission and α-amino-3-hydroxy-5-methyl-4-isoxazole-propionic acid receptor- and N-methyl-D-aspartate receptor-mediated currents is inhibited by IGF-1R inhibitor. Finally, activation of extracellular signal-related kinase (ERK)-1/2 and protein kinase B (Akt) in seizures in rats is increased by exogenous IGF-1 and diminished by picropodophyllin. A behavioural study reveals that the ERK1/2 or Akt inhibitor attenuates seizure activity. These results indicate that increased IGF-1 levels after recurrent hippocampal neuronal firings might, in turn, promote seizure activity via IGF-1R-dependent mechanisms. The present study presents a previously unappreciated role of IGF-1R in the development of seizure activity. © 2015 Authors; published by Portland Press Limited.

Word length and lexical activation: longer is better.

PubMed

Pitt, Mark A; Samuel, Arthur G

2006-10-01

Many models of spoken word recognition posit the existence of lexical and sublexical representations, with excitatory and inhibitory mechanisms used to affect the activation levels of such representations. Bottom-up evidence provides excitatory input, and inhibition from phonetically similar representations leads to lexical competition. In such a system, long words should produce stronger lexical activation than short words, for 2 reasons: Long words provide more bottom-up evidence than short words, and short words are subject to greater inhibition due to the existence of more similar words. Four experiments provide evidence for this view. In addition, reaction-time-based partitioning of the data shows that long words generate greater activation that is available both earlier and for a longer time than is the case for short words. As a result, lexical influences on phoneme identification are extremely robust for long words but are quite fragile and condition-dependent for short words. Models of word recognition must consider words of all lengths to capture the true dynamics of lexical activation. Copyright 2006 APA.