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Sample records for hippocampal network oscillations

  1. Regulation of Hippocampal Firing by Network Oscillations during Sleep.

    PubMed

    Miyawaki, Hiroyuki; Diba, Kamran

    2016-04-01

    It has been hypothesized that waking leads to higher-firing neurons, with increased energy expenditure, and that sleep serves to return activity to baseline levels. Oscillatory activity patterns during different stages of sleep may play specific roles in this process, but consensus has been missing. To evaluate these phenomena in the hippocampus, we recorded from region CA1 neurons in rats across the 24-hr cycle, and we found that their firing increased upon waking and decreased 11% per hour across sleep. Waking and sleeping also affected lower- and higher-firing neurons differently. Interestingly, the incidences of sleep spindles and sharp-wave ripples (SWRs), typically associated with cortical plasticity, were predictive of ensuing firing changes and were more robustly predictive than other oscillatory events. Spindles and SWRs were initiated during non-REM sleep, yet the changes were incorporated in the network over the following REM sleep epoch. These findings indicate an important role for spindles and SWRs and provide novel evidence of a symbiotic relationship between non-REM and REM stages of sleep in the homeostatic regulation of neuronal activity. PMID:26972321

  2. Differential involvement of oriens/pyramidale interneurones in hippocampal network oscillations in vitro.

    PubMed

    Gloveli, Tengis; Dugladze, Tamar; Saha, Sikha; Monyer, Hannah; Heinemann, Uwe; Traub, Roger D; Whittington, Miles A; Buhl, Eberhard H

    2005-01-01

    Using whole-cell patch-clamp recordings in conjunction with post hoc anatomy we investigated the physiological properties of hippocampal stratum oriens and stratum pyramidale inhibitory interneurones, before and following the induction of pharmacologically evoked gamma frequency network oscillations. Prior to kainate-induced transient epochs of gamma activity, two distinct classes of oriens interneurones, oriens lacunosum-moleculare (O-LM) and trilaminar cells, showed prominent differences in their membrane and firing properties, as well as in the amplitude and kinetics of their excitatory postsynaptic events. In the active network both types of neurone received a phasic barrage of gamma frequency excitatory inputs but, due to their differential functional integration, showed clear differences in their output patterns. While O-LM cells fired intermittently at theta frequency, trilaminar interneurones discharged on every gamma cycle and showed a propensity to fire spike doublets. Two other classes of fast spiking interneurones, perisomatic targeting basket and bistratified cells, in the active network discharged predominantly single action potentials on every gamma cycle. Thus, within a locally excited network, O-LM cells are likely to provide a theta-frequency patterned output to distal dendritic segments, whereas basket and bistratified cells are involved in the generation of locally synchronous gamma band oscillations. The anatomy and output profile of trilaminar cells suggest they are involved in the projection of locally generated gamma rhythms to distal sites. Therefore a division of labour appears to exist whereby different frequencies and spatiotemporal properties of hippocampal rhythms are mediated by different interneurone subtypes. PMID:15486016

  3. CA3 Synaptic Silencing Attenuates Kainic Acid-Induced Seizures and Hippocampal Network Oscillations123

    PubMed Central

    Yu, Lily M. Y.; Wintzer, Marie E.

    2016-01-01

    Abstract Epilepsy is a neurological disorder defined by the presence of seizure activity, manifest both behaviorally and as abnormal activity in neuronal networks. An established model to study the disorder in rodents is the systemic injection of kainic acid, an excitatory neurotoxin that at low doses quickly induces behavioral and electrophysiological seizures. Although the CA3 region of the hippocampus has been suggested to be crucial for kainic acid-induced seizure, because of its strong expression of kainate glutamate receptors and its high degree of recurrent connectivity, the precise role of excitatory transmission in CA3 in the generation of seizure and the accompanying increase in neuronal oscillations remains largely untested. Here we use transgenic mice in which CA3 pyramidal cell synaptic transmission can be inducibly silenced in the adult to demonstrate CA3 excitatory output is required for both the generation of epileptiform oscillatory activity and the progression of behavioral seizures. PMID:27022627

  4. Network models provide insights into how oriens–lacunosum-moleculare and bistratified cell interactions influence the power of local hippocampal CA1 theta oscillations

    PubMed Central

    Ferguson, Katie A.; Huh, Carey Y. L.; Amilhon, Bénédicte; Manseau, Frédéric; Williams, Sylvain; Skinner, Frances K.

    2015-01-01

    Hippocampal theta is a 4–12 Hz rhythm associated with episodic memory, and although it has been studied extensively, the cellular mechanisms underlying its generation are unclear. The complex interactions between different interneuron types, such as those between oriens–lacunosum-moleculare (OLM) interneurons and bistratified cells (BiCs), make their contribution to network rhythms difficult to determine experimentally. We created network models that are tied to experimental work at both cellular and network levels to explore how these interneuron interactions affect the power of local oscillations. Our cellular models were constrained with properties from patch clamp recordings in the CA1 region of an intact hippocampus preparation in vitro. Our network models are composed of three different types of interneurons: parvalbumin-positive (PV+) basket and axo-axonic cells (BC/AACs), PV+ BiCs, and somatostatin-positive OLM cells. Also included is a spatially extended pyramidal cell model to allow for a simplified local field potential representation, as well as experimentally-constrained, theta frequency synaptic inputs to the interneurons. The network size, connectivity, and synaptic properties were constrained with experimental data. To determine how the interactions between OLM cells and BiCs could affect local theta power, we explored how the number of OLM-BiC connections and connection strength affected local theta power. We found that our models operate in regimes that could be distinguished by whether OLM cells minimally or strongly affected the power of network theta oscillations due to balances that, respectively, allow compensatory effects or not. Inactivation of OLM cells could result in no change or even an increase in theta power. We predict that the dis-inhibitory effect of OLM cells to BiCs to pyramidal cell interactions plays a critical role in the resulting power of network theta oscillations. Overall, our network models reveal a dynamic interplay

  5. Rhythms of the hippocampal network.

    PubMed

    Colgin, Laura Lee

    2016-04-01

    The hippocampal local field potential (LFP) shows three major types of rhythms: theta, sharp wave-ripples and gamma. These rhythms are defined by their frequencies, they have behavioural correlates in several species including rats and humans, and they have been proposed to carry out distinct functions in hippocampal memory processing. However, recent findings have challenged traditional views on these behavioural functions. In this Review, I discuss our current understanding of the origins and the mnemonic functions of hippocampal theta, sharp wave-ripples and gamma rhythms on the basis of findings from rodent studies. In addition, I present an updated synthesis of their roles and interactions within the hippocampal network. PMID:26961163

  6. Cholinergic modulation of hippocampal network function

    PubMed Central

    Teles-Grilo Ruivo, Leonor M.; Mellor, Jack R.

    2013-01-01

    Cholinergic septohippocampal projections from the medial septal area to the hippocampus are proposed to have important roles in cognition by modulating properties of the hippocampal network. However, the precise spatial and temporal profile of acetylcholine release in the hippocampus remains unclear making it difficult to define specific roles for cholinergic transmission in hippocampal dependent behaviors. This is partly due to a lack of tools enabling specific intervention in, and recording of, cholinergic transmission. Here, we review the organization of septohippocampal cholinergic projections and hippocampal acetylcholine receptors as well as the role of cholinergic transmission in modulating cellular excitability, synaptic plasticity, and rhythmic network oscillations. We point to a number of open questions that remain unanswered and discuss the potential for recently developed techniques to provide a radical reappraisal of the function of cholinergic inputs to the hippocampus. PMID:23908628

  7. Network Mechanisms Generating Abnormal and Normal Hippocampal High-Frequency Oscillations: A Computational Analysis1,2,3

    PubMed Central

    Gliske, Stephen; Catoni, Nicholas

    2015-01-01

    Abstract High-frequency oscillations (HFOs) are an intriguing potential biomarker for epilepsy, typically categorized according to peak frequency as either ripples (100–250 Hz) or fast ripples (>250 Hz). In the hippocampus, fast ripples were originally thought to be more specific to epileptic tissue, but it is still very difficult to distinguish which HFOs are caused by normal versus pathological brain activity. In this study, we use a computational model of hippocampus to investigate possible network mechanisms underpinning normal ripples, pathological ripples, and fast ripples. Our results unify several prior findings regarding HFO mechanisms, and also make several new predictions regarding abnormal HFOs. We show that HFOs are generic, emergent phenomena whose characteristics reflect a wide range of connectivity and network input. Although produced by different mechanisms, both normal and abnormal HFOs generate similar ripple frequencies, underscoring that peak frequency is unable to distinguish the two. Abnormal ripples are generic phenomena that arise when input to pyramidal cells overcomes network inhibition, resulting in high-frequency, uncoordinated firing. In addition, fast ripples transiently and sporadically arise from the precise conditions that produce abnormal ripples. Lastly, we show that such abnormal conditions do not require any specific network structure to produce coherent HFOs, as even completely asynchronous activity is capable of producing abnormal ripples and fast ripples in this manner. These results provide a generic, network-based explanation for the link between pathological ripples and fast ripples, and a unifying description for the entire spectrum from normal ripples to pathological fast ripples. PMID:26146658

  8. The effects of high-frequency oscillations in hippocampal electrical activities on the classification of epileptiform events using artificial neural networks

    NASA Astrophysics Data System (ADS)

    Chiu, Alan W. L.; Jahromi, Shokrollah S.; Khosravani, Houman; Carlen, Peter L.; Bardakjian, Berj L.

    2006-03-01

    The existence of hippocampal high-frequency electrical activities (greater than 100 Hz) during the progression of seizure episodes in both human and animal experimental models of epilepsy has been well documented (Bragin A, Engel J, Wilson C L, Fried I and Buzsáki G 1999 Hippocampus 9 137-42 Khosravani H, Pinnegar C R, Mitchell J R, Bardakjian B L, Federico P and Carlen P L 2005 Epilepsia 46 1-10). However, this information has not been studied between successive seizure episodes or utilized in the application of seizure classification. In this study, we examine the dynamical changes of an in vitro low Mg2+ rat hippocampal slice model of epilepsy at different frequency bands using wavelet transforms and artificial neural networks. By dividing the time-frequency spectrum of each seizure-like event (SLE) into frequency bins, we can analyze their burst-to-burst variations within individual SLEs as well as between successive SLE episodes. Wavelet energy and wavelet entropy are estimated for intracellular and extracellular electrical recordings using sufficiently high sampling rates (10 kHz). We demonstrate that the activities of high-frequency oscillations in the 100-400 Hz range increase as the slice approaches SLE onsets and in later episodes of SLEs. Utilizing the time-dependent relationship between different frequency bands, we can achieve frequency-dependent state classification. We demonstrate that activities in the frequency range 100-400 Hz are critical for the accurate classification of the different states of electrographic seizure-like episodes (containing interictal, preictal and ictal states) in brain slices undergoing recurrent spontaneous SLEs. While preictal activities can be classified with an average accuracy of 77.4 ± 6.7% utilizing the frequency spectrum in the range 0-400 Hz, we can also achieve a similar level of accuracy by using a nonlinear relationship between 100-400 Hz and <4 Hz frequency bands only.

  9. 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

  10. Network synchronization in hippocampal neurons.

    PubMed

    Penn, Yaron; Segal, Menahem; Moses, Elisha

    2016-03-22

    Oscillatory activity is widespread in dynamic neuronal networks. The main paradigm for the origin of periodicity consists of specialized pacemaking elements that synchronize and drive the rest of the network; however, other models exist. Here, we studied the spontaneous emergence of synchronized periodic bursting in a network of cultured dissociated neurons from rat hippocampus and cortex. Surprisingly, about 60% of all active neurons were self-sustained oscillators when disconnected, each with its own natural frequency. The individual neuron's tendency to oscillate and the corresponding oscillation frequency are controlled by its excitability. The single neuron intrinsic oscillations were blocked by riluzole, and are thus dependent on persistent sodium leak currents. Upon a gradual retrieval of connectivity, the synchrony evolves: Loose synchrony appears already at weak connectivity, with the oscillators converging to one common oscillation frequency, yet shifted in phase across the population. Further strengthening of the connectivity causes a reduction in the mean phase shifts until zero-lag is achieved, manifested by synchronous periodic network bursts. Interestingly, the frequency of network bursting matches the average of the intrinsic frequencies. Overall, the network behaves like other universal systems, where order emerges spontaneously by entrainment of independent rhythmic units. Although simplified with respect to circuitry in the brain, our results attribute a basic functional role for intrinsic single neuron excitability mechanisms in driving the network's activity and dynamics, contributing to our understanding of developing neural circuits. PMID:26961000

  11. Ketamine Protects Gamma Oscillations by Inhibiting Hippocampal LTD

    PubMed Central

    Huang, Lanting; Yang, Xiu-Juan; Huang, Ying; Sun, Eve Y.

    2016-01-01

    NMDA receptors have been widely reported to be involved in the regulation of synaptic plasticity through effects on long-term potentiation (LTP) and long-term depression (LTD). LTP and LTD have been implicated in learning and memory processes. Besides synaptic plasticity, it is known that the phenomenon of gamma oscillations is critical in cognitive functions. Synaptic plasticity has been widely studied, however it is still not clear, to what degree synaptic plasticity regulates the oscillations of neuronal networks. Two NMDA receptor antagonists, ketamine and memantine, have been shown to regulate LTP and LTD, to promote cognitive functions, and have even been reported to bring therapeutic effects in major depression and Alzheimer’s disease respectively. These compounds allow us to investigate the putative interrelationship between network oscillations and synaptic plasticity and to learn more about the mechanisms of their therapeutic effects. In the present study, we have identified that ketamine and memantine could inhibit LTD, without impairing LTP in the CA1 region of mouse hippocampus, which may underlie the mechanism of these drugs’ therapeutic effects. Our results suggest that NMDA-induced LTD caused a marked loss in the gamma power, and pretreatment with 10 μM ketamine prevented the oscillatory loss via its inhibitory effect on LTD. Our study provides a new understanding of the role of NMDA receptors on hippocampal plasticity and oscillations. PMID:27467732

  12. Ketamine Protects Gamma Oscillations by Inhibiting Hippocampal LTD.

    PubMed

    Huang, Lanting; Yang, Xiu-Juan; Huang, Ying; Sun, Eve Y; Sun, Mu

    2016-01-01

    NMDA receptors have been widely reported to be involved in the regulation of synaptic plasticity through effects on long-term potentiation (LTP) and long-term depression (LTD). LTP and LTD have been implicated in learning and memory processes. Besides synaptic plasticity, it is known that the phenomenon of gamma oscillations is critical in cognitive functions. Synaptic plasticity has been widely studied, however it is still not clear, to what degree synaptic plasticity regulates the oscillations of neuronal networks. Two NMDA receptor antagonists, ketamine and memantine, have been shown to regulate LTP and LTD, to promote cognitive functions, and have even been reported to bring therapeutic effects in major depression and Alzheimer's disease respectively. These compounds allow us to investigate the putative interrelationship between network oscillations and synaptic plasticity and to learn more about the mechanisms of their therapeutic effects. In the present study, we have identified that ketamine and memantine could inhibit LTD, without impairing LTP in the CA1 region of mouse hippocampus, which may underlie the mechanism of these drugs' therapeutic effects. Our results suggest that NMDA-induced LTD caused a marked loss in the gamma power, and pretreatment with 10 μM ketamine prevented the oscillatory loss via its inhibitory effect on LTD. Our study provides a new understanding of the role of NMDA receptors on hippocampal plasticity and oscillations. PMID:27467732

  13. Running speed alters the frequency of hippocampal gamma oscillations

    PubMed Central

    Ahmed, Omar J.; Mehta, Mayank R.

    2012-01-01

    Successful spatial navigation is thought to employ a combination of at least two strategies: the following of landmark cues and path integration. Path integration requires that the brain use the speed and direction of movement in a meaningful way to continuously compute the position of the animal. Indeed, the running speed of rats modulates both the firing rate of neurons and the spectral properties of low frequency, theta oscillations seen in the local field potential (LFP) of the hippocampus, a region important for spatial memory formation. Higher frequency, gamma-band LFP oscillations are usually associated with decision-making, increased attention and improved reaction times. Here, we show that increased running speed is accompanied by large, systematic increases in the frequency of hippocampal CA1 network oscillations spanning the entire gamma range (30–120 Hz) and beyond. These speed-dependent changes in frequency are seen on both linear tracks and two-dimensional platforms, and are thus independent of the behavioral task. Synchrony between anatomically distant CA1 regions also shifts to higher gamma frequencies as running speed increases. The changes in frequency are strongly correlated with changes in the firing rates of individual interneurons, consistent with models of gamma generation. Our results suggest that as a rat runs faster, there are faster gamma frequency transitions between sequential place cell-assemblies. This may help to preserve the spatial specificity of place cells and spatial memories at vastly different running speeds. PMID:22623683

  14. Hippocampal gamma-frequency oscillations: from interneurones to pyramidal cells, and back.

    PubMed

    Mann, Edward O; Radcliffe, Catrin A; Paulsen, Ole

    2005-01-01

    GABAergic interneurones are necessary for the emergence of hippocampal gamma-frequency network oscillations, during which they play a key role in the synchronization of pyramidal cell firing. However, it remains to be resolved how distinct interneurone subtypes contribute to gamma-frequency oscillations, in what way the spatiotemporal pattern of interneuronal input affects principal cell activity, and by which mechanisms the interneurones themselves are synchronized. Here we summarize recent evidence from cholinergically induced gamma-frequency network oscillations in vitro, showing that perisomatic-targeting GABAergic interneurones provide prominent rhythmic inhibition in pyramidal cells, and that these interneurones are synchronized by recurrent excitation. We conclude by presenting a minimal integrate-and-fire network model which demonstrates that this excitatory-inhibitory feedback loop is sufficient to explain the generation of intrahippocampal gamma-frequency oscillations. PMID:15539391

  15. Oscillations of complex networks

    NASA Astrophysics Data System (ADS)

    Wang, Xingang; Lai, Ying-Cheng; Lai, Choy Heng

    2006-12-01

    A complex network processing information or physical flows is usually characterized by a number of macroscopic quantities such as the diameter and the betweenness centrality. An issue of significant theoretical and practical interest is how such quantities respond to sudden changes caused by attacks or disturbances in recoverable networks, i.e., functions of the affected nodes are only temporarily disabled or partially limited. By introducing a model to address this issue, we find that, for a finite-capacity network, perturbations can cause the network to oscillate persistently in the sense that the characterizing quantities vary periodically or randomly with time. We provide a theoretical estimate of the critical capacity-parameter value for the onset of the network oscillation. The finding is expected to have broad implications as it suggests that complex networks may be structurally highly dynamic.

  16. Hippocampal-Prefrontal Theta Oscillations Support Memory Integration.

    PubMed

    Backus, Alexander R; Schoffelen, Jan-Mathijs; Szebényi, Szabolcs; Hanslmayr, Simon; Doeller, Christian F

    2016-02-22

    Integration of separate memories forms the basis of inferential reasoning--an essential cognitive process that enables complex behavior. Considerable evidence suggests that both hippocampus and medial prefrontal cortex (mPFC) play a crucial role in memory integration. Although previous studies indicate that theta oscillations facilitate memory processes, the electrophysiological mechanisms underlying memory integration remain elusive. To bridge this gap, we recorded magnetoencephalography data while participants performed an inference task and employed novel source reconstruction techniques to estimate oscillatory signals from the hippocampus. We found that hippocampal theta power during encoding predicts subsequent memory integration. Moreover, we observed increased theta coherence between hippocampus and mPFC. Our results suggest that integrated memory representations arise through hippocampal theta oscillations, possibly reflecting dynamic switching between encoding and retrieval states, and facilitating communication with mPFC. These findings have important implications for our understanding of memory-based decision making and knowledge acquisition. PMID:26832442

  17. Midline thalamic neurons are differentially engaged during hippocampus network oscillations.

    PubMed

    Lara-Vásquez, Ariel; Espinosa, Nelson; Durán, Ernesto; Stockle, Marcelo; Fuentealba, Pablo

    2016-01-01

    The midline thalamus is reciprocally connected with the medial temporal lobe, where neural circuitry essential for spatial navigation and memory formation resides. Yet, little information is available on the dynamic relationship between activity patterns in the midline thalamus and medial temporal lobe. Here, we report on the functional heterogeneity of anatomically-identified thalamic neurons and the differential modulation of their activity with respect to dorsal hippocampal rhythms in the anesthetized mouse. Midline thalamic neurons expressing the calcium-binding protein calretinin, irrespective of their selective co-expression of calbindin, discharged at overall low levels, did not increase their activity during hippocampal theta oscillations, and their firing rates were inhibited during hippocampal sharp wave-ripples. Conversely, thalamic neurons lacking calretinin discharged at higher rates, increased their activity during hippocampal theta waves, but remained unaffected during sharp wave-ripples. Our results indicate that the midline thalamic system comprises at least two different classes of thalamic projection neuron, which can be partly defined by their differential engagement by hippocampal pathways during specific network oscillations that accompany distinct behavioral contexts. Thus, different midline thalamic neuronal populations might be selectively recruited to support distinct stages of memory processing, consistent with the thalamus being pivotal in the dialogue of cortical circuits. PMID:27411890

  18. Midline thalamic neurons are differentially engaged during hippocampus network oscillations

    PubMed Central

    Lara-Vásquez, Ariel; Espinosa, Nelson; Durán, Ernesto; Stockle, Marcelo; Fuentealba, Pablo

    2016-01-01

    The midline thalamus is reciprocally connected with the medial temporal lobe, where neural circuitry essential for spatial navigation and memory formation resides. Yet, little information is available on the dynamic relationship between activity patterns in the midline thalamus and medial temporal lobe. Here, we report on the functional heterogeneity of anatomically-identified thalamic neurons and the differential modulation of their activity with respect to dorsal hippocampal rhythms in the anesthetized mouse. Midline thalamic neurons expressing the calcium-binding protein calretinin, irrespective of their selective co-expression of calbindin, discharged at overall low levels, did not increase their activity during hippocampal theta oscillations, and their firing rates were inhibited during hippocampal sharp wave-ripples. Conversely, thalamic neurons lacking calretinin discharged at higher rates, increased their activity during hippocampal theta waves, but remained unaffected during sharp wave-ripples. Our results indicate that the midline thalamic system comprises at least two different classes of thalamic projection neuron, which can be partly defined by their differential engagement by hippocampal pathways during specific network oscillations that accompany distinct behavioral contexts. Thus, different midline thalamic neuronal populations might be selectively recruited to support distinct stages of memory processing, consistent with the thalamus being pivotal in the dialogue of cortical circuits. PMID:27411890

  19. The contribution of electrical synapses to field potential oscillations in the hippocampal formation

    PubMed Central

    Posłuszny, Anna

    2014-01-01

    Electrical synapses are a type of cellular membrane junction referred to as gap junctions (GJs). They provide a direct way to exchange ions between coupled cells and have been proposed as a structural basis for fast transmission of electrical potentials between neurons in the brain. For this reason GJs have been regarded as an important component within the neuronal networks that underlie synchronous neuronal activity and field potential oscillations. Initially, GJs appeared to play a particularly key role in the generation of high frequency oscillatory patterns in field potentials. In order to assess the scale of neuronal GJs contribution to field potential oscillations in the hippocampal formation, in vivo and in vitro studies are reviewed here. These investigations have shown that blocking the main neuronal GJs, those containing connexin 36 (Cx36-GJs), or knocking out the Cx36 gene affect field potential oscillatory patterns related to awake active behavior (gamma and theta rhythm) but have no effect on high frequency oscillations occurring during silent wake and sleep. Precisely how Cx36-GJs influence population activity of neurons is more complex than previously thought. Analysis of studies on the properties of transmission through GJ channels as well as Cx36-GJs functioning in pairs of coupled neurons provides some explanations of the specific influence of Cx36-GJs on field potential oscillations. It is proposed here that GJ transmission is strongly modulated by the level of neuronal network activity and changing behavioral states. Therefore, contribution of GJs to field potential oscillatory patterns depends on the behavioral state. I propose here a model, based on large body of experimental data gathered in this field by several authors, in which Cx36-GJ transmission especially contributes to oscillations related to active behavior, where it plays a role in filtering and enhancing coherent signals in the network under high-noise conditions. In contrast

  20. The synchronous activity of lateral habenular neurons is essential for regulating hippocampal theta oscillation.

    PubMed

    Aizawa, Hidenori; Yanagihara, Shin; Kobayashi, Megumi; Niisato, Kazue; Takekawa, Takashi; Harukuni, Rie; McHugh, Thomas J; Fukai, Tomoki; Isomura, Yoshikazu; Okamoto, Hitoshi

    2013-05-15

    Lateral habenula (LHb) has attracted growing interest as a regulator of serotonergic and dopaminergic neurons in the CNS. However, it remains unclear how the LHb modulates brain states in animals. To identify the neural substrates that are under the influence of LHb regulation, we examined the effects of rat LHb lesions on the hippocampal oscillatory activity associated with the transition of brain states. Our results showed that the LHb lesion shortened the theta activity duration both in anesthetized and sleeping rats. Furthermore, this inhibitory effect of LHb lesion on theta maintenance depended upon an intact serotonergic median raphe, suggesting that LHb activity plays an essential role in maintaining hippocampal theta oscillation via the serotonergic raphe. Multiunit recording of sleeping rats further revealed that firing of LHb neurons showed significant phase-locking activity at each theta oscillation cycle in the hippocampus. LHb neurons showing activity that was coordinated with that of the hippocampal theta were localized in the medial LHb division, which receives afferents from the diagonal band of Broca (DBB), a pacemaker region for the hippocampal theta oscillation. Thus, our findings indicate that the DBB may pace not only the hippocampus, but also the LHb, during rapid eye movement sleep. Since serotonin is known to negatively regulate theta oscillation in the hippocampus, phase-locking activity of the LHb neurons may act, under the influence of the DBB, to maintain the hippocampal theta oscillation by modulating the activity of serotonergic neurons. PMID:23678132

  1. Modeling carbachol-induced hippocampal network synchronization using hidden Markov models

    NASA Astrophysics Data System (ADS)

    Dragomir, Andrei; Akay, Yasemin M.; Akay, Metin

    2010-10-01

    In this work we studied the neural state transitions undergone by the hippocampal neural network using a hidden Markov model (HMM) framework. We first employed a measure based on the Lempel-Ziv (LZ) estimator to characterize the changes in the hippocampal oscillation patterns in terms of their complexity. These oscillations correspond to different modes of hippocampal network synchronization induced by the cholinergic agonist carbachol in the CA1 region of mice hippocampus. HMMs are then used to model the dynamics of the LZ-derived complexity signals as first-order Markov chains. Consequently, the signals corresponding to our oscillation recordings can be segmented into a sequence of statistically discriminated hidden states. The segmentation is used for detecting transitions in neural synchronization modes in data recorded from wild-type and triple transgenic mice models (3xTG) of Alzheimer's disease (AD). Our data suggest that transition from low-frequency (delta range) continuous oscillation mode into high-frequency (theta range) oscillation, exhibiting repeated burst-type patterns, occurs always through a mode resembling a mixture of the two patterns, continuous with burst. The relatively random patterns of oscillation during this mode may reflect the fact that the neuronal network undergoes re-organization. Further insight into the time durations of these modes (retrieved via the HMM segmentation of the LZ-derived signals) reveals that the mixed mode lasts significantly longer (p < 10-4) in 3xTG AD mice. These findings, coupled with the documented cholinergic neurotransmission deficits in the 3xTG mice model, may be highly relevant for the case of AD.

  2. Hippocampal Sharp-Wave Ripples Influence Selective Activation of the Default Mode Network.

    PubMed

    Kaplan, Raphael; Adhikari, Mohit H; Hindriks, Rikkert; Mantini, Dante; Murayama, Yusuke; Logothetis, Nikos K; Deco, Gustavo

    2016-03-01

    The default mode network (DMN) is a commonly observed resting-state network (RSN) that includes medial temporal, parietal, and prefrontal regions involved in episodic memory [1-3]. The behavioral relevance of endogenous DMN activity remains elusive, despite an emerging literature correlating resting fMRI fluctuations with memory performance [4, 5]-particularly in DMN regions [6-8]. Mechanistic support for the DMN's role in memory consolidation might come from investigation of large deflections (sharp-waves) in the hippocampal local field potential that co-occur with high-frequency (>80 Hz) oscillations called ripples-both during sleep [9, 10] and awake deliberative periods [11-13]. Ripples are ideally suited for memory consolidation [14, 15], since the reactivation of hippocampal place cell ensembles occurs during ripples [16-19]. Moreover, the number of ripples after learning predicts subsequent memory performance in rodents [20-22] and humans [23], whereas electrical stimulation of the hippocampus after learning interferes with memory consolidation [24-26]. A recent study in macaques showed diffuse fMRI neocortical activation and subcortical deactivation specifically after ripples [27]. Yet it is unclear whether ripples and other hippocampal neural events influence endogenous fluctuations in specific RSNs-like the DMN-unitarily. Here, we examine fMRI datasets from anesthetized monkeys with simultaneous hippocampal electrophysiology recordings, where we observe a dramatic increase in the DMN fMRI signal following ripples, but not following other hippocampal electrophysiological events. Crucially, we find increases in ongoing DMN activity after ripples, but not in other RSNs. Our results relate endogenous DMN fluctuations to hippocampal ripples, thereby linking network-level resting fMRI fluctuations with behaviorally relevant circuit-level neural dynamics. PMID:26898464

  3. Hippocampal Sharp-Wave Ripples Influence Selective Activation of the Default Mode Network

    PubMed Central

    Kaplan, Raphael; Adhikari, Mohit H.; Hindriks, Rikkert; Mantini, Dante; Murayama, Yusuke; Logothetis, Nikos K.; Deco, Gustavo

    2016-01-01

    Summary The default mode network (DMN) is a commonly observed resting-state network (RSN) that includes medial temporal, parietal, and prefrontal regions involved in episodic memory [1, 2, 3]. The behavioral relevance of endogenous DMN activity remains elusive, despite an emerging literature correlating resting fMRI fluctuations with memory performance [4, 5]—particularly in DMN regions [6, 7, 8]. Mechanistic support for the DMN’s role in memory consolidation might come from investigation of large deflections (sharp-waves) in the hippocampal local field potential that co-occur with high-frequency (>80 Hz) oscillations called ripples—both during sleep [9, 10] and awake deliberative periods [11, 12, 13]. Ripples are ideally suited for memory consolidation [14, 15], since the reactivation of hippocampal place cell ensembles occurs during ripples [16, 17, 18, 19]. Moreover, the number of ripples after learning predicts subsequent memory performance in rodents [20, 21, 22] and humans [23], whereas electrical stimulation of the hippocampus after learning interferes with memory consolidation [24, 25, 26]. A recent study in macaques showed diffuse fMRI neocortical activation and subcortical deactivation specifically after ripples [27]. Yet it is unclear whether ripples and other hippocampal neural events influence endogenous fluctuations in specific RSNs—like the DMN—unitarily. Here, we examine fMRI datasets from anesthetized monkeys with simultaneous hippocampal electrophysiology recordings, where we observe a dramatic increase in the DMN fMRI signal following ripples, but not following other hippocampal electrophysiological events. Crucially, we find increases in ongoing DMN activity after ripples, but not in other RSNs. Our results relate endogenous DMN fluctuations to hippocampal ripples, thereby linking network-level resting fMRI fluctuations with behaviorally relevant circuit-level neural dynamics. PMID:26898464

  4. Human Hippocampal Theta Oscillations during Movement without Visual Cues.

    PubMed

    Qasim, Salman E; Jacobs, Joshua

    2016-03-16

    The hippocampus exhibits theta oscillations when animals navigate. Vass et al. (2016) discovered that theta oscillations are also present when humans are moved through a virtual environment without sensory feedback, indicating that theta oscillations have a general role in spatial cognition beyond sensorimotor processing. PMID:26985718

  5. Distinct firing patterns of identified basket and dendrite-targeting interneurons in the prefrontal cortex during hippocampal theta and local spindle oscillations.

    PubMed

    Hartwich, Katja; Pollak, Thomas; Klausberger, Thomas

    2009-07-29

    The medial prefrontal cortex is involved in working memory and executive control. However, the collective spatiotemporal organization of the cellular network has not been possible to explain during different brain states. We show that pyramidal cells in the prelimbic cortex fire synchronized to hippocampal theta and local spindle oscillations in anesthetized rats. To identify which types of interneurons contribute to the synchronized activity, we recorded and juxtacellularly labeled parvalbumin- and calbindin-expressing (PV+/CB+) basket cells and CB-expressing, PV-negative (CB+/PV-) dendrite-targeting interneurons during both network oscillations. All CB+/PV- dendrite-targeting cells strongly decreased their firing rate during hippocampal theta oscillations. Most PV+/CB+ basket cells fired at the peak of dorsal CA1 theta cycles, similar to prefrontal pyramidal cells. We show that pyramidal cells in the ventral hippocampus also fire around the peak of dorsal CA1 theta cycles, in contrast to previously reported dorsal hippocampal pyramidal cells. Therefore, prefrontal neurons might be driven by monosynaptic connections from the ventral hippocampus during theta oscillations. During prefrontal spindle oscillations, the majority of pyramidal cells and PV+/CB+ basket cells fired preferentially at the trough and early ascending phase, but CB+/PV- dendrite-targeting cells fired uniformly at all phases. We conclude that PV+/CB+ basket cells contribute to rhythmic responses of prefrontal pyramidal cells in relation to hippocampal and thalamic inputs and CB+/PV- dendrite-targeting cells modulate the excitability of dendrites and spines regardless of these field rhythms. Distinct classes of GABAergic interneuron in the prefrontal cortex contribute differentially to the synchronization of pyramidal cells during network oscillations. PMID:19641119

  6. Cannabinoids attenuate hippocampal gamma oscillations by suppressing excitatory synaptic input onto CA3 pyramidal neurons and fast spiking basket cells

    PubMed Central

    Holderith, Noémi; Németh, Beáta; Papp, Orsolya I; Veres, Judit M; Nagy, Gergő A; Hájos, Norbert

    2011-01-01

    Abstract CB1 cannabinoid receptor (CB1R) activation by exogenous ligands can impair memory processes, which critically depend on synchronous neuronal activities that are temporarily structured by oscillations. In this study, we aimed to reveal the mechanisms underlying the cannabinoid-induced decrease in gamma oscillations. We first verified that cannabinoids (CP55,940 and WIN55,212-2) readily suppressed carbachol-induced gamma oscillations in the CA3 region of hippocampal slices via activation of CB1Rs. The cannabinoid-induced decrease in the peak power of oscillations was accompanied by reduced and less precise firing activity in CA3 pyramidal cells and fast spiking basket cells. By examining the cannabinoid sensitivity of synaptic inputs we found that the amplitude of evoked excitatory postsynaptic currents was significantly suppressed upon CB1R activation in both CA3 pyramidal cells and fast spiking basket cells. In contrast, evoked inhibitory postsynaptic currents in CA3 pyramidal cells were unaltered. Furthermore, we observed that a CB1R agonist-induced decrease in the oscillation power at the beginning of the drug application was accompanied primarily by the reduced discharge of fast spiking basket cells, while pyramidal cell firing was unaltered. This result implies that the dampening of cholinergically induced gamma oscillations in the hippocampus by cannabinoids can be explained by a reduced excitatory input predominantly onto fast spiking basket cells, which leads to a reduction in neuronal firing frequency and precision, and thus to smaller field potentials. In addition, we uncovered that the spontaneously occurring sharp wave-ripple activities in hippocampal slices could also be suppressed by CB1R activation suggesting that cannabinoids profoundly reduce the intrinsically generated oscillatory activities at distinct frequencies in CA3 networks by reducing synaptic neurotransmission. PMID:21859823

  7. From network heterogeneities to familiarity detection and hippocampal memory management

    NASA Astrophysics Data System (ADS)

    Wang, Jane X.; Poe, Gina; Zochowski, Michal

    2008-10-01

    Hippocampal-neocortical interactions are key to the rapid formation of novel associative memories in the hippocampus and consolidation to long term storage sites in the neocortex. We investigated the role of network correlates during information processing in hippocampal-cortical networks. We found that changes in the intrinsic network dynamics due to the formation of structural network heterogeneities alone act as a dynamical and regulatory mechanism for stimulus novelty and familiarity detection, thereby controlling memory management in the context of memory consolidation. This network dynamic, coupled with an anatomically established feedback between the hippocampus and the neocortex, recovered heretofore unexplained properties of neural activity patterns during memory management tasks which we observed during sleep in multiunit recordings from behaving animals. Our simple dynamical mechanism shows an experimentally matched progressive shift of memory activation from the hippocampus to the neocortex and thus provides the means to achieve an autonomous off-line progression of memory consolidation.

  8. Ripples make waves: binding structured activity and plasticity in hippocampal networks.

    PubMed

    Sadowski, Josef H L P; Jones, Matthew W; Mellor, Jack R

    2011-01-01

    Establishing novel episodic memories and stable spatial representations depends on an exquisitely choreographed, multistage process involving the online encoding and offline consolidation of sensory information, a process that is largely dependent on the hippocampus. Each step is influenced by distinct neural network states that influence the pattern of activation across cellular assemblies. In recent years, the occurrence of hippocampal sharp wave ripple (SWR) oscillations has emerged as a potentially vital network phenomenon mediating the steps between encoding and consolidation, both at a cellular and network level by promoting the rapid replay and reactivation of recent activity patterns. Such events facilitate memory formation by optimising the conditions for synaptic plasticity to occur between contingent neural elements. In this paper, we explore the ways in which SWRs and other network events can bridge the gap between spatiomnemonic processing at cellular/synaptic and network levels in the hippocampus. PMID:21961073

  9. Hippocampal and neocortical gamma oscillations predict memory formation in humans.

    PubMed

    Sederberg, Per B; Schulze-Bonhage, Andreas; Madsen, Joseph R; Bromfield, Edward B; McCarthy, David C; Brandt, Armin; Tully, Michele S; Kahana, Michael J

    2007-05-01

    Functional magnetic resonance imaging (fMRI) of the human brain has shown that the hippocampus and the left temporal and frontal cortices play a key role in the formation of new verbal memories. We recorded electrical activity from 2349 surgically implanted intracranial electrodes in epilepsy patients while they studied and later recalled lists of common words. Using these recordings, we demonstrate that gamma oscillations (44-64 Hz) in the hippocampus and the left temporal and frontal cortices predict successful encoding of new verbal memories. This increase in gamma oscillations was not seen in other frequency bands, whose activity generally decreased during successful memory formation. These findings identify a role for gamma oscillations in verbal memory formation with the hippocampus and the left temporal and frontal cortices, the same regions implicated using noninvasive fMRI recording methods. PMID:16831858

  10. A Topological Model of the Hippocampal Cell Assembly Network

    PubMed Central

    Babichev, Andrey; Ji, Daoyun; Mémoli, Facundo; Dabaghian, Yuri A.

    2016-01-01

    It is widely accepted that the hippocampal place cells' spiking activity produces a cognitive map of space. However, many details of this representation's physiological mechanism remain unknown. For example, it is believed that the place cells exhibiting frequent coactivity form functionally interconnected groups—place cell assemblies—that drive readout neurons in the downstream networks. However, the sheer number of coactive combinations is extremely large, which implies that only a small fraction of them actually gives rise to cell assemblies. The physiological processes responsible for selecting the winning combinations are highly complex and are usually modeled via detailed synaptic and structural plasticity mechanisms. Here we propose an alternative approach that allows modeling the cell assembly network directly, based on a small number of phenomenological selection rules. We then demonstrate that the selected population of place cell assemblies correctly encodes the topology of the environment in biologically plausible time, and may serve as a schematic model of the hippocampal network. PMID:27313527

  11. Atorvastatin enhances kainate-induced gamma oscillations in rat hippocampal slices.

    PubMed

    Li, Chengzhang; Wang, Jiangang; Zhao, Jianhua; Wang, Yali; Liu, Zhihua; Guo, Fang Li; Wang, Xiao Fang; Vreugdenhil, Martin; Lu, Cheng Biao

    2016-09-01

    Atorvastatin has been shown to affect cognitive functions in rodents and humans. However, the underlying mechanism is not fully understood. Because hippocampal gamma oscillations (γ, 20-80 Hz) are associated with cognitive functions, we studied the effect of atorvastatin on persistent kainate-induced γ oscillation in the CA3 area of rat hippocampal slices. The involvement of NMDA receptors and multiple kinases was tested before and after administration of atorvastatin. Whole-cell current-clamp and voltage-clamp recordings were made from CA3 pyramidal neurons and interneurons before and after atorvastatin application. Atorvastatin increased γ power by ~ 50% in a concentration-dependent manner, without affecting dominant frequency. Whereas atorvastatin did not affect intrinsic properties of both pyramidal neurons and interneurons, it increased the firing frequency of interneurons but not that of pyramidal neurons. Furthermore, whereas atorvastatin did not affect synaptic current amplitude, it increased the frequency of spontaneous inhibitory post-synaptic currents, but did not affect the frequency of spontaneous excitatory post-synaptic currents. The atorvastatin-induced enhancement of γ oscillations was prevented by pretreatment with the PKA inhibitor H89, the ERK inhibitor U0126, or the PI3K inhibitor wortmanin, but not by the NMDA receptor antagonist D-AP5. Taken together, these results demonstrate that atorvastatin enhanced the kainate-induced γ oscillation by increasing interneuron excitability, with an involvement of multiple intracellular kinase pathways. Our study suggests that the classical cholesterol-lowering agent atorvastatin may improve cognitive functions compromised in disease, via the enhancement of hippocampal γ oscillations. PMID:27336700

  12. A hippocampal network for spatial coding during immobility and sleep.

    PubMed

    Kay, Kenneth; Sosa, Marielena; Chung, Jason E; Karlsson, Mattias P; Larkin, Margaret C; Frank, Loren M

    2016-03-10

    How does an animal know where it is when it stops moving? Hippocampal place cells fire at discrete locations as subjects traverse space, thereby providing an explicit neural code for current location during locomotion. In contrast, during awake immobility, the hippocampus is thought to be dominated by neural firing representing past and possible future experience. The question of whether and how the hippocampus constructs a representation of current location in the absence of locomotion has been unresolved. Here we report that a distinct population of hippocampal neurons, located in the CA2 subregion, signals current location during immobility, and does so in association with a previously unidentified hippocampus-wide network pattern. In addition, signalling of location persists into brief periods of desynchronization prevalent in slow-wave sleep. The hippocampus thus generates a distinct representation of current location during immobility, pointing to mnemonic processing specific to experience occurring in the absence of locomotion. PMID:26934224

  13. A context-sensitive mechanism in hippocampal CA1 networks.

    PubMed

    Tsukada, Minoru; Fukushima, Yasuhiro

    2011-02-01

    This paper presents a possible context-sensitive mechanism in a neural network and at single neuron levels based on the experiments of hippocampal CA1 and their theoretical models. First, the spatiotemporal learning rule (STLR, non-Hebbian) and the Hebbian rule (HEBB) are experimentally shown to coexist in dendrite-soma interactions in single hippocampal pyramidal cells of CA1. Second, the functional differences between STLR and HEBB are theoretically shown in pattern separation and pattern completion. Third, the interaction between STLR and HEBB in neural levels is proposed to play an important role in forming a selective context determined by value information, which is related to expected reward and behavioral estimation. PMID:20844974

  14. Associative Memory Storage and Retrieval: Involvement of Theta Oscillations in Hippocampal Information Processing

    PubMed Central

    Stella, Federico; Treves, Alessandro

    2011-01-01

    Theta oscillations are thought to play a critical role in neuronal information processing, especially in the hippocampal region, where their presence is particularly salient. A detailed description of theta dynamics in this region has revealed not only a consortium of layer-specific theta dipoles, but also within-layer differences in the expression of theta. This complex and articulated arrangement of current flows is reflected in the way neuronal firing is modulated in time. Several models have proposed that these different theta modulators flexibly coordinate hippocampal regions, to support associative memory formation and retrieval. Here, we summarily review different approaches related to this issue and we describe a mechanism, based on experimental and simulation results, for memory retrieval in CA3 involving theta modulation. PMID:21961072

  15. Signal dispersion within a hippocampal neural network

    NASA Technical Reports Server (NTRS)

    Horowitz, J. M.; Mates, J. W. B.

    1975-01-01

    A model network is described, representing two neural populations coupled so that one population is inhibited by activity it excites in the other. Parameters and operations within the model represent EPSPs, IPSPs, neural thresholds, conduction delays, background activity and spatial and temporal dispersion of signals passing from one population to the other. Simulations of single-shock and pulse-train driving of the network are presented for various parameter values. Neuronal events from 100 to 300 msec following stimulation are given special consideration in model calculations.

  16. Ovarian cycle-linked plasticity of δ-GABAA receptor subunits in hippocampal interneurons affects γ oscillations in vivo.

    PubMed

    Barth, Albert M I; Ferando, Isabella; Mody, Istvan

    2014-01-01

    GABAA receptors containing δ subunits (δ-GABAARs) are GABA-gated ion channels with extra- and perisynaptic localization, strong sensitivity to neurosteroids (NS), and a high degree of plasticity. In selective brain regions they are expressed on specific principal cells and interneurons (INs), and generate a tonic conductance that controls neuronal excitability and oscillations. Plasticity of δ-GABAARs in principal cells has been described during states of altered NS synthesis including acute stress, puberty, ovarian cycle, pregnancy and the postpartum period, with direct consequences on neuronal excitability and network dynamics. The defining network events implicated in cognitive function, memory formation and encoding are γ oscillations (30-120 Hz), a well-timed loop of excitation and inhibition between principal cells and PV-expressing INs (PV + INs). The δ-GABAARs of INs can modify γ oscillations, and a lower expression of δ-GABAARs on INs during pregnancy alters γ frequency recorded in vitro. The ovarian cycle is another physiological event with large fluctuations in NS levels and δ-GABAARs. Stages of the cycle are paralleled by swings in memory performance, cognitive function, and mood in both humans and rodents. Here we show δ-GABAARs changes during the mouse ovarian cycle in hippocampal cell types, with enhanced expression during diestrus in principal cells and specific INs. The plasticity of δ-GABAARs on PV-INs decreases the magnitude of γ oscillations continuously recorded in area CA1 throughout several days in vivo during diestrus and increases it during estrus. Such recurring changes in γ magnitude were not observed in non-cycling wild-type (WT) females, cycling females lacking δ-GABAARs only on PV-INs (PV-Gabrd (-/-)), and in male mice during a time course equivalent to the ovarian cycle. Our findings may explain the impaired memory and cognitive performance experienced by women with premenstrual syndrome (PMS) or premenstrual dysphoric

  17. Functional clustering in hippocampal cultures: relating network structure and dynamics

    NASA Astrophysics Data System (ADS)

    Feldt, S.; Wang, J. X.; Shtrahman, E.; Dzakpasu, R.; Olariu, E.; Żochowski, M.

    2010-12-01

    In this work we investigate the relationship between gross anatomic structural network properties, neuronal dynamics and the resultant functional structure in dissociated rat hippocampal cultures. Specifically, we studied cultures as they developed under two conditions: the first supporting glial cell growth (high glial group), and the second one inhibiting it (low glial group). We then compared structural network properties and the spatio-temporal activity patterns of the neurons. Differences in dynamics between the two groups could be linked to the impact of the glial network on the neuronal network as the cultures developed. We also implemented a recently developed algorithm called the functional clustering algorithm (FCA) to obtain the resulting functional network structure. We show that this new algorithm is useful for capturing changes in functional network structure as the networks evolve over time. The FCA detects changes in functional structure that are consistent with expected dynamical differences due to the impact of the glial network. Cultures in the high glial group show an increase in global synchronization as the cultures age, while those in the low glial group remain locally synchronized. We additionally use the FCA to quantify the amount of synchronization present in the cultures and show that the total level of synchronization in the high glial group is stronger than in the low glial group. These results indicate an interdependence between the glial and neuronal networks present in dissociated cultures.

  18. Astroglial Metabolic Networks Sustain Hippocampal Synaptic Transmission

    NASA Astrophysics Data System (ADS)

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

    2008-12-01

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

  19. Methylxanthine-evoked perturbation of spontaneous and evoked activities in isolated newborn rat hippocampal networks.

    PubMed

    Ruangkittisakul, A; Sharopov, S; Kantor, C; Kuribayashi, J; Mildenberger, E; Luhmann, H J; Kilb, W; Ballanyi, K

    2015-08-20

    Treatment of apnea of prematurity with methylxanthines like caffeine, aminophylline or theophylline can evoke hippocampal seizures. However, it is unknown at which interstitial brain concentrations methylxanthines promote such neonatal seizures or interfere with physiological 'early network oscillations' (ENOs) that are considered as pivotal for maturation of hippocampal neural networks. We studied theophylline and caffeine effects on ENOs in CA3 neurons (CA3-ENOs) and CA3 electrical stimulation-evoked monosynaptic CA1 field potentials (CA1-FPs) in sliced and intact hippocampi, respectively, from 8 to 10-days-old rats. Submillimolar doses of theophylline and caffeine, blocking adenosine receptors and phosphodiesterase-4 (PDE4), did not affect CA3-ENOs, ENO-associated cytosolic Ca(2+) transients or CA1-FPs nor did they provoke seizure-like discharges. Low millimolar doses of theophylline (⩾1mM) or caffeine (⩾5mM), blocking GABAA and glycine receptors plus sarcoplasmic-endoplasmic reticulum Ca(2+) ATPase (SERCA)-type Ca(2+) ATPases, evoked seizure-like discharges with no indication of cytosolic Ca(2+) dysregulation. Inhibiting PDE4 with rolipram or glycine receptors with strychnine had no effect on CA3-ENOs and did not occlude seizure-like events as tested with theophylline. GABAA receptor blockade induced seizure-like discharges and occluded theophylline-evoked seizure-like discharges in the slices, but not in the intact hippocampi. In summary, submillimolar methylxanthine concentrations do not acutely affect spontaneous CA3-ENOs or electrically evoked synaptic activities and low millimolar doses are needed to evoke seizure-like discharges in isolated developing hippocampal neural networks. We conclude that mechanisms of methylxanthine-related seizure-like discharges do not involve SERCA inhibition-related neuronal Ca(2+) dysregulation, PDE4 blockade or adenosine and glycine receptor inhibition, whereas GABA(A) receptor blockade may contribute partially. PMID

  20. Generation of oscillating gene regulatory network motifs

    NASA Astrophysics Data System (ADS)

    van Dorp, M.; Lannoo, B.; Carlon, E.

    2013-07-01

    Using an improved version of an evolutionary algorithm originally proposed by François and Hakim [Proc. Natl. Acad. Sci. USAPNASA60027-842410.1073/pnas.0304532101 101, 580 (2004)], we generated small gene regulatory networks in which the concentration of a target protein oscillates in time. These networks may serve as candidates for oscillatory modules to be found in larger regulatory networks and protein interaction networks. The algorithm was run for 105 times to produce a large set of oscillating modules, which were systematically classified and analyzed. The robustness of the oscillations against variations of the kinetic rates was also determined, to filter out the least robust cases. Furthermore, we show that the set of evolved networks can serve as a database of models whose behavior can be compared to experimentally observed oscillations. The algorithm found three smallest (core) oscillators in which nonlinearities and number of components are minimal. Two of those are two-gene modules: the mixed feedback loop, already discussed in the literature, and an autorepressed gene coupled with a heterodimer. The third one is a single gene module which is competitively regulated by a monomer and a dimer. The evolutionary algorithm also generated larger oscillating networks, which are in part extensions of the three core modules and in part genuinely new modules. The latter includes oscillators which do not rely on feedback induced by transcription factors, but are purely of post-transcriptional type. Analysis of post-transcriptional mechanisms of oscillation may provide useful information for circadian clock research, as recent experiments showed that circadian rhythms are maintained even in the absence of transcription.

  1. Enhancement of CA3 hippocampal network activity by activation of group II metabotropic glutamate receptors

    PubMed Central

    Ster, Jeanne; Mateos, José María; Grewe, Benjamin Friedrich; Coiret, Guyllaume; Corti, Corrado; Corsi, Mauro; Helmchen, Fritjof; Gerber, Urs

    2011-01-01

    Impaired function or expression of group II metabotropic glutamate receptors (mGluRIIs) is observed in brain disorders such as schizophrenia. This class of receptor is thought to modulate activity of neuronal circuits primarily by inhibiting neurotransmitter release. Here, we characterize a postsynaptic excitatory response mediated by somato-dendritic mGluRIIs in hippocampal CA3 pyramidal cells and in stratum oriens interneurons. The specific mGluRII agonists DCG-IV or LCCG-1 induced an inward current blocked by the mGluRII antagonist LY341495. Experiments with transgenic mice revealed a significant reduction of the inward current in mGluR3−/− but not in mGluR2−/− mice. The excitatory response was associated with periods of synchronized activity at theta frequency. Furthermore, cholinergically induced network oscillations exhibited decreased frequency when mGluRIIs were blocked. Thus, our data indicate that hippocampal responses are modulated not only by presynaptic mGluRIIs that reduce glutamate release but also by postsynaptic mGluRIIs that depolarize neurons and enhance CA3 network activity. PMID:21628565

  2. Oscillation Phase Locking and Late ERP Components of Intracranial Hippocampal Recordings Correlate to Patient Performance in a Working Memory Task

    PubMed Central

    Kleen, Jonathan K.; Testorf, Markus E.; Roberts, David W.; Scott, Rod C.; Jobst, Barbara J.; Holmes, Gregory L.; Lenck-Santini, Pierre-Pascal

    2016-01-01

    In working memory tasks, stimulus presentation induces a resetting of intracranial temporal lobe oscillations in multiple frequency bands. To further understand the functional relevance of this phenomenon, we investigated whether working memory performance depends on the phase precision of ongoing oscillations in the hippocampus. We recorded intra-hippocampal local field potentials in individuals performing a working memory task. Two types of trials were administered. For high memory trials presentation of a list of four letters (“List”) was followed by a single letter memory probe (“Test”). Low memory load trials, consisting of four identical letters (AAAA) followed by a probe with the same letter (A), were interspersed. Significant phase locking of ongoing oscillations across trials, estimated by the Pairwise Phase Consistency Index (PPCI) was observed in delta (0.5–4 Hz), theta (5–7 Hz), and alpha (8–12 Hz) bands during stimulus presentation and recall but was increased in low memory load trials. Across patients however, higher delta PPCIs during recall in the left hippocampus were associated with faster reaction times. Because phase locking could also be interpreted as a consequence of a stimulus evoked potential, we performed event related potential analysis (ERP) and examined the relationship of ERP components with performance. We found that both amplitude and latency of late ERP components correlated with both reaction time and accuracy. We propose that, in the Sternberg task, phase locking of oscillations, or alternatively its ERP correlate, synchronizes networks within the hippocampus and connected structures that are involved in working memory. PMID:27378885

  3. Distinct hippocampal functional networks revealed by tractography-based parcellation.

    PubMed

    Adnan, Areeba; Barnett, Alexander; Moayedi, Massieh; McCormick, Cornelia; Cohn, Melanie; McAndrews, Mary Pat

    2016-07-01

    Recent research suggests the anterior and posterior hippocampus form part of two distinct functional neural networks. Here we investigate the structural underpinnings of this functional connectivity difference using diffusion-weighted imaging-based parcellation. Using this technique, we substantiated that the hippocampus can be parcellated into distinct anterior and posterior segments. These structurally defined segments did indeed show different patterns of resting state functional connectivity, in that the anterior segment showed greater connectivity with temporal and orbitofrontal cortex, whereas the posterior segment was more highly connected to medial and lateral parietal cortex. Furthermore, we showed that the posterior hippocampal connectivity to memory processing regions, including the dorsolateral prefrontal cortex, parahippocampal, inferior temporal and fusiform gyri and the precuneus, predicted interindividual relational memory performance. These findings provide important support for the integration of structural and functional connectivity in understanding the brain networks underlying episodic memory. PMID:26206251

  4. Establishing a Statistical Link between Network Oscillations and Neural Synchrony

    PubMed Central

    Zhou, Pengcheng; Burton, Shawn D.; Snyder, Adam C.; Smith, Matthew A.; Urban, Nathaniel N.; Kass, Robert E.

    2015-01-01

    Pairs of active neurons frequently fire action potentials or “spikes” nearly synchronously (i.e., within 5 ms of each other). This spike synchrony may occur by chance, based solely on the neurons’ fluctuating firing patterns, or it may occur too frequently to be explicable by chance alone. When spike synchrony above chances levels is present, it may subserve computation for a specific cognitive process, or it could be an irrelevant byproduct of such computation. Either way, spike synchrony is a feature of neural data that should be explained. A point process regression framework has been developed previously for this purpose, using generalized linear models (GLMs). In this framework, the observed number of synchronous spikes is compared to the number predicted by chance under varying assumptions about the factors that affect each of the individual neuron’s firing-rate functions. An important possible source of spike synchrony is network-wide oscillations, which may provide an essential mechanism of network information flow. To establish the statistical link between spike synchrony and network-wide oscillations, we have integrated oscillatory field potentials into our point process regression framework. We first extended a previously-published model of spike-field association and showed that we could recover phase relationships between oscillatory field potentials and firing rates. We then used this new framework to demonstrate the statistical relationship between oscillatory field potentials and spike synchrony in: 1) simulated neurons, 2) in vitro recordings of hippocampal CA1 pyramidal cells, and 3) in vivo recordings of neocortical V4 neurons. Our results provide a rigorous method for establishing a statistical link between network oscillations and neural synchrony. PMID:26465621

  5. Establishing a Statistical Link between Network Oscillations and Neural Synchrony.

    PubMed

    Zhou, Pengcheng; Burton, Shawn D; Snyder, Adam C; Smith, Matthew A; Urban, Nathaniel N; Kass, Robert E

    2015-10-01

    Pairs of active neurons frequently fire action potentials or "spikes" nearly synchronously (i.e., within 5 ms of each other). This spike synchrony may occur by chance, based solely on the neurons' fluctuating firing patterns, or it may occur too frequently to be explicable by chance alone. When spike synchrony above chances levels is present, it may subserve computation for a specific cognitive process, or it could be an irrelevant byproduct of such computation. Either way, spike synchrony is a feature of neural data that should be explained. A point process regression framework has been developed previously for this purpose, using generalized linear models (GLMs). In this framework, the observed number of synchronous spikes is compared to the number predicted by chance under varying assumptions about the factors that affect each of the individual neuron's firing-rate functions. An important possible source of spike synchrony is network-wide oscillations, which may provide an essential mechanism of network information flow. To establish the statistical link between spike synchrony and network-wide oscillations, we have integrated oscillatory field potentials into our point process regression framework. We first extended a previously-published model of spike-field association and showed that we could recover phase relationships between oscillatory field potentials and firing rates. We then used this new framework to demonstrate the statistical relationship between oscillatory field potentials and spike synchrony in: 1) simulated neurons, 2) in vitro recordings of hippocampal CA1 pyramidal cells, and 3) in vivo recordings of neocortical V4 neurons. Our results provide a rigorous method for establishing a statistical link between network oscillations and neural synchrony. PMID:26465621

  6. Oscillations Go the Distance: Low-Frequency Human Hippocampal Oscillations Code Spatial Distance in the Absence of Sensory Cues during Teleportation.

    PubMed

    Vass, Lindsay K; Copara, Milagros S; Seyal, Masud; Shahlaie, Kiarash; Farias, Sarah Tomaszewski; Shen, Peter Y; Ekstrom, Arne D

    2016-03-16

    Low-frequency (delta/theta band) hippocampal neural oscillations play prominent roles in computational models of spatial navigation, but their exact function remains unknown. Some theories propose they are primarily generated in response to sensorimotor processing, while others suggest a role in memory-related processing. We directly recorded hippocampal EEG activity in patients undergoing seizure monitoring while they explored a virtual environment containing teleporters. Critically, this manipulation allowed patients to experience movement through space in the absence of visual and self-motion cues. The prevalence and duration of low-frequency hippocampal oscillations were unchanged by this manipulation, indicating that sensorimotor processing was not required to elicit them during navigation. Furthermore, the frequency-wise pattern of oscillation prevalence during teleportation contained spatial information capable of classifying the distance teleported. These results demonstrate that movement-related sensory information is not required to drive spatially informative low-frequency hippocampal oscillations during navigation and suggest a specific function in memory-related spatial updating. PMID:26924436

  7. Driven synchronization in random networks of oscillators.

    PubMed

    Hindes, Jason; Myers, Christopher R

    2015-07-01

    Synchronization is a universal phenomenon found in many non-equilibrium systems. Much recent interest in this area has overlapped with the study of complex networks, where a major focus is determining how a system's connectivity patterns affect the types of behavior that it can produce. Thus far, modeling efforts have focused on the tendency of networks of oscillators to mutually synchronize themselves, with less emphasis on the effects of external driving. In this work, we discuss the interplay between mutual and driven synchronization in networks of phase oscillators of the Kuramoto type, and explore how the structure and emergence of such states depend on the underlying network topology for simple random networks with a given degree distribution. We find a variety of interesting dynamical behaviors, including bifurcations and bistability patterns that are qualitatively different for heterogeneous and homogeneous networks, and which are separated by a Takens-Bogdanov-Cusp singularity in the parameter region where the coupling strength between oscillators is weak. Our analysis is connected to the underlying dynamics of oscillator clusters for important states and transitions. PMID:26232970

  8. Sparse encoding of automatic visual association in hippocampal networks.

    PubMed

    Hulme, Oliver J; Skov, Martin; Chadwick, Martin J; Siebner, Hartwig R; Ramsøy, Thomas Z

    2014-11-15

    Intelligent action entails exploiting predictions about associations between elements of ones environment. The hippocampus and mediotemporal cortex are endowed with the network topology, physiology, and neurochemistry to automatically and sparsely code sensori-cognitive associations that can be reconstructed from single or partial inputs. Whilst acquiring fMRI data and performing an attentional task, participants were incidentally presented with a sequence of cartoon images. By assigning subjects a post-scan free-association task on the same images we assayed the density of associations triggered by these stimuli. Using multivariate Bayesian decoding, we show that human hippocampal and temporal neocortical structures host sparse associative representations that are automatically triggered by visual input. Furthermore, as predicted theoretically, there was a significant increase in sparsity in the Cornu Ammonis subfields, relative to the entorhinal cortex. Remarkably, the sparsity of CA encoding correlated significantly with associative memory performance over subjects; elsewhere within the temporal lobe, entorhinal, parahippocampal, perirhinal and fusiform cortices showed the highest model evidence for the sparse encoding of associative density. In the absence of reportability or attentional confounds, this charts a distribution of visual associative representations within hippocampal populations and their temporal lobe afferent fields, and demonstrates the viability of retrospective associative sampling techniques for assessing the form of reflexive associative encoding. PMID:25038440

  9. The Global Oscillation Network Group (GONG) Project

    PubMed

    Harvey; Hill; Hubbard; Kennedy; Leibacher; Pintar; Gilman; Noyes; Title; Toomre; Ulrich; Bhatnagar; Kennewell; Marquette; Patron; Saa; Yasukawa

    1996-05-31

    Helioseismology requires nearly continuous observations of the oscillations of the solar surface for long periods of time in order to obtain precise measurements of the sun's normal modes of oscillation. The GONG project acquires velocity images from a network of six identical instruments distributed around the world. The GONG network began full operation in October 1995. It has achieved a duty cycle of 89 percent and reduced the magnitude of spectral artifacts by a factor of 280 in power, compared with single-site observations. The instrumental noise is less than the observed solar background. PMID:8662455

  10. Cell-specific synaptic plasticity induced by network oscillations

    PubMed Central

    Zarnadze, Shota; Bäuerle, Peter; Santos-Torres, Julio; Böhm, Claudia; Schmitz, Dietmar; Geiger, Jörg RP

    2016-01-01

    Gamma rhythms are known to contribute to the process of memory encoding. However, little is known about the underlying mechanisms at the molecular, cellular and network levels. Using local field potential recording in awake behaving mice and concomitant field potential and whole-cell recordings in slice preparations we found that gamma rhythms lead to activity-dependent modification of hippocampal networks, including alterations in sharp wave-ripple complexes. Network plasticity, expressed as long-lasting increases in sharp wave-associated synaptic currents, exhibits enhanced excitatory synaptic strength in pyramidal cells that is induced postsynaptically and depends on metabotropic glutamate receptor-5 activation. In sharp contrast, alteration of inhibitory synaptic strength is independent of postsynaptic activation and less pronounced. Further, we found a cell type-specific, directionally biased synaptic plasticity of two major types of GABAergic cells, parvalbumin- and cholecystokinin-expressing interneurons. Thus, we propose that gamma frequency oscillations represent a network state that introduces long-lasting synaptic plasticity in a cell-specific manner. DOI: http://dx.doi.org/10.7554/eLife.14912.001 PMID:27218453

  11. Cell-specific synaptic plasticity induced by network oscillations.

    PubMed

    Zarnadze, Shota; Bäuerle, Peter; Santos-Torres, Julio; Böhm, Claudia; Schmitz, Dietmar; Geiger, Jörg Rp; Dugladze, Tamar; Gloveli, Tengis

    2016-01-01

    Gamma rhythms are known to contribute to the process of memory encoding. However, little is known about the underlying mechanisms at the molecular, cellular and network levels. Using local field potential recording in awake behaving mice and concomitant field potential and whole-cell recordings in slice preparations we found that gamma rhythms lead to activity-dependent modification of hippocampal networks, including alterations in sharp wave-ripple complexes. Network plasticity, expressed as long-lasting increases in sharp wave-associated synaptic currents, exhibits enhanced excitatory synaptic strength in pyramidal cells that is induced postsynaptically and depends on metabotropic glutamate receptor-5 activation. In sharp contrast, alteration of inhibitory synaptic strength is independent of postsynaptic activation and less pronounced. Further, we found a cell type-specific, directionally biased synaptic plasticity of two major types of GABAergic cells, parvalbumin- and cholecystokinin-expressing interneurons. Thus, we propose that gamma frequency oscillations represent a network state that introduces long-lasting synaptic plasticity in a cell-specific manner. PMID:27218453

  12. Removing entorhinal cortex input to the dentate gyrus does not impede low frequency oscillations, an EEG-biomarker of hippocampal epileptogenesis

    PubMed Central

    Meyer, Martin; Kienzler-Norwood, Friederike; Bauer, Sebastian; Rosenow, Felix; Norwood, Braxton A.

    2016-01-01

    Following prolonged perforant pathway stimulation (PPS) in rats, a seizure-free “latent period” is observed that lasts around 3 weeks. During this time, aberrant neuronal activity occurs, which has been hypothesized to contribute to the generation of an “epileptic” network. This study was designed to 1) examine the pathological network activity that occurs in the dentate gyrus during the latent period, and 2) determine whether suppressing this activity by removing the main input to the dentate gyrus could stop or prolong epileptogenesis. Immediately following PPS, continuous video-EEG monitoring was used to record spontaneous neuronal activity and detect seizures. During the latent period, low frequency oscillations (LFOs), occurring at a rate of approximately 1 Hz, were detected in the dentate gyrus of all rats that developed epilepsy. LFO incidence was apparently random, but often decreased in the hour preceding a spontaneous seizure. Bilateral transection of the perforant pathway did not impact the incidence of hippocampal LFOs, the latency to epilepsy, or hippocampal neuropathology. Our main findings are: 1) LFOs are a reliable biomarker of hippocampal epileptogenesis, and 2) removing entorhinal cortex input to the hippocampus neither reduces the occurrence of LFOs nor has a demonstrable antiepileptogenic effect. PMID:27160925

  13. Dampened hippocampal oscillations and enhanced spindle activity in an asymptomatic model of developmental cortical malformations

    PubMed Central

    Cid, Elena; Gomez-Dominguez, Daniel; Martin-Lopez, David; Gal, Beatriz; Laurent, François; Ibarz, Jose M.; Francis, Fiona; Menendez de la Prida, Liset

    2014-01-01

    Developmental cortical malformations comprise a large spectrum of histopathological brain abnormalities and syndromes. Their genetic, developmental and clinical complexity suggests they should be better understood in terms of the complementary action of independently timed perturbations (i.e., the multiple-hit hypothesis). However, understanding the underlying biological processes remains puzzling. Here we induced developmental cortical malformations in offspring, after intraventricular injection of methylazoxymethanol (MAM) in utero in mice. We combined extensive histological and electrophysiological studies to characterize the model. We found that MAM injections at E14 and E15 induced a range of cortical and hippocampal malformations resembling histological alterations of specific genetic mutations and transplacental mitotoxic agent injections. However, in contrast to most of these models, intraventricularly MAM-injected mice remained asymptomatic and showed no clear epilepsy-related phenotype as tested in long-term chronic recordings and with pharmacological manipulations. Instead, they exhibited a non-specific reduction of hippocampal-related brain oscillations (mostly in CA1); including theta, gamma and HFOs; and enhanced thalamocortical spindle activity during non-REM sleep. These data suggest that developmental cortical malformations do not necessarily correlate with epileptiform activity. We propose that the intraventricular in utero MAM approach exhibiting a range of rhythmopathies is a suitable model for multiple-hit studies of associated neurological disorders. PMID:24782720

  14. Ventromedial prefrontal cortex drives hippocampal theta oscillations induced by mismatch computations.

    PubMed

    Garrido, Marta I; Barnes, Gareth R; Kumaran, Dharshan; Maguire, Eleanor A; Dolan, Raymond J

    2015-10-15

    Detecting environmental change is fundamental for adaptive behavior in an uncertain world. Previous work indicates the hippocampus supports the generation of novelty signals via implementation of a match-mismatch detector that signals when an incoming sensory input violates expectations based on past experience. While existing work has emphasized the particular contribution of the hippocampus, here we ask which other brain structures also contribute to match-mismatch detection. Furthermore, we leverage the fine-grained temporal resolution of magnetoencephalography (MEG) to investigate whether mismatch computations are spectrally confined to the theta range, based on the prominence of this range of oscillations in models of hippocampal function. By recording MEG activity while human subjects perform a task that incorporates conditions of match-mismatch novelty we show that mismatch signals are confined to the theta band and are expressed in both the hippocampus and ventromedial prefrontal cortex (vmPFC). Effective connectivity analyses (dynamic causal modeling) show that the hippocampus and vmPFC work as a functional circuit during mismatch detection. Surprisingly, our results suggest that the vmPFC drives the hippocampus during the generation and processing of mismatch signals. Our findings provide new evidence that the hippocampal-vmPFC circuit is engaged during novelty processing, which has implications for emerging theories regarding the role of vmPFC in memory. PMID:26187453

  15. Whisking, Sniffing, and the Hippocampal θ-Rhythm: A Tale of Two Oscillators

    PubMed Central

    Kleinfeld, David; Deschênes, Martin; Ulanovsky, Nachum

    2016-01-01

    The hippocampus has unique access to neuronal activity across all of the neocortex. Yet an unanswered question is how the transfer of information between these structures is gated. One hypothesis involves temporal-locking of activity in the neocortex with that in the hippocampus. New data from the Matthew E. Diamond laboratory shows that the rhythmic neuronal activity that accompanies vibrissa-based sensation, in rats, transiently locks to ongoing hippocampal θ-rhythmic activity during the sensory-gathering epoch of a discrimination task. This result complements past studies on the locking of sniffing and the θ-rhythm as well as the relation of sniffing and whisking. An overarching possibility is that the preBötzinger inspiration oscillator, which paces whisking, can selectively lock with the θ-rhythm to traffic sensorimotor information between the rat’s neocortex and hippocampus. PMID:26890361

  16. Chimera states in mechanical oscillator networks

    PubMed Central

    Martens, Erik Andreas; Thutupalli, Shashi; Fourrière, Antoine; Hallatschek, Oskar

    2013-01-01

    The synchronization of coupled oscillators is a fascinating manifestation of self-organization that nature uses to orchestrate essential processes of life, such as the beating of the heart. Although it was long thought that synchrony and disorder were mutually exclusive steady states for a network of identical oscillators, numerous theoretical studies in recent years have revealed the intriguing possibility of “chimera states,” in which the symmetry of the oscillator population is broken into a synchronous part and an asynchronous part. However, a striking lack of empirical evidence raises the question of whether chimeras are indeed characteristic of natural systems. This calls for a palpable realization of chimera states without any fine-tuning, from which physical mechanisms underlying their emergence can be uncovered. Here, we devise a simple experiment with mechanical oscillators coupled in a hierarchical network to show that chimeras emerge naturally from a competition between two antagonistic synchronization patterns. We identify a wide spectrum of complex states, encompassing and extending the set of previously described chimeras. Our mathematical model shows that the self-organization observed in our experiments is controlled by elementary dynamical equations from mechanics that are ubiquitous in many natural and technological systems. The symmetry-breaking mechanism revealed by our experiments may thus be prevalent in systems exhibiting collective behavior, such as power grids, optomechanical crystals, or cells communicating via quorum sensing in microbial populations. PMID:23759743

  17. Collective oscillations in disordered neural networks

    NASA Astrophysics Data System (ADS)

    Olmi, Simona; Livi, Roberto; Politi, Antonio; Torcini, Alessandro

    2010-04-01

    We investigate the onset of collective oscillations in a excitatory pulse-coupled network of leaky integrate-and-fire neurons in the presence of quenched and annealed disorder. We find that the disorder induces a weak form of chaos that is analogous to that arising in the Kuramoto model for a finite number N of oscillators [O. V. Popovych , Phys. Rev. E 71 065201(R) (2005)]. In fact, the maximum Lyapunov exponent turns out to scale to zero for N→∞ , with an exponent that is different for the two types of disorder. In the thermodynamic limit, the random-network dynamics reduces to that of a fully homogeneous system with a suitably scaled coupling strength. Moreover, we show that the Lyapunov spectrum of the periodically collective state scales to zero as 1/N2 , analogously to the scaling found for the “splay state.”

  18. Self-sustained oscillations of complex genomic regulatory networks

    NASA Astrophysics Data System (ADS)

    Ye, Weiming; Huang, Xiaodong; Huang, Xuhui; Li, Pengfei; Xia, Qinzhi; Hu, Gang

    2010-05-01

    Recently, self-sustained oscillations in complex networks consisting of non-oscillatory nodes have attracted great interest in diverse natural and social fields. Oscillatory genomic regulatory networks are one of the most typical examples of this kind. Given an oscillatory genomic network, it is important to reveal the central structure generating the oscillation. However, if the network consists of large numbers of genes and interactions, the oscillation generator is deeply hidden in the complicated interactions. We apply the dominant phase-advanced driving path method proposed in Qian et al. (2010) [1] to reduce complex genomic regulatory networks to one-dimensional and unidirectionally linked network graphs where negative regulatory loops are explored to play as the central generators of the oscillations, and oscillation propagation pathways in the complex networks are clearly shown by tree branches radiating from the loops. Based on the above understanding we can control oscillations of genomic networks with high efficiency.

  19. Ventromedial prefrontal cortex drives hippocampal theta oscillations induced by mismatch computations

    PubMed Central

    Garrido, Marta I.; Barnes, Gareth R.; Kumaran, Dharshan; Maguire, Eleanor A.; Dolan, Raymond J.

    2015-01-01

    Detecting environmental change is fundamental for adaptive behavior in an uncertain world. Previous work indicates the hippocampus supports the generation of novelty signals via implementation of a match–mismatch detector that signals when an incoming sensory input violates expectations based on past experience. While existing work has emphasized the particular contribution of the hippocampus, here we ask which other brain structures also contribute to match–mismatch detection. Furthermore, we leverage the fine-grained temporal resolution of magnetoencephalography (MEG) to investigate whether mismatch computations are spectrally confined to the theta range, based on the prominence of this range of oscillations in models of hippocampal function. By recording MEG activity while human subjects perform a task that incorporates conditions of match–mismatch novelty we show that mismatch signals are confined to the theta band and are expressed in both the hippocampus and ventromedial prefrontal cortex (vmPFC). Effective connectivity analyses (dynamic causal modeling) show that the hippocampus and vmPFC work as a functional circuit during mismatch detection. Surprisingly, our results suggest that the vmPFC drives the hippocampus during the generation and processing of mismatch signals. Our findings provide new evidence that the hippocampal–vmPFC circuit is engaged during novelty processing, which has implications for emerging theories regarding the role of vmPFC in memory. PMID:26187453

  20. Self-sustaining oscillations in complex networks of excitable elements

    NASA Astrophysics Data System (ADS)

    McGraw, Patrick; Menzinger, Michael

    2011-03-01

    Random networks of symmetrically coupled, excitable elements can self-organize into coherently oscillating states if the networks contain loops (indeed loops are abundant in random networks) and if the initial conditions are sufficiently random. In the oscillating state, signals propagate in a single direction and one or a few network loops are selected as driving loops in which the excitation periodically circulates. We analyze the mechanism, describe the oscillating states, identify the pacemaker loops, and explain key features of their distribution.

  1. Oscillations in interconnected complex networks under intentional attack

    NASA Astrophysics Data System (ADS)

    Zhang, Wen-Ping; Xia, Yongxiang; Tan, Fei

    2016-01-01

    Many real-world networks are interconnected with each other. In this paper, we study the traffic dynamics in interconnected complex networks under an intentional attack. We find that with the shortest time delay routing strategy, the traffic dynamics can show the stable state, periodic, quasi-periodic and chaotic oscillations, when the capacity redundancy parameter changes. Moreover, compared with isolated complex networks, oscillations always take place in interconnected networks more easily. Thirdly, in interconnected networks, oscillations are affected strongly by the coupling probability and coupling preference.

  2. Model reduction for networks of coupled oscillators

    NASA Astrophysics Data System (ADS)

    Gottwald, Georg A.

    2015-05-01

    We present a collective coordinate approach to describe coupled phase oscillators. We apply the method to study synchronisation in a Kuramoto model. In our approach, an N-dimensional Kuramoto model is reduced to an n-dimensional ordinary differential equation with n ≪ N , constituting an immense reduction in complexity. The onset of both local and global synchronisation is reproduced to good numerical accuracy, and we are able to describe both soft and hard transitions. By introducing two collective coordinates, the approach is able to describe the interaction of two partially synchronised clusters in the case of bimodally distributed native frequencies. Furthermore, our approach allows us to accurately describe finite size scalings of the critical coupling strength. We corroborate our analytical results by comparing with numerical simulations of the Kuramoto model with all-to-all coupling networks for several distributions of the native frequencies.

  3. Network dynamics mediated by heterogeneous topology as related to hippocampal memory management

    NASA Astrophysics Data System (ADS)

    Wang, Jane; Poe, Gina; Zochowski, Michal

    2009-03-01

    Hippocampal-cortical network interactions, including reactivation of recently acquired memories in the hippocampus during sleep, are key to the consolidation of memory traces to long-term storage sites in the neocortex. Network heterogeneities, in the form of regional changes in the connectivity densities of excitatory synapses, support this process in simulated hippocampal-cortical networks by regulating intrinsic network dynamics and thus mediating stimulus familiarity detection as well as selective memory consolidation. We characterize this network model by investigating dynamics due to distributed and overlapping memory structures and examine the ability of regional heterogeneities to both selectively activate in the presence of controlled stimuli and reactivate in the absence of stimuli, the former being indicative of active exploration and the latter of memory replay during sleep.

  4. No evidence for role of extracellular choline-acetyltransferase in generation of gamma oscillations in rat hippocampal slices in vitro.

    PubMed

    Hollnagel, J O; ul Haq, R; Behrens, C J; Maslarova, A; Mody, I; Heinemann, U

    2015-01-22

    Acetylcholine (ACh) is well known to induce persistent γ-oscillations in the hippocampus when applied together with physostigmine, an inhibitor of the ACh degrading enzyme acetylcholinesterase (AChE). Here we report that physostigmine alone can also dose-dependently induce γ-oscillations in rat hippocampal slices. We hypothesized that this effect was due to the presence of choline in the extracellular space and that this choline is taken up into cholinergic fibers where it is converted to ACh by the enzyme choline-acetyltransferase (ChAT). Release of ACh from cholinergic fibers in turn may then induce γ-oscillations. We therefore tested the effects of the choline uptake inhibitor hemicholinium-3 (HC-3) on persistent γ-oscillations either induced by physostigmine alone or by co-application of ACh and physostigmine. We found that HC-3 itself did not induce γ-oscillations and also did not prevent physostigmine-induced γ-oscillation while washout of physostigmine and ACh-induced γ-oscillations was accelerated. It was recently reported that ChAT might also be present in the extracellular space (Vijayaraghavan et al., 2013). Here we show that the effect of physostigmine was prevented by the ChAT inhibitor (2-benzoylethyl)-trimethylammonium iodide (BETA) which could indicate extracellular synthesis of ACh. However, when we tested for effects of extracellularly applied acetyl-CoA, a substrate of ChAT for synthesis of ACh, physostigmine-induced γ-oscillations were attenuated. Together, these findings do not support the idea that ACh can be synthesized by an extracellularly located ChAT. PMID:25453770

  5. 5-Hydroxytryptamine1A receptor-activation hyperpolarizes pyramidal cells and suppresses hippocampal gamma oscillations via Kir3 channel activation

    PubMed Central

    Johnston, April; McBain, Chris J; Fisahn, André

    2014-01-01

    Rhythmic cortical neuronal oscillations in the gamma frequency band (30–80 Hz, gamma oscillations) have been associated with cognitive processes such as sensory perception and integration, attention, learning, and memory. Gamma oscillations are disrupted in disorders for which cognitive deficits are hallmark symptoms such as schizophrenia and Alzheimer's disease. In vitro, various neurotransmitters have been found to modulate gamma oscillations. Serotonin (5-HT) has long been known to be important for both behavioural and cognitive functions such as learning and memory. Multiple 5-HT receptor subtypes are expressed in the CA3 region of the hippocampus and high doses of 5-HT reduce the power of induced gamma oscillations. Hypothesizing that 5-HT may have cell- and receptor subtype-specific modulatory effects, we investigated the receptor subtypes, cell types and cellular mechanisms engaged by 5-HT in the modulation of gamma oscillations in mice and rats. We found that 5-HT decreases the power of kainate-induced hippocampal gamma oscillations in both species via the 5-HT1A receptor subtype. Whole-cell patch clamp recordings demonstrated that this decrease was caused by a hyperpolarization of CA3 pyramidal cells and a reduction of their firing frequency, but not by alteration of inhibitory neurotransmission. Finally, our results show that the effect on pyramidal cells is mediated via the G protein-coupled receptor inwardly rectifying potassium channel Kir3. Our findings suggest this novel cellular mechanism as a potential target for therapies that are aimed at alleviating cognitive decline by helping the brain to maintain or re-establish normal gamma oscillation levels in neuropsychiatric and neurodegenerative disorders. PMID:25107925

  6. Optogenetic identification of an intrinsic cholinergically driven inhibitory oscillator sensitive to cannabinoids and opioids in hippocampal CA1

    PubMed Central

    Nagode, Daniel A; Tang, Ai-Hui; Yang, Kun; Alger, Bradley E

    2014-01-01

    Neuronal electrical oscillations in the theta (4–14 Hz) and gamma (30–80 Hz) ranges are necessary for the performance of certain animal behaviours and cognitive processes. Perisomatic GABAergic inhibition is prominently involved in cortical oscillations driven by ACh release from septal cholinergic afferents. In neocortex and hippocampal CA3 regions, parvalbumin (PV)-expressing basket cells, activated by ACh and glutamatergic agonists, largely mediate oscillations. However, in CA1 hippocampus in vitro, cholinergic agonists or the optogenetic release of endogenous ACh from septal afferents induces rhythmic, theta-frequency inhibitory postsynaptic currents (IPSCs) in pyramidal cells, even with glutamatergic transmission blocked. The IPSCs are regulated by exogenous and endogenous cannabinoids, suggesting that they arise from type 1 cannabinoid receptor-expressing (CB1R+) interneurons – mainly cholecystokinin (CCK)-expressing cells. Nevertheless, an occult contribution of PV-expressing interneurons to these rhythms remained conceivable. Here, we directly test this hypothesis by selectively silencing CA1 PV-expressing cells optogenetically with halorhodopsin or archaerhodopsin. However, this had no effect on theta-frequency IPSC rhythms induced by carbachol (CCh). In contrast, the silencing of glutamic acid decarboxylase 2-positive interneurons, which include the CCK-expressing basket cells, strongly suppressed inhibitory oscillations; PV-expressing interneurons appear to play no role. The low-frequency IPSC oscillations induced by CCh or optogenetically stimulated ACh release were also inhibited by a μ-opioid receptor (MOR) agonist, which was unexpected because MORs in CA1 are not usually associated with CCK-expressing cells. Our results reveal novel properties of an inhibitory oscillator circuit within CA1 that is activated by muscarinic agonists. The oscillations could contribute to behaviourally relevant, atropine-sensitive, theta rhythms and link

  7. Synaptic mechanisms of pattern completion in the hippocampal CA3 network.

    PubMed

    Guzman, Segundo Jose; Schlögl, Alois; Frotscher, Michael; Jonas, Peter

    2016-09-01

    The hippocampal CA3 region plays a key role in learning and memory. Recurrent CA3-CA3 synapses are thought to be the subcellular substrate of pattern completion. However, the synaptic mechanisms of this network computation remain enigmatic. To investigate these mechanisms, we combined functional connectivity analysis with network modeling. Simultaneous recording from up to eight CA3 pyramidal neurons revealed that connectivity was sparse, spatially uniform, and highly enriched in disynaptic motifs (reciprocal, convergence, divergence, and chain motifs). Unitary connections were composed of one or two synaptic contacts, suggesting efficient use of postsynaptic space. Real-size modeling indicated that CA3 networks with sparse connectivity, disynaptic motifs, and single-contact connections robustly generated pattern completion. Thus, macro- and microconnectivity contribute to efficient memory storage and retrieval in hippocampal networks. PMID:27609885

  8. Hippocampal Neuro-Networks and Dendritic Spine Perturbations in Epileptogenesis Are Attenuated by Neuroprotectin D1

    PubMed Central

    Musto, Alberto E.; Walker, Chelsey P.; Petasis, Nicos A.; Bazan, Nicolas G.

    2015-01-01

    Purpose Limbic epileptogenesis triggers molecular and cellular events that foster the establishment of aberrant neuronal networks that, in turn, contribute to temporal lobe epilepsy (TLE). Here we have examined hippocampal neuronal network activities in the pilocarpine post-status epilepticus model of limbic epileptogenesis and asked whether or not the docosahexaenoic acid (DHA)-derived lipid mediator, neuroprotectin D1 (NPD1), modulates epileptogenesis. Methods Status epilepticus (SE) was induced by intraperitoneal administration of pilocarpine in adult male C57BL/6 mice. To evaluate simultaneous hippocampal neuronal networks, local field potentials were recorded from multi-microelectrode arrays (silicon probe) chronically implanted in the dorsal hippocampus. NPD1 (570 μg/kg) or vehicle was administered intraperitoneally daily for five consecutive days 24 hours after termination of SE. Seizures and epileptiform activity were analyzed in freely-moving control and treated mice during epileptogenesis and epileptic periods. Then hippocampal dendritic spines were evaluated using Golgi-staining. Results We found brief spontaneous microepileptiform activity with high amplitudes in the CA1 pyramidal and stratum radiatum in epileptogenesis. These aberrant activities were attenuated following systemic NPD1 administration, with concomitant hippocampal dendritic spine protection. Moreover, NPD1 treatment led to a reduction in spontaneous recurrent seizures. Conclusions Our results indicate that NPD1 displays neuroprotective bioactivity on the hippocampal neuronal network ensemble that mediates aberrant circuit activity during epileptogenesis. Insight into the molecular signaling mediated by neuroprotective bioactivity of NPD1 on neuronal network dysfunction may contribute to the development of anti-epileptogenic therapeutic strategies. PMID:25617763

  9. Creation and perturbation of planar networks of chemical oscillators

    PubMed Central

    Tompkins, Nathan; Cambria, Matthew Carl; Wang, Adam L.; Heymann, Michael; Fraden, Seth

    2015-01-01

    Methods for creating custom planar networks of diffusively coupled chemical oscillators and perturbing individual oscillators within the network are presented. The oscillators consist of the Belousov-Zhabotinsky (BZ) reaction contained in an emulsion. Networks of drops of the BZ reaction are created with either Dirichlet (constant-concentration) or Neumann (no-flux) boundary conditions in a custom planar configuration using programmable illumination for the perturbations. The differences between the observed network dynamics for each boundary condition are described. Using light, we demonstrate the ability to control the initial conditions of the network and to cause individual oscillators within the network to undergo sustained period elongation or a one-time phase delay. PMID:26117136

  10. Symmetry-broken states on networks of coupled oscillators

    NASA Astrophysics Data System (ADS)

    Jiang, Xin; Abrams, Daniel M.

    2016-05-01

    When identical oscillators are coupled together in a network, dynamical steady states are often assumed to reflect network symmetries. Here, we show that alternative persistent states may also exist that break the symmetries of the underlying coupling network. We further show that these symmetry-broken coexistent states are analogous to those dubbed "chimera states," which can occur when identical oscillators are coupled to one another in identical ways.

  11. Chaos in generically coupled phase oscillator networks with nonpairwise interactions

    NASA Astrophysics Data System (ADS)

    Bick, Christian; Ashwin, Peter; Rodrigues, Ana

    2016-09-01

    The Kuramoto-Sakaguchi system of coupled phase oscillators, where interaction between oscillators is determined by a single harmonic of phase differences of pairs of oscillators, has very simple emergent dynamics in the case of identical oscillators that are globally coupled: there is a variational structure that means the only attractors are full synchrony (in-phase) or splay phase (rotating wave/full asynchrony) oscillations and the bifurcation between these states is highly degenerate. Here we show that nonpairwise coupling—including three and four-way interactions of the oscillator phases—that appears generically at the next order in normal-form based calculations can give rise to complex emergent dynamics in symmetric phase oscillator networks. In particular, we show that chaos can appear in the smallest possible dimension of four coupled phase oscillators for a range of parameter values.

  12. Two generalized algorithms measuring phase-amplitude cross-frequency coupling in neuronal oscillations network.

    PubMed

    Li, Qun; Zheng, Chen-Guang; Cheng, Ning; Wang, Yi-Yi; Yin, Tao; Zhang, Tao

    2016-06-01

    An increasing number of studies pays attention to cross-frequency coupling in neuronal oscillations network, as it is considered to play an important role in exchanging and integrating of information. In this study, two generalized algorithms, phase-amplitude coupling-evolution map approach and phase-amplitude coupling-conditional mutual information which have been developed and applied originally in an identical rhythm, are generalized to measure cross-frequency coupling. The effectiveness of quantitatively distinguishing the changes of coupling strength from the measurement of phase-amplitude coupling (PAC) is demonstrated based on simulation data. The data suggest that the generalized algorithms are able to effectively evaluate the strength of PAC, which are consistent with those traditional approaches, such as PAC-PLV and PAC-MI. Experimental data, which are local field potentials obtained from anaesthetized SD rats, have also been analyzed by these two generalized approaches. The data show that the theta-low gamma PAC in the hippocampal CA3-CA1 network is significantly decreased in the glioma group compared to that in the control group. The results, obtained from either simulation data or real experimental signals, are consistent with that of those traditional approaches PAC-MI and PAC-PLV. It may be considered as a proper indicator for the cross frequency coupling in sub-network, such as the hippocampal CA3 and CA1. PMID:27275379

  13. Perceptual grouping by entrainment in coupled Kuramoto oscillator networks.

    PubMed

    Meier, Martin; Haschke, Robert; Ritter, Helge J

    2014-01-01

    In this article we present a network composed of coupled Kuramoto oscillators, which is able to solve a broad spectrum of perceptual grouping tasks. Based on attracting and repelling interactions between these oscillators, the network dynamics forms various phase-synchronized clusters of oscillators corresponding to individual groups of similar input features. The degree of similarity between features is determined by a set of underlying receptive fields, which are learned directly from the feature domain. After illustrating the theoretical principles of the network, the approach is evaluated in an image segmentation task. Furthermore, the influence of a varying degree of sparse couplings is evaluated. PMID:24571099

  14. Phthalates and neurotoxic effects on hippocampal network plasticity.

    PubMed

    Holahan, Matthew R; Smith, Catherine A

    2015-05-01

    Phthalates are synthetically derived chemicals used as plasticizers in a variety of common household products. They are not chemically bound to plastic polymers and over time, easily migrate out of these products and into the environment. Experimental investigations evaluating the biological impact of phthalate exposure on developing organisms are critical given that estimates of phthalate exposure are considerably higher in infants and children compared to adults. Extensive growth and re-organization of neurocircuitry occurs during development leaving the brain highly susceptible to environmental insults. This review summarizes the effects of phthalate exposure on brain structure and function with particular emphasis on developmental aspects of hippocampal structural and functional plasticity. In general, it appears that widespread disruptions in hippocampal functional and structural plasticity occur following developmental (pre-, peri- and post-natal) exposure to phthalates. Whether these changes occur as a direct neurotoxic effect of phthalates or an indirect effect through disruption of endogenous endocrine functions is not fully understood. Comprehensive investigations that simultaneously assess the neurodevelopmental, neurotoxic, neuroendocrine and behavioral correlates of phthalate exposure are needed to provide an opportunity to thoroughly evaluate the neurotoxic potential of phthalates throughout the lifespan. PMID:25749100

  15. Network structure of functional hippocampal lateralization in birds.

    PubMed

    Jonckers, Elisabeth; Güntürkün, Onur; De Groof, Geert; Van der Linden, Annemie; Bingman, Verner P

    2015-11-01

    Functional hemispheric asymmetry is a common feature of vertebrate brain organization, yet little is known about how hemispheric dominance is implemented at the neural level. One notable example of hemispheric dominance in birds is the leading role of the left hippocampal formation in controlling navigational processes that support homing in pigeons. Relying on resting state fMRI analyses (where Functional connectivity (FC) can be determined by placing a reference 'seed' for connectivity in one hemisphere), we show that following seeding in either an anterior or posterior region of the hippocampal formation of homing pigeons and starlings, the emergent FC maps are consistently larger following seeding of the left hippocampus. Left seedings are also more likely to result in FC maps that extend to the contralateral hippocampus and outside the boundaries of the hippocampus. The data support the hypothesis that broader FC is one neural-organizational property that confers, with respect to navigation, functional dominance to the left hippocampus of birds. PMID:25821141

  16. Modulation of Hippocampal Theta Oscillations and Spatial Memory by Relaxin-3 Neurons of the Nucleus Incertus

    ERIC Educational Resources Information Center

    Ma, Sherie; Olucha-Bordonau, Francisco E.; Hossain, M. Akhter; Lin, Feng; Kuei, Chester; Liu, Changlu; Wade, John D.; Sutton, Steven W.; Nunez, Angel; Gundlach, Andrew L.

    2009-01-01

    Hippocampal theta rhythm is thought to underlie learning and memory, and it is well established that "pacemaker" neurons in medial septum (MS) modulate theta activity. Recent studies in the rat demonstrated that brainstem-generated theta rhythm occurs through a multisynaptic pathway via the nucleus incertus (NI), which is the primary source of the…

  17. On controlling networks of limit-cycle oscillators

    NASA Astrophysics Data System (ADS)

    Skardal, Per Sebastian; Arenas, Alex

    2016-09-01

    The control of network-coupled nonlinear dynamical systems is an active area of research in the nonlinear science community. Coupled oscillator networks represent a particularly important family of nonlinear systems, with applications ranging from the power grid to cardiac excitation. Here, we study the control of network-coupled limit cycle oscillators, extending the previous work that focused on phase oscillators. Based on stabilizing a target fixed point, our method aims to attain complete frequency synchronization, i.e., consensus, by applying control to as few oscillators as possible. We develop two types of controls. The first type directs oscillators towards larger amplitudes, while the second does not. We present numerical examples of both control types and comment on the potential failures of the method.

  18. A Degenerate Optical Parametric Oscillator Network for Coherent Computation

    NASA Astrophysics Data System (ADS)

    Wang, Zhe; Marandi, Alireza; Takata, Kenta; Byer, Robert L.; Yamamoto, Yoshihisa

    Laws of physics have proved useful for solving combinatorial optimization problems. This chapter introduces a network of degenerate optical parametric oscillators which takes advantage of principles of quantum optics to tackle NP-hard problems. The underlying mechanism originates from the bistability of the output phase of each oscillator, coherent interactions between coupled oscillators, and the inherent preference of the network for oscillating in a mode with the minimum photon loss. Computational experiments have been extensively performed using instances of an NP-hard problem in graph theory with the number of vertices ranging from 4 to 20000. The numerical results clearly demonstrate the effectiveness of the network. In addition, the network can be physically implemented on a single ring cavity with multiple trains of femtosecond pulses and configurable mutual couplings. The implementation has been realized for the instance on the cubic graph with 4 vertices, and no computational error is detected in 1000 runs.

  19. How adaptation shapes spike rate oscillations in recurrent neuronal networks

    PubMed Central

    Augustin, Moritz; Ladenbauer, Josef; Obermayer, Klaus

    2012-01-01

    Neural mass signals from in-vivo recordings often show oscillations with frequencies ranging from <1 to 100 Hz. Fast rhythmic activity in the beta and gamma range can be generated by network-based mechanisms such as recurrent synaptic excitation-inhibition loops. Slower oscillations might instead depend on neuronal adaptation currents whose timescales range from tens of milliseconds to seconds. Here we investigate how the dynamics of such adaptation currents contribute to spike rate oscillations and resonance properties in recurrent networks of excitatory and inhibitory neurons. Based on a network of sparsely coupled spiking model neurons with two types of adaptation current and conductance-based synapses with heterogeneous strengths and delays we use a mean-field approach to analyze oscillatory network activity. For constant external input, we find that spike-triggered adaptation currents provide a mechanism to generate slow oscillations over a wide range of adaptation timescales as long as recurrent synaptic excitation is sufficiently strong. Faster rhythms occur when recurrent inhibition is slower than excitation and oscillation frequency increases with the strength of inhibition. Adaptation facilitates such network-based oscillations for fast synaptic inhibition and leads to decreased frequencies. For oscillatory external input, adaptation currents amplify a narrow band of frequencies and cause phase advances for low frequencies in addition to phase delays at higher frequencies. Our results therefore identify the different key roles of neuronal adaptation dynamics for rhythmogenesis and selective signal propagation in recurrent networks. PMID:23450654

  20. Synchronization in Complex Oscillator Networks and Smart Grids

    SciTech Connect

    Dorfler, Florian; Chertkov, Michael; Bullo, Francesco

    2012-07-24

    The emergence of synchronization in a network of coupled oscillators is a fascinating topic in various scientific disciplines. A coupled oscillator network is characterized by a population of heterogeneous oscillators and a graph describing the interaction among them. It is known that a strongly coupled and sufficiently homogeneous network synchronizes, but the exact threshold from incoherence to synchrony is unknown. Here we present a novel, concise, and closed-form condition for synchronization of the fully nonlinear, non-equilibrium, and dynamic network. Our synchronization condition can be stated elegantly in terms of the network topology and parameters, or equivalently in terms of an intuitive, linear, and static auxiliary system. Our results significantly improve upon the existing conditions advocated thus far, they are provably exact for various interesting network topologies and parameters, they are statistically correct for almost all networks, and they can be applied equally to synchronization phenomena arising in physics and biology as well as in engineered oscillator networks such as electric power networks. We illustrate the validity, the accuracy, and the practical applicability of our results in complex networks scenarios and in smart grid applications.

  1. Synchronization in complex oscillator networks and smart grids.

    PubMed

    Dörfler, Florian; Chertkov, Michael; Bullo, Francesco

    2013-02-01

    The emergence of synchronization in a network of coupled oscillators is a fascinating topic in various scientific disciplines. A widely adopted model of a coupled oscillator network is characterized by a population of heterogeneous phase oscillators, a graph describing the interaction among them, and diffusive and sinusoidal coupling. It is known that a strongly coupled and sufficiently homogeneous network synchronizes, but the exact threshold from incoherence to synchrony is unknown. Here, we present a unique, concise, and closed-form condition for synchronization of the fully nonlinear, nonequilibrium, and dynamic network. Our synchronization condition can be stated elegantly in terms of the network topology and parameters or equivalently in terms of an intuitive, linear, and static auxiliary system. Our results significantly improve upon the existing conditions advocated thus far, they are provably exact for various interesting network topologies and parameters; they are statistically correct for almost all networks; and they can be applied equally to synchronization phenomena arising in physics and biology as well as in engineered oscillator networks, such as electrical power networks. We illustrate the validity, the accuracy, and the practical applicability of our results in complex network scenarios and in smart grid applications. PMID:23319658

  2. Synchronization in complex oscillator networks and smart grids

    PubMed Central

    Dörfler, Florian; Chertkov, Michael; Bullo, Francesco

    2013-01-01

    The emergence of synchronization in a network of coupled oscillators is a fascinating topic in various scientific disciplines. A widely adopted model of a coupled oscillator network is characterized by a population of heterogeneous phase oscillators, a graph describing the interaction among them, and diffusive and sinusoidal coupling. It is known that a strongly coupled and sufficiently homogeneous network synchronizes, but the exact threshold from incoherence to synchrony is unknown. Here, we present a unique, concise, and closed-form condition for synchronization of the fully nonlinear, nonequilibrium, and dynamic network. Our synchronization condition can be stated elegantly in terms of the network topology and parameters or equivalently in terms of an intuitive, linear, and static auxiliary system. Our results significantly improve upon the existing conditions advocated thus far, they are provably exact for various interesting network topologies and parameters; they are statistically correct for almost all networks; and they can be applied equally to synchronization phenomena arising in physics and biology as well as in engineered oscillator networks, such as electrical power networks. We illustrate the validity, the accuracy, and the practical applicability of our results in complex network scenarios and in smart grid applications. PMID:23319658

  3. Control of coupled oscillator networks with application to microgrid technologies.

    PubMed

    Skardal, Per Sebastian; Arenas, Alex

    2015-08-01

    The control of complex systems and network-coupled dynamical systems is a topic of vital theoretical importance in mathematics and physics with a wide range of applications in engineering and various other sciences. Motivated by recent research into smart grid technologies, we study the control of synchronization and consider the important case of networks of coupled phase oscillators with nonlinear interactions-a paradigmatic example that has guided our understanding of self-organization for decades. We develop a method for control based on identifying and stabilizing problematic oscillators, resulting in a stable spectrum of eigenvalues, and in turn a linearly stable synchronized state. The amount of control, that is, number of oscillators, required to stabilize the network is primarily dictated by the coupling strength, dynamical heterogeneity, and mean degree of the network, and depends little on the structural heterogeneity of the network itself. PMID:26601231

  4. Control of coupled oscillator networks with application to microgrid technologies

    PubMed Central

    Skardal, Per Sebastian; Arenas, Alex

    2015-01-01

    The control of complex systems and network-coupled dynamical systems is a topic of vital theoretical importance in mathematics and physics with a wide range of applications in engineering and various other sciences. Motivated by recent research into smart grid technologies, we study the control of synchronization and consider the important case of networks of coupled phase oscillators with nonlinear interactions—a paradigmatic example that has guided our understanding of self-organization for decades. We develop a method for control based on identifying and stabilizing problematic oscillators, resulting in a stable spectrum of eigenvalues, and in turn a linearly stable synchronized state. The amount of control, that is, number of oscillators, required to stabilize the network is primarily dictated by the coupling strength, dynamical heterogeneity, and mean degree of the network, and depends little on the structural heterogeneity of the network itself. PMID:26601231

  5. K-Lysine acetyltransferase 2a regulates a hippocampal gene expression network linked to memory formation

    PubMed Central

    Stilling, Roman M; Rönicke, Raik; Benito, Eva; Urbanke, Hendrik; Capece, Vincenzo; Burkhardt, Susanne; Bahari-Javan, Sanaz; Barth, Jonas; Sananbenesi, Farahnaz; Schütz, Anna L; Dyczkowski, Jerzy; Martinez-Hernandez, Ana; Kerimoglu, Cemil; Dent, Sharon YR; Bonn, Stefan; Reymann, Klaus G; Fischer, Andre

    2014-01-01

    Neuronal histone acetylation has been linked to memory consolidation, and targeting histone acetylation has emerged as a promising therapeutic strategy for neuropsychiatric diseases. However, the role of histone-modifying enzymes in the adult brain is still far from being understood. Here we use RNA sequencing to screen the levels of all known histone acetyltransferases (HATs) in the hippocampal CA1 region and find that K-acetyltransferase 2a (Kat2a)—a HAT that has not been studied for its role in memory function so far—shows highest expression. Mice that lack Kat2a show impaired hippocampal synaptic plasticity and long-term memory consolidation. We furthermore show that Kat2a regulates a highly interconnected hippocampal gene expression network linked to neuroactive receptor signaling via a mechanism that involves nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB). In conclusion, our data establish Kat2a as a novel and essential regulator of hippocampal memory consolidation. PMID:25024434

  6. Slow oscillations during sleep coordinate interregional communication in cortical networks.

    PubMed

    Cox, Roy; van Driel, Joram; de Boer, Marieke; Talamini, Lucia M

    2014-12-10

    Large-amplitude sleep slow oscillations group faster neuronal oscillations and are of functional relevance for memory performance. However, relatively little is known about the impact of slow oscillations on functionally coupled networks. Here, we provide a comprehensive view on how human slow oscillatory dynamics influence various measures of brain processing. We demonstrate that slow oscillations coordinate interregional cortical communication, as assessed by phase synchrony in the sleep spindle frequency range and cross-frequency coupling between spindle and beta activity. Furthermore, we show that the organizing role of slow oscillations is restricted to circumscribed topographical areas. These findings add importantly to our basic understanding of the orchestrating role of slow oscillations. In addition, they are of considerable relevance for accounts of sleep-dependent memory reprocessing and consolidation. PMID:25505340

  7. Synchronization-based computation through networks of coupled oscillators

    PubMed Central

    Malagarriga, Daniel; García-Vellisca, Mariano A.; Villa, Alessandro E. P.; Buldú, Javier M.; García-Ojalvo, Jordi; Pons, Antonio J.

    2015-01-01

    The mesoscopic activity of the brain is strongly dynamical, while at the same time exhibits remarkable computational capabilities. In order to examine how these two features coexist, here we show that the patterns of synchronized oscillations displayed by networks of neural mass models, representing cortical columns, can be used as substrates for Boolean-like computations. Our results reveal that the same neural mass network may process different combinations of dynamical inputs as different logical operations or combinations of them. This dynamical feature of the network allows it to process complex inputs in a very sophisticated manner. The results are reproduced experimentally with electronic circuits of coupled Chua oscillators, showing the robustness of this kind of computation to the intrinsic noise and parameter mismatch of the coupled oscillators. We also show that the information-processing capabilities of coupled oscillations go beyond the simple juxtaposition of logic gates. PMID:26300765

  8. Synchronization-based computation through networks of coupled oscillators.

    PubMed

    Malagarriga, Daniel; García-Vellisca, Mariano A; Villa, Alessandro E P; Buldú, Javier M; García-Ojalvo, Jordi; Pons, Antonio J

    2015-01-01

    The mesoscopic activity of the brain is strongly dynamical, while at the same time exhibits remarkable computational capabilities. In order to examine how these two features coexist, here we show that the patterns of synchronized oscillations displayed by networks of neural mass models, representing cortical columns, can be used as substrates for Boolean-like computations. Our results reveal that the same neural mass network may process different combinations of dynamical inputs as different logical operations or combinations of them. This dynamical feature of the network allows it to process complex inputs in a very sophisticated manner. The results are reproduced experimentally with electronic circuits of coupled Chua oscillators, showing the robustness of this kind of computation to the intrinsic noise and parameter mismatch of the coupled oscillators. We also show that the information-processing capabilities of coupled oscillations go beyond the simple juxtaposition of logic gates. PMID:26300765

  9. Astrocytes regulate heterogeneity of presynaptic strengths in hippocampal networks.

    PubMed

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

    2016-05-10

    Dendrites are neuronal structures specialized for receiving and processing information through their many synaptic inputs. How input strengths are modified across dendrites in ways that are crucial for synaptic integration and plasticity remains unclear. We examined in single hippocampal neurons the mechanism of heterosynaptic interactions and the heterogeneity of synaptic strengths of pyramidal cell inputs. Heterosynaptic presynaptic plasticity that counterbalances input strengths requires N-methyl-d-aspartate receptors (NMDARs) and astrocytes. Importantly, this mechanism is shared with the mechanism for maintaining highly heterogeneous basal presynaptic strengths, which requires astrocyte Ca(2+) signaling involving NMDAR activation, astrocyte membrane depolarization, and L-type Ca(2+) channels. Intracellular infusion of NMDARs or Ca(2+)-channel blockers into astrocytes, conditionally ablating the GluN1 NMDAR subunit, or optogenetically hyperpolarizing astrocytes with archaerhodopsin promotes homogenization of convergent presynaptic inputs. Our findings support the presence of an astrocyte-dependent cellular mechanism that enhances the heterogeneity of presynaptic strengths of convergent connections, which may help boost the computational power of dendrites. PMID:27118849

  10. Altered inhibition in the hippocampal neural networks after spreading depression.

    PubMed

    Mesgari, M; Ghaffarian, N; Khaleghi Ghadiri, M; Sadeghian, H; Speckmann, E-J; Stummer, W; Gorji, A

    2015-09-24

    Prolonged neuronal depression after spreading depression (SD) is followed by a late cellular and synaptic hyperexcitability. Intra- and extracellular recordings of bioelectrical activities were performed in the rodent hippocampus to investigate the role of γ-aminobutyric acid (GABA)-mediated inhibition in the late hyperexcitable state of SD. The effect of KCl-induced negative DC potential shifts was investigated on extracellularly recorded paired-pulse depression (PPD) and bicuculline-induced afterdischarges as well as intracellularly recorded inhibitory post synaptic potentials (IPSPs) in the hippocampal CA1 area. The results revealed that SD decreased the degree of PPD, enhanced the number and duration of bicuculline-induced afterdischarges, and reduced the amplitude and duration of IPSPs. Application of low concentrations of bicuculline before the induction of SD enhanced the inhibitory effect of SD on IPSPs. Data indicate the contribution of GABA-mediated inhibition to SD-induced delayed hyperexcitability. Modulation of GABA function in the late hyperexcitability phase of SD may play a role in therapeutic management of SD-related neurological disorders. PMID:26210578

  11. Dopamine D3 Receptors Inhibit Hippocampal Gamma Oscillations by Disturbing CA3 Pyramidal Cell Firing Synchrony.

    PubMed

    Lemercier, Clément E; Schulz, Steffen B; Heidmann, Karin E; Kovács, Richard; Gerevich, Zoltan

    2015-01-01

    Cortical gamma oscillations are associated with cognitive processes and are altered in several neuropsychiatric conditions such as schizophrenia and Alzheimer's disease. Since dopamine D3 receptors are possible targets in treatment of these conditions, it is of great importance to understand their role in modulation of gamma oscillations. The effect of D3 receptors on gamma oscillations and the underlying cellular mechanisms were investigated by extracellular local field potential and simultaneous intracellular sharp micro-electrode recordings in the CA3 region of the hippocampus in vitro. D3 receptors decreased the power and broadened the bandwidth of gamma oscillations induced by acetylcholine or kainate. Blockade of the D3 receptors resulted in faster synchronization of the oscillations, suggesting that endogenous dopamine in the hippocampus slows down the dynamics of gamma oscillations by activation of D3 receptors. Investigating the underlying cellular mechanisms for these effects showed that D3 receptor activation decreased the rate of action potentials (APs) during gamma oscillations and reduced the precision of the AP phase coupling to the gamma cycle in CA3 pyramidal cells. The results may offer an explanation how selective activation of D3 receptors may impair cognition and how, in converse, D3 antagonists may exert pro-cognitive and antipsychotic effects. PMID:26779018

  12. Dopamine D3 Receptors Inhibit Hippocampal Gamma Oscillations by Disturbing CA3 Pyramidal Cell Firing Synchrony

    PubMed Central

    Lemercier, Clément E.; Schulz, Steffen B.; Heidmann, Karin E.; Kovács, Richard; Gerevich, Zoltan

    2016-01-01

    Cortical gamma oscillations are associated with cognitive processes and are altered in several neuropsychiatric conditions such as schizophrenia and Alzheimer’s disease. Since dopamine D3 receptors are possible targets in treatment of these conditions, it is of great importance to understand their role in modulation of gamma oscillations. The effect of D3 receptors on gamma oscillations and the underlying cellular mechanisms were investigated by extracellular local field potential and simultaneous intracellular sharp micro-electrode recordings in the CA3 region of the hippocampus in vitro. D3 receptors decreased the power and broadened the bandwidth of gamma oscillations induced by acetylcholine or kainate. Blockade of the D3 receptors resulted in faster synchronization of the oscillations, suggesting that endogenous dopamine in the hippocampus slows down the dynamics of gamma oscillations by activation of D3 receptors. Investigating the underlying cellular mechanisms for these effects showed that D3 receptor activation decreased the rate of action potentials (APs) during gamma oscillations and reduced the precision of the AP phase coupling to the gamma cycle in CA3 pyramidal cells. The results may offer an explanation how selective activation of D3 receptors may impair cognition and how, in converse, D3 antagonists may exert pro-cognitive and antipsychotic effects. PMID:26779018

  13. Perturbed Hippocampal Synaptic Inhibition and γ-Oscillations in a Neuroligin-4 Knockout Mouse Model of Autism.

    PubMed

    Hammer, Matthieu; Krueger-Burg, Dilja; Tuffy, Liam Patrick; Cooper, Benjamin Hillman; Taschenberger, Holger; Goswami, Sarit Pati; Ehrenreich, Hannelore; Jonas, Peter; Varoqueaux, Frederique; Rhee, Jeong-Seop; Brose, Nils

    2015-10-20

    Loss-of-function mutations in the synaptic adhesion protein Neuroligin-4 are among the most common genetic abnormalities associated with autism spectrum disorders, but little is known about the function of Neuroligin-4 and the consequences of its loss. We assessed synaptic and network characteristics in Neuroligin-4 knockout mice, focusing on the hippocampus as a model brain region with a critical role in cognition and memory, and found that Neuroligin-4 deletion causes subtle defects of the protein composition and function of GABAergic synapses in the hippocampal CA3 region. Interestingly, these subtle synaptic changes are accompanied by pronounced perturbations of γ-oscillatory network activity, which has been implicated in cognitive function and is altered in multiple psychiatric and neurodevelopmental disorders. Our data provide important insights into the mechanisms by which Neuroligin-4-dependent GABAergic synapses may contribute to autism phenotypes and indicate new strategies for therapeutic approaches. PMID:26456829

  14. Delayed feedback control of synchronization in weakly coupled oscillator networks

    NASA Astrophysics Data System (ADS)

    Novičenko, Viktor

    2015-08-01

    We study control of synchronization in weakly coupled oscillator networks by using a phase-reduction approach. Starting from a general class of limit-cycle oscillators we derive a phase model, which shows that delayed feedback control changes effective coupling strengths and effective frequencies. We derive the analytical condition for critical control gain, where the phase dynamics of the oscillator becomes extremely sensitive to any perturbations. As a result the network can attain phase synchronization even if the natural interoscillatory couplings are small. In addition, we demonstrate that delayed feedback control can disrupt the coherent phase dynamic in synchronized networks. The validity of our results is illustrated on networks of diffusively coupled Stuart-Landau and FitzHugh-Nagumo models.

  15. Synchronization, quantum correlations and entanglement in oscillator networks

    PubMed Central

    Manzano, Gonzalo; Galve, Fernando; Giorgi, Gian Luca; Hernández-García, Emilio; Zambrini, Roberta

    2013-01-01

    Synchronization is one of the paradigmatic phenomena in the study of complex systems. It has been explored theoretically and experimentally mostly to understand natural phenomena, but also in view of technological applications. Although several mechanisms and conditions for synchronous behavior in spatially extended systems and networks have been identified, the emergence of this phenomenon has been largely unexplored in quantum systems until very recently. Here we discuss synchronization in quantum networks of different harmonic oscillators relaxing towards a stationary state, being essential the form of dissipation. By local tuning of one of the oscillators, we establish the conditions for synchronous dynamics, in the whole network or in a motif. Beyond the classical regime we show that synchronization between (even unlinked) nodes witnesses the presence of quantum correlations and entanglement. Furthermore, synchronization and entanglement can be induced between two different oscillators if properly linked to a random network. PMID:23486526

  16. Aberrant functional connectivity in dissociable hippocampal networks is associated with deficits in memory.

    PubMed

    Voets, Natalie L; Zamboni, Giovanna; Stokes, Mark G; Carpenter, Katherine; Stacey, Richard; Adcock, Jane E

    2014-04-01

    In the healthy human brain, evidence for dissociable memory networks along the anterior-posterior axis of the hippocampus suggests that this structure may not function as a unitary entity. Failure to consider these functional divisions may explain diverging results among studies of memory adaptation in disease. Using task-based and resting functional MRI, we show that chronic seizures disrupting the anterior medial temporal lobe (MTL) preserve anterior and posterior hippocampal-cortical dissociations, but alter signaling between these and other key brain regions. During performance of a memory encoding task, we found reduced neural activity in human patients with unilateral temporal lobe epilepsy relative to age-matched healthy controls, but no upregulation of fMRI signal in unaffected hippocampal subregions. Instead, patients showed aberrant resting fMRI connectivity within anterior and posterior hippocampal-cortical networks, which was associated with memory decline, distinguishing memory-intact from memory-impaired patients. Our results highlight a critical role for intact hippocampo-cortical functional communication in memory and provide evidence that chronic injury-induced functional reorganization in the diseased MTL is behavioral inefficient. PMID:24695711

  17. A quantitative theory of the functions of the hippocampal CA3 network in memory.

    PubMed

    Rolls, Edmund T

    2013-01-01

    A quantitative computational theory of the operation of the hippocampal CA3 system as an autoassociation or attractor network used in episodic memory system is described. In this theory, the CA3 system operates as a single attractor or autoassociation network to enable rapid, one-trial, associations between any spatial location (place in rodents, or spatial view in primates) and an object or reward, and to provide for completion of the whole memory during recall from any part. The theory is extended to associations between time and object or reward to implement temporal order memory, also important in episodic memory. The dentate gyrus (DG) performs pattern separation by competitive learning to produce sparse representations suitable for setting up new representations in CA3 during learning, producing for example neurons with place-like fields from entorhinal cortex grid cells. The dentate granule cells produce by the very small number of mossy fiber (MF) connections to CA3 a randomizing pattern separation effect important during learning but not recall that separates out the patterns represented by CA3 firing to be very different from each other, which is optimal for an unstructured episodic memory system in which each memory must be kept distinct from other memories. The direct perforant path (pp) input to CA3 is quantitatively appropriate to provide the cue for recall in CA3, but not for learning. Tests of the theory including hippocampal subregion analyses and hippocampal NMDA receptor knockouts are described, and support the theory. PMID:23805074

  18. A quantitative theory of the functions of the hippocampal CA3 network in memory

    PubMed Central

    Rolls, Edmund T.

    2013-01-01

    A quantitative computational theory of the operation of the hippocampal CA3 system as an autoassociation or attractor network used in episodic memory system is described. In this theory, the CA3 system operates as a single attractor or autoassociation network to enable rapid, one-trial, associations between any spatial location (place in rodents, or spatial view in primates) and an object or reward, and to provide for completion of the whole memory during recall from any part. The theory is extended to associations between time and object or reward to implement temporal order memory, also important in episodic memory. The dentate gyrus (DG) performs pattern separation by competitive learning to produce sparse representations suitable for setting up new representations in CA3 during learning, producing for example neurons with place-like fields from entorhinal cortex grid cells. The dentate granule cells produce by the very small number of mossy fiber (MF) connections to CA3 a randomizing pattern separation effect important during learning but not recall that separates out the patterns represented by CA3 firing to be very different from each other, which is optimal for an unstructured episodic memory system in which each memory must be kept distinct from other memories. The direct perforant path (pp) input to CA3 is quantitatively appropriate to provide the cue for recall in CA3, but not for learning. Tests of the theory including hippocampal subregion analyses and hippocampal NMDA receptor knockouts are described, and support the theory. PMID:23805074

  19. Apolipoprotein E4 Causes Age-Dependent Disruption of Slow Gamma Oscillations during Hippocampal Sharp-Wave Ripples.

    PubMed

    Gillespie, Anna K; Jones, Emily A; Lin, Yuan-Hung; Karlsson, Mattias P; Kay, Kenneth; Yoon, Seo Yeon; Tong, Leslie M; Nova, Philip; Carr, Jessie S; Frank, Loren M; Huang, Yadong

    2016-05-18

    Apolipoprotein (apo) E4 is the major genetic risk factor for Alzheimer's disease (AD), but the mechanism by which it causes cognitive decline is unclear. In knockin (KI) mice, human apoE4 causes age-dependent learning and memory impairments and degeneration of GABAergic interneurons in the hippocampal dentate gyrus. Here we report two functional apoE4-KI phenotypes involving sharp-wave ripples (SWRs), hippocampal network events critical for memory processes. Aged apoE4-KI mice had fewer SWRs than apoE3-KI mice and significantly reduced slow gamma activity during SWRs. Elimination of apoE4 in GABAergic interneurons, which prevents learning and memory impairments, rescued SWR-associated slow gamma activity but not SWR abundance in aged mice. SWR abundance was reduced similarly in young and aged apoE4-KI mice; however, the full SWR-associated slow gamma deficit emerged only in aged apoE4-KI mice. These results suggest that progressive decline of interneuron-enabled slow gamma activity during SWRs critically contributes to apoE4-mediated learning and memory impairments. VIDEO ABSTRACT. PMID:27161522

  20. Control analysis for autonomously oscillating biochemical networks.

    PubMed

    Reijenga, Karin A; Westerhoff, Hans V; Kholodenko, Boris N; Snoep, Jacky L

    2002-01-01

    It has hitherto not been possible to analyze the control of oscillatory dynamic cellular processes in other than qualitative ways. The control coefficients, used in metabolic control analyses of steady states, cannot be applied directly to dynamic systems. We here illustrate a way out of this limitation that uses Fourier transforms to convert the time domain into the stationary frequency domain, and then analyses the control of limit cycle oscillations. In addition to the already known summation theorems for frequency and amplitude, we reveal summation theorems that apply to the control of average value, waveform, and phase differences of the oscillations. The approach is made fully operational in an analysis of yeast glycolytic oscillations. It follows an experimental approach, sampling from the model output and using discrete Fourier transforms of this data set. It quantifies the control of various aspects of the oscillations by the external glucose concentration and by various internal molecular processes. We show that the control of various oscillatory properties is distributed over the system enzymes in ways that differ among those properties. The models that are described in this paper can be accessed on http://jjj.biochem.sun.ac.za. PMID:11751299

  1. Discrimination of complex form by simple oscillator networks.

    PubMed

    Nagai, Yoshinori; Taylor, Ryan R L; Loh, Yik-Wen; Maddess, Ted

    2009-01-01

    Natural images are rich in higher order spatial correlations. Brain scanning, psychophysics and electrophysiology indicate that humans are sensitive to these image properties. A useful tool for exploring this sense is the set of isotrigon textures. Like natural images these textures have low dimensionality relative to random images, but like random images contain no average structure in their first to third order correlation functions. Thus, the structured appearance of these textures results from higher order correlations. One way to generate the higher order products inherent in higher order correlations is recursive nonlinear processing. We therefore decided to examine if very small oscillator networks could produce a profile of activity that matches human isotrigon discrimination performance across 53 isotrigon texture types. Human performance was measured in 23 subjects. The two best network types found contained as few as 4 oscillators. The input oscillators are of a novel cubic form and the final readout oscillator was a logistic oscillator. Mean readout oscillator activity matched human performance reasonably well even though the network parameters were fixed for all 53 texture types. Overall it appears that relatively simple, short range, and biologically plausible, recursive processing could provide the basis for discrimination of complex form. PMID:19919282

  2. Oscillations in the bistable regime of neuronal networks

    NASA Astrophysics Data System (ADS)

    Roxin, Alex; Compte, Albert

    2016-07-01

    Bistability between attracting fixed points in neuronal networks has been hypothesized to underlie persistent activity observed in several cortical areas during working memory tasks. In network models this kind of bistability arises due to strong recurrent excitation, sufficient to generate a state of high activity created in a saddle-node (SN) bifurcation. On the other hand, canonical network models of excitatory and inhibitory neurons (E-I networks) robustly produce oscillatory states via a Hopf (H) bifurcation due to the E-I loop. This mechanism for generating oscillations has been invoked to explain the emergence of brain rhythms in the β to γ bands. Although both bistability and oscillatory activity have been intensively studied in network models, there has not been much focus on the coincidence of the two. Here we show that when oscillations emerge in E-I networks in the bistable regime, their phenomenology can be explained to a large extent by considering coincident SN and H bifurcations, known as a codimension two Takens-Bogdanov bifurcation. In particular, we find that such oscillations are not composed of a stable limit cycle, but rather are due to noise-driven oscillatory fluctuations. Furthermore, oscillations in the bistable regime can, in principle, have arbitrarily low frequency.

  3. Oscillations in the bistable regime of neuronal networks.

    PubMed

    Roxin, Alex; Compte, Albert

    2016-07-01

    Bistability between attracting fixed points in neuronal networks has been hypothesized to underlie persistent activity observed in several cortical areas during working memory tasks. In network models this kind of bistability arises due to strong recurrent excitation, sufficient to generate a state of high activity created in a saddle-node (SN) bifurcation. On the other hand, canonical network models of excitatory and inhibitory neurons (E-I networks) robustly produce oscillatory states via a Hopf (H) bifurcation due to the E-I loop. This mechanism for generating oscillations has been invoked to explain the emergence of brain rhythms in the β to γ bands. Although both bistability and oscillatory activity have been intensively studied in network models, there has not been much focus on the coincidence of the two. Here we show that when oscillations emerge in E-I networks in the bistable regime, their phenomenology can be explained to a large extent by considering coincident SN and H bifurcations, known as a codimension two Takens-Bogdanov bifurcation. In particular, we find that such oscillations are not composed of a stable limit cycle, but rather are due to noise-driven oscillatory fluctuations. Furthermore, oscillations in the bistable regime can, in principle, have arbitrarily low frequency. PMID:27575167

  4. Synchronization versus neighborhood similarity in complex networks of nonidentical oscillators

    NASA Astrophysics Data System (ADS)

    Freitas, Celso; Macau, Elbert; Viana, Ricardo Luiz

    2015-09-01

    Does the assignment order of a fixed collection of slightly distinct subsystems into given communication channels influence the overall ensemble behavior? We discuss this question in the context of complex networks of nonidentical interacting oscillators. Three types of connection configurations are considered: Similar, Dissimilar, and Neutral patterns. These different groups correspond, respectively, to oscillators alike, distinct, and indifferent relative to their neighbors. To construct such scenarios we define a vertex-weighted graph measure, the total dissonance, which comprises the sum of the dissonances between all neighbor oscillators in the network. Our numerical simulations show that the more homogeneous a network, the higher tend to be both the coupling strength required for phase locking and the associated final phase configuration spread over the circle. On the other hand, the initial spread of partial synchronization occurs faster for Similar patterns in comparison to Dissimilar ones, while neutral patterns are an intermediate situation between both extremes.

  5. Long-Term Dynamical Constraints on Pharmacologically Evoked Potentiation Imply Activity Conservation within In Vitro Hippocampal Networks

    PubMed Central

    Dzakpasu, Rhonda

    2015-01-01

    This paper describes a long-term study of network dynamics from in vitro, cultured hippocampal neurons after a pharmacological induction of synaptic potentiation. We plate a suspension of hippocampal neurons on an array of extracellular electrodes and record electrical activity in the absence of the drugs several days after treatment. While previous studies have reported on potentiation lasting up to a few hours after treatment, to the best of our knowledge, this is the first report to characterize the network effects of a potentiating mechanism several days after treatment. Using this reduced, two-dimensional in vitro network of hippocampal neurons, we show that the effects of potentiation are persistent over time but are modulated under a conservation of spike principle. We suggest that this conservation principle might be mediated by the appearance of a resonant inter-spike interval that prevents the network from advancing towards a state of hyperexcitability. PMID:26070215

  6. Reaching Synchronization in Networked Harmonic Oscillators With Outdated Position Data.

    PubMed

    Song, Qiang; Yu, Wenwu; Cao, Jinde; Liu, Fang

    2016-07-01

    This paper studies the synchronization problem for a network of coupled harmonic oscillators by proposing a distributed control algorithm based only on delayed position states, i.e., outdated position states stored in memory. The coupling strength of the network is conveniently designed according to the absolute values and the principal arguments of the nonzero eigenvalues of the network Laplacian matrix. By analyzing a finite number of stability switches of the network with respect to the variation in the time delay, some necessary and sufficient conditions are derived for reaching synchronization in networked harmonic oscillators with positive and negative coupling strengths, respectively, and it is shown that the time delay should be taken from a set of intervals bounded by some critical values. Simulation examples are given to illustrate the effectiveness of the theoretical analysis. PMID:26241985

  7. Vector Symbolic Spiking Neural Network Model of Hippocampal Subarea CA1 Novelty Detection Functionality.

    PubMed

    Agerskov, Claus

    2016-04-01

    A neural network model is presented of novelty detection in the CA1 subdomain of the hippocampal formation from the perspective of information flow. This computational model is restricted on several levels by both anatomical information about hippocampal circuitry and behavioral data from studies done in rats. Several studies report that the CA1 area broadcasts a generalized novelty signal in response to changes in the environment. Using the neural engineering framework developed by Eliasmith et al., a spiking neural network architecture is created that is able to compare high-dimensional vectors, symbolizing semantic information, according to the semantic pointer hypothesis. This model then computes the similarity between the vectors, as both direct inputs and a recalled memory from a long-term memory network by performing the dot-product operation in a novelty neural network architecture. The developed CA1 model agrees with available neuroanatomical data, as well as the presented behavioral data, and so it is a biologically realistic model of novelty detection in the hippocampus, which can provide a feasible explanation for experimentally observed dynamics. PMID:26890351

  8. Transition from amplitude to oscillation death in a network of oscillators

    SciTech Connect

    Nandan, Mauparna; Hens, C. R.; Dana, Syamal K.; Pal, Pinaki

    2014-12-01

    We report a transition from a homogeneous steady state (HSS) to inhomogeneous steady states (IHSSs) in a network of globally coupled identical oscillators. We perturb a synchronized population of oscillators in the network with a few local negative or repulsive mean field links. The whole population splits into two clusters for a certain number of repulsive mean field links and a range of coupling strength. For further increase of the strength of interaction, these clusters collapse into a HSS followed by a transition to IHSSs where all the oscillators populate either of the two stable steady states. We analytically determine the origin of HSS and its transition to IHSS in relation to the number of repulsive mean-field links and the strength of interaction using a reductionism approach to the model network. We verify the results with numerical examples of the paradigmatic Landau-Stuart limit cycle system and the chaotic Rössler oscillator as dynamical nodes. During the transition from HSS to IHSSs, the network follows the Turing type symmetry breaking pitchfork or transcritical bifurcation depending upon the system dynamics.

  9. Transition from amplitude to oscillation death in a network of oscillators.

    PubMed

    Nandan, Mauparna; Hens, C R; Pal, Pinaki; Dana, Syamal K

    2014-12-01

    We report a transition from a homogeneous steady state (HSS) to inhomogeneous steady states (IHSSs) in a network of globally coupled identical oscillators. We perturb a synchronized population of oscillators in the network with a few local negative or repulsive mean field links. The whole population splits into two clusters for a certain number of repulsive mean field links and a range of coupling strength. For further increase of the strength of interaction, these clusters collapse into a HSS followed by a transition to IHSSs where all the oscillators populate either of the two stable steady states. We analytically determine the origin of HSS and its transition to IHSS in relation to the number of repulsive mean-field links and the strength of interaction using a reductionism approach to the model network. We verify the results with numerical examples of the paradigmatic Landau-Stuart limit cycle system and the chaotic Rössler oscillator as dynamical nodes. During the transition from HSS to IHSSs, the network follows the Turing type symmetry breaking pitchfork or transcritical bifurcation depending upon the system dynamics. PMID:25554023

  10. Multiplex Networks of Cortical and Hippocampal Neurons Revealed at Different Timescales

    PubMed Central

    Timme, Nicholas; Ito, Shinya; Myroshnychenko, Maxym; Yeh, Fang-Chin; Hiolski, Emma; Hottowy, Pawel; Beggs, John M.

    2014-01-01

    Recent studies have emphasized the importance of multiplex networks – interdependent networks with shared nodes and different types of connections – in systems primarily outside of neuroscience. Though the multiplex properties of networks are frequently not considered, most networks are actually multiplex networks and the multiplex specific features of networks can greatly affect network behavior (e.g. fault tolerance). Thus, the study of networks of neurons could potentially be greatly enhanced using a multiplex perspective. Given the wide range of temporally dependent rhythms and phenomena present in neural systems, we chose to examine multiplex networks of individual neurons with time scale dependent connections. To study these networks, we used transfer entropy – an information theoretic quantity that can be used to measure linear and nonlinear interactions – to systematically measure the connectivity between individual neurons at different time scales in cortical and hippocampal slice cultures. We recorded the spiking activity of almost 12,000 neurons across 60 tissue samples using a 512-electrode array with 60 micrometer inter-electrode spacing and 50 microsecond temporal resolution. To the best of our knowledge, this preparation and recording method represents a superior combination of number of recorded neurons and temporal and spatial recording resolutions to any currently available in vivo system. We found that highly connected neurons (“hubs”) were localized to certain time scales, which, we hypothesize, increases the fault tolerance of the network. Conversely, a large proportion of non-hub neurons were not localized to certain time scales. In addition, we found that long and short time scale connectivity was uncorrelated. Finally, we found that long time scale networks were significantly less modular and more disassortative than short time scale networks in both tissue types. As far as we are aware, this analysis represents the first

  11. Stable and transient multicluster oscillation death in nonlocally coupled networks

    NASA Astrophysics Data System (ADS)

    Schneider, Isabelle; Kapeller, Marie; Loos, Sarah; Zakharova, Anna; Fiedler, Bernold; Schöll, Eckehard

    2015-11-01

    In a network of nonlocally coupled Stuart-Landau oscillators with symmetry-breaking coupling, we study numerically, and explain analytically, a family of inhomogeneous steady states (oscillation death). They exhibit multicluster patterns, depending on the cluster distribution prescribed by the initial conditions. Besides stable oscillation death, we also find a regime of long transients asymptotically approaching synchronized oscillations. To explain these phenomena analytically in dependence on the coupling range and the coupling strength, we first use a mean-field approximation, which works well for large coupling ranges but fails for coupling ranges, which are small compared to the cluster size. Going beyond standard mean-field theory, we predict the boundaries of the different stability regimes as well as the transient times analytically in excellent agreement with numerical results.

  12. Lactate Effectively Covers Energy Demands during Neuronal Network Activity in Neonatal Hippocampal Slices

    PubMed Central

    Ivanov, Anton; Mukhtarov, Marat; Bregestovski, Piotr; Zilberter, Yuri

    2011-01-01

    Although numerous experimental data indicate that lactate is efficiently used for energy by the mature brain, the direct measurements of energy metabolism parameters during neuronal network activity in early postnatal development have not been performed. Therefore, the role of lactate in the energy metabolism of neurons at this age remains unclear. In this study, we monitored field potentials and contents of oxygen and NAD(P)H in correlation with oxidative metabolism during intense network activity in the CA1 hippocampal region of neonatal brain slices. We show that in the presence of glucose, lactate is effectively utilized as an energy substrate, causing an augmentation of oxidative metabolism. Moreover, in the absence of glucose lactate is fully capable of maintaining synaptic function. Therefore, during network activity in neonatal slices, lactate can be an efficient energy substrate capable of sustaining and enhancing aerobic energy metabolism. PMID:21602909

  13. Rational design of functional and tunable oscillating enzymatic networks

    NASA Astrophysics Data System (ADS)

    Semenov, Sergey N.; Wong, Albert S. Y.; van der Made, R. Martijn; Postma, Sjoerd G. J.; Groen, Joost; van Roekel, Hendrik W. H.; de Greef, Tom F. A.; Huck, Wilhelm T. S.

    2015-02-01

    Life is sustained by complex systems operating far from equilibrium and consisting of a multitude of enzymatic reaction networks. The operating principles of biology's regulatory networks are known, but the in vitro assembly of out-of-equilibrium enzymatic reaction networks has proved challenging, limiting the development of synthetic systems showing autonomous behaviour. Here, we present a strategy for the rational design of programmable functional reaction networks that exhibit dynamic behaviour. We demonstrate that a network built around autoactivation and delayed negative feedback of the enzyme trypsin is capable of producing sustained oscillating concentrations of active trypsin for over 65 h. Other functions, such as amplification, analog-to-digital conversion and periodic control over equilibrium systems, are obtained by linking multiple network modules in microfluidic flow reactors. The methodology developed here provides a general framework to construct dissipative, tunable and robust (bio)chemical reaction networks.

  14. Rational design of functional and tunable oscillating enzymatic networks.

    PubMed

    Semenov, Sergey N; Wong, Albert S Y; van der Made, R Martijn; Postma, Sjoerd G J; Groen, Joost; van Roekel, Hendrik W H; de Greef, Tom F A; Huck, Wilhelm T S

    2015-02-01

    Life is sustained by complex systems operating far from equilibrium and consisting of a multitude of enzymatic reaction networks. The operating principles of biology's regulatory networks are known, but the in vitro assembly of out-of-equilibrium enzymatic reaction networks has proved challenging, limiting the development of synthetic systems showing autonomous behaviour. Here, we present a strategy for the rational design of programmable functional reaction networks that exhibit dynamic behaviour. We demonstrate that a network built around autoactivation and delayed negative feedback of the enzyme trypsin is capable of producing sustained oscillating concentrations of active trypsin for over 65 h. Other functions, such as amplification, analog-to-digital conversion and periodic control over equilibrium systems, are obtained by linking multiple network modules in microfluidic flow reactors. The methodology developed here provides a general framework to construct dissipative, tunable and robust (bio)chemical reaction networks. PMID:25615670

  15. Synchronized Rhythmic Oscillation in a Noisy Neural Network

    NASA Astrophysics Data System (ADS)

    Yu, Yuguo; Liu, Feng; Wang, Wei

    2003-12-01

    The occurrence of synchronized oscillation and its critical behavior in a globally coupled stochastic Hodgkin-Huxley (HH) neuronal network are studied in this paper. It is found that there is a critical curve for the coupling strength versus noise intensity, which shows a V-shaped structure and divides the network behavior into an asynchronous firing state and a synchronous one. Analysis of the scaling behavior near the bifurcation point reveals that this transition is analogous to a second-order phase transition. The frequency of synchronized oscillations is within the range of 40-80 Hz, and its physical origin is explored by studying single HH neuron’s impedance. The intrinsic property of single neuron may account for the generation and the frequency characteristics of synchronized rhythmic oscillations.

  16. Entropy-production-driven oscillators in simple nonequilibrium networks

    NASA Astrophysics Data System (ADS)

    Weber, Jeffrey K.; Pande, Vijay S.

    2015-03-01

    The development of tractable nonequilibrium simulation methods represents a bottleneck for efforts to describe the functional dynamics that occur within living cells. We here employ a nonequilibrium approach called the λ ensemble to characterize the dissipative dynamics of a simple Markovian network driven by an external potential. In the highly dissipative regime brought about by the λ bias, we observe a dynamical structure characteristic of cellular architectures: The entropy production drives a damped oscillator over state populations in the network. We illustrate the properties of such oscillations in weakly and strongly driven regimes, and we discuss how control structures associated with the "dynamical phase transition" in the system can be related to switches and oscillators in cellular dynamics.

  17. 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. PMID:24966414

  18. Electrical and Pharmacological Stimuli Reveal a Greater Susceptibility for CA3 Network Excitability in Hippocampal Slices from Aged vs. Adult Fischer 344 Rats

    PubMed Central

    Kanak, Daniel J.; Jones, Ryan T.; Tokhi, Ashish; Willingham, Amy L.; Zaveri, Hitten P.; Rose, Gregory M.; Patrylo, Peter R.

    2011-01-01

    Clinical data and experimental studies in rats have shown that the aged CNS is more susceptible to the proconvulsive effects of the excitotoxic glutamate analogues kainate (KA) and domoate (DA), which bind high-affinity receptors localized at mossy fiber (MF) synapses in the CA3 subregion of the hippocampus. Although decreased renal clearance appears to play a role in the hypersensitivity of the aged hippocampus to systemically-administered DA, it is unclear if the excitability of the CA3 network is also altered with age. Therefore, this study monitored CA3 field potential activity in hippocampal slices from aged and adult male Fischer 344 rats in response to electrical and pharmacological network stimulation targeted to the MF-CA3 circuit. Network challenges with repetitive hilar stimulation or bath application of nanomolar concentrations of KA more readily elicited excitable network activity (e.g. population spike facilitation, multiple population spikes, and epileptiform bursts) in slices from aged vs. adult rats, although basal network excitability was comparable between age groups. Additionally, exposure to 200 nM KA often abolished epileptiform activity and revealed theta or gamma oscillations instead. However, slices from aged rats were less sensitive to the rhythmogenic effects of 200 nM KA. Taken together, these findings suggest that aging decreases the capacity of the CA3 network to constrain the spread of excitability during focal excitatory network challenges. PMID:22396884

  19. A novel function for Wnt signaling modulating neuronal firing activity and the temporal structure of spontaneous oscillation in the entorhinal-hippocampal circuit.

    PubMed

    Oliva, Carolina A; Inestrosa, Nibaldo C

    2015-07-01

    During early and late postnatal developments, the establishment of functional neuronal connectivity depends on molecules like Wnt that help the recently formed synapses to establish and consolidate their new cellular interactions. However, unlike other molecules, whether Wnt can modulate the firing properties of cells is unknown. Here, for the first time we explore the physiological effect of the canonical and non-canonical Wnt pathways on a circuit that is currently generating oscillatory activity, the entorhinal cortex-hippocampal circuit. Our results indicate that Wnt pathways have strong influence in the circuital and cellular properties depending on the Wnt protein isoforms, concentration, and type of neuronal circuit. Antibodies against canonical and non-canonical ligands, as well as WASP-1 and sFRP-2, demonstrate that constitutive release of Wnts contributes to the maintenance of the network and intrinsic properties of the circuit. Furthermore, we found that the excess of Wnt3a or the permanent intracellular activation of the pathway with BIO-6 accelerates the period of the oscillation by disrupting the oscillatory units (Up states) in short units, presumably by affecting the synaptic mechanisms that couples neurons into the oscillatory cycle, but without affecting the spike generation. Instead, low doses of Wnt5a increase the period of the oscillation in EC by incorporating new cells into the network activity, probably modifying firing activity in other places of the circuit. Moreover, we found that Wnt signaling operates under different principles in the hippocampus. Using pyrvinium pamoate, a Wnt/β-catenin dependent pathway inhibitor, we demonstrated that this pathway is essential to keep the firing activity in the circuit CA3, and in less degree of CA1 circuit. However, CA1 circuit possesses homeostatic mechanisms to up-regulate the firing activity when it has been suppressed in CA3, and to down-modulate the cellular excitability when exacerbated

  20. The Global Oscillation Network Group site survey, 2: Results

    NASA Technical Reports Server (NTRS)

    Hill, Frank; Fischer, George; Forgach, Suzanne; Grier, Jennifer; Leibacher, John W.; Jones, Harrison P.; Jones, Patricia B.; Kupke, Renate; Stebbins, Robin T.; Clay, Donald W.

    1994-01-01

    The Global Oscillation Network Group (GONG) Project will place a network of instruments around the world to observe solar oscillations as continuously as possible for three years. The Project has now chosen the six network sites based on analysis of survey data from fifteen sites around the world. The chosen sites are: Big Bear Solar Observatory, California; Mauna Loa Solar Observatory, Hawaii; Learmonth Solar Observatory, Australia; Udaipur Solar Observatory, India; Observatorio del Teide, Tenerife; and Cerro Tololo Interamerican Observatory, Chile. Total solar intensity at each site yields information on local cloud cover, extinction coefficient, and transparency fluctuations. In addition, the performance of 192 reasonable networks assembled from the individual site records is compared using a statistical principal components analysis. An accompanying paper descibes the analysis methods in detail; here we present the results of both the network and individual site analyses. The selected network has a duty cycle of 93.3%, in good agreement with numerical simulations. The power spectrum of the network observing window shows a first diurnal sidelobe height of 3 x 10(exp -4) with respect to the central component, an improvement of a factor of 1300 over a single site. The background level of the network spectrum is lower by a factor of 50 compared to a single-site spectrum.

  1. Premature changes in neuronal excitability account for hippocampal network impairment and autistic-like behavior in neonatal BTBR T+tf/J mice.

    PubMed

    Cellot, Giada; Maggi, Laura; Di Castro, Maria Amalia; Catalano, Myriam; Migliore, Rosanna; Migliore, Michele; Scattoni, Maria Luisa; Calamandrei, Gemma; Cherubini, Enrico

    2016-01-01

    Coherent network oscillations (GDPs), generated in the immature hippocampus by the synergistic action of GABA and glutamate, both depolarizing and excitatory, play a key role in the construction of neuronal circuits. In particular, GDPs-associated calcium transients act as coincident detectors for enhancing synaptic efficacy at emerging GABAergic and glutamatergic synapses. Here, we show that, immediately after birth, in the CA3 hippocampal region of the BTBR T+tf/J mouse, an animal model of idiopathic autism, GDPs are severely impaired. This effect was associated with an increased GABAergic neurotransmission and a reduced neuronal excitability. In spite its depolarizing action on CA3 pyramidal cells (in single channel experiments EGABA was positive to Em), GABA exerted at the network level an inhibitory effect as demonstrated by isoguvacine-induced reduction of neuronal firing. We implemented a computational model in which experimental findings could be interpreted as the result of two competing effects: a reduction of the intrinsic excitability of CA3 principal cells and a reduction of the shunting activity in GABAergic interneurons projecting to principal cells. It is therefore likely that premature changes in neuronal excitability within selective hippocampal circuits of BTBR mice lead to GDPs dysfunction and behavioral deficits reminiscent of those found in autistic patients. PMID:27526668

  2. Premature changes in neuronal excitability account for hippocampal network impairment and autistic-like behavior in neonatal BTBR T+tf/J mice

    PubMed Central

    Cellot, Giada; Maggi, Laura; Di Castro, Maria Amalia; Catalano, Myriam; Migliore, Rosanna; Migliore, Michele; Scattoni, Maria Luisa; Calamandrei, Gemma; Cherubini, Enrico

    2016-01-01

    Coherent network oscillations (GDPs), generated in the immature hippocampus by the synergistic action of GABA and glutamate, both depolarizing and excitatory, play a key role in the construction of neuronal circuits. In particular, GDPs-associated calcium transients act as coincident detectors for enhancing synaptic efficacy at emerging GABAergic and glutamatergic synapses. Here, we show that, immediately after birth, in the CA3 hippocampal region of the BTBR T+tf/J mouse, an animal model of idiopathic autism, GDPs are severely impaired. This effect was associated with an increased GABAergic neurotransmission and a reduced neuronal excitability. In spite its depolarizing action on CA3 pyramidal cells (in single channel experiments EGABA was positive to Em), GABA exerted at the network level an inhibitory effect as demonstrated by isoguvacine-induced reduction of neuronal firing. We implemented a computational model in which experimental findings could be interpreted as the result of two competing effects: a reduction of the intrinsic excitability of CA3 principal cells and a reduction of the shunting activity in GABAergic interneurons projecting to principal cells. It is therefore likely that premature changes in neuronal excitability within selective hippocampal circuits of BTBR mice lead to GDPs dysfunction and behavioral deficits reminiscent of those found in autistic patients. PMID:27526668

  3. Hippocampal unified multi-atlas network (HUMAN): protocol and scale validation of a novel segmentation tool

    NASA Astrophysics Data System (ADS)

    Amoroso, N.; Errico, R.; Bruno, S.; Chincarini, A.; Garuccio, E.; Sensi, F.; Tangaro, S.; Tateo, A.; Bellotti, R.; Alzheimers Disease Neuroimaging Initiative,the

    2015-11-01

    In this study we present a novel fully automated Hippocampal Unified Multi-Atlas-Networks (HUMAN) algorithm for the segmentation of the hippocampus in structural magnetic resonance imaging. In multi-atlas approaches atlas selection is of crucial importance for the accuracy of the segmentation. Here we present an optimized method based on the definition of a small peri-hippocampal region to target the atlas learning with linear and non-linear embedded manifolds. All atlases were co-registered to a data driven template resulting in a computationally efficient method that requires only one test registration. The optimal atlases identified were used to train dedicated artificial neural networks whose labels were then propagated and fused to obtain the final segmentation. To quantify data heterogeneity and protocol inherent effects, HUMAN was tested on two independent data sets provided by the Alzheimer’s Disease Neuroimaging Initiative and the Open Access Series of Imaging Studies. HUMAN is accurate and achieves state-of-the-art performance (Dice{{}\\text{ADNI}} =0.929+/- 0.003 and Dice{{}\\text{OASIS}} =0.869+/- 0.002 ). It is also a robust method that remains stable when applied to the whole hippocampus or to sub-regions (patches). HUMAN also compares favorably with a basic multi-atlas approach and a benchmark segmentation tool such as FreeSurfer.

  4. Braess's paradox in oscillator networks, desynchronization and power outage

    NASA Astrophysics Data System (ADS)

    Witthaut, Dirk; Timme, Marc

    2012-08-01

    Robust synchronization is essential to ensure the stable operation of many complex networked systems such as electric power grids. Increasing energy demands and more strongly distributing power sources raise the question of where to add new connection lines to the already existing grid. Here we study how the addition of individual links impacts the emergence of synchrony in oscillator networks that model power grids on coarse scales. We reveal that adding new links may not only promote but also destroy synchrony and link this counter-intuitive phenomenon to Braess's paradox known for traffic networks. We analytically uncover its underlying mechanism in an elementary grid example, trace its origin to geometric frustration in phase oscillators, and show that it generically occurs across a wide range of systems. As an important consequence, upgrading the grid requires particular care when adding new connections because some may destabilize the synchronization of the grid—and thus induce power outages.

  5. Explosive transitions to synchronization in networks of phase oscillators

    PubMed Central

    Leyva, I.; Navas, A.; Sendiña-Nadal, I.; Almendral, J. A.; Buldú, J. M.; Zanin, M.; Papo, D.; Boccaletti, S.

    2013-01-01

    The emergence of dynamical abrupt transitions in the macroscopic state of a system is currently a subject of the utmost interest. The occurrence of a first-order phase transition to synchronization of an ensemble of networked phase oscillators was reported, so far, for very particular network architectures. Here, we show how a sharp, discontinuous transition can occur, instead, as a generic feature of networks of phase oscillators. Precisely, we set conditions for the transition from unsynchronized to synchronized states to be first-order, and demonstrate how these conditions can be attained in a very wide spectrum of situations. We then show how the occurrence of such transitions is always accompanied by the spontaneous setting of frequency-degree correlation features. Third, we show that the conditions for abrupt transitions can be even softened in several cases. Finally, we discuss, as a possible application, the use of this phenomenon to express magnetic-like states of synchronization. PMID:23412391

  6. Emerging dynamics in neuronal networks of diffusively coupled hard oscillators.

    PubMed

    Ponta, L; Lanza, V; Bonnin, M; Corinto, F

    2011-06-01

    Oscillatory networks are a special class of neural networks where each neuron exhibits time periodic behavior. They represent bio-inspired architectures which can be exploited to model biological processes such as the binding problem and selective attention. In this paper we investigate the dynamics of networks whose neurons are hard oscillators, namely they exhibit the coexistence of different stable attractors. We consider a constant external stimulus applied to each neuron, which influences the neuron's own natural frequency. We show that, due to the interaction between different kinds of attractors, as well as between attractors and repellors, new interesting dynamics arises, in the form of synchronous oscillations of various amplitudes. We also show that neurons subject to different stimuli are able to synchronize if their couplings are strong enough. PMID:21411276

  7. Synchronization in the network of chaotic microwave oscillators

    NASA Astrophysics Data System (ADS)

    Moskalenko, O.; Phrolov, N.; Koronovskii, A.; Hramov, A.

    2013-10-01

    Time scale synchronization in networks of chaotic microwave oscillators with the different topologies of the links between nodes has been studied. As a node element of the network the one-dimensional distributed model of the low-voltage vircator has been used. To characterize the degree of synchronization in the whole network the synchronization index has been introduced. The transition to the synchronous regime is shown to take place via cluster time scale synchronization. Meanwhile, the spectral structure of the output signals is complicated sufficiently which allows using such devices in a number of practical applications.

  8. Collective behavior of interacting locally synchronized oscillations in neuronal networks

    NASA Astrophysics Data System (ADS)

    Jalili, Mahdi

    2012-10-01

    Local circuits in the cortex and hippocampus are endowed with resonant, oscillatory firing properties which underlie oscillations in various frequency ranges (e.g. gamma range) frequently observed in the local field potentials, and in electroencephalography. Synchronized oscillations are thought to play important roles in information binding in the brain. This paper addresses the collective behavior of interacting locally synchronized oscillations in realistic neural networks. A network of five neurons is proposed in order to produce locally synchronized oscillations. The neuron models are Hindmarsh-Rose type with electrical and/or chemical couplings. We construct large-scale models using networks of such units which capture the essential features of the dynamics of cells and their connectivity patterns. The profile of the spike synchronization is then investigated considering different model parameters such as strength and ratio of excitatory/inhibitory connections. We also show that transmission time-delay might enhance the spike synchrony. The influence of spike-timing-dependence-plasticity is also studies on the spike synchronization.

  9. A memristor oscillator based on a twin-T network

    NASA Astrophysics Data System (ADS)

    Li, Zhi-Jun; Zeng, Yi-Cheng

    2013-04-01

    A novel inductance-free nonlinear oscillator circuit with a single bifurcation parameter is presented in this paper. This circuit is composed of a twin-T oscillator, a passive RC network, and a flux-controlled memristor. With an increase in the control parameter, the circuit exhibits complicated chaotic behaviors from double periodicity. The dynamic properties of the circuit are demonstrated by means of equilibrium stability, Lyapunov exponent spectra, and bifurcation diagrams. In order to confirm the occurrence of chaotic behavior in the circuit, an analog realization of the piecewise-linear flux-controlled memristor is proposed, and Pspice simulation is conducted on the resulting circuit.

  10. Estradiol rapidly modulates synaptic plasticity of hippocampal neurons: Involvement of kinase networks.

    PubMed

    Hasegawa, Yoshitaka; Hojo, Yasushi; Kojima, Hiroki; Ikeda, Muneki; Hotta, Keisuke; Sato, Rei; Ooishi, Yuuki; Yoshiya, Miyuki; Chung, Bon-Chu; Yamazaki, Takeshi; Kawato, Suguru

    2015-09-24

    Estradiol (E2) is locally synthesized within the hippocampus in addition to the gonads. Rapid modulation of hippocampal synaptic plasticity by E2 is essential for synaptic regulation. Molecular mechanisms of modulation through synaptic estrogen receptor (ER) and its downstream signaling, however, have been still unknown. We investigated induction of LTP by the presence of E2 upon weak theta burst stimulation (weak-TBS) in CA1 region of adult male hippocampus. Since only weak-TBS did not induce full-LTP, weak-TBS was sub-threshold stimulation. We observed LTP induction by the presence of E2, after incubation of hippocampal slices with 10nM E2 for 30 min, upon weak-TBS. This E2-induced LTP was blocked by ICI, an ER antagonist. This E2-LTP induction was inhibited by blocking Erk MAPK, PKA, PKC, PI3K, NR2B and CaMKII, individually, suggesting that Erk MAPK, PKA, PKC, PI3K and CaMKII may be involved in downstream signaling for activation of NMDA receptors. Interestingly, dihydrotestosterone suppressed the E2-LTP. We also investigated rapid changes of dendritic spines (=postsynapses) in response to E2, using hippocampal slices from adult male rats. We found 1nM E2 increased the density of spines by approximately 1.3-fold within 2h by imaging Lucifer Yellow-injected CA1 pyramidal neurons. The E2-induced spine increase was blocked by ICI. The increase in spines was suppressed by blocking PI3K, Erk MAPK, p38 MAPK, PKA, PKC, LIMK, CaMKII or calcineurin, individually. On the other hand, blocking JNK did not inhibit the E2-induced spine increase. Taken together, these results suggest that E2 rapidly induced LTP and also increased the spine density through kinase networks that are driven by synaptic ER. This article is part of a Special Issue entitled SI: Brain and Memory. PMID:25595055

  11. Estradiol rapidly modulates spinogenesis in hippocampal dentate gyrus: Involvement of kinase networks.

    PubMed

    Hojo, Yasushi; Munetomo, Arisa; Mukai, Hideo; Ikeda, Muneki; Sato, Rei; Hatanaka, Yusuke; Murakami, Gen; Komatsuzaki, Yoshimasa; Kimoto, Tetsuya; Kawato, Suguru

    2015-08-01

    This article is part of a Special Issue "Estradiol and cognition". Estradiol (E2) is locally synthesized within the hippocampus and the gonads. Rapid modulation of hippocampal synaptic plasticity by E2 is essential for synaptic regulation. The molecular mechanisms of modulation through the synaptic estrogen receptor (ER) and its downstream signaling, however, are largely unknown in the dentate gyrus (DG). We investigated the E2-induced modulation of dendritic spines in male adult rat hippocampal slices by imaging Lucifer Yellow-injected DG granule cells. Treatments with 1 nM E2 increased the density of spines by approximately 1.4-fold within 2h. Spine head diameter analysis showed that the density of middle-head spines (0.4-0.5 μm) was significantly increased. The E2-induced spine density increase was suppressed by blocking Erk MAPK, PKA, PKC and LIMK. These suppressive effects by kinase inhibitors are not non-specific ones because the GSK-3β antagonist did not inhibit E2-induced spine increase. The ER antagonist ICI 182,780 also blocked the E2-induced spine increase. Taken together, these results suggest that E2 rapidly increases the density of spines through kinase networks that are driven by synaptic ER. PMID:26122288

  12. The 5-HT6 receptor antagonist idalopirdine potentiates the effects of acetylcholinesterase inhibition on neuronal network oscillations and extracellular acetylcholine levels in the rat dorsal hippocampus.

    PubMed

    Herrik, Kjartan F; Mørk, Arne; Richard, Nelly; Bundgaard, Christoffer; Bastlund, Jesper F; de Jong, Inge E M

    2016-08-01

    The 5-HT6 receptor has emerged as a promising target for cognitive disorders and combining a 5-HT6 receptor antagonist with an acetylcholinesterase inhibitor (AChEI) represents a novel approach for the symptomatic treatment of Alzheimer's disease (AD). A recent phase 2 trial showed that the selective 5-HT6 receptor antagonist idalopirdine (Lu AE58054) improved cognition in patients with moderate AD on stable treatment with the AChEI donepezil. Here we investigated the effects of idalopirdine in combination with donepezil on hippocampal function using in vivo electrophysiology and microdialysis. Network oscillations in the hippocampus were recorded during electrical stimulation of the brainstem nucleus pontis oralis (nPO) in the anesthetized rat and hippocampal acetylcholine (ACh) levels were measured in the freely-moving rat. In addition, potential pharmacokinetic interactions between idalopirdine and donepezil were assessed. Idalopirdine alone did not affect hippocampal network oscillations or ACh levels. Donepezil (0.3 and 1.0 mg/kg i.v.) dose-dependently increased hippocampal theta and gamma power during nPO stimulation. Idalopirdine (2 mg/kg i.v.), administered 1 h prior to donepezil, potentiated the theta and gamma response to 0.3 mg/kg donepezil and prolonged the gamma response to 1 mg/kg donepezil. Donepezil (1.3 mg/kg s.c.) increased extracellular ACh levels in the hippocampus and this was further augmented by administration of idalopirdine (10 mg/kg p.o.) 2 h prior to donepezil. These effects could not be attributed to a pharmacokinetic interaction between the compounds. This study demonstrates that idalopirdine potentiates the effects of donepezil on two pharmacodynamic biomarkers associated with cognition, i.e. neuronal oscillations and extracellular ACh levels in the hippocampus. Such potentiation could contribute to the procognitive effects of idalopirdine observed in donepezil-treated AD patients. PMID:27039041

  13. Network burst activity in hippocampal neuronal cultures: the role of synaptic and intrinsic currents.

    PubMed

    Suresh, Jyothsna; Radojicic, Mihailo; Pesce, Lorenzo L; Bhansali, Anita; Wang, Janice; Tryba, Andrew K; Marks, Jeremy D; van Drongelen, Wim

    2016-06-01

    The goal of this work was to define the contributions of intrinsic and synaptic mechanisms toward spontaneous network-wide bursting activity, observed in dissociated rat hippocampal cell cultures. This network behavior is typically characterized by short-duration bursts, separated by order of magnitude longer interburst intervals. We hypothesize that while short-timescale synaptic processes modulate spectro-temporal intraburst properties and network-wide burst propagation, much longer timescales of intrinsic membrane properties such as persistent sodium (Nap) currents govern burst onset during interburst intervals. To test this, we used synaptic receptor antagonists picrotoxin, 6-cyano-7-nitroquinoxaline-2,3-dione (CNQX), and 3-(2-carboxypiperazine-4-yl)propyl-1-phosphonate (CPP) to selectively block GABAA, AMPA, and NMDA receptors and riluzole to selectively block Nap channels. We systematically compared intracellular activity (recorded with patch clamp) and network activity (recorded with multielectrode arrays) in eight different synaptic connectivity conditions: GABAA + NMDA + AMPA, NMDA + AMPA, GABAA + AMPA, GABAA + NMDA, AMPA, NMDA, GABAA, and all receptors blocked. Furthermore, we used mixed-effects modeling to quantify the aforementioned independent and interactive synaptic receptor contributions toward spectro-temporal burst properties including intraburst spike rate, burst activity index, burst duration, power in the local field potential, network connectivity, and transmission delays. We found that blocking intrinsic Nap currents completely abolished bursting activity, demonstrating their critical role in burst onset within the network. On the other hand, blocking different combinations of synaptic receptors revealed that spectro-temporal burst properties are uniquely associated with synaptic functionality and that excitatory connectivity is necessary for the presence of network-wide bursting. In addition to confirming the critical contribution of direct

  14. Spatial-temporal dynamics of chaotic behavior in cultured hippocampal networks.

    PubMed

    Chen, Wenjuan; Li, Xiangning; Pu, Jiangbo; Luo, Qingming

    2010-06-01

    Using multiple nonlinear techniques, we revealed the existence of chaos in the spontaneous activity of neuronal networks in vitro. The spatial-temporal dynamics of these networks indicated that emergent transition between chaotic behavior and superburst occurred periodically in low-frequency oscillations. An analysis of network-wide activity indicated that chaos was synchronized among different sites. Moreover, we found that the degree of chaos increased as the number of active sites in the network increased during long-term development (over three months in vitro). The chaotic behavior of the dissociated networks had similar spatial-temporal characteristics (rapid transition, periodicity, and synchronization) as the intact brain; however, the degree of chaos depended on the number of active sites at the mesoscopic level. This work could provide insight into neural coding and neurocybernetics. PMID:20866436

  15. Glycolysis and oxidative phosphorylation in neurons and astrocytes during network activity in hippocampal slices

    PubMed Central

    Ivanov, Anton I; Malkov, Anton E; Waseem, Tatsiana; Mukhtarov, Marat; Buldakova, Svetlana; Gubkina, Olena; Zilberter, Misha; Zilberter, Yuri

    2014-01-01

    Network activation triggers a significant energy metabolism increase in both neurons and astrocytes. Questions of the primary neuronal energy substrate (e.g., glucose vs. lactate) as well as the relative contributions of glycolysis and oxidative phosphorylation and their cellular origin (neurons vs. astrocytes) are still a matter of debates. Using simultaneous measurements of electrophysiological and metabolic parameters during synaptic stimulation in hippocampal slices from mature mice, we show that neurons and astrocytes use both glycolysis and oxidative phosphorylation to meet their energy demands. Supplementation or replacement of glucose in artificial cerebrospinal fluid (ACSF) with pyruvate or lactate strongly modifies parameters related to network activity-triggered energy metabolism. These effects are not induced by changes in ATP content, pHi, [Ca2+]i or accumulation of reactive oxygen species. Our results suggest that during network activation, a significant fraction of NAD(P)H response (its overshoot phase) corresponds to glycolysis and the changes in cytosolic NAD(P)H and mitochondrial FAD are coupled. Our data do not support the hypothesis of a preferential utilization of astrocyte-released lactate by neurons during network activation in slices—instead, we show that during such activity glucose is an effective energy substrate for both neurons and astrocytes. PMID:24326389

  16. Synchronization in neuronal oscillator networks with input heterogeneity and arbitrary network structure

    NASA Astrophysics Data System (ADS)

    Davison, Elizabeth; Dey, Biswadip; Leonard, Naomi

    Mathematical studies of synchronization in networks of neuronal oscillators offer insight into neuronal ensemble behavior in the brain. Systematic means to understand how network structure and external input affect synchronization in network models have the potential to improve methods for treating synchronization-related neurological disorders such as epilepsy and Parkinson's disease. To elucidate the complex relationships between network structure, external input, and synchronization, we investigate synchronous firing patterns in arbitrary networks of neuronal oscillators coupled through gap junctions with heterogeneous external inputs. We first apply a passivity-based Lyapunov analysis to undirected networks of homogeneous FitzHugh-Nagumo (FN) oscillators with homogeneous inputs and derive a sufficient condition on coupling strength that guarantees complete synchronization. In biologically relevant regimes, we employ Gronwall's inequality to obtain a bound tighter than those previously reported. We extend both analyses to a homogeneous FN network with heterogeneous inputs and show how cluster synchronization emerges under conditions on the symmetry of the coupling matrix and external inputs. Our results can be generalized to any network of semi-passive oscillators.

  17. Maintaining Consistency of Spatial Information in the Hippocampal Network: A Combinatorial Geometry Model.

    PubMed

    Dabaghian, Y

    2016-06-01

    Place cells in the rat hippocampus play a key role in creating the animal's internal representation of the world. During active navigation, these cells spike only in discrete locations, together encoding a map of the environment. Electrophysiological recordings have shown that the animal can revisit this map mentally during both sleep and awake states, reactivating the place cells that fired during its exploration in the same sequence in which they were originally activated. Although consistency of place cell activity during active navigation is arguably enforced by sensory and proprioceptive inputs, it remains unclear how a consistent representation of space can be maintained during spontaneous replay. We propose a model that can account for this phenomenon and suggest that a spatially consistent replay requires a number of constraints on the hippocampal network that affect its synaptic architecture and the statistics of synaptic connection strengths. PMID:27137840

  18. Frequency Response and Gap Tuning for Nonlinear Electrical Oscillator Networks

    PubMed Central

    Bhat, Harish S.; Vaz, Garnet J.

    2013-01-01

    We study nonlinear electrical oscillator networks, the smallest example of which consists of a voltage-dependent capacitor, an inductor, and a resistor driven by a pure tone source. By allowing the network topology to be that of any connected graph, such circuits generalize spatially discrete nonlinear transmission lines/lattices that have proven useful in high-frequency analog devices. For such networks, we develop two algorithms to compute the steady-state response when a subset of nodes are driven at the same fixed frequency. The algorithms we devise are orders of magnitude more accurate and efficient than stepping towards the steady-state using a standard numerical integrator. We seek to enhance a given network's nonlinear behavior by altering the eigenvalues of the graph Laplacian, i.e., the resonances of the linearized system. We develop a Newton-type method that solves for the network inductances such that the graph Laplacian achieves a desired set of eigenvalues; this method enables one to move the eigenvalues while keeping the network topology fixed. Running numerical experiments using three different random graph models, we show that shrinking the gap between the graph Laplacian's first two eigenvalues dramatically improves a network's ability to (i) transfer energy to higher harmonics, and (ii) generate large-amplitude signals. Our results shed light on the relationship between a network's structure, encoded by the graph Laplacian, and its function, defined in this case by the presence of strongly nonlinear effects in the frequency response. PMID:24223751

  19. Emergence of amplitude death scenario in a network of oscillators under repulsive delay interaction

    NASA Astrophysics Data System (ADS)

    Bera, Bidesh K.; Hens, Chittaranjan; Ghosh, Dibakar

    2016-07-01

    We report the existence of amplitude death in a network of identical oscillators under repulsive mean coupling. Amplitude death appears in a globally coupled network of identical oscillators with instantaneous repulsive mean coupling only when the number of oscillators is more than two. We further investigate that, amplitude death may emerge even in two coupled oscillators as well as network of oscillators if we introduce delay time in the repulsive mean coupling. We have analytically derived the region of amplitude death island and find out how strength of delay controls the death regime in two coupled or a large network of coupled oscillators. We have verified our results on network of delayed Mackey-Glass systems where parameters are set in hyperchaotic regime. We have also tested our coupling approach in two paradigmatic limit cycle oscillators: Stuart-Landau and Van der Pol oscillators.

  20. Interplay between population firing stability and single neuron dynamics in hippocampal networks.

    PubMed

    Slomowitz, Edden; Styr, Boaz; Vertkin, Irena; Milshtein-Parush, Hila; Nelken, Israel; Slutsky, Michael; Slutsky, Inna

    2015-01-01

    Neuronal circuits' ability to maintain the delicate balance between stability and flexibility in changing environments is critical for normal neuronal functioning. However, to what extent individual neurons and neuronal populations maintain internal firing properties remains largely unknown. In this study, we show that distributions of spontaneous population firing rates and synchrony are subject to accurate homeostatic control following increase of synaptic inhibition in cultured hippocampal networks. Reduction in firing rate triggered synaptic and intrinsic adaptive responses operating as global homeostatic mechanisms to maintain firing macro-stability, without achieving local homeostasis at the single-neuron level. Adaptive mechanisms, while stabilizing population firing properties, reduced short-term facilitation essential for synaptic discrimination of input patterns. Thus, invariant ongoing population dynamics emerge from intrinsically unstable activity patterns of individual neurons and synapses. The observed differences in the precision of homeostatic control at different spatial scales challenge cell-autonomous theory of network homeostasis and suggest the existence of network-wide regulation rules. PMID:25556699

  1. Altered Intrinsic Pyramidal Neuron Properties and Pathway-Specific Synaptic Dysfunction Underlie Aberrant Hippocampal Network Function in a Mouse Model of Tauopathy

    PubMed Central

    Booth, Clair A.; Witton, Jonathan; Nowacki, Jakub; Tsaneva-Atanasova, Krasimira; Jones, Matthew W.; Randall, Andrew D.

    2016-01-01

    The formation and deposition of tau protein aggregates is proposed to contribute to cognitive impairments in dementia by disrupting neuronal function in brain regions, including the hippocampus. We used a battery of in vivo and in vitro electrophysiological recordings in the rTg4510 transgenic mouse model, which overexpresses a mutant form of human tau protein, to investigate the effects of tau pathology on hippocampal neuronal function in area CA1 of 7- to 8-month-old mice, an age point at which rTg4510 animals exhibit advanced tau pathology and progressive neurodegeneration. In vitro recordings revealed shifted theta-frequency resonance properties of CA1 pyramidal neurons, deficits in synaptic transmission at Schaffer collateral synapses, and blunted plasticity and imbalanced inhibition at temporoammonic synapses. These changes were associated with aberrant CA1 network oscillations, pyramidal neuron bursting, and spatial information coding in vivo. Our findings relate tauopathy-associated changes in cellular neurophysiology to altered behavior-dependent network function. SIGNIFICANCE STATEMENT Dementia is characterized by the loss of learning and memory ability. The deposition of tau protein aggregates in the brain is a pathological hallmark of dementia; and the hippocampus, a brain structure known to be critical in processing learning and memory, is one of the first and most heavily affected regions. Our results show that, in area CA1 of hippocampus, a region involved in spatial learning and memory, tau pathology is associated with specific disturbances in synaptic, cellular, and network-level function, culminating in the aberrant encoding of spatial information and spatial memory impairment. These studies identify several novel ways in which hippocampal information processing may be disrupted in dementia, which may provide targets for future therapeutic intervention. PMID:26758828

  2. Task induced modulation of neural oscillations in electrophysiological brain networks.

    PubMed

    Brookes, M J; Liddle, E B; Hale, J R; Woolrich, M W; Luckhoo, H; Liddle, P F; Morris, P G

    2012-12-01

    In recent years, one of the most important findings in systems neuroscience has been the identification of large scale distributed brain networks. These networks support healthy brain function and are perturbed in a number of neurological disorders (e.g. schizophrenia). Their study is therefore an important and evolving focus for neuroscience research. The majority of network studies are conducted using functional magnetic resonance imaging (fMRI) which relies on changes in blood oxygenation induced by neural activity. However recently, a small number of studies have begun to elucidate the electrical origin of fMRI networks by searching for correlations between neural oscillatory signals from spatially separate brain areas in magnetoencephalography (MEG) data. Here we advance this research area. We introduce two methodological extensions to previous independent component analysis (ICA) approaches to MEG network characterisation: 1) we show how to derive pan-spectral networks that combine independent components computed within individual frequency bands. 2) We show how to measure the temporal evolution of each network with millisecond temporal resolution. We apply our approach to ~10h of MEG data recorded in 28 experimental sessions during 3 separate cognitive tasks showing that a number of networks could be identified and were robust across time, task, subject and recording session. Further, we show that neural oscillations in those networks are modulated by memory load, and task relevance. This study furthers recent findings on electrodynamic brain networks and paves the way for future clinical studies in patients in which abnormal connectivity is thought to underlie core symptoms. PMID:22906787

  3. Asymptotic periodicity in networks of degrade-and-fire oscillators

    NASA Astrophysics Data System (ADS)

    Blumenthal, Alex; Fernandez, Bastien

    2016-06-01

    Networks of coupled degrade-and-fire (DF) oscillators are simple dynamical models of assemblies of interacting self-repressing genes. For mean-field interactions, which most mathematical studies have assumed so far, every trajectory must approach a periodic orbit. Moreover, asymptotic cluster distributions can be computed explicitly in terms of coupling intensity, and a massive collection of distributions collapses when this intensity passes a threshold. Here, we show that most of these dynamical features persist for an arbitrary coupling topology. In particular, we prove that, in any system of DF oscillators for which in and out coupling weights balance, trajectories with reasonable firing sequences must be asymptotically periodic, and periodic orbits are uniquely determined by their firing sequence. In addition to these structural results, illustrative examples are presented, for which the dynamics can be entirely described.

  4. [Alteration of neural oscillations in hippocampal CA3 area in the fast avoidance response rat before and after electric shock avoidance training].

    PubMed

    Wang, Wei-Wei; Wang, Dan-Dan; Wang, Dan; Guan, Yan; Tang, Ying-Ying; Ye, Zheng; Li, Jing; Li, Min; Zhu, Zai-Man; Pan, Qun-Wan

    2015-10-25

    The purpose of the present study is to explore the relationship of spatial learning ability and specific electrical activities of neural oscillations in the rat. The fast and general avoidance response groups were selected on the basis of the animals' responses to the electric shock in Y type maze, and their local field potentials (LFPs) of hippocampal CA3 area were recorded by wireless telemetry before and after shock avoidance training, respectively. The components of neural oscillations related to spatial identifying and learning ability were analyzed. The results showed that, compared with the general avoidance response group, the fast avoidance response group did not show any differences of LFPs in hippocampal CA3 area before electric shock avoidance trial, but showed significantly increased percentages of 0-10 Hz and 30-40 Hz rhythm in right hippocampal CA3 area after the shock avoidance training (P < 0.01 or P < 0.05). Fast Fourier transform showed that percentage increase of 0-10 Hz band occurred mainly in θ (3-7 Hz) frequency, and 30-40 Hz frequency change was equivalent to the γ1 band. Furthermore, compared with those before training, only the percentages of β, β2 (20-30 Hz) and γ1 rhythm increased (P < 0.01 or P < 0.05) in fast avoidance response rats after training, while the θ rhythm percentage remained unchanged. In contrast, θ rhythm percentage and the large amplitude (intensity: +2.5 - -2.5 db) θ waves in right CA3 area of general avoidance response rats were significantly reduced after training (P < 0.01). These results suggest that the increased percentages of β2 and γ1 rhythm and high-level (unchanged) percentage of θ rhythm in the right hippocampus CA3 area might be related to strong spatial cognition ability of fast avoidance response rats. PMID:26490066

  5. Analysis of torsional oscillations using an artificial neural network

    SciTech Connect

    Hsu, Y.Y.; Jeng, L,H. )

    1992-12-01

    In this paper, a novel approach using an artificial neural network (ANN) is proposed for the analysis of torsional oscillations in a power system. In the developed artificial neural network, those system variables such as generator loadings and capacitor compensation ratio which have major impacts on the damping characteristics of torsional oscillatio modes are employed as the inputs. The outputs of the neural net provide the desired eigenvalues for torsional modes. Once the connection weights of the neural network have been learned using a set of training data derived off-line, the neural network can be applied to torsional analysis in real-time situations. To demonstrate the effectiveness of the proposed neural net, torsional analysis is performed on the IEEE First Benchmark Model. It is concluded from the test results that accurate assessment of the torsional mode eigenvalues can be achieved by the neural network in a very efficient manner. Thereofore, the proposed neural network approach can serve as a valuable tool to system operators in conducting SSR analysis in operational planning.

  6. Attractor-Map Versus Autoassociation Based Attractor Dynamics in the Hippocampal Network

    PubMed Central

    Colgin, Laura L.; Leutgeb, Stefan; Jezek, Karel; Leutgeb, Jill K.; Moser, Edvard I.; Moser, May-Britt

    2010-01-01

    The autoassociative memory model of hippocampal field CA3 postulates that Hebbian associations among external input features produce attractor states embedded in a recurrent synaptic matrix. In contrast, the attractor-map model postulates that a two-dimensional continuum of attractor states is preconfigured in the network during development and that transitions among these states are governed primarily by self-motion information (“path-integration”), giving rise to the strong spatial characteristic of hippocampal activity. In this model, learned associations between “coordinates” on the attractor map and external cues can result in abrupt jumps between states, in the case of mismatches between the current input and previous associations between internal coordinates and external landmarks. Both models predict attractor dynamics, but for fundamentally different reasons; however, the two models are not a priori mutually exclusive. We contrasted these two models by comparing the dynamics of state transitions when two previously learned environmental shapes were morphed between their endpoints, in animals that had first experienced the environments either at the same location, or at two different locations, connected by a passageway through which they walked. As predicted from attractor-map theory, the latter animals expressed abrupt transitions between representations at the midpoint of the morph series. Contrary to the predictions of autoassociation theory, the former group expressed no evidence of attractor dynamics during the morph series; there was only a gradual transition between endpoints. The results of this critical test thus cast the autoassociator theory for CA3 into doubt and indicate the need for a new theory for this structure. PMID:20445029

  7. Electrophysiological properties of hippocampal-cortical neural networks, role in the processes of learning and memory in rats.

    PubMed

    Li, Chang-Jun; Lu, Yun; Zhou, Mei; Guo, Lian-Jun

    2014-06-01

    The recording of hippocampal and cortical long-term potentiation (LTP) in rats in vivo is an appropriate and commonly used method to describe changes in cellular mechanisms underlying synaptic plasticity. Recently, we introduced a method for the simultaneous recording of LTP in bilateral CA1 regions and parietal association cortex (PtA), and observed differences between the Schaffer collateral-CA1 pathway (SC), Schaffer collateral/associational commissural pathway (SAC) and Schaffer collateral/associational commissural-cortex pathway (SACC). In this study, we found that (1) synaptic transmission of the SAC and SACC pathways depended on hippocampal commissural fibers [dorsal and ventral hippocampal commissural fibers, the medial septum (MS) and hippocampal CA3 commissural fibers], (2) nerve conduction velocity of the SACC pathway might be higher than that of the SAC pathway, (3) the input/output (I/O) curve of the SC pathway was shifted to the left side, compared to that of the SAC and SACC pathways, (4) all three pathways could induce stable LTP; however, LTP of the SAC and SACC pathways was much stronger than that of the SC pathway, (5) the degree of paired-pulse facilitation (PPF) was weaker in the SC pathway than that in the SAC and SACC pathways, (6) after cutting off the corpus callosum and commissural fibers, spatial learning and memory were impaired, and the ability to explore the novel environment and spontaneous locomotor activity were weakened. Taken together, our results suggested that hippocampal commissural fibers were very important for exchanging information between hemispheres, and basic differences in electrophysiological properties of hippocampal-cortical neural networks play a vital role in the processes of learning and memory. PMID:24504908

  8. Universal quantum computation with a nonlinear oscillator network

    NASA Astrophysics Data System (ADS)

    Goto, Hayato

    2016-05-01

    We theoretically show that a nonlinear oscillator network with controllable parameters can be used for universal quantum computation. The initialization is achieved by a quantum-mechanical bifurcation based on quantum adiabatic evolution, which yields a Schrödinger cat state. All the elementary quantum gates are also achieved by quantum adiabatic evolution, in which dynamical phases accompanying the adiabatic evolutions are controlled by the system parameters. Numerical simulation results indicate that high gate fidelities can be achieved, where no dissipation is assumed.

  9. 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.

  10. 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.

  11. The role of electrical coupling in generating and modulating oscillations in a neuronal network.

    PubMed

    Mouser, Christina; Bose, Amitabha; Nadim, Farzan

    2016-08-01

    A simplified model of the crustacean gastric mill network is considered. Rhythmic activity in this network has largely been attributed to half center oscillations driven by mutual inhibition. We use mathematical modeling and dynamical systems theory to show that rhythmic oscillations in this network may also depend on, or even arise from, a voltage-dependent electrical coupling between one of the cells in the half-center network and a projection neuron that lies outside of the network. This finding uncovers a potentially new mechanism for the generation of oscillations in neuronal networks. PMID:27188714

  12. The formation and distribution of hippocampal synapses on patterned neuronal networks

    NASA Astrophysics Data System (ADS)

    Dowell-Mesfin, Natalie M.

    Communication within the central nervous system is highly orchestrated with neurons forming trillions of specialized junctions called synapses. In vivo, biochemical and topographical cues can regulate neuronal growth. Biochemical cues also influence synaptogenesis and synaptic plasticity. The effects of topography on the development of synapses have been less studied. In vitro, neuronal growth is unorganized and complex making it difficult to study the development of networks. Patterned topographical cues guide and control the growth of neuronal processes (axons and dendrites) into organized networks. The aim of this dissertation was to determine if patterned topographical cues can influence synapse formation and distribution. Standard fabrication and compression molding procedures were used to produce silicon masters and polystyrene replicas with topographical cues presented as 1 mum high pillars with diameters of 0.5 and 2.0 mum and gaps of 1.0 to 5.0 mum. Embryonic rat hippocampal neurons grown unto patterned surfaces. A developmental analysis with immunocytochemistry was used to assess the distribution of pre- and post-synaptic proteins. Activity-dependent pre-synaptic vesicle uptake using functional imaging dyes was also performed. Adaptive filtering computer algorithms identified synapses by segmenting juxtaposed pairs of pre- and post-synaptic labels. Synapse number and area were automatically extracted from each deconvolved data set. In addition, neuronal processes were traced automatically to assess changes in synapse distribution. The results of these experiments demonstrated that patterned topographic cues can induce organized and functional neuronal networks that can serve as models for the study of synapse formation and plasticity as well as for the development of neuroprosthetic devices.

  13. Evaluating the Small-World-Ness of a Sampled Network: Functional Connectivity of Entorhinal-Hippocampal Circuitry

    PubMed Central

    She, Qi; Chen, Guanrong; Chan, Rosa H. M.

    2016-01-01

    The amount of publicly accessible experimental data has gradually increased in recent years, which makes it possible to reconsider many longstanding questions in neuroscience. In this paper, an efficient framework is presented for reconstructing functional connectivity using experimental spike-train data. A modified generalized linear model (GLM) with L1-norm penalty was used to investigate 10 datasets. These datasets contain spike-train data collected from the entorhinal-hippocampal region in the brains of rats performing different tasks. The analysis shows that entorhinal-hippocampal network of well-trained rats demonstrated significant small-world features. It is found that the connectivity structure generated by distance-dependent models is responsible for the observed small-world features of the reconstructed networks. The models are utilized to simulate a subset of units recorded from a large biological neural network using multiple electrodes. Two metrics for quantifying the small-world-ness both suggest that the reconstructed network from the sampled nodes estimates a more prominent small-world-ness feature than that of the original unknown network when the number of recorded neurons is small. Finally, this study shows that it is feasible to adjust the estimated small-world-ness results based on the number of neurons recorded to provide a more accurate reference of the network property. PMID:26902707

  14. Phase dependency of long-term potentiation induction during the intermittent bursts of carbachol-induced β oscillation in rat hippocampal slices

    PubMed Central

    Nishimura, Motoshi; Nakatsuka, Hiroki; Natsume, Kiyohisa

    2012-01-01

    The rodent hippocampus possesses theta (θ) and beta (β) rhythms, which occur intermittently as bursts. Both rhythms are related to spatial memory processing in a novel environment. θ rhythm is related to spatial memory encoding process. β rhythm is related to the match/mismatch process. In the match/mismatch process, rodent hippocampus detects a representation matching sensory inputs of the current place among the retrieved internal representations of places. Long-term synaptic potentiation (LTP) is induced in both processes. The cholinergic agent carbachol induces intermittent θ and β oscillations in in vitro slices similar to in vivo bursts. LTP is facilitated during the generation of θ oscillation, suggesting that the facilitation of LTP is dependent upon the phases of intermittent burst (burst phases) of the oscillation. However, whether this is the case for β oscillation has not yet been studied. In the present study, LTP-inducing θ-burst stimulation was administered at the different burst phases of carbachol-induced β oscillations (CIBO), and the synaptic changes were measured at CA3-CA3 pyramidal cell synapses (CA3 synapse) and at CA3-CA1 pyramidal cell synapses (CA1 synapse). At the CA3 synapse, the largest magnitude of LTP was induced at the late burst phases of CIBO. At the CA1 synapse, LTP was induced only at the late burst phases. Modulation of LTP was suppressed when CIBO was blocked by the application of atropine at both synapses. The results suggest that the bursts of hippocampal β rhythm can determine the optimal temporal period for completing with the match/mismatch process.

  15. Insensitive dependence of delay-induced oscillation death on complex networks

    NASA Astrophysics Data System (ADS)

    Zou, Wei; Zheng, Xing; Zhan, Meng

    2011-06-01

    Oscillation death (also called amplitude death), a phenomenon of coupling induced stabilization of an unstable equilibrium, is studied for an arbitrary symmetric complex network with delay-coupled oscillators, and the critical conditions for its linear stability are explicitly obtained. All cases including one oscillator, a pair of oscillators, regular oscillator networks, and complex oscillator networks with delay feedback coupling, can be treated in a unified form. For an arbitrary symmetric network, we find that the corresponding smallest eigenvalue of the Laplacian λN (0 >λN ≥ -1) completely determines the death island, and as λN is located within the insensitive parameter region for nearly all complex networks, the death island keeps nearly the largest and does not sensitively depend on the complex network structures. This insensitivity effect has been tested for many typical complex networks including Watts-Strogatz (WS) and Newman-Watts (NW) small world networks, general scale-free (SF) networks, Erdos-Renyi (ER) random networks, geographical networks, and networks with community structures and is expected to be helpful for our understanding of dynamics on complex networks.

  16. Immature hippocampal neuronal networks do not develop tolerance to the excitatory actions of ethanol.

    PubMed

    Galindo, Rafael; Valenzuela, C Fernando

    2006-10-01

    Ethanol (EtOH) damages the hippocampus, a brain region that is involved in learning and memory processes. The mechanisms responsible for this effect of EtOH are not fully understood. We recently demonstrated that acute EtOH exposure potently stimulates oscillatory activity driven by the excitatory actions of GABA in the CA3 region of the neonatal rat hippocampus. This activity can be recorded during the growth spurt period as giant depolarizing potentials (GDPs). Here, we characterized the effects of prolonged EtOH exposure on GDPs. In the first study, we prepared hippocampal coronal slices from neonatal rats and exposed these to control artificial cerebrospinal fluid (ACSF) or ACSF plus 50 mM EtOH for 3-4 h. We then performed whole-cell patch-clamp electrophysiological recordings from CA3 pyramidal neurons, which revealed that tolerance to the GDP stimulating effects of EtOH did not occur after continuous exposure. In the second study, we exposed neonatal rats to air or air plus 1.9 g/dl EtOH in vapor chambers for 4h/day for 1 or 3 days (neonatal peak blood EtOH concentration = 40-45 mM). We then performed slice electrophysiological studies 24 h after the end of EtOH exposure and found that there was no statistically significant difference in the acute effect of 50 mM EtOH on GDP frequency in samples from neonates exposed to air or air plus EtOH. These findings indicate that EtOH persistently stimulates network-driven oscillatory activity in the developing hippocampus. We propose that the lack of adaptive response to continuous EtOH exposure could make immature neuronal networks particularly vulnerable to the actions of this agent. PMID:17307647

  17. Entropy and stability of phase synchronisation of oscillators on networks

    SciTech Connect

    Kalloniatis, Alexander C.

    2014-09-15

    I examine the role of entropy in the transition from incoherence to phase synchronisation in the Kuramoto model of N coupled phase oscillators on a general undirected network. In a Hamiltonian ‘action-angle’ formulation, auxiliary variables J{sub i} combine with the phases θ{sub i} to determine a conserved system with a 2N dimensional phase space. In the vicinity of the fixed point for phase synchronisation, θ{sub i}≈θ{sub j}, which is known to be stable, the auxiliary variables J{sub i} exhibit instability. This manifests Liouville’s Theorem in the phase synchronised regime in that contraction in the θ{sub i} parts of phase space are compensated for by expansion in the auxiliary dimensions. I formulate an entropy rate based on the projection of the J{sub i} onto eigenvectors of the graph Laplacian that satisfies Pesin’s Theorem. This leads to the insight that the evolution to phase synchronisation of the Kuramoto model is equivalent to the approach to a state of monotonically increasing entropy. Indeed, for unequal intrinsic frequencies on the nodes, the networks that achieve the closest to exact phase synchronisation are those which enjoy the highest entropy production. I compare numerical results for a range of networks.

  18. Do slow and fast gamma rhythms correspond to distinct functional states in the hippocampal network?

    PubMed

    Colgin, Laura Lee

    2015-09-24

    For decades, hippocampal gamma was thought to be a single type of rhythm with a continuously varying frequency. However, an increasing body of evidence supports a new hypothesis regarding hippocampal gamma. The patterns traditionally defined as hippocampal gamma may actually comprise separate gamma subtypes with distinct frequencies and unique functions. The present review discusses the evidence for and against this new viewpoint. This review will also point out key questions that remain to be answered to validate the two-gamma hypothesis. This article is part of a Special Issue entitled SI: Brain and Memory. PMID:25591484

  19. Graph analysis of the anatomical network organization of the hippocampal formation and parahippocampal region in the rat.

    PubMed

    Binicewicz, F Z M; van Strien, N M; Wadman, W J; van den Heuvel, M P; Cappaert, N L M

    2016-04-01

    Graph theory was used to analyze the anatomical network of the rat hippocampal formation and the parahippocampal region (van Strien et al., Nat Rev Neurosci 10(4):272-282, 2009). For this analysis, the full network was decomposed along the three anatomical axes, resulting in three networks that describe the connectivity within the rostrocaudal, dorsoventral and laminar dimensions. The rostrocaudal network had a connection density of 12 % and a path length of 2.4. The dorsoventral network had a high cluster coefficient (0.53), a relatively high path length (1.62) and a rich club was identified. The modularity analysis revealed three modules in the dorsoventral network. The laminar network contained most information. The laminar dimension revealed a network with high clustering coefficient (0.47), a relatively high path length (2.11) and four significantly increased characteristic network building blocks (structural motifs). Thirteen rich club nodes were identified, almost all of them situated in the parahippocampal region. Six connector hubs were detected and all of them were located in the entorhinal cortex. Three large modules were revealed, indicating a close relationship between the perirhinal and postrhinal cortex as well as between the lateral and medial entorhinal cortex. These results confirmed the central position of the entorhinal cortex in the (para)hippocampal network and this possibly explains why pathology in this region has such profound impact on cognitive function, as seen in several brain diseases. The results also have implications for the idea of strict separation of the "spatial" and the "non-spatial" information stream into the hippocampus. This two-stream memory model suggests that the information influx from, respectively, the postrhinal-medial entorhinal cortex and the perirhinal-lateral entorhinal cortex is separate, but the current analysis shows that this apparent separation is not determined by anatomical constraints. PMID:25618022

  20. Network Profiles of the Dorsal Anterior Cingulate and Dorsal Prefrontal Cortex in Schizophrenia During Hippocampal-Based Associative Memory.

    PubMed

    Woodcock, Eric A; Wadehra, Sunali; Diwadkar, Vaibhav A

    2016-01-01

    Schizophrenia is a disorder characterized by brain network dysfunction, particularly during behavioral tasks that depend on frontal and hippocampal mechanisms. Here, we investigated network profiles of the regions of the frontal cortex during memory encoding and retrieval, phases of processing essential to associative memory. Schizophrenia patients (n = 12) and healthy control (HC) subjects (n = 10) participated in an established object-location associative memory paradigm that drives frontal-hippocampal interactions. Network profiles were modeled of both the dorsal prefrontal (dPFC) and the dorsal anterior cingulate cortex (dACC) as seeds using psychophysiological interaction analyses, a robust framework for investigating seed-based connectivity in specific task contexts. The choice of seeds was motivated by previous evidence of involvement of these regions during associative memory. Differences between patients and controls were evaluated using second-level analyses of variance (ANOVA) with seed (dPFC vs. dACC), group (patients vs. controls), and memory process (encoding and retrieval) as factors. Patients showed a pattern of exaggerated modulation by each of the dACC and the dPFC during memory encoding and retrieval. Furthermore, group by memory process interactions were observed within regions of the hippocampus. In schizophrenia patients, relatively diminished modulation during encoding was associated with increased modulation during retrieval. These results suggest a pattern of complex dysfunctional network signatures of critical forebrain regions in schizophrenia. Evidence of dysfunctional frontal-medial temporal lobe network signatures in schizophrenia is consistent with the illness' characterization as a disconnection syndrome. PMID:27092063

  1. Network Profiles of the Dorsal Anterior Cingulate and Dorsal Prefrontal Cortex in Schizophrenia During Hippocampal-Based Associative Memory

    PubMed Central

    Woodcock, Eric A.; Wadehra, Sunali; Diwadkar, Vaibhav A.

    2016-01-01

    Schizophrenia is a disorder characterized by brain network dysfunction, particularly during behavioral tasks that depend on frontal and hippocampal mechanisms. Here, we investigated network profiles of the regions of the frontal cortex during memory encoding and retrieval, phases of processing essential to associative memory. Schizophrenia patients (n = 12) and healthy control (HC) subjects (n = 10) participated in an established object-location associative memory paradigm that drives frontal-hippocampal interactions. Network profiles were modeled of both the dorsal prefrontal (dPFC) and the dorsal anterior cingulate cortex (dACC) as seeds using psychophysiological interaction analyses, a robust framework for investigating seed-based connectivity in specific task contexts. The choice of seeds was motivated by previous evidence of involvement of these regions during associative memory. Differences between patients and controls were evaluated using second-level analyses of variance (ANOVA) with seed (dPFC vs. dACC), group (patients vs. controls), and memory process (encoding and retrieval) as factors. Patients showed a pattern of exaggerated modulation by each of the dACC and the dPFC during memory encoding and retrieval. Furthermore, group by memory process interactions were observed within regions of the hippocampus. In schizophrenia patients, relatively diminished modulation during encoding was associated with increased modulation during retrieval. These results suggest a pattern of complex dysfunctional network signatures of critical forebrain regions in schizophrenia. Evidence of dysfunctional frontal-medial temporal lobe network signatures in schizophrenia is consistent with the illness’ characterization as a disconnection syndrome. PMID:27092063

  2. Impact of symmetry breaking in networks of globally coupled oscillators

    NASA Astrophysics Data System (ADS)

    Premalatha, K.; Chandrasekar, V. K.; Senthilvelan, M.; Lakshmanan, M.

    2015-05-01

    We analyze the consequences of symmetry breaking in the coupling in a network of globally coupled identical Stuart-Landau oscillators. We observe that symmetry breaking leads to increased disorderliness in the dynamical behavior of oscillatory states and consequently results in a rich variety of dynamical states. Depending on the strength of the nonisochronicity parameter, we find various dynamical states such as amplitude chimera, amplitude cluster, frequency chimera, and frequency cluster states. In addition we also find disparate transition routes to recently observed chimera death states in the presence of symmetry breaking even with global coupling. We also analytically verify the chimera death region, which corroborates the numerical results. These results are compared with that of the symmetry-preserving case as well.

  3. Synchronization and spatiotemporal patterns in coupled phase oscillators on a weighted planar network

    NASA Astrophysics Data System (ADS)

    Kagawa, Yuki; Takamatsu, Atsuko

    2009-04-01

    To reveal the relation between network structures found in two-dimensional biological systems, such as protoplasmic tube networks in the plasmodium of true slime mold, and spatiotemporal oscillation patterns emerged on the networks, we constructed coupled phase oscillators on weighted planar networks and investigated their dynamics. Results showed that the distribution of edge weights in the networks strongly affects (i) the propensity for global synchronization and (ii) emerging ratios of oscillation patterns, such as traveling and concentric waves, even if the total weight is fixed. In-phase locking, traveling wave, and concentric wave patterns were, respectively, observed most frequently in uniformly weighted, center weighted treelike, and periphery weighted ring-shaped networks. Controlling the global spatiotemporal patterns with the weight distribution given by the local weighting (coupling) rules might be useful in biological network systems including the plasmodial networks and neural networks in the brain.

  4. A Data Gathering Scheme in Wireless Sensor Networks Based on Synchronization of Chaotic Spiking Oscillator Networks

    SciTech Connect

    Nakano, Hidehiro; Utani, Akihide; Miyauchi, Arata; Yamamoto, Hisao

    2011-04-19

    This paper studies chaos-based data gathering scheme in multiple sink wireless sensor networks. In the proposed scheme, each wireless sensor node has a simple chaotic oscillator. The oscillators generate spike signals with chaotic interspike intervals, and are impulsively coupled by the signals via wireless communication. Each wireless sensor node transmits and receives sensor information only in the timing of the couplings. The proposed scheme can exhibit various chaos synchronous phenomena and their breakdown phenomena, and can effectively gather sensor information with the significantly small number of transmissions and receptions compared with the conventional scheme. Also, the proposed scheme can flexibly adapt various wireless sensor networks not only with a single sink node but also with multiple sink nodes. This paper introduces our previous works. Through simulation experiments, we show effectiveness of the proposed scheme and discuss its development potential.

  5. GABAB receptor deficiency causes failure of neuronal homeostasis in hippocampal networks.

    PubMed

    Vertkin, Irena; Styr, Boaz; Slomowitz, Edden; Ofir, Nir; Shapira, Ilana; Berner, David; Fedorova, Tatiana; Laviv, Tal; Barak-Broner, Noa; Greitzer-Antes, Dafna; Gassmann, Martin; Bettler, Bernhard; Lotan, Ilana; Slutsky, Inna

    2015-06-23

    Stabilization of neuronal activity by homeostatic control systems is fundamental for proper functioning of neural circuits. Failure in neuronal homeostasis has been hypothesized to underlie common pathophysiological mechanisms in a variety of brain disorders. However, the key molecules regulating homeostasis in central mammalian neural circuits remain obscure. Here, we show that selective inactivation of GABAB, but not GABA(A), receptors impairs firing rate homeostasis by disrupting synaptic homeostatic plasticity in hippocampal networks. Pharmacological GABA(B) receptor (GABA(B)R) blockade or genetic deletion of the GB(1a) receptor subunit disrupts homeostatic regulation of synaptic vesicle release. GABA(B)Rs mediate adaptive presynaptic enhancement to neuronal inactivity by two principle mechanisms: First, neuronal silencing promotes syntaxin-1 switch from a closed to an open conformation to accelerate soluble N-ethylmaleimide-sensitive factor attachment protein receptor (SNARE) complex assembly, and second, it boosts spike-evoked presynaptic calcium flux. In both cases, neuronal inactivity removes tonic block imposed by the presynaptic, GB(1a)-containing receptors on syntaxin-1 opening and calcium entry to enhance probability of vesicle fusion. We identified the GB(1a) intracellular domain essential for the presynaptic homeostatic response by tuning intermolecular interactions among the receptor, syntaxin-1, and the Ca(V)2.2 channel. The presynaptic adaptations were accompanied by scaling of excitatory quantal amplitude via the postsynaptic, GB(1b)-containing receptors. Thus, GABA(B)Rs sense chronic perturbations in GABA levels and transduce it to homeostatic changes in synaptic strength. Our results reveal a novel role for GABA(B)R as a key regulator of population firing stability and propose that disruption of homeostatic synaptic plasticity may underlie seizure's persistence in the absence of functional GABA(B)Rs. PMID:26056260

  6. GABAB receptor deficiency causes failure of neuronal homeostasis in hippocampal networks

    PubMed Central

    Vertkin, Irena; Styr, Boaz; Slomowitz, Edden; Ofir, Nir; Shapira, Ilana; Berner, David; Fedorova, Tatiana; Laviv, Tal; Barak-Broner, Noa; Greitzer-Antes, Dafna; Gassmann, Martin; Bettler, Bernhard; Lotan, Ilana; Slutsky, Inna

    2015-01-01

    Stabilization of neuronal activity by homeostatic control systems is fundamental for proper functioning of neural circuits. Failure in neuronal homeostasis has been hypothesized to underlie common pathophysiological mechanisms in a variety of brain disorders. However, the key molecules regulating homeostasis in central mammalian neural circuits remain obscure. Here, we show that selective inactivation of GABAB, but not GABAA, receptors impairs firing rate homeostasis by disrupting synaptic homeostatic plasticity in hippocampal networks. Pharmacological GABAB receptor (GABABR) blockade or genetic deletion of the GB1a receptor subunit disrupts homeostatic regulation of synaptic vesicle release. GABABRs mediate adaptive presynaptic enhancement to neuronal inactivity by two principle mechanisms: First, neuronal silencing promotes syntaxin-1 switch from a closed to an open conformation to accelerate soluble N-ethylmaleimide-sensitive factor attachment protein receptor (SNARE) complex assembly, and second, it boosts spike-evoked presynaptic calcium flux. In both cases, neuronal inactivity removes tonic block imposed by the presynaptic, GB1a-containing receptors on syntaxin-1 opening and calcium entry to enhance probability of vesicle fusion. We identified the GB1a intracellular domain essential for the presynaptic homeostatic response by tuning intermolecular interactions among the receptor, syntaxin-1, and the CaV2.2 channel. The presynaptic adaptations were accompanied by scaling of excitatory quantal amplitude via the postsynaptic, GB1b-containing receptors. Thus, GABABRs sense chronic perturbations in GABA levels and transduce it to homeostatic changes in synaptic strength. Our results reveal a novel role for GABABR as a key regulator of population firing stability and propose that disruption of homeostatic synaptic plasticity may underlie seizure's persistence in the absence of functional GABABRs. PMID:26056260

  7. Good vibrations switch attention: an affective function for network oscillations in evolutionary simulations.

    PubMed

    Heerebout, Bram T; Phaf, R Hans

    2010-05-01

    In the present study, a new hypothesis on the neural mechanisms linking affect to attention was brought forward by evolutionary simulations on agents navigating a virtual environment while collecting food and avoiding predation. The connection strengths between nodes in the networks controlling the agents were subjected to random variation, and the fittest agents were selected for reproduction. Unexpectedly, oscillations of node activations emerged, which drastically enhanced the agent's fitness. We analyzed the mechanisms involved in the modulation of attention and found that oscillations acted on competitive networks. Response selection depended on the connection structure, but the speed and efficacy of switching between selections was modulated by oscillation frequency. The main focus of the present study was the differential emergence of stimulus-specific oscillation frequencies. Oscillations had a higher frequency in an appetitive motivational state than in an aversive state. We suggest that oscillations in biological networks also mediate the affective modulation of attention. PMID:20498346

  8. Chimera states in networks of phase oscillators: The case of two small populations

    NASA Astrophysics Data System (ADS)

    Panaggio, Mark J.; Abrams, Daniel M.; Ashwin, Peter; Laing, Carlo R.

    2016-01-01

    Chimera states are dynamical patterns in networks of coupled oscillators in which regions of synchronous and asynchronous oscillation coexist. Although these states are typically observed in large ensembles of oscillators and analyzed in the continuum limit, chimeras may also occur in systems with finite (and small) numbers of oscillators. Focusing on networks of 2 N phase oscillators that are organized in two groups, we find that chimera states, corresponding to attracting periodic orbits, appear with as few as two oscillators per group and demonstrate that for N >2 the bifurcations that create them are analogous to those observed in the continuum limit. These findings suggest that chimeras, which bear striking similarities to dynamical patterns in nature, are observable and robust in small networks that are relevant to a variety of real-world systems.

  9. Does hyperbolicity impede emergence of chimera states in networks of nonlocally coupled chaotic oscillators?

    NASA Astrophysics Data System (ADS)

    Semenova, N.; Zakharova, A.; Schöll, E.; Anishchenko, V.

    2015-11-01

    We analyze nonlocally coupled networks of identical chaotic oscillators with either time-discrete or time-continuous dynamics (Henon map, Lozi map, Lorenz system). We hypothesize that chimera states, in which spatial domains of coherent (synchronous) and incoherent (desynchronized) dynamics coexist, can be obtained only in networks of oscillators with nonhyperbolic chaotic attractors and cannot be found in networks of systems with hyperbolic chaotic attractors. This hypothesis is supported by analytical results and numerical simulations for hyperbolic and nonhyperbolic cases.

  10. Local Optogenetic Induction of Fast (20–40 Hz) Pyramidal-Interneuron Network Oscillations in the In Vitro and In Vivo CA1 Hippocampus: Modulation by CRF and Enforcement of Perirhinal Theta Activity

    PubMed Central

    Dine, Julien; Genewsky, Andreas; Hladky, Florian; Wotjak, Carsten T.; Deussing, Jan M.; Zieglgänsberger, Walter; Chen, Alon; Eder, Matthias

    2016-01-01

    The neurophysiological processes that can cause theta-to-gamma frequency range (4–80 Hz) network oscillations in the rhinal cortical-hippocampal system and the potential connectivity-based interactions of such forebrain rhythms are a topic of intensive investigation. Here, using selective Channelrhodopsin-2 (ChR2) expression in mouse forebrain glutamatergic cells, we were able to locally, temporally precisely, and reliably induce fast (20–40 Hz) field potential oscillations in hippocampal area CA1 in vitro (at 25°C) and in vivo (i.e., slightly anesthetized NEX-Cre-ChR2 mice). As revealed by pharmacological analyses and patch-clamp recordings from pyramidal cells and GABAergic interneurons in vitro, these light-triggered oscillations can exclusively arise from sustained suprathreshold depolarization (~200 ms or longer) and feedback inhibition of CA1 pyramidal neurons, as being mandatory for prototypic pyramidal-interneuron network (P-I) oscillations. Consistently, the oscillations comprised rhythmically occurring population spikes (generated by pyramidal cells) and their frequency increased with increasing spectral power. We further demonstrate that the optogenetically driven CA1 oscillations, which remain stable over repeated evocations, are impaired by the stress hormone corticotropin-releasing factor (CRF, 125 nM) in vitro and, even more remarkably, found that they are accompanied by concurrent states of enforced theta activity in the memory-associated perirhinal cortex (PrC) in vivo. The latter phenomenon most likely derives from neurotransmission via a known, but poorly studied excitatory CA1→PrC pathway. Collectively, our data provide evidence for the existence of a prototypic (CRF-sensitive) P-I gamma rhythm generator in area CA1 and suggest that CA1 P-I oscillations can rapidly up-regulate theta activity strength in hippocampus-innervated rhinal networks, at least in the PrC. PMID:27199662

  11. Local Optogenetic Induction of Fast (20-40 Hz) Pyramidal-Interneuron Network Oscillations in the In Vitro and In Vivo CA1 Hippocampus: Modulation by CRF and Enforcement of Perirhinal Theta Activity.

    PubMed

    Dine, Julien; Genewsky, Andreas; Hladky, Florian; Wotjak, Carsten T; Deussing, Jan M; Zieglgänsberger, Walter; Chen, Alon; Eder, Matthias

    2016-01-01

    The neurophysiological processes that can cause theta-to-gamma frequency range (4-80 Hz) network oscillations in the rhinal cortical-hippocampal system and the potential connectivity-based interactions of such forebrain rhythms are a topic of intensive investigation. Here, using selective Channelrhodopsin-2 (ChR2) expression in mouse forebrain glutamatergic cells, we were able to locally, temporally precisely, and reliably induce fast (20-40 Hz) field potential oscillations in hippocampal area CA1 in vitro (at 25°C) and in vivo (i.e., slightly anesthetized NEX-Cre-ChR2 mice). As revealed by pharmacological analyses and patch-clamp recordings from pyramidal cells and GABAergic interneurons in vitro, these light-triggered oscillations can exclusively arise from sustained suprathreshold depolarization (~200 ms or longer) and feedback inhibition of CA1 pyramidal neurons, as being mandatory for prototypic pyramidal-interneuron network (P-I) oscillations. Consistently, the oscillations comprised rhythmically occurring population spikes (generated by pyramidal cells) and their frequency increased with increasing spectral power. We further demonstrate that the optogenetically driven CA1 oscillations, which remain stable over repeated evocations, are impaired by the stress hormone corticotropin-releasing factor (CRF, 125 nM) in vitro and, even more remarkably, found that they are accompanied by concurrent states of enforced theta activity in the memory-associated perirhinal cortex (PrC) in vivo. The latter phenomenon most likely derives from neurotransmission via a known, but poorly studied excitatory CA1→PrC pathway. Collectively, our data provide evidence for the existence of a prototypic (CRF-sensitive) P-I gamma rhythm generator in area CA1 and suggest that CA1 P-I oscillations can rapidly up-regulate theta activity strength in hippocampus-innervated rhinal networks, at least in the PrC. PMID:27199662

  12. Taxonomic Separation of Hippocampal Networks: Principal Cell Populations and Adult Neurogenesis.

    PubMed

    van Dijk, R Maarten; Huang, Shih-Hui; Slomianka, Lutz; Amrein, Irmgard

    2016-01-01

    While many differences in hippocampal anatomy have been described between species, it is typically not clear if they are specific to a particular species and related to functional requirements or if they are shared by species of larger taxonomic units. Without such information, it is difficult to infer how anatomical differences may impact on hippocampal function, because multiple taxonomic levels need to be considered to associate behavioral and anatomical changes. To provide information on anatomical changes within and across taxonomic ranks, we present a quantitative assessment of hippocampal principal cell populations in 20 species or strain groups, with emphasis on rodents, the taxonomic group that provides most animals used in laboratory research. Of special interest is the importance of adult hippocampal neurogenesis (AHN) in species-specific adaptations relative to other cell populations. Correspondence analysis of cell numbers shows that across taxonomic units, phylogenetically related species cluster together, sharing similar proportions of principal cell populations. CA3 and hilus are strong separators that place rodent species into a tight cluster based on their relatively large CA3 and small hilus while non-rodent species (including humans and non-human primates) are placed on the opposite side of the spectrum. Hilus and CA3 are also separators within rodents, with a very large CA3 and rather small hilar cell populations separating mole-rats from other rodents that, in turn, are separated from each other by smaller changes in the proportions of CA1 and granule cells. When adult neurogenesis is included, the relatively small populations of young neurons, proliferating cells and hilar neurons become main drivers of taxonomic separation within rodents. The observations provide challenges to the computational modeling of hippocampal function, suggest differences in the organization of hippocampal information streams in rodent and non-rodent species, and

  13. Taxonomic Separation of Hippocampal Networks: Principal Cell Populations and Adult Neurogenesis

    PubMed Central

    van Dijk, R. Maarten; Huang, Shih-Hui; Slomianka, Lutz; Amrein, Irmgard

    2016-01-01

    While many differences in hippocampal anatomy have been described between species, it is typically not clear if they are specific to a particular species and related to functional requirements or if they are shared by species of larger taxonomic units. Without such information, it is difficult to infer how anatomical differences may impact on hippocampal function, because multiple taxonomic levels need to be considered to associate behavioral and anatomical changes. To provide information on anatomical changes within and across taxonomic ranks, we present a quantitative assessment of hippocampal principal cell populations in 20 species or strain groups, with emphasis on rodents, the taxonomic group that provides most animals used in laboratory research. Of special interest is the importance of adult hippocampal neurogenesis (AHN) in species-specific adaptations relative to other cell populations. Correspondence analysis of cell numbers shows that across taxonomic units, phylogenetically related species cluster together, sharing similar proportions of principal cell populations. CA3 and hilus are strong separators that place rodent species into a tight cluster based on their relatively large CA3 and small hilus while non-rodent species (including humans and non-human primates) are placed on the opposite side of the spectrum. Hilus and CA3 are also separators within rodents, with a very large CA3 and rather small hilar cell populations separating mole-rats from other rodents that, in turn, are separated from each other by smaller changes in the proportions of CA1 and granule cells. When adult neurogenesis is included, the relatively small populations of young neurons, proliferating cells and hilar neurons become main drivers of taxonomic separation within rodents. The observations provide challenges to the computational modeling of hippocampal function, suggest differences in the organization of hippocampal information streams in rodent and non-rodent species, and

  14. Rapid throughput analysis demonstrates that chemicals with distinct seizurogenic mechanisms differentially alter Ca2+ dynamics in networks formed by hippocampal neurons in culture.

    PubMed

    Cao, Zhengyu; Zou, Xiaohan; Cui, Yanjun; Hulsizer, Susan; Lein, Pamela J; Wulff, Heike; Pessah, Isaac N

    2015-04-01

    Primary cultured hippocampal neurons (HN) form functional networks displaying synchronous Ca(2+) oscillations (SCOs) whose patterns influence plasticity. Whether chemicals with distinct seizurogenic mechanisms differentially alter SCO patterns was investigated using mouse HN loaded with the Ca(2+) indicator fluo-4-AM. Intracellular Ca(2+) dynamics were recorded from 96 wells simultaneously in real-time using fluorescent imaging plate reader. Although quiescent at 4 days in vitro (DIV), HN acquired distinctive SCO patterns as they matured to form extensive dendritic networks by 16 DIV. Challenge with kainate, a kainate receptor (KAR) agonist, 4-aminopyridine (4-AP), a K(+) channel blocker, or pilocarpine, a muscarinic acetylcholine receptor agonist, caused distinct changes in SCO dynamics. Kainate at <1 µM produced a rapid rise in baseline Ca(2+) (Phase I response) associated with high-frequency and low-amplitude SCOs (Phase II response), whereas SCOs were completely repressed with >1 µM kainate. KAR competitive antagonist CNQX [6-cyano-7-nitroquinoxaline-2,3-dione] (1-10 µM) normalized Ca(2+) dynamics to the prekainate pattern. Pilocarpine lacked Phase I activity but caused a sevenfold prolongation of Phase II SCOs without altering either their frequency or amplitude, an effect normalized by atropine (0.3-1 µM). 4-AP (1-30 µM) elicited a delayed Phase I response associated with persistent high-frequency, low-amplitude SCOs, and these disturbances were mitigated by pretreatment with the KCa activator SKA-31 [naphtho[1,2-d]thiazol-2-ylamine]. Consistent with its antiepileptic and neuroprotective activities, nonselective voltage-gated Na(+) and Ca(2+) channel blocker lamotrigine partially resolved kainate- and pilocarpine-induced Ca(2+) dysregulation. This rapid throughput approach can discriminate among distinct seizurogenic mechanisms that alter Ca(2+) dynamics in neuronal networks and may be useful in screening antiepileptic drug candidates. PMID:25583085

  15. Excitation of Oscillations in the Magnetic Network on the Sun.

    PubMed

    Hasan; Kalkofen; van Ballegooijen AA

    2000-05-20

    We examine the excitation of oscillations in the magnetic network of the Sun through the footpoint motion of photospheric magnetic flux tubes located in intergranular lanes. The motion is derived from a time series of high-resolution G-band and continuum filtergrams using an object-tracking technique. We model the response of the flux tube to the footpoint motion in terms of the Klein-Gordon equation, which is solved analytically as an initial value problem for transverse (kink) waves. We compute the wave energy flux in upward-propagating transverse waves. In general we find that the injection of energy into the chromosphere occurs in short-duration pulses, which would lead to a time variability in chromospheric emission that is incompatible with observations. Therefore, we consider the effects of turbulent convective flows on flux tubes in intergranular lanes. The turbulent flows are simulated by adding high-frequency motions (periods 5-50 s) with an amplitude of 1 km s(-1). The latter are simulated by adding random velocity fluctuations to the observationally determined velocities. In this case, we find that the energy flux is much less intermittent and can in principle carry adequate energy for chromospheric heating. PMID:10829010

  16. Log-periodic oscillations due to discrete effects in complex networks

    NASA Astrophysics Data System (ADS)

    Sienkiewicz, Julian; Fronczak, Piotr; Hołyst, Janusz A.

    2007-06-01

    We show how discretization affects two major characteristics in complex networks: internode distances (measured as the shortest number of edges between network sites) and average path length, and as a result there are log-periodic oscillations of the above quantities. The effect occurs both in numerical network models as well as in such real systems as coauthorship, language, food, and public transport networks. Analytical description of these oscillations fits well numerical simulations. We consider a simple case of the network optimization problem, arguing that discrete effects can lead to a nontrivial solution.

  17. Oscillations emerging from noise-driven steady state in networks with electrical synapses and subthreshold resonance

    PubMed Central

    Tchumatchenko, Tatjana; Clopath, Claudia

    2014-01-01

    Oscillations play a critical role in cognitive phenomena and have been observed in many brain regions. Experimental evidence indicates that classes of neurons exhibit properties that could promote oscillations, such as subthreshold resonance and electrical gap junctions. Typically, these two properties are studied separately but it is not clear which is the dominant determinant of global network rhythms. Our aim is to provide an analytical understanding of how these two effects destabilize the fluctuation-driven state, in which neurons fire irregularly, and lead to an emergence of global synchronous oscillations. Here we show how the oscillation frequency is shaped by single neuron resonance, electrical and chemical synapses.The presence of both gap junctions and subthreshold resonance are necessary for the emergence of oscillations. Our results are in agreement with several experimental observations such as network responses to oscillatory inputs and offer a much-needed conceptual link connecting a collection of disparate effects observed in networks. PMID:25405458

  18. Coherent and intermittent ensemble oscillations emerge from networks of irregular spiking neurons.

    PubMed

    Hoseini, Mahmood S; Wessel, Ralf

    2016-01-01

    Local field potential (LFP) recordings from spatially distant cortical circuits reveal episodes of coherent gamma oscillations that are intermittent, and of variable peak frequency and duration. Concurrently, single neuron spiking remains largely irregular and of low rate. The underlying potential mechanisms of this emergent network activity have long been debated. Here we reproduce such intermittent ensemble oscillations in a model network, consisting of excitatory and inhibitory model neurons with the characteristics of regular-spiking (RS) pyramidal neurons, and fast-spiking (FS) and low-threshold spiking (LTS) interneurons. We find that fluctuations in the external inputs trigger reciprocally connected and irregularly spiking RS and FS neurons in episodes of ensemble oscillations, which are terminated by the recruitment of the LTS population with concurrent accumulation of inhibitory conductance in both RS and FS neurons. The model qualitatively reproduces experimentally observed phase drift, oscillation episode duration distributions, variation in the peak frequency, and the concurrent irregular single-neuron spiking at low rate. Furthermore, consistent with previous experimental studies using optogenetic manipulation, periodic activation of FS, but not RS, model neurons causes enhancement of gamma oscillations. In addition, increasing the coupling between two model networks from low to high reveals a transition from independent intermittent oscillations to coherent intermittent oscillations. In conclusion, the model network suggests biologically plausible mechanisms for the generation of episodes of coherent intermittent ensemble oscillations with irregular spiking neurons in cortical circuits. PMID:26561602

  19. Nocturnal Mnemonics: Sleep and Hippocampal Memory Processing

    PubMed Central

    Saletin, Jared M.; Walker, Matthew P.

    2012-01-01

    As critical as waking brain function is to learning and memory, an established literature now describes an equally important yet complementary role for sleep in information processing. This overview examines the specific contribution of sleep to human hippocampal memory processing; both the detriments caused by a lack of sleep, and conversely, the proactive benefits that develop following the presence of sleep. First, a role for sleep before learning is discussed, preparing the hippocampus for initial memory encoding. Second, a role for sleep after learning is considered, modulating the post-encoding consolidation of hippocampal-dependent memory. Third, a model is outlined in which these encoding and consolidation operations are symbiotically accomplished, associated with specific NREM sleep physiological oscillations. As a result, the optimal network outcome is achieved: increasing hippocampal independence and hence overnight consolidation, while restoring next-day sparse hippocampal encoding capacity for renewed learning ability upon awakening. Finally, emerging evidence is considered suggesting that, unlike previous conceptions, sleep does not universally consolidate all information. Instead, and based on explicit as well as saliency cues during initial encoding, sleep executes the discriminatory offline consolidation only of select information. Consequently, sleep promotes the targeted strengthening of some memories while actively forgetting others; a proposal with significant theoretical and clinical ramifications. PMID:22557988

  20. Theta phase shift in spike timing and modulation of gamma oscillation: a dynamic code for spatial alternation during fixation in rat hippocampal area CA1

    PubMed Central

    Nishida, Hiroshi; David Redish, A.; Lauwereyns, Johan

    2014-01-01

    Although hippocampus is thought to perform various memory-related functions, little is known about the underlying dynamics of neural activity during a preparatory stage before a spatial choice. Here we focus on neural activity that reflects a memory-based code for spatial alternation, independent of current sensory and motor parameters. We recorded multiple single units and local field potentials in the stratum pyramidale of dorsal hippocampal area CA1 while rats performed a delayed spatial-alternation task. This task includes a 1-s fixation in a nose-poke port between selecting alternating reward sites and so provides time-locked enter-and-leave events. At the single-unit level, we concentrated on neurons that were specifically active during the 1-s fixation period, when the rat was ready and waiting for a cue to pursue the task. These neurons showed selective activity as a function of the alternation sequence. We observed a marked shift in the phase timing of the neuronal spikes relative to the theta oscillation, from the theta peak at the beginning of fixation to the theta trough at the end of fixation. The gamma-band local field potential also changed during the fixation period: the high-gamma power (60–90 Hz) decreased and the low-gamma power (30–45 Hz) increased toward the end. These two gamma components were observed at different phases of the ongoing theta oscillation. Taken together, our data suggest a switch in the type of information processing through the fixation period, from externally cued to internally generated. PMID:24478159

  1. Seizure-induced alterations in fast-spiking basket cell GABA currents modulate frequency and coherence of gamma oscillation in network simulations

    NASA Astrophysics Data System (ADS)

    Proddutur, Archana; Yu, Jiandong; Elgammal, Fatima S.; Santhakumar, Vijayalakshmi

    2013-12-01

    Gamma frequency oscillations have been proposed to contribute to memory formation and retrieval. Fast-spiking basket cells (FS-BCs) are known to underlie development of gamma oscillations. Fast, high amplitude GABA synapses and gap junctions have been suggested to contribute to gamma oscillations in FS-BC networks. Recently, we identified that, apart from GABAergic synapses, FS-BCs in the hippocampal dentate gyrus have GABAergic currents mediated by extrasynaptic receptors. Our experimental studies demonstrated two specific changes in FS-BC GABA currents following experimental seizures [Yu et al., J. Neurophysiol. 109, 1746 (2013)]: increase in the magnitude of extrasynaptic (tonic) GABA currents and a depolarizing shift in GABA reversal potential (EGABA). Here, we use homogeneous networks of a biophysically based model of FS-BCs to examine how the presence of extrasynaptic GABA conductance (gGABA-extra) and experimentally identified, seizure-induced changes in gGABA-extra and EGABA influence network activity. Networks of FS-BCs interconnected by fast GABAergic synapses developed synchronous firing in the dentate gamma frequency range (40-100 Hz). Systematic investigation revealed that the biologically realistic range of 30 to 40 connections between FS-BCs resulted in greater coherence in the gamma frequency range when networks were activated by Poisson-distributed dendritic synaptic inputs rather than by homogeneous somatic current injections, which were balanced for FS-BC firing frequency in unconnected networks. Distance-dependent conduction delay enhanced coherence in networks with 30-40 FS-BC interconnections while inclusion of gap junctional conductance had a modest effect on coherence. In networks activated by somatic current injections resulting in heterogeneous FS-BC firing, increasing gGABA-extra reduced the frequency and coherence of FS-BC firing when EGABA was shunting (-74 mV), but failed to alter average FS-BC frequency when EGABA was depolarizing

  2. Seizure-induced alterations in fast-spiking basket cell GABA currents modulate frequency and coherence of gamma oscillation in network simulations

    SciTech Connect

    Proddutur, Archana; Yu, Jiandong; Elgammal, Fatima S.; Santhakumar, Vijayalakshmi

    2013-12-15

    Gamma frequency oscillations have been proposed to contribute to memory formation and retrieval. Fast-spiking basket cells (FS-BCs) are known to underlie development of gamma oscillations. Fast, high amplitude GABA synapses and gap junctions have been suggested to contribute to gamma oscillations in FS-BC networks. Recently, we identified that, apart from GABAergic synapses, FS-BCs in the hippocampal dentate gyrus have GABAergic currents mediated by extrasynaptic receptors. Our experimental studies demonstrated two specific changes in FS-BC GABA currents following experimental seizures [Yu et al., J. Neurophysiol. 109, 1746 (2013)]: increase in the magnitude of extrasynaptic (tonic) GABA currents and a depolarizing shift in GABA reversal potential (E{sub GABA}). Here, we use homogeneous networks of a biophysically based model of FS-BCs to examine how the presence of extrasynaptic GABA conductance (g{sub GABA-extra}) and experimentally identified, seizure-induced changes in g{sub GABA-extra} and E{sub GABA} influence network activity. Networks of FS-BCs interconnected by fast GABAergic synapses developed synchronous firing in the dentate gamma frequency range (40–100 Hz). Systematic investigation revealed that the biologically realistic range of 30 to 40 connections between FS-BCs resulted in greater coherence in the gamma frequency range when networks were activated by Poisson-distributed dendritic synaptic inputs rather than by homogeneous somatic current injections, which were balanced for FS-BC firing frequency in unconnected networks. Distance-dependent conduction delay enhanced coherence in networks with 30–40 FS-BC interconnections while inclusion of gap junctional conductance had a modest effect on coherence. In networks activated by somatic current injections resulting in heterogeneous FS-BC firing, increasing g{sub GABA-extra} reduced the frequency and coherence of FS-BC firing when E{sub GABA} was shunting (−74 mV), but failed to alter average

  3. Effects of immunity on global oscillations in epidemic spreading in small-world networks

    NASA Astrophysics Data System (ADS)

    Gao, Ke; Hua, Da-yin

    2010-08-01

    Considering a decay of an individual immunity, we investigated a susceptible-infectedrefractory-susceptible (SIRS) model in Watts-Strogatz (WS) small-word networks. It is found that when an individual immunity does not change or decays slowly in an immune period, the system can exhibit a transition from a stationary state to a large amplitude sustained oscillation. When the immunity decays rapidly in the immune period, the transition disappears and there is no oscillation. Furthermore, based on the spatio-temporal evolution patterns, it is disclosed that a long immunity period takes an important role in the emergence of the global oscillation in small world networks.

  4. Rapid increase of spines by dihydrotestosterone and testosterone in hippocampal neurons: Dependence on synaptic androgen receptor and kinase networks.

    PubMed

    Hatanaka, Yusuke; Hojo, Yasushi; Mukai, Hideo; Murakami, Gen; Komatsuzaki, Yoshimasa; Kim, Jonghyuk; Ikeda, Muneki; Hiragushi, Ayako; Kimoto, Tetsuya; Kawato, Suguru

    2015-09-24

    Rapid modulation of hippocampal synaptic plasticity by locally synthesized androgen is important in addition to circulating androgen. Here, we investigated the rapid changes of dendritic spines in response to the elevation of dihydrotestosterone (DHT) and testosterone (T), by using hippocampal slices from adult male rats, in order to clarify whether these signaling processes include synaptic/extranuclear androgen receptor (AR) and activation of kinases. We found that the application of 10nM DHT and 10nM T increased the total density of spines by approximately 1.3-fold within 2h, by imaging Lucifer Yellow-injected CA1 pyramidal neurons. Interestingly, DHT and T increased different head-sized spines. While DHT increased middle- and large-head spines, T increased small-head spines. Androgen-induced spinogenesis was suppressed by individually blocking Erk MAPK, PKA, PKC, p38 MAPK, LIMK or calcineurin. On the other hand, blocking CaMKII did not inhibit spinogenesis. Blocking PI3K altered the spine head diameter distribution, but did not change the total spine density. Blocking mRNA and protein synthesis did not suppress the enhancing effects induced by DHT or T. The enhanced spinogenesis by androgens was blocked by AR antagonist, which AR was localized postsynaptically. Taken together, these results imply that enhanced spinogenesis by DHT and T is mediated by synaptic/extranuclear AR which rapidly drives the kinase networks. This article is part of a Special Issue entitled SI: Brain and Memory. PMID:25511993

  5. The role of topological features of intercellular communication networks by the synchronization of cellular oscillators

    NASA Astrophysics Data System (ADS)

    Markovič, R.; Gosak, M.; Marhl, M.

    2012-08-01

    Because of the complexity of processes that govern the regulatory mechanisms which control the cellular functions and dynamic behavior, mathematical models and numerical simulations are needed to fully grasp the mechanisms and functions of biological rhythms. In the last decade the theory of complex networks is frequently applied to address those issues. In the present paper we investigate theoretically the role of the intercellular communication network structure by synchronization of cellular oscillators. Motivated by the fact that in biological systems the interplay between the network structure and the dynamics taking place on it is closely interrelated, we develop a spatial network representation of an ensemble of cells in which we can tune the network organization between a scale-free network with dominating long-range connections and a homogeneous network with mostly adjacent neurons connected. Our results reveal that for noise-induced oscillations in excitable cells and for chaotic bursting oscillations the most synchronized response is obtained for the intermediate regime where long-as well as short-range connections constitute the intercellular network. On the other hand, for periodic oscillations it is found than the scale-free network topology ensures the greatest collective response. We argue that those findings are related to flexibility properties of individual cells.

  6. Bifurcations in phase oscillator networks with a central element

    NASA Astrophysics Data System (ADS)

    Burylko, Oleksandr; Kazanovich, Yakov; Borisyuk, Roman

    2012-06-01

    A system of phase oscillators with identical natural frequencies and the star-like architecture of connections is considered. Interaction functions are described by two terms of Fourier expansion. Bifurcation analysis of small systems containing 3 or 4 oscillators has been performed. The results are summarized in bifurcation diagrams that provide a full description of the boundaries between regions with different dynamics and the types of bifurcations that lead to the changes in the topology of phase space. The bifurcations include changes of fixed point stability and formation (destruction) of limit and heteroclinic cycles. For the system with 4 oscillators chaotic behaviour has been investigated. The results can be useful to control system dynamics through an appropriate choice and variation of parameter values. The generalization of the results to the systems with an arbitrary number of oscillators and application of the results in computational neuroscience are discussed.

  7. Phase relationships between segmentally organized oscillators in the leech heartbeat pattern generating network.

    PubMed

    Masino, Mark A; Calabrese, Ronald L

    2002-03-01

    Motor pattern generating networks that produce segmentally distributed motor outflow are often portrayed as a series of coupled segmental oscillators that produce a regular progression (constant phase differences) in their rhythmic activity. The leech heartbeat central pattern generator is paced by a core timing network, which consists of two coupled segmental oscillators in segmental ganglia 3 and 4. The segmental oscillators comprise paired mutually inhibitory oscillator interneurons and the processes of intersegmental coordinating interneurons. As a first step in understanding the coordination of segmental motor outflow by this pattern generator, we describe the functional synaptic interactions, and activity and phase relationships of the heart interneurons of the timing network, in isolated nerve cord preparations. In the timing network, most (approximately 75%) of the coordinating interneuron action potentials were generated at a primary spike initiation site located in ganglion 4 (G4). A secondary spike initiation site in ganglion 3 (G3) became active in the absence of activity at the primary site. Generally, the secondary site was characterized by a reluctance to burst and a lower spike frequency, when compared with the primary site. Oscillator interneurons in G3 inhibited spike activity at both initiation sites, whereas oscillator interneurons in G4 inhibited spike activity only at the primary initiation site. This asymmetry in the control of spike activity in the coordinating interneurons may account for the observation that the phase of the coordinating interneurons is more tightly linked to the G3 than G4 oscillator interneurons. The cycle period of the timing network and the phase difference between the ipsilateral G3 and G4 oscillator interneurons were regular within individual preparations, but varied among preparations. This variation in phase differences observed across preparations implies that modulated intrinsic membrane and synaptic properties

  8. Decreased functional connectivity in dorsolateral prefrontal cortical networks in adult macaques with neonatal hippocampal lesions: Relations to visual working memory deficits.

    PubMed

    Meng, Yuguang; Hu, Xiaoping; Bachevalier, Jocelyne; Zhang, Xiaodong

    2016-10-01

    Neonatal hippocampal lesions in monkeys impairs normal performance on both relational and working memory tasks, suggesting that the early lesions have impacted the normal development of prefrontal-hippocampal functional interactions necessary for normal performance on these tasks. Given that working memory processes engage distributed neuronal networks associated with the prefrontal cortex, it is critical to explore the integrity of distributed neural networks of dorsolateral prefrontal cortex (dlPFC) following neonatal hippocampal lesions in monkeys. We used resting-state functional MRI to assess functional connectivity of dlPFC networks in monkeys with neonatal neurotoxic hippocampal lesion (Neo-Hibo, n=4) and sham-operated control animals (Neo-C, n=4). Significant differences in the patterns of dlPFC functional networks were found between Groups Neo-Hibo and Neo-C. The within-group maps and the between-group comparisons yielded a highly coherent picture showing altered interactions of core regions of the working memory network (medial prefrontal cortex and posterior parietal cortex) as well as the dorsal (fundus of superior temporal area and superior temporal cortex) and ventral (V4 and infero-temporal cortex) visual processing areas in animals with Neo-Hibo lesions. Correlations between functional connectivity changes and working memory impairment in the same animals were found only between the dlPFC and visual cortical areas (V4 and infero-temporal cortex). Thus, the impact of the neonatal hippocampal lesions extends to multiple cortical areas interconnected with the dlPFC. PMID:27063864

  9. Strong effects of network architecture in the entrainment of coupled oscillator systems

    NASA Astrophysics Data System (ADS)

    Kori, Hiroshi; Mikhailov, Alexander S.

    2006-12-01

    Random networks of coupled phase oscillators, representing an approximation for systems of coupled limit-cycle oscillators, are considered. Entrainment of such networks by periodic external forcing applied to a subset of their elements is numerically and analytically investigated. For a large class of interaction functions, we find that the entrainment window with a tongue shape becomes exponentially narrow for networks with higher hierarchical organization. However, the entrainment is significantly facilitated if the networks are directionally biased—i.e., closer to the feedforward networks. Furthermore, we show that the networks with high entrainment ability can be constructed by evolutionary optimization processes. The neural network structure of the master clock of the circadian rhythm in mammals is discussed from the viewpoint of our results.

  10. Stimulus-evoked high frequency oscillations are present in neuronal networks on microelectrode arrays

    PubMed Central

    Hales, Chadwick M.; Zeller-Townson, Riley; Newman, Jonathan P.; Shoemaker, James T.; Killian, Nathan J.; Potter, Steve M.

    2012-01-01

    Pathological high frequency oscillations (250–600 Hz) are present in the brains of epileptic animals and humans. The etiology of these oscillations and how they contribute to the diseased state remains unclear. This work identifies the presence of microstimulation-evoked high frequency oscillations (250–400 Hz) in dissociated neuronal networks cultured on microelectrode arrays (MEAs). Oscillations are more apparent with higher stimulus voltages. As with in vivo studies, activity is isolated to a single electrode, however, the MEA provides improved spatial resolution with no spread of the oscillation to adjacent electrodes 200 μm away. Oscillations develop across four weeks in vitro. Oscillations still occur in the presence of tetrodotoxin and synaptic blockers, and they cause no apparent disruption in the ability of oscillation-presenting electrodes to elicit directly evoked action potentials (dAPs) or promote the spread of synaptic activity throughout the culture. Chelating calcium with ethylene glycol tetraacetic acid (EGTA) causes a temporal prolongation of the oscillation. Finally, carbenoxolone significantly reduces or eliminates the high frequency oscillations. Gap junctions may play a significant role in maintaining the oscillation given the inhibitory effect of carbenoxolone, the propagating effect of reduced calcium conditions and the isolated nature of the activity as demonstrated in previous studies. This is the first demonstration of stimulus-evoked high frequency oscillations in dissociated cultures. Unlike current models that rely on complex in vivo recording conditions, this work presents a simple controllable model in neuronal cultures on MEAs to further investigate how the oscillations occur at the molecular level and how they may contribute to the pathophysiology of disease. PMID:22615686

  11. Switching mechanism of sensor-motor coordination through an oscillator network model.

    PubMed

    Funato, Tetsuro; Kurabayashi, Daisuke; Nara, Masahito; Aonuma, Hitoshi

    2008-06-01

    Insects have small brains, but their behavior is highly adaptive; this leads us to conclude that their brains possess a simple adaptation mechanism. This paper focuses on the pheromone processing of crickets, varying their aggression depending on their global neural connection, and proposes a behavior selection mechanism that can be controlled by network transformation. The controller is composed of an oscillator network, and its behavior is decided by the synchrony of organic oscillations. Furthermore, every network component corresponds to a certain brain module. A model is realized by using an analog circuit, and it is applied to a simple robot that displays the behavior of a real insect. PMID:18558540

  12. Noise-assisted energy transport in electrical oscillator networks with off-diagonal dynamical disorder

    PubMed Central

    León-Montiel, Roberto de J.; Quiroz-Juárez, Mario A.; Quintero-Torres, Rafael; Domínguez-Juárez, Jorge L.; Moya-Cessa, Héctor M.; Torres, Juan P.; Aragón, José L.

    2015-01-01

    Noise is generally thought as detrimental for energy transport in coupled oscillator networks. However, it has been shown that for certain coherently evolving systems, the presence of noise can enhance, somehow unexpectedly, their transport efficiency; a phenomenon called environment-assisted quantum transport (ENAQT) or dephasing-assisted transport. Here, we report on the experimental observation of such effect in a network of coupled electrical oscillators. We demonstrate that by introducing stochastic fluctuations in one of the couplings of the network, a relative enhancement in the energy transport efficiency of 22.5 ± 3.6% can be observed. PMID:26610864

  13. Noise-assisted energy transport in electrical oscillator networks with off-diagonal dynamical disorder.

    PubMed

    León-Montiel, Roberto de J; Quiroz-Juárez, Mario A; Quintero-Torres, Rafael; Domínguez-Juárez, Jorge L; Moya-Cessa, Héctor M; Torres, Juan P; Aragón, José L

    2015-01-01

    Noise is generally thought as detrimental for energy transport in coupled oscillator networks. However, it has been shown that for certain coherently evolving systems, the presence of noise can enhance, somehow unexpectedly, their transport efficiency; a phenomenon called environment-assisted quantum transport (ENAQT) or dephasing-assisted transport. Here, we report on the experimental observation of such effect in a network of coupled electrical oscillators. We demonstrate that by introducing stochastic fluctuations in one of the couplings of the network, a relative enhancement in the energy transport efficiency of 22.5 ± 3.6% can be observed. PMID:26610864

  14. Large-Scale, High-Resolution Multielectrode-Array Recording Depicts Functional Network Differences of Cortical and Hippocampal Cultures

    PubMed Central

    Ito, Shinya; Yeh, Fang-Chin; Hiolski, Emma; Rydygier, Przemyslaw; Gunning, Deborah E.; Hottowy, Pawel; Timme, Nicholas; Litke, Alan M.; Beggs, John M.

    2014-01-01

    Understanding the detailed circuitry of functioning neuronal networks is one of the major goals of neuroscience. Recent improvements in neuronal recording techniques have made it possible to record the spiking activity from hundreds of neurons simultaneously with sub-millisecond temporal resolution. Here we used a 512-channel multielectrode array system to record the activity from hundreds of neurons in organotypic cultures of cortico-hippocampal brain slices from mice. To probe the network structure, we employed a wavelet transform of the cross-correlogram to categorize the functional connectivity in different frequency ranges. With this method we directly compare, for the first time, in any preparation, the neuronal network structures of cortex and hippocampus, on the scale of hundreds of neurons, with sub-millisecond time resolution. Among the three frequency ranges that we investigated, the lower two frequency ranges (gamma (30–80 Hz) and beta (12–30 Hz) range) showed similar network structure between cortex and hippocampus, but there were many significant differences between these structures in the high frequency range (100–1000 Hz). The high frequency networks in cortex showed short tailed degree-distributions, shorter decay length of connectivity density, smaller clustering coefficients, and positive assortativity. Our results suggest that our method can characterize frequency dependent differences of network architecture from different brain regions. Crucially, because these differences between brain regions require millisecond temporal scales to be observed and characterized, these results underscore the importance of high temporal resolution recordings for the understanding of functional networks in neuronal systems. PMID:25126851

  15. Rhythmic Oscillations of Excitatory Bursting Hodkin-Huxley Neuronal Network with Synaptic Learning

    PubMed Central

    Shi, Qi; Han, Fang; Wang, Zhijie; Li, Caiyun

    2016-01-01

    Rhythmic oscillations of neuronal network are actually kind of synchronous behaviors, which play an important role in neural systems. In this paper, the properties of excitement degree and oscillation frequency of excitatory bursting Hodkin-Huxley neuronal network which incorporates a synaptic learning rule are studied. The effects of coupling strength, synaptic learning rate, and other parameters of chemical synapses, such as synaptic delay and decay time constant, are explored, respectively. It is found that the increase of the coupling strength can weaken the extent of excitement, whereas increasing the synaptic learning rate makes the network more excited in a certain range; along with the increasing of the delay time and the decay time constant, the excitement degree increases at the beginning, then decreases, and keeps stable. It is also found that, along with the increase of the synaptic learning rate, the coupling strength, the delay time, and the decay time constant, the oscillation frequency of the network decreases monotonically. PMID:27073393

  16. Network oscillations of inferior olive neurons: entrainment and phase-locking of locally-coupled oscillators

    NASA Astrophysics Data System (ADS)

    Chartrand, Thomas; Goldman, Mark S.; Lewis, Timothy J.

    2015-03-01

    Although the inferior olive is known to contribute to the generation of timing and error signals for motor control, the specific role of its distinctive spatiotemporal activity patterns is still controversial. Olivary neurons display regular, sometimes synchronized oscillations of subthreshold membrane potential, driven in part by the highest density of electrical coupling of any brain region. We show that a reduced model of coupled phase oscillators is sufficient to reproduce and study experimental observations previously only demonstrated in more complex models. These include stable phase differences, variability of entrainment frequency, wave propagation, and cluster formation. Using the phase-response curve (PRC) of a conductance-based model of olivary neurons, we derive our phase model according to the theory of weakly-coupled oscillators. We retain the heterogeneity of intrinsic frequencies and heterogeneous, spatially constrained coupling as weak perturbations to the limit-cycle dynamics. Generalizing this model to an ensemble of coupled oscillator lattices with frequency and coupling disorder, we study the onset of entrainment and phase-locking as coupling is strengthened, including the scaling of cluster sizes with coupling strength near each phase transition.

  17. Alterations in cortical network oscillations and parvalbumin neurons in schizophrenia.

    PubMed

    Gonzalez-Burgos, Guillermo; Cho, Raymond Y; Lewis, David A

    2015-06-15

    Cognitive deficits are a core clinical feature of schizophrenia but respond poorly to available medications. Thus, understanding the neural basis of these deficits is crucial for the development of new therapeutic interventions. The types of cognitive processes affected in schizophrenia are thought to depend on the precisely timed transmission of information in cortical regions via synchronous oscillations at gamma band frequency. Here, we review 1) data from clinical studies suggesting that induction of frontal cortex gamma oscillations during tasks that engage cognitive or complex perceptual functions is attenuated in schizophrenia; 2) findings from basic neuroscience studies highlighting the features of parvalbumin-positive interneurons that are critical for gamma oscillation production; and 3) results from recent postmortem human brain studies providing additional molecular bases for parvalbumin-positive interneuron alterations in prefrontal cortical circuitry in schizophrenia. PMID:25863358

  18. Alterations in Cortical Network Oscillations and Parvalbumin Neurons in Schizophrenia

    PubMed Central

    Gonzalez-Burgos, Guillermo; Cho, Raymond Y; Lewis, David A

    2015-01-01

    Cognitive deficits are a core clinical feature of schizophrenia but respond poorly to available medications. Thus, understanding the neural basis of these deficits is crucial for the development of new therapeutic interventions. The types of cognitive processes affected in schizophrenia are thought to depend on the precisely timed transmission of information in cortical regions via synchronous oscillations at gamma band frequency. Here, we review 1) data from clinical studies suggesting that induction of frontal cortex gamma oscillations during tasks that engage cognitive or complex perceptual functions is attenuated in schizophrenia, 2) findings from basic neuroscience studies highlighting the features of parvalbumin-positive (PV) interneurons that are critical for gamma oscillation production and 3) results from recent postmortem human brain studies providing additional molecular bases for PV interneuron alterations in prefrontal cortical circuitry in schizophrenia. PMID:25863358

  19. Adding connections can hinder network synchronization of time-delayed oscillators

    NASA Astrophysics Data System (ADS)

    Hart, Joseph D.; Pade, Jan Philipp; Pereira, Tiago; Murphy, Thomas E.; Roy, Rajarshi

    2015-08-01

    We provide experimental evidence that adding links to a network's structure can hinder synchronization. Our experiments and theoretical analysis of networks of time-delayed optoelectronic oscillators uncover the scenario of loss of identical synchronization upon connectivity modifications. This counterintuitive loss of synchronization can occur even when the network structure is improved from a connectivity perspective. Utilizing a master stability function approach, we show that a time delay in the coupling of nodes plays a crucial role in determining a network's synchronization properties and that this effect is more prominent in directed networks than in undirected networks, especially for large networks. Our results provide insight into the impact of structural modifications in networks with equal coupling delays and open the path to design changes to the network connectivity to sustain and control the performance of real-world networks.

  20. Co-expression network-based analysis of hippocampal expression data associated with Alzheimer's disease using a novel algorithm

    PubMed Central

    YUE, HONG; YANG, BO; YANG, FANG; HU, XIAO-LI; KONG, FAN-BIN

    2016-01-01

    Recent progress in bioinformatics has facilitated the clarification of biological processes associated with complex diseases. Numerous methods of co-expression analysis have been proposed for use in the study of pairwise relationships among genes. In the present study, a combined network based on gene pairs was constructed following the conversion and combination of gene pair score values using a novel algorithm across multiple approaches. Three hippocampal expression profiles of patients with Alzheimer's disease (AD) and normal controls were extracted from the ArrayExpress database, and a total of 144 differentially expressed (DE) genes across multiple studies were identified by a rank product (RP) method. Five groups of co-expression gene pairs and five networks were identified and constructed using four existing methods [weighted gene co-expression network analysis (WGCNA), empirical Bayesian (EB), differentially co-expressed genes and links (DCGL), search tool for the retrieval of interacting genes/proteins database (STRING)] and a novel rank-based algorithm with combined score, respectively. Topological analysis indicated that the co-expression network constructed by the WGCNA method had the tendency to exhibit small-world characteristics, and the combined co-expression network was confirmed to be a scale-free network. Functional analysis of the co-expression gene pairs was conducted by Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. The co-expression gene pairs were mostly enriched in five pathways, namely proteasome, oxidative phosphorylation, Parkinson's disease, Huntington's disease and AD. This study provides a new perspective to co-expression analysis. Since different methods of analysis often present varying abilities, the novel combination algorithm may provide a more credible and robust outcome, and could be used to complement to traditional co-expression analysis. PMID:27168792

  1. Emergence of rich-club topology and coordinated dynamics in development of hippocampal functional networks in vitro.

    PubMed

    Schroeter, Manuel S; Charlesworth, Paul; Kitzbichler, Manfred G; Paulsen, Ole; Bullmore, Edward T

    2015-04-01

    Recent studies demonstrated that the anatomical network of the human brain shows a "rich-club" organization. This complex topological feature implies that highly connected regions, hubs of the large-scale brain network, are more densely interconnected with each other than expected by chance. Rich-club nodes were traversed by a majority of short paths between peripheral regions, underlining their potential importance for efficient global exchange of information between functionally specialized areas of the brain. Network hubs have also been described at the microscale of brain connectivity (so-called "hub neurons"). Their role in shaping synchronous dynamics and forming microcircuit wiring during development, however, is not yet fully understood. The present study aimed to investigate the role of hubs during network development, using multi-electrode arrays and functional connectivity analysis during spontaneous multi-unit activity (MUA) of dissociated primary mouse hippocampal neurons. Over the first 4 weeks in vitro, functional connectivity significantly increased in strength, density, and size, with mature networks demonstrating a robust modular and small-world topology. As expected by a "rich-get-richer" growth rule of network evolution, MUA graphs were found to form rich-clubs at an early stage in development (14 DIV). Later on, rich-club nodes were a consistent topological feature of MUA graphs, demonstrating high nodal strength, efficiency, and centrality. Rich-club nodes were also found to be crucial for MUA dynamics. They often served as broker of spontaneous activity flow, confirming that hub nodes and rich-clubs may play an important role in coordinating functional dynamics at the microcircuit level. PMID:25855164

  2. Emergence of Rich-Club Topology and Coordinated Dynamics in Development of Hippocampal Functional Networks In Vitro

    PubMed Central

    Charlesworth, Paul; Kitzbichler, Manfred G.; Paulsen, Ole

    2015-01-01

    Recent studies demonstrated that the anatomical network of the human brain shows a “rich-club” organization. This complex topological feature implies that highly connected regions, hubs of the large-scale brain network, are more densely interconnected with each other than expected by chance. Rich-club nodes were traversed by a majority of short paths between peripheral regions, underlining their potential importance for efficient global exchange of information between functionally specialized areas of the brain. Network hubs have also been described at the microscale of brain connectivity (so-called “hub neurons”). Their role in shaping synchronous dynamics and forming microcircuit wiring during development, however, is not yet fully understood. The present study aimed to investigate the role of hubs during network development, using multi-electrode arrays and functional connectivity analysis during spontaneous multi-unit activity (MUA) of dissociated primary mouse hippocampal neurons. Over the first 4 weeks in vitro, functional connectivity significantly increased in strength, density, and size, with mature networks demonstrating a robust modular and small-world topology. As expected by a “rich-get-richer” growth rule of network evolution, MUA graphs were found to form rich-clubs at an early stage in development (14 DIV). Later on, rich-club nodes were a consistent topological feature of MUA graphs, demonstrating high nodal strength, efficiency, and centrality. Rich-club nodes were also found to be crucial for MUA dynamics. They often served as broker of spontaneous activity flow, confirming that hub nodes and rich-clubs may play an important role in coordinating functional dynamics at the microcircuit level. PMID:25855164

  3. Noise-induced synchronous stochastic oscillations in small scale cultured heart-cell networks

    NASA Astrophysics Data System (ADS)

    Yuan, Lan; Liu, Zhi-Qiang; Zhang, Hui-Min; Ding, Xue-Li; Yang, Ming-Hao; Gu, Hua-Guang; Ren, Wei

    2011-02-01

    This paper reports that the synchronous integer multiple oscillations of heart-cell networks or clusters are observed in the biology experiment. The behaviour of the integer multiple rhythm is a transition between super- and subthreshold oscillations, the stochastic mechanism of the transition is identified. The similar synchronized oscillations are theoretically reproduced in the stochastic network composed of heterogeneous cells whose behaviours are chosen as excitable or oscillatory states near a Hopf bifurcation point. The parameter regions of coupling strength and noise density that the complex oscillatory rhythms can be simulated are identified. The results show that the rhythm results from a simple stochastic alternating process between super- and sub-threshold oscillations. Studies on single heart cells forming these clusters reveal excitable or oscillatory state nearby a Hopf bifurcation point underpinning the stochastic alternation. In discussion, the results are related to some abnormal heartbeat rhythms such as the sinus arrest.

  4. Microscopic mechanism for self-organized quasiperiodicity in random networks of nonlinear oscillators

    NASA Astrophysics Data System (ADS)

    Burioni, Raffaella; di Santo, Serena; di Volo, Matteo; Vezzani, Alessandro

    2014-10-01

    Self-organized quasiperiodicity is one of the most puzzling dynamical phases observed in systems of nonlinear coupled oscillators. The single dynamical units are not locked to the periodic mean field they produce, but they still feature a coherent behavior, through an unexplained complex form of correlation. We consider a class of leaky integrate-and-fire oscillators on random sparse and massive networks with dynamical synapses, featuring self-organized quasiperiodicity, and we show how complex collective oscillations arise from constructive interference of microscopic dynamics. In particular, we find a simple quantitative relationship between two relevant microscopic dynamical time scales and the macroscopic time scale of the global signal. We show that the proposed relation is a general property of collective oscillations, common to all the partially synchronous dynamical phases analyzed. We argue that an analogous mechanism could be at the origin of similar network dynamics.

  5. Bifurcation-based adiabatic quantum computation with a nonlinear oscillator network

    PubMed Central

    Goto, Hayato

    2016-01-01

    The dynamics of nonlinear systems qualitatively change depending on their parameters, which is called bifurcation. A quantum-mechanical nonlinear oscillator can yield a quantum superposition of two oscillation states, known as a Schrödinger cat state, via quantum adiabatic evolution through its bifurcation point. Here we propose a quantum computer comprising such quantum nonlinear oscillators, instead of quantum bits, to solve hard combinatorial optimization problems. The nonlinear oscillator network finds optimal solutions via quantum adiabatic evolution, where nonlinear terms are increased slowly, in contrast to conventional adiabatic quantum computation or quantum annealing, where quantum fluctuation terms are decreased slowly. As a result of numerical simulations, it is concluded that quantum superposition and quantum fluctuation work effectively to find optimal solutions. It is also notable that the present computer is analogous to neural computers, which are also networks of nonlinear components. Thus, the present scheme will open new possibilities for quantum computation, nonlinear science, and artificial intelligence. PMID:26899997

  6. Gamma oscillations in the midbrain spatial attention network: linking circuits to function

    PubMed Central

    Sridharan, Devarajan; Knudsen, Eric I

    2016-01-01

    Gamma-band (25–140 Hz) oscillations are ubiquitous in mammalian forebrain structures involved in sensory processing, attention, learning and memory. The optic tectum (OT) is the central structure in a midbrain network that participates critically in controlling spatial attention. In this review, we summarize recent advances in characterizing a neural circuit in this midbrain network that generates large amplitude, space-specific, gamma oscillations in the avian OT, both in vivo and in vitro. We describe key physiological and pharmacological mechanisms that produce and regulate the structure of these oscillations. The extensive similarities between midbrain gamma oscillations in birds and those in the neocortex and hippocampus of mammals, offer important insights into the functional significance of a midbrain gamma oscillatory code. PMID:25485519

  7. Bifurcation-based adiabatic quantum computation with a nonlinear oscillator network

    NASA Astrophysics Data System (ADS)

    Goto, Hayato

    2016-02-01

    The dynamics of nonlinear systems qualitatively change depending on their parameters, which is called bifurcation. A quantum-mechanical nonlinear oscillator can yield a quantum superposition of two oscillation states, known as a Schrödinger cat state, via quantum adiabatic evolution through its bifurcation point. Here we propose a quantum computer comprising such quantum nonlinear oscillators, instead of quantum bits, to solve hard combinatorial optimization problems. The nonlinear oscillator network finds optimal solutions via quantum adiabatic evolution, where nonlinear terms are increased slowly, in contrast to conventional adiabatic quantum computation or quantum annealing, where quantum fluctuation terms are decreased slowly. As a result of numerical simulations, it is concluded that quantum superposition and quantum fluctuation work effectively to find optimal solutions. It is also notable that the present computer is analogous to neural computers, which are also networks of nonlinear components. Thus, the present scheme will open new possibilities for quantum computation, nonlinear science, and artificial intelligence.

  8. Bifurcation-based adiabatic quantum computation with a nonlinear oscillator network.

    PubMed

    Goto, Hayato

    2016-01-01

    The dynamics of nonlinear systems qualitatively change depending on their parameters, which is called bifurcation. A quantum-mechanical nonlinear oscillator can yield a quantum superposition of two oscillation states, known as a Schrödinger cat state, via quantum adiabatic evolution through its bifurcation point. Here we propose a quantum computer comprising such quantum nonlinear oscillators, instead of quantum bits, to solve hard combinatorial optimization problems. The nonlinear oscillator network finds optimal solutions via quantum adiabatic evolution, where nonlinear terms are increased slowly, in contrast to conventional adiabatic quantum computation or quantum annealing, where quantum fluctuation terms are decreased slowly. As a result of numerical simulations, it is concluded that quantum superposition and quantum fluctuation work effectively to find optimal solutions. It is also notable that the present computer is analogous to neural computers, which are also networks of nonlinear components. Thus, the present scheme will open new possibilities for quantum computation, nonlinear science, and artificial intelligence. PMID:26899997

  9. Gamma oscillations in the midbrain spatial attention network: linking circuits to function.

    PubMed

    Sridharan, Devarajan; Knudsen, Eric I

    2015-04-01

    Gamma-band (25-140Hz) oscillations are ubiquitous in mammalian forebrain structures involved in sensory processing, attention, learning and memory. The optic tectum (OT) is the central structure in a midbrain network that participates critically in controlling spatial attention. In this review, we summarize recent advances in characterizing a neural circuit in this midbrain network that generates large amplitude, space-specific, gamma oscillations in the avian OT, both in vivo and in vitro. We describe key physiological and pharmacological mechanisms that produce and regulate the structure of these oscillations. The extensive similarities between midbrain gamma oscillations in birds and those in the neocortex and hippocampus of mammals, offer important insights into the functional significance of a midbrain gamma oscillatory code. PMID:25485519

  10. A beta2-frequency (20–30 Hz) oscillation in nonsynaptic networks of somatosensory cortex

    PubMed Central

    Roopun, Anita K.; Middleton, Steven J.; Cunningham, Mark O.; LeBeau, Fiona E. N.; Bibbig, Andrea; Whittington, Miles A.; Traub, Roger D.

    2006-01-01

    Beta2 frequency (20–30 Hz) oscillations appear over somatosensory and motor cortices in vivo during motor preparation and can be coherent with muscle electrical activity. We describe a beta2 frequency oscillation occurring in vitro in networks of layer V pyramidal cells, the cells of origin of the corticospinal tract. This beta2 oscillation depends on gap junctional coupling, but it survives a cut through layer 4 and, hence, does not depend on apical dendritic electrogenesis. It also survives a blockade of α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptors or a blockade of GABAA receptors that is sufficient to suppress gamma (30–70 Hz) oscillations in superficial cortical layers. The oscillation period is determined by the M type of K+ current. PMID:17030821

  11. Transitions between dynamical behaviors of oscillator networks induced by diversity of nodes and edges

    NASA Astrophysics Data System (ADS)

    Werner, Sebastian; Lehnertz, Klaus

    2015-07-01

    We study the impact of dynamical and structural heterogeneity on the collective dynamics of large small-world networks of pulse-coupled integrate-and-fire oscillators endowed with refractory periods and time delay. Depending on the choice of homogeneous control parameters (here, refractoriness and coupling strength), these networks exhibit a large spectrum of dynamical behaviors, including asynchronous, partially synchronous, and fully synchronous states. Networks exhibit transitions between these dynamical behaviors upon introducing heterogeneity. We show that the probability for a network to exhibit a certain dynamical behavior (network susceptibility) is affected differently by dynamical and structural heterogeneity and depends on the respective homogeneous dynamics.

  12. Transitions between dynamical behaviors of oscillator networks induced by diversity of nodes and edges.

    PubMed

    Werner, Sebastian; Lehnertz, Klaus

    2015-07-01

    We study the impact of dynamical and structural heterogeneity on the collective dynamics of large small-world networks of pulse-coupled integrate-and-fire oscillators endowed with refractory periods and time delay. Depending on the choice of homogeneous control parameters (here, refractoriness and coupling strength), these networks exhibit a large spectrum of dynamical behaviors, including asynchronous, partially synchronous, and fully synchronous states. Networks exhibit transitions between these dynamical behaviors upon introducing heterogeneity. We show that the probability for a network to exhibit a certain dynamical behavior (network susceptibility) is affected differently by dynamical and structural heterogeneity and depends on the respective homogeneous dynamics. PMID:26232952

  13. The fundamental organization of cardiac mitochondria as a network of coupled oscillators.

    PubMed

    Aon, Miguel Antonio; Cortassa, Sonia; O'Rourke, Brian

    2006-12-01

    Mitochondria can behave as individual oscillators whose dynamics may obey collective, network properties. We have shown that cardiomyocytes exhibit high-amplitude, self-sustained, and synchronous oscillations of bioenergetic parameters when the mitochondrial network is stressed to a critical state. Computational studies suggested that additional low-amplitude, high-frequency oscillations were also possible. Herein, employing power spectral analysis, we show that the temporal behavior of mitochondrial membrane potential (DeltaPsi(m)) in cardiomyocytes under physiological conditions is oscillatory and characterized by a broad frequency distribution that obeys a homogeneous power law (1/f(beta)) with a spectral exponent, beta = 1.74. Additionally, relative dispersional analysis shows that mitochondrial oscillatory dynamics exhibits long-term memory, characterized by an inverse power law that scales with a fractal dimension (D(f)) of 1.008, distinct from random behavior (D(f) = 1.5), over at least three orders of magnitude. Analysis of a computational model of the mitochondrial oscillator suggests that the mechanistic origin of the power law behavior is based on the inverse dependence of amplitude versus frequency of oscillation related to the balance between reactive oxygen species production and scavenging. The results demonstrate that cardiac mitochondria behave as a network of coupled oscillators under both physiological and pathophysiological conditions. PMID:16980364

  14. Intermittent and sustained periodic windows in networked chaotic Rössler oscillators

    SciTech Connect

    He, Zhiwei; Sun, Yong; Zhan, Meng

    2013-12-15

    Route to chaos (or periodicity) in dynamical systems is one of fundamental problems. Here, dynamical behaviors of coupled chaotic Rössler oscillators on complex networks are investigated and two different types of periodic windows with the variation of coupling strength are found. Under a moderate coupling, the periodic window is intermittent, and the attractors within the window extremely sensitively depend on the initial conditions, coupling parameter, and topology of the network. Therefore, after adding or removing one edge of network, the periodic attractor can be destroyed and substituted by a chaotic one, or vice versa. In contrast, under an extremely weak coupling, another type of periodic window appears, which insensitively depends on the initial conditions, coupling parameter, and network. It is sustained and unchanged for different types of network structure. It is also found that the phase differences of the oscillators are almost discrete and randomly distributed except that directly linked oscillators more likely have different phases. These dynamical behaviors have also been generally observed in other networked chaotic oscillators.

  15. Oscillations, complex spatiotemporal behavior, and information transport in networks of excitatory and inhibitory neurons

    SciTech Connect

    Destexhe, A. )

    1994-08-01

    Various types of spatiotemporal behavior are described for two-dimensional networks of excitatory and inhibitory neurons with time delayed interactions. It is described how the network behaves as several structural parameters are varied, such as the number of neurons, the connectivity, and the values of synaptic weights. A transition from spatially uniform oscillations to spatiotemporal chaos via intermittentlike behavior is observed. The properties of spatiotemporally chaotic solutions are investigated by evaluating the largest positive Lyapunov exponent and the loss of correlation with distance. Finally, properties of information transport are evaluated during uniform oscillations and spatiotemporal chaos. It is shown that the diffusion coefficient increases significantly in the spatiotemporal phase similar to the increase of transport coefficients at the onset of fluid turbulence. It is proposed that such a property should be seen in other media, such as chemical turbulence or networks of oscillators. The possibility of measuring information transport from appropriate experiments is also discussed.

  16. Alterations of functional properties of hippocampal networks following repetitive closed-head injury.

    PubMed

    Logue, Omar C; Cramer, Nathan P; Xu, Xiufen; Perl, Daniel P; Galdzicki, Zygmunt

    2016-03-01

    Traumatic brain injury (TBI) is the leading cause of death for persons under the age of 45. Military service members who have served on multiple combat deployments and contact-sport athletes are at particular risk of sustaining repetitive TBI (rTBI). Cognitive and behavioral deficits resulting from rTBI are well documented. Optimal associative LTP, occurring in the CA1 hippocampal Schaffer collateral pathway, is required for both memory formation and retrieval. Surprisingly, ipsilateral Schaffer collateral CA1 LTP evoked by 100Hz tetanus was enhanced in mice from the 3× closed head injury (3× CHI) treatment group in comparison to LTP in contralateral or 3× Sham CA1 area, and in spite of reduced freezing during contextual fear conditioning at one week following 3× CHI. Electrophysiological activity of CA1 neurons was evaluated with whole-cell patch-clamp recordings. 3× CHI ipsilateral CA1 neurons exhibited significant increases in action potential amplitude and maximum rise and decay slope while the action potential duration was decreased. Recordings of CA1 neuron postsynaptic currents were conducted to detect spontaneous excitatory and inhibitory postsynaptic currents (sEPSCs/sIPSCs) and respective miniature currents (mEPSCs and mIPSCs). In the 3× CHI mice, sEPSCs and sIPSCs in ipsilateral CA1 neurons had an increased frequency of events but decreased amplitudes. In addition, 3× CHI altered the action potential-independent miniature postsynaptic currents. The mEPSCs of ipsilateral CA1 neurons exhibited both an increased frequency of events and larger amplitudes. Moreover, the effect of 3× CHI on mIPSCs was opposite to that of the sIPSCs. Specifically, the frequency of the mIPSCs was decreased while the amplitudes were increased. These results are consistent with a mechanism in which repetitive closed-head injury affects CA1 hippocampal function by promoting a remodeling of excitatory and inhibitory synaptic inputs leading to impairment in hippocampal

  17. Spike-time reliability of layered neural oscillator networks

    NASA Astrophysics Data System (ADS)

    Lin, K. K.; Shea-Brown, E.; Young, L.-S.

    2013-01-01

    If a network of neurons is repeatedly driven by the same fluctuating signal, will it give the same response each time? If so, the network is said to be reliable. Reliability is of interest in computational neuroscience because the degree to which a network is reliable constrains its ability to encode information in precise temporal patterns of spikes. This note outlines how the question of reliability may be fruitfully formulated and studied within the framework of random dynamical systems theory. A specific network architecture, that of a single-layer network, is examined. For the type of single-neuron dynamics and coupling considered here, single-layer networks are found to be very reliable. A qualitative explanation is proposed for this phenomenon.

  18. Emergence and coherence of oscillations in star networks of stochastic excitable elements

    NASA Astrophysics Data System (ADS)

    Kromer, Justus A.; Schimansky-Geier, Lutz; Neiman, Alexander B.

    2016-04-01

    We study the emergence and coherence of stochastic oscillations in star networks of excitable elements in which peripheral nodes receive independent random inputs. A biophysical model of a distal branch of sensory neuron in which peripheral nodes of Ranvier are coupled to a central node by myelinated cable segments is used along with a generic model of networked stochastic active rotators. We show that coherent oscillations can emerge due to stochastic synchronization of peripheral nodes and that the degree of coherence can be maximized by tuning the coupling strength and the size of the network. Analytical results are obtained for the strong-coupling regime of the active rotator network. In particular, we show that in the strong-coupling regime, the network dynamics can be described by an effective single active rotator with rescaled parameters and noise.

  19. Stoichiometric network analysis of the oxalate-persulfate-silver oscillator

    NASA Astrophysics Data System (ADS)

    Clarke, Bruce L.

    1992-08-01

    This paper illustrates an approach that can refine mechanisms and obtain information about rate constants from dynamical phase diagrams which show the regions of oscillation of a mechanism as a function of the experimental parameters. Possible mechanisms for the experimentally oscillating oxalate-persulfate-silver system are examined. Starting with a proposed mechanism by Ouyang and de Kepper, which they could not make oscillate, we show that some variations of the mechanism are stable for all nonnegative values of the rate constants. Other variations are unstable. For these variations, feedback cycles that lead to instability are compared with a conceptual picture of feedback in the experimental system. One unstable mechanism fits the picture well. Its unimportant reactions are omitted and an analytical solution for the unstable region using 13 adjustable parameters is obtained. The rate constants are adjusted to match this solution to the experimentally measured phase diagram. A good fit can only be obtained if [O2] is too low and k1 is much smaller than the known value. Both discrepancies are resolved if Ag2+ oxidizes water. The analysis predicts the width of the unstable region can increase when more O2 enters the reactor.

  20. a Network of Oscillators Emulating the Italian High-Voltage Power Grid

    NASA Astrophysics Data System (ADS)

    Fortuna, Luigi; Frasca, Mattia; Sarra Fiore, Angelo

    2012-10-01

    In this paper, a dynamical model based on Kuramoto-like oscillators is used to represent the Italian high-voltage power grid. Nodes of the network are generators/substations, while links are the physical connections between generators/substations. The normal operating regime of the power grid corresponds to the regime in which the oscillations of all the nodes are synchronized. We studied the conditions for synchronization and the effect of dynamical perturbations on the nodes. The analysis allows to define several dynamical parameters assessing the dynamical robustness of the network.

  1. Synchronization of Coupled Oscillators on Newman Watts Small-World Networks

    NASA Astrophysics Data System (ADS)

    Guan, Jian-Yue; Xu, Xin-Jian; Wu, Zhi-Xi; Wang, Ying-Hai

    2006-06-01

    We investigate the collection behaviour of coupled phase oscillators on Newman-Watts small-world networks in one and two dimensions. Each component of the network is assumed as an oscillator and each interacts with the others following the Kuramoto model. We then study the onset of global synchronization of phases and frequencies based on dynamic simulations and finite-size scaling. Both the phase and frequency synchronization are observed to emerge in the presence of a tiny fraction of shortcuts and enhanced with the increases of nearest neighbours and lattice dimensions.

  2. Empathy in Hippocampal Amnesia

    PubMed Central

    Beadle, J. N.; Tranel, D.; Cohen, N. J.; Duff, M. C.

    2013-01-01

    Empathy is critical to the quality of our relationships with others and plays an important role in life satisfaction and well-being. The scientific investigation of empathy has focused on characterizing its cognitive and neural substrates, and has pointed to the importance of a network of brain regions involved in emotional experience and perspective taking (e.g., ventromedial prefrontal cortex, amygdala, anterior insula, cingulate). While the hippocampus has rarely been the focus of empathy research, the hallmark properties of the hippocampal declarative memory system (e.g., representational flexibility, relational binding, on-line processing capacity) make it well-suited to meet some of the crucial demands of empathy, and a careful investigation of this possibility could make a significant contribution to the neuroscientific understanding of empathy. The present study is a preliminary investigation of the role of the hippocampal declarative memory system in empathy. Participants were three patients (1 female) with focal, bilateral hippocampal (HC) damage and severe declarative memory impairments and three healthy demographically matched comparison participants. Empathy was measured as a trait through a battery of gold standard questionnaires and through on-line ratings and prosocial behavior in response to a series of empathy inductions. Patients with hippocampal amnesia reported lower cognitive and emotional trait empathy than healthy comparison participants. Unlike healthy comparison participants, in response to the empathy inductions hippocampal patients reported no increase in empathy ratings or prosocial behavior. The results provide preliminary evidence for a role for hippocampal declarative memory in empathy. PMID:23526601

  3. Strange Dynamics in a Fractional Derivative of Complex-Order Network of Chaotic Oscillators

    NASA Astrophysics Data System (ADS)

    Pinto, Carla M. A.

    We study the peculiar dynamical features of a fractional derivative of complex-order network. The network is composed of two unidirectional rings of cells, coupled through a "buffer" cell. The network has a Z3 × Z5 cyclic symmetry group. The complex derivative Dα±jβ, with α, β ∈ R+ is a generalization of the concept of integer order derivative, where α = 1, β = 0. Each cell is modeled by the Chen oscillator. Numerical simulations of the coupled cell system associated with the network expose patterns such as equilibria, periodic orbits, relaxation oscillations, quasiperiodic motion, and chaos, in one or in two rings of cells. In addition, fixing β = 0.8, we perceive differences in the qualitative behavior of the system, as the parameter c ∈ [13, 24] of the Chen oscillator and/or the real part of the fractional derivative, α ∈ {0.5, 0.6, 0.7, 0.8, 0.9, 1.0}, are varied. Some patterns produced by the coupled system are constrained by the network architecture, but other features are only understood in the light of the internal dynamics of each cell, in this case, the Chen oscillator. What is more important, architecture and/or internal dynamics?

  4. Impaired Visual Object Processing Across an Occipital- Frontal-Hippocampal Brain Network in Schizophrenia: An integrated neuroimaging study

    PubMed Central

    Sehatpour, Pejman; Dias, Elisa C.; Butler, Pamela D.; Revheim, Nadine; Guilfoyle, David N.; Foxe, John J.; Javitt, Daniel C.

    2013-01-01

    Background Perceptual closure refers to the ability to identify objects with partial information. Deficits in schizophrenia are indexed by impaired generation of the closure-related negativity (NCL) from ventral stream visual cortex (lateral occipital complex, LOC), as part of a network of brain regions that also includes dorsal stream visual regions, prefrontal cortex (PFC) and hippocampus. This study evaluates network-level interactions during perceptual closure in schizophrenia using parallel ERP, fMRI and neuropsychological assessment. Methods ERP were obtained from 24 patients and 20 healthy volunteers in response to fragmented (closeable) and control scrambled (noncloseable) line drawings. fMRI were obtained from 11 patients and 12 controls. Patterns of between group differences for predefined ERP components and fMRI regions of interest were determined using both analysis of variance and structural equation modeling. Global neuropsychological performance was assessed using elements of the WAIS-III, WMS-III and MATRICS batteries. Results Patients showed impaired visual P1 generation, reflecting dorsal stream dysfunction, along with impaired generation of NCL components over PFC and LOC. In fMRI, patients showed impaired activation of dorsal and ventral visual regions, PFC and hippocampus. Impaired activation of dorsal stream visual regions contributed significantly to impaired PFC activation. Impaired PFC activation contributed significantly to impaired activation of hippocampus and LOC. Impaired LOC and hippocampal activation contributed significantly to deficits on WAIS-III Perceptual Organization Index (POI) and other tests of impaired perceptual processing in schizophrenia. Conclusion Schizophrenia is associated with severe activation deficits across a distributed network of sensory and higher order cognitive regions. Deficit in early visual processing within the dorsal visual stream contributes significantly to impaired frontal activation which, in turn

  5. Performance of the Birmingham Solar-Oscillations Network (BiSON)

    NASA Astrophysics Data System (ADS)

    Hale, S. J.; Howe, R.; Chaplin, W. J.; Davies, G. R.; Elsworth, Y. P.

    2016-01-01

    The Birmingham Solar-Oscillations Network (BiSON) has been operating with a full complement of six stations since 1992. Over 20 years later, we look back on the network history. The meta-data from the sites have been analysed to assess performance in terms of site insolation, with a brief look at the challenges that have been encountered over the years. We explain how the international community can gain easy access to the ever-growing dataset produced by the network, and finally look to the future of the network and the potential impact of nearly 25 years of technology miniaturisation.

  6. Influence of molecular structure on the properties of out-of-equilibrium oscillating enzymatic reaction networks.

    PubMed

    Wong, Albert S Y; Postma, Sjoerd G J; Vialshin, Ilia N; Semenov, Sergey N; Huck, Wilhelm T S

    2015-09-30

    Our knowledge of the properties and dynamics of complex molecular reaction networks, for example those found in living systems, considerably lags behind the understanding of elementary chemical reactions. In part, this is because chemical reactions networks are nonlinear systems that operate under conditions far from equilibrium. Of particular interest is the role of individual reaction rates on the stability of the network output. In this research we use a rational approach combined with computational methods, to produce complex behavior (in our case oscillations) and show that small changes in molecular structure are sufficient to impart large changes in network behavior. PMID:26352485

  7. Periodic oscillation for a Hopfield neural networks with neutral delays

    NASA Astrophysics Data System (ADS)

    Gui, Zhanji; Ge, Weigao; Yang, Xiao-Song

    2007-04-01

    In this Letter, a Hopfield neural networks model with neutral delay are investigated by means of an abstract continuous theorem of k-set contractive operator and some analysis technique. Sufficient conditions are obtained for the existence of periodic solutions.

  8. The Global Oscillation Network Group site survey. 1: Data collection and analysis methods

    NASA Technical Reports Server (NTRS)

    Hill, Frank; Fischer, George; Grier, Jennifer; Leibacher, John W.; Jones, Harrison B.; Jones, Patricia P.; Kupke, Renate; Stebbins, Robin T.

    1994-01-01

    The Global Oscillation Network Group (GONG) Project is planning to place a set of instruments around the world to observe solar oscillations as continuously as possible for at least three years. The Project has now chosen the sites that will comprise the network. This paper describes the methods of data collection and analysis that were used to make this decision. Solar irradiance data were collected with a one-minute cadence at fifteen sites around the world and analyzed to produce statistics of cloud cover, atmospheric extinction, and transparency power spectra at the individual sites. Nearly 200 reasonable six-site networks were assembled from the individual stations, and a set of statistical measures of the performance of the networks was analyzed using a principal component analysis. An accompanying paper presents the results of the survey.

  9. Bifurcation-based adiabatic quantum computation with a nonlinear oscillator network

    NASA Astrophysics Data System (ADS)

    Goto, Hayato

    The dynamics of nonlinear systems qualitatively change depending on their parameters, which is called bifurcation. A quantum-mechanical nonlinear oscillator can yield a quantum superposition of two oscillation states, known as a Schrödinger cat state, via its bifurcation with a slowly varying parameter. Here we propose a quantum computer comprising such quantum nonlinear oscillators, instead of quantum bits, to solve hard combinatorial optimization problems. The nonlinear oscillator network finds optimal solutions via quantum adiabatic evolution, where nonlinear terms are increased slowly, in contrast to conventional adiabatic quantum computation or quantum annealing. To distinguish them, we refer to the present approach as bifurcation-based adiabatic quantum computation. Our numerical simulation results suggest that quantum superposition and quantum fluctuation work effectively to find optimal solutions.

  10. Synchronization in a network of phase-coupled oscillators: the role of learning and time delay

    NASA Astrophysics Data System (ADS)

    Timms, Liam; English, Lars

    2013-03-01

    We investigate numerically the interplay of network ``learning'' and finite signal speed in one and two-dimensional arrays of coupled Kuramoto oscillators. The finite signal speed is introduced into the dynamical system via a time-delay in the coupling. The network structures we examine include various one and two-dimensional arrays with both long and short-range connectivity; the structure of these arrays is imposed via a time delay and a connection matrix. The learning is governed by the Hebbian learning rule which allows the coupling strengths between pairs of oscillators to vary dynamically. It corresponds to a neurological type of learning in which the synapses between neural oscillators increase in strength when they fire action potentials together. We explore the coherent spatio-temporal patterns that can emerge as a function of model parameters such as learning rate and signal speed.

  11. Noise-induced coherence and network oscillations in a reduced bursting model.

    PubMed

    Reinker, Stefan; Li, Yue-Xian; Kuske, Rachel

    2006-08-01

    The dynamics of the Hindmarsh-Rose (HR) model of bursting thalamic neurons is reduced to a system of two linear differential equations that retains the subthreshold resonance properties of the HR model. Introducing a reset mechanism after a threshold crossing, we turn this system into a resonant integrate-and-fire (RIF) model. Using Monte-Carlo simulations and mathematical analysis, we examine the effects of noise and the subthreshold dynamic properties of the RIF model on the occurrence of coherence resonance (CR). Synchronized burst firing occurs in a network of such model neurons with excitatory pulse-coupling. The coherence level of the network oscillations shows a stochastic resonance-like dependence on the noise level. Stochastic analysis of the equations shows that the slow recovery from the spike-induced inhibition is crucial in determining the frequencies of the CR and the subthreshold resonance in the original HR model. In this particular type of CR, the oscillation frequency strongly depends on the intrinsic time scales but changes little with the noise intensity. We give analytical quantities to describe this CR mechanism and illustrate its influence on the emerging network oscillations. We discuss the profound physiological roles this kind of CR may have in information processing in neurons possessing a subthreshold resonant frequency and in generating synchronized network oscillations with a frequency that is determined by intrinsic properties of the neurons. PMID:17149822

  12. Noise-induced Synchronized Oscillations in an Inhibitory Neural Network

    NASA Astrophysics Data System (ADS)

    José, Jorge V.; Tiesinga, Paul

    2003-05-01

    We study the properties of synchronized states in a neuronal network model that represents circuitry of the thalamus or the locust antennal lobe. We find noise-driven and noise-sustained synchronized neural cluster states. We determine the theoretical maximum information output of these networks in terms of the Shannon entropy. Synchronized states are usually characterized by more regular spike trains and reduced information output. We find, however, that even a single neuron can still transmit a significant amount of information. The information content is contained in the changing participation of neurons in neural assemblies. Similar neural assemblies were recently observed in the locust olfactory system.

  13. Comparison of Brain Networks During Interictal Oscillations and Spikes on Magnetoencephalography and Intracerebral EEG.

    PubMed

    Jmail, Nawel; Gavaret, Martine; Bartolomei, F; Chauvel, P; Badier, Jean-Michel; Bénar, Christian-G

    2016-09-01

    Electromagnetic source localization in electroencephalography (EEG) and magnetoencephalography (MEG) allows finding the generators of transient interictal epileptiform discharges ('interictal spikes'). In intracerebral EEG (iEEG), oscillatory activity (above 30 Hz) has also been shown to be a marker of neuronal dysfunction. Still, the difference between networks involved in transient and oscillatory activities remains largely unknown. Our goal was thus to extract and compare the networks involved in interictal oscillations and spikes, and to compare the non-invasive results to those obtained directly within the brain. In five patients with both MEG and iEEG recordings, we computed correlation graphs across regions, for (1) interictal spikes and (2) epileptic oscillations around 30 Hz. We show that the corresponding networks can involve a widespread set of regions (average of 10 per patient), with only partial overlap (38 % of the total number of regions in MEG, 50 % in iEEG). The non-invasive results were concordant with intracerebral recordings (79 % for the spikes and 50 % for the oscillations). We compared our interictal results to iEEG ictal data. The regions labeled as seizure onset zone (SOZ) belonged to interictal networks in a large proportion of cases: 75 % (resp. 58 %) for spikes and 58 % (resp. 33 %) for oscillations in iEEG (resp. MEG). A subset of SOZ regions were detected by one type of discharges but not the other (25 % for spikes and 8 % for oscillations). Our study suggests that spike and oscillatory activities involve overlapping but distinct networks, and are complementary for presurgical mapping. PMID:27334988

  14. The use of maps in the analysis of networks of coupled neuronal oscillators

    NASA Astrophysics Data System (ADS)

    Goel, Pranay

    In this thesis we study aspects of periodic activity in model mutually-coupled oscillators inspired by the nervous system. We define and use maps describing the timing of activity on successive cycles. The central theme here is to examine emergent behavior in networks through the properties of the individual oscillators. In the first chapter, we describe Phase Response Curves (PRCs), which map the changes in the period of an oscillator to perturbations at different phases along the cycle. We consider various networks of oscillators, pulse-coupled through their PRCs: rings, chains, arrays, and global coupling. We study conditions under which stable patterns, such as synchrony and waves, may be found. In the second and third chapters, we model beta (12--30 Hz) and gamma (30--80 Hz) rhythms in the nervous system in reduced networks of excitatory and inhibitory neurons. We look at the intriguing results of experiments that show increases in beta band activity in human MEGs upon taking the sedative Diapam. We show that the model network is able to mimic the experimental data. The model then clarifies the inhibitory action of the drug in tissue. We look at another experiment that finds disruption of long-range synchrony of gamma oscillations in transgenic mice with altered excitatory kinetics. We study this behavior in a reduced network that encodes for conduction delays across spatially distal sites. The model provides an explanation of this phenomenon in terms of the properties of the cells involved in generating the rhythm. In our analyses, we use maps to study stability of the patterns of activity.

  15. Neuronal oscillations and functional interactions between resting state networks.

    PubMed

    Lei, Xu; Wang, Yulin; Yuan, Hong; Mantini, Dante

    2014-07-01

    Functional magnetic imaging (fMRI) studies showed that resting state activity in the healthy brain is organized into multiple large-scale networks encompassing distant regions. A key finding of resting state fMRI studies is the anti-correlation typically observed between the dorsal attention network (DAN) and the default mode network (DMN), which - during task performance - are activated and deactivated, respectively. Previous studies have suggested that alcohol administration modulates the balance of activation/deactivation in brain networks, as well as it induces significant changes in oscillatory activity measured by electroencephalography (EEG). However, our knowledge of alcohol-induced changes in band-limited EEG power and their potential link with the functional interactions between DAN and DMN is still very limited. Here we address this issue, examining the neuronal effects of alcohol administration during resting state by using simultaneous EEG-fMRI. Our findings show increased EEG power in the theta frequency band (4-8 Hz) after administration of alcohol compared to placebo, which was prominent over the frontal cortex. More interestingly, increased frontal tonic EEG activity in this band was associated with greater anti-correlation between the DAN and the frontal component of the DMN. Furthermore, EEG theta power and DAN-DMN anti-correlation were relatively greater in subjects who reported a feeling of euphoria after alcohol administration, which may result from a diminished inhibition exerted by the prefrontal cortex. Overall, our findings suggest that slow brain rhythms are responsible for dynamic functional interactions between brain networks. They also confirm the applicability and potential usefulness of EEG-fMRI for central nervous system drug research. PMID:25050432

  16. Transient scaling and resurgence of chimera states in networks of Boolean phase oscillators.

    PubMed

    Rosin, David P; Rontani, Damien; Haynes, Nicholas D; Schöll, Eckehard; Gauthier, Daniel J

    2014-09-01

    We study networks of nonlocally coupled electronic oscillators that can be described approximately by a Kuramoto-like model. The experimental networks show long complex transients from random initial conditions on the route to network synchronization. The transients display complex behaviors, including resurgence of chimera states, which are network dynamics where order and disorder coexists. The spatial domain of the chimera state moves around the network and alternates with desynchronized dynamics. The fast time scale of our oscillators (on the order of 100ns) allows us to study the scaling of the transient time of large networks of more than a hundred nodes, which has not yet been confirmed previously in an experiment and could potentially be important in many natural networks. We find that the average transient time increases exponentially with the network size and can be modeled as a Poisson process in experiment and simulation. This exponential scaling is a result of a synchronization rate that follows a power law of the phase-space volume. PMID:25314385

  17. Hippocampal place cell instability after lesions of the head direction cell network

    NASA Technical Reports Server (NTRS)

    Calton, Jeffrey L.; Stackman, Robert W.; Goodridge, Jeremy P.; Archey, William B.; Dudchenko, Paul A.; Taube, Jeffrey S.; Oman, C. M. (Principal Investigator)

    2003-01-01

    The occurrence of cells that encode spatial location (place cells) or head direction (HD cells) in the rat limbic system suggests that these cell types are important for spatial navigation. We sought to determine whether place fields of hippocampal CA1 place cells would be altered in animals receiving lesions of brain areas containing HD cells. Rats received bilateral lesions of anterodorsal thalamic nuclei (ADN), postsubiculum (PoS), or sham lesions, before place cell recording. Although place cells from lesioned animals did not differ from controls on many place-field characteristics, such as place-field size and infield firing rate, the signal was significantly degraded with respect to measures of outfield firing rate, spatial coherence, and information content. Surprisingly, place cells from lesioned animals were more likely modulated by the directional heading of the animal. Rotation of the landmark cue showed that place fields from PoS-lesioned animals were not controlled by the cue and shifted unpredictably between sessions. Although fields from ADN-lesioned animals tended to have less landmark control than fields from control animals, this impairment was mild compared with cells recorded from PoS-lesioned animals. Removal of the prominent visual cue also led to instability of place-field representations in PoS-lesioned, but not ADN-lesioned, animals. Together, these findings suggest that an intact HD system is not necessary for the maintenance of place fields, but lesions of brain areas that convey the HD signal can degrade this signal, and lesions of the PoS might lead to perceptual or mnemonic deficits, leading to place-field instability between sessions.

  18. The Slow Oscillation in Cortical and Thalamic Networks: Mechanisms and Functions

    PubMed Central

    Neske, Garrett T.

    2016-01-01

    During even the most quiescent behavioral periods, the cortex and thalamus express rich spontaneous activity in the form of slow (<1 Hz), synchronous network state transitions. Throughout this so-called slow oscillation, cortical and thalamic neurons fluctuate between periods of intense synaptic activity (Up states) and almost complete silence (Down states). The two decades since the original characterization of the slow oscillation in the cortex and thalamus have seen considerable advances in deciphering the cellular and network mechanisms associated with this pervasive phenomenon. There are, nevertheless, many questions regarding the slow oscillation that await more thorough illumination, particularly the mechanisms by which Up states initiate and terminate, the functional role of the rhythmic activity cycles in unconscious or minimally conscious states, and the precise relation between Up states and the activated states associated with waking behavior. Given the substantial advances in multineuronal recording and imaging methods in both in vivo and in vitro preparations, the time is ripe to take stock of our current understanding of the slow oscillation and pave the way for future investigations of its mechanisms and functions. My aim in this Review is to provide a comprehensive account of the mechanisms and functions of the slow oscillation, and to suggest avenues for further exploration. PMID:26834569

  19. Neuronal oscillations form parietal/frontal networks during contour integration

    PubMed Central

    Castellano, Marta; Plöchl, Michael; Vicente, Raul; Pipa, Gordon

    2014-01-01

    The ability to integrate visual features into a global coherent percept that can be further categorized and manipulated are fundamental abilities of the neural system. While the processing of visual information involves activation of early visual cortices, the recruitment of parietal and frontal cortices has been shown to be crucial for perceptual processes. Yet is it not clear how both cortical and long-range oscillatory activity leads to the integration of visual features into a coherent percept. Here, we will investigate perceptual grouping through the analysis of a contour categorization task, where the local elements that form contour must be linked into a coherent structure, which is then further processed and manipulated to perform the categorization task. The contour formation in our visual stimulus is a dynamic process where, for the first time, visual perception of contours is disentangled from the onset of visual stimulation or from motor preparation, cognitive processes that until now have been behaviorally attached to perceptual processes. Our main finding is that, while local and long-range synchronization at several frequencies seem to be an ongoing phenomena, categorization of a contour could only be predicted through local oscillatory activity within parietal/frontal sources, which in turn, would synchronize at gamma (>30 Hz) frequency. Simultaneously, fronto-parietal beta (13–30 Hz) phase locking forms a network spanning across neural sources that are not category specific. Both long range networks, i.e., the gamma network that is category specific, and the beta network that is not category specific, are functionally distinct but spatially overlapping. Altogether, we show that a critical mechanism underlying contour categorization involves oscillatory activity within parietal/frontal cortices, as well as its synchronization across distal cortical sites. PMID:25165437

  20. Self-excited relaxation oscillations in networks of impulse neurons

    NASA Astrophysics Data System (ADS)

    Glyzin, S. D.; Kolesov, A. Yu; Rozov, N. Kh

    2015-06-01

    This paper addresses the problem of mathematical modelling of neuron activity. New classes of singularly perturbed differential-difference equations with Volterra-type delay are proposed and used to describe how single neurons and also neural networks function with various kinds of connections (electrical or chemical). Special asymptotic methods are developed which make it possible to analyse questions of the existence and stability of relaxation periodic motions in such systems. Bibliography: 56 titles.

  1. Spike Train Dynamics Underlying Pattern Formation in Integrate-and-Fire Oscillator Networks

    NASA Astrophysics Data System (ADS)

    Bressloff, P. C.; Coombes, S.

    1998-09-01

    A dynamical mechanism underlying pattern formation in a spatially extended network of integrate-and-fire oscillators with synaptic interactions is identified. It is shown how in the strong coupling regime the network undergoes a discrete Turing-Hopf bifurcation of the firing times from a synchronous state to a state with periodic or quasiperiodic variations of the interspike intervals on closed orbits. The separation of these orbits in phase space results in a spatially periodic pattern of mean firing rate across the network that is modulated by deterministic fluctuations of the instantaneous firing rate.

  2. A G-protein subunit translocation embedded network motif underlies GPCR regulation of calcium oscillations.

    PubMed

    Giri, Lopamudra; Patel, Anilkumar K; Karunarathne, W K Ajith; Kalyanaraman, Vani; Venkatesh, K V; Gautam, N

    2014-07-01

    G-protein βγ subunits translocate reversibly from the plasma membrane to internal membranes on receptor activation. Translocation rates differ depending on the γ subunit type. There is limited understanding of the role of the differential rates of Gβγ translocation in modulating signaling dynamics in a cell. Bifurcation analysis of the calcium oscillatory network structure predicts that the translocation rate of a signaling protein can regulate the damping of system oscillation. Here, we examined whether the Gβγ translocation rate regulates calcium oscillations induced by G-protein-coupled receptor activation. Oscillations in HeLa cells expressing γ subunit types with different translocation rates were imaged and quantitated. The results show that differential Gβγ translocation rates can underlie the diversity in damping characteristics of calcium oscillations among cells. Mathematical modeling shows that a translocation embedded motif regulates damping of G-protein-mediated calcium oscillations consistent with experimental data. The current study indicates that such a motif may act as a tuning mechanism to design oscillations with varying damping patterns by using intracellular translocation of a signaling component. PMID:24988358

  3. Variety of alternative stable phase-locking in networks of electrically coupled relaxation oscillators.

    PubMed

    Meyrand, Pierre; Bem, Tiaza

    2014-01-01

    We studied the dynamics of a large-scale model network comprised of oscillating electrically coupled neurons. Cells are modeled as relaxation oscillators with short duty cycle, so they can be considered either as models of pacemaker cells, spiking cells with fast regenerative and slow recovery variables or firing rate models of excitatory cells with synaptic depression or cellular adaptation. It was already shown that electrically coupled relaxation oscillators exhibit not only synchrony but also anti-phase behavior if electrical coupling is weak. We show that a much wider spectrum of spatiotemporal patterns of activity can emerge in a network of electrically coupled cells as a result of switching from synchrony, produced by short external signals of different spatial profiles. The variety of patterns increases with decreasing rate of neuronal firing (or duty cycle) and with decreasing strength of electrical coupling. We study also the effect of network topology--from all-to-all--to pure ring connectivity, where only the closest neighbors are coupled. We show that the ring topology promotes anti-phase behavior as compared to all-to-all coupling. It also gives rise to a hierarchical organization of activity: during each of the main phases of a given pattern cells fire in a particular sequence determined by the local connectivity. We have analyzed the behavior of the network using geometric phase plane methods and we give heuristic explanations of our findings. Our results show that complex spatiotemporal activity patterns can emerge due to the action of stochastic or sensory stimuli in neural networks without chemical synapses, where each cell is equally coupled to others via gap junctions. This suggests that in developing nervous systems where only electrical coupling is present such a mechanism can lead to the establishment of proto-networks generating premature multiphase oscillations whereas the subsequent emergence of chemical synapses would later stabilize

  4. A million-plus neuron model of the hippocampal dentate gyrus: Dependency of spatio-temporal network dynamics on topography.

    PubMed

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

    2015-01-01

    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. 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 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 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" that organize the processing of entorhinal signals. PMID:26737346

  5. A Million-Plus Neuron Model of the Hippocampal Dentate Gyrus: Dependency of Spatio-Temporal Network Dynamics on Topography

    PubMed Central

    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. 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 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 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” that organize the processing of entorhinal signals. PMID:26737346

  6. Chimera states: coexistence of coherence and incoherence in networks of coupled oscillators

    NASA Astrophysics Data System (ADS)

    Panaggio, Mark J.; Abrams, Daniel M.

    2015-03-01

    A chimera state is a spatio-temporal pattern in a network of identical coupled oscillators in which synchronous and asynchronous oscillation coexist. This state of broken symmetry, which usually coexists with a stable spatially symmetric state, has intrigued the nonlinear dynamics community since its discovery in the early 2000s. Recent experiments have led to increasing interest in the origin and dynamics of these states. Here we review the history of research on chimera states and highlight major advances in understanding their behaviour.

  7. Theta Oscillation Reveals the Temporal Involvement of Different Attentional Networks in Contingent Reorienting

    PubMed Central

    Chang, Chi-Fu; Liang, Wei-Kuang; Lai, Chiou-Lian; Hung, Daisy L.; Juan, Chi-Hung

    2016-01-01

    In the visual world, rapidly reorienting to relevant objects outside the focus of attention is vital for survival. This ability from the interaction between goal-directed and stimulus-driven attentional control is termed contingent reorienting. Neuroimaging studies have demonstrated activations of the ventral and dorsal attentional networks (DANs) which exhibit right hemisphere dominance, but the temporal dynamics of the attentional networks still remain unclear. The present study used event-related potential (ERP) to index the locus of spatial attention and Hilbert-Huang transform (HHT) to acquire the time-frequency information during contingent reorienting. The ERP results showed contingent reorienting induced significant N2pc on both hemispheres. In contrast, our time-frequency analysis found further that, unlike the N2pc, theta oscillation during contingent reorienting differed between hemispheres and experimental sessions. The inter-trial coherence (ITC) of the theta oscillation demonstrated that the two sides of the attentional networks became phase-locked to contingent reorienting at different stages. The left attentional networks were associated with contingent reorienting in the first experimental session whereas the bilateral attentional networks play a more important role in this process in the subsequent session. This phase-locked information suggests a dynamic temporal evolution of the involvement of different attentional networks in contingent reorienting and a potential role of the left ventral network in the first session. PMID:27375459

  8. Pronounced differences in signal processing and synaptic plasticity between piriform-hippocampal network stages: a prominent role for adenosine

    PubMed Central

    Trieu, Brian H; Kramár, Enikö A; Cox, Conor D; Jia, Yousheng; Wang, Weisheng; Gall, Christine M; Lynch, Gary

    2015-01-01

    Key points Extended trains of theta rhythm afferent activity lead to a biphasic response facilitation in field CA1 but not in the lateral perforant path input to the dentate gyrus. Processes that reverse long-term potentiation in field CA1 are not operative in the lateral perforant path: multiple lines of evidence indicate that this reflects differences in adenosine signalling. Adenosine A1 receptors modulate baseline synaptic transmission in the lateral olfactory tract but not the associational afferents of the piriform cortex. Levels of ecto-5’-nucleotidase (CD73), an enzyme that converts extracellular ATP into adenosine, are markedly different between regions and correlate with adenosine signalling and the efficacy of theta pulse stimulation in reversing long-term potentiation. Variations in transmitter mobilization, CD73 levels, and afferent divergence result in multivariate differences in signal processing through nodes in the cortico-hippocampal network. Abstract The present study evaluated learning-related synaptic operations across the serial stages of the olfactory cortex-hippocampus network. Theta frequency stimulation produced very different time-varying responses in the Schaffer-commissural projections than in the lateral perforant path (LPP), an effect associated with distinctions in transmitter mobilization. Long-term potentiation (LTP) had a higher threshold in LPP field potential studies but not in voltage clamped neurons; coupled with input/output relationships, these results suggest that LTP threshold differences reflect the degree of input divergence. Theta pulse stimulation erased LTP in CA1 but not in the dentate gyrus (DG), although adenosine eliminated potentiation in both areas, suggesting that theta increases extracellular adenosine to a greater degree in CA1. Moreover, adenosine A1 receptor antagonism had larger effects on theta responses in CA1 than in the DG, and concentrations of ecto-5’-nucleotidase (CD73) were much higher in CA1

  9. Gap junction networks can generate both ripple-like and fast ripple-like oscillations

    PubMed Central

    Simon, Anna; Traub, Roger D.; Vladimirov, Nikita; Jenkins, Alistair; Nicholson, Claire; Whittaker, Roger G.; Schofield, Ian; Clowry, Gavin J.; Cunningham, Mark O.; Whittington, Miles A.

    2014-01-01

    Fast ripples (FRs) are network oscillations, defined variously as having frequencies of > 150 to > 250 Hz, with a controversial mechanism. FRs appear to indicate a propensity of cortical tissue to originate seizures. Here, we demonstrate field oscillations, at up to 400 Hz, in spontaneously epileptic human cortical tissue in vitro, and present a network model that could explain FRs themselves, and their relation to ‘ordinary’ (slower) ripples. We performed network simulations with model pyramidal neurons, having axons electrically coupled. Ripples (< 250 Hz) were favored when conduction of action potentials, axon to axon, was reliable. Whereas ripple population activity was periodic, firing of individual axons varied in relative phase. A switch from ripples to FRs took place when an ectopic spike occurred in a cell coupled to another cell, itself multiply coupled to others. Propagation could then start in one direction only, a condition suitable for re-entry. The resulting oscillations were > 250 Hz, were sustained or interrupted, and had little jitter in the firing of individual axons. The form of model FR was similar to spontaneously occurring FRs in excised human epileptic tissue. In vitro, FRs were suppressed by a gap junction blocker. Our data suggest that a given network can produce ripples, FRs, or both, via gap junctions, and that FRs are favored by clusters of axonal gap junctions. If axonal gap junctions indeed occur in epileptic tissue, and are mediated by connexin 26 (recently shown to mediate coupling between immature neocortical pyramidal cells), then this prediction is testable. PMID:24118191

  10. Response of energy envelop in complex oscillator networks to external stochastic excitations

    NASA Astrophysics Data System (ADS)

    Jin, Xiao-Ling; Huang, Zhi-Long; Chen, Guanrong; Leung, Andrew Y. T.

    2010-07-01

    The response of energy envelop in complex nonlinear oscillator networks to stochastic excitations is studied. First, by using the stochastic averaging method for quasi-nonintegrable-Hamiltonian systems, the averaged Fokker-Planck-Kolmogorov equation governing the probability density of the Hamiltonian is established. Then, the stationary probability density of the Hamiltonian is derived, and the stationary probability density of the averaged energy as well as the statistical moments of the Hamiltonian is obtained. To that end, an illustrative example is provided with the analytical relationship between the response and the network parameters as well as the network structure. Specific solutions are presented for five representative topological structures. Throughout extensive simulations, the effects of system parameters, such as the network size, coupling strength and intensities of stochastic excitations on the response of the energy envelop of the networks, are carefully observed and analyzed.