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Sample records for hippocampal network oscillations

  1. Cannabinoids inhibit hippocampal GABAergic transmission and network oscillations.

    PubMed

    Hájos, N; Katona, I; Naiem, S S; MacKie, K; Ledent, C; Mody, I; Freund, T F

    2000-09-01

    Using a new antibody developed against the C-terminus of the cannabinoid receptor (CB1), the immunostaining in the hippocampus revealed additional axon terminals relative to the pattern reported previously with an N-terminus antibody. Due to a greater sensitivity of this antibody, a large proportion of boutons in the dendritic layers displaying symmetrical (GABAergic) synapses were also strongly immunoreactive for CB1 receptors, as were axon terminals of perisomatic inhibitory cells containing cholecystokinin. Asymmetrical (glutamatergic) synapses, however, were always negative for CB1. To investigate the effect of presynaptic CB1 receptor activation on hippocampal inhibition, we recorded inhibitory postsynaptic currents (IPSCs) from principal cells. Bath application of CB1 receptor agonists (WIN55,212-2 and CP55,940) suppressed IPSCs evoked by local electrical stimulation, which could be prevented or reversed by the CB1 receptor antagonist SR141716A. Action potential-driven IPSCs, evoked by pharmacological stimulation of a subset of interneurons, were also decreased by CB1 receptor activation. We also examined the effects of CB1 receptor agonists on Ca2+-independent miniature IPSCs (mIPSC). Both agonists were without significant effect on the frequency or amplitude of mIPSCs. Synchronous gamma oscillations induced by kainic acid in the CA3 region of hippocampal slices were reversibly reduced in amplitude by the CB1 receptor agonist CP 55,940, which is consistent with an action on IPSCs. We used CB1-/- knock-out mice to confirm the specificity of the antibody and of the agonist (WIN55,212-2) action. We conclude that activation of presynaptic CB1 receptors decreases Ca2+-dependent GABA release, and thereby reduces the power of hippocampal network oscillations.

  2. Network recruitment to coherent oscillations in a hippocampal computer model

    PubMed Central

    Krieger, Abba; Litt, Brian

    2011-01-01

    Coherent neural oscillations represent transient synchronization of local neuronal populations in both normal and pathological brain activity. These oscillations occur at or above gamma frequencies (>30 Hz) and often are propagated to neighboring tissue under circumstances that are both normal and abnormal, such as gamma binding or seizures. The mechanisms that generate and propagate these oscillations are poorly understood. In the present study we demonstrate, via a detailed computational model, a mechanism whereby physiological noise and coupling initiate oscillations and then recruit neighboring tissue, in a manner well described by a combination of stochastic resonance and coherence resonance. We develop a novel statistical method to quantify recruitment using several measures of network synchrony. This measurement demonstrates that oscillations spread via preexisting network connections such as interneuronal connections, recurrent synapses, and gap junctions, provided that neighboring cells also receive sufficient inputs in the form of random synaptic noise. “Epileptic” high-frequency oscillations (HFOs), produced by pathologies such as increased synaptic activity and recurrent connections, were superior at recruiting neighboring tissue. “Normal” HFOs, associated with fast firing of inhibitory cells and sparse pyramidal cell firing, tended to suppress surrounding cells and showed very limited ability to recruit. These findings point to synaptic noise and physiological coupling as important targets for understanding the generation and propagation of both normal and pathological HFOs, suggesting potential new diagnostic and therapeutic approaches to human disorders such as epilepsy. PMID:21273309

  3. Synaptic plasticity by antidromic firing during hippocampal network oscillations.

    PubMed

    Bukalo, Olena; Campanac, Emilie; Hoffman, Dax A; Fields, R Douglas

    2013-03-26

    Learning and other cognitive tasks require integrating new experiences into context. In contrast to sensory-evoked synaptic plasticity, comparatively little is known of how synaptic plasticity may be regulated by intrinsic activity in the brain, much of which can involve nonclassical modes of neuronal firing and integration. Coherent high-frequency oscillations of electrical activity in CA1 hippocampal neurons [sharp-wave ripple complexes (SPW-Rs)] functionally couple neurons into transient ensembles. These oscillations occur during slow-wave sleep or at rest. Neurons that participate in SPW-Rs are distinguished from adjacent nonparticipating neurons by firing action potentials that are initiated ectopically in the distal region of axons and propagate antidromically to the cell body. This activity is facilitated by GABA(A)-mediated depolarization of axons and electrotonic coupling. The possible effects of antidromic firing on synaptic strength are unknown. We find that facilitation of spontaneous SPW-Rs in hippocampal slices by increasing gap-junction coupling or by GABA(A)-mediated axon depolarization resulted in a reduction of synaptic strength, and electrical stimulation of axons evoked a widespread, long-lasting synaptic depression. Unlike other forms of synaptic plasticity, this synaptic depression is not dependent upon synaptic input or glutamate receptor activation, but rather requires L-type calcium channel activation and functional gap junctions. Synaptic stimulation delivered after antidromic firing, which was otherwise too weak to induce synaptic potentiation, triggered a long-lasting increase in synaptic strength. Rescaling synaptic weights in subsets of neurons firing antidromically during SPW-Rs might contribute to memory consolidation by sharpening specificity of subsequent synaptic input and promoting incorporation of novel information.

  4. Simultaneous activation of gamma and theta network oscillations in rat hippocampal slice cultures.

    PubMed

    Fischer, Yacov; Wittner, Lucia; Freund, Tamas F; Gähwiler, Beat H

    2002-03-15

    Hippocampal activity in vivo is characterized by concurrent oscillations at theta (4-15 Hz) and gamma (20-80 Hz) frequencies. Here we show that cholinergic receptor activation (methacholine 10-20 nm) in hippocampal slice cultures induces an oscillatory mode of activity, in which the intrinsic network oscillator (located in the CA3 area) expresses simultaneous theta and gamma network oscillations. Pyramidal cells display synaptic theta oscillations, characterized by cycles consisting of population EPSP-IPSP sequences that are dominated by population IPSPs. These rhythmic IPSPs most probably result from theta-modulated spiking activity of several interneurons. At the same time, the majority of interneurons consistently display synaptic gamma oscillations. These oscillatory cycles consist of fast depolarizing rhythmic events that are likely to reflect excitatory input from CA3 pyramidal cells. Interneurons comprising this functional group were identified morphologically. They include four known types of interneurons (basket, O-LM, bistratified and str. lucidum-specific cells) and one new type of CA3 interneuron (multi-subfield cell). The oscillatory activity of these interneurons is only weakly correlated between neighbouring cells, and in about half of these (44 %) is modulated by depolarizing theta rhythmicity. The overall characteristics of acetylcholine-induced oscillations in slice cultures closely resemble the rhythmicity observed in hippocampal field and single cell recordings in vivo. Both rhythmicities depend on intrinsic synaptic interactions, and are expressed by different cell types. The fact that these oscillations persist in a network lacking extra-hippocampal connections emphasizes the importance of intrinsic mechanisms in determining this form of hippocampal activity.

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

    PubMed

    Miyawaki, Hiroyuki; Diba, Kamran

    2016-04-04

    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.

  6. Fast synaptic inhibition promotes synchronized gamma oscillations in hippocampal interneuron networks

    PubMed Central

    Bartos, Marlene; Vida, Imre; Frotscher, Michael; Meyer, Axel; Monyer, Hannah; Geiger, Jörg R. P.; Jonas, Peter

    2002-01-01

    Networks of GABAergic interneurons are of critical importance for the generation of gamma frequency oscillations in the brain. To examine the underlying synaptic mechanisms, we made paired recordings from “basket cells” (BCs) in different subfields of hippocampal slices, using transgenic mice that express enhanced green fluorescent protein (EGFP) under the control of the parvalbumin promoter. Unitary inhibitory postsynaptic currents (IPSCs) showed large amplitude and fast time course with mean amplitude-weighted decay time constants of 2.5, 1.2, and 1.8 ms in the dentate gyrus, and the cornu ammonis area 3 (CA3) and 1 (CA1), respectively (33–34°C). The decay of unitary IPSCs at BC–BC synapses was significantly faster than that at BC–principal cell synapses, indicating target cell-specific differences in IPSC kinetics. In addition, electrical coupling was found in a subset of BC–BC pairs. To examine whether an interneuron network with fast inhibitory synapses can act as a gamma frequency oscillator, we developed an interneuron network model based on experimentally determined properties. In comparison to previous interneuron network models, our model was able to generate oscillatory activity with higher coherence over a broad range of frequencies (20–110 Hz). In this model, high coherence and flexibility in frequency control emerge from the combination of synaptic properties, network structure, and electrical coupling. PMID:12235359

  7. α2-containing GABAA receptors expressed in hippocampal region CA3 control fast network oscillations.

    PubMed

    Heistek, Tim S; Ruiperez-Alonso, Marta; Timmerman, A Jaap; Brussaard, Arjen B; Mansvelder, Huibert D

    2013-02-15

    GABA(A) receptors are critically involved in hippocampal oscillations. GABA(A) receptor α1 and α2 subunits are differentially expressed throughout the hippocampal circuitry and thereby may have distinct contributions to oscillations. It is unknown which GABA(A) receptor α subunit controls hippocampal oscillations and where these receptors are expressed. To address these questions we used transgenic mice expressing GABA(A) receptor α1 and/or α2 subunits with point mutations (H101R) that render these receptors insensitive to allosteric modulation at the benzodiazepine binding site, and tested how increased or decreased function of α subunits affects hippocampal oscillations. Positive allosteric modulation by zolpidem prolonged decay kinetics of hippocampal GABAergic synaptic transmission and reduced the frequency of cholinergically induced oscillations. Allosteric modulation of GABAergic receptors in CA3 altered oscillation frequency in CA1, while modulation of GABA receptors in CA1 did not affect oscillations. In mice having a point mutation (H101R) at the GABA(A) receptor α2 subunit, zolpidem effects on cholinergically induced oscillations were strongly reduced compared to wild-type animals, while zolpidem modulation was still present in mice with the H101R mutation at the α1 subunit. Furthermore, genetic knockout of α2 subunits strongly reduced oscillations, whereas knockout of α1 subunits had no effect. Allosteric modulation of GABAergic receptors was strongly reduced in unitary connections between fast spiking interneurons and pyramidal neurons in CA3 of α2H101R mice, but not of α1H101R mice, suggesting that fast spiking interneuron to pyramidal neuron synapses in CA3 contain α2 subunits. These findings suggest that α2-containing GABA(A) receptors expressed in the CA3 region provide the inhibition that controls hippocampal rhythm during cholinergically induced oscillations.

  8. Influence of slow oscillation on hippocampal activity and ripples through cortico-hippocampal synaptic interactions, analyzed by a cortical-CA3-CA1 network model

    PubMed Central

    Taxidis, Jiannis; Mizuseki, Kenji; Mason, Robert; Owen, Markus R.

    2013-01-01

    Hippocampal sharp wave-ripple complexes (SWRs) involve the synchronous discharge of thousands of cells throughout the CA3-CA1-subiculum-entorhinal cortex axis. Their strong transient output affects cortical targets, rendering SWRs a possible means for memory transfer from the hippocampus to the neocortex for long-term storage. Neurophysiological observations of hippocampal activity modulation by the cortical slow oscillation (SO) during deep sleep and anesthesia, and correlations between ripples and UP states, support the role of SWRs in memory consolidation through a cortico-hippocampal feedback loop. We couple a cortical network exhibiting SO with a hippocampal CA3-CA1 computational network model exhibiting SWRs, in order to model such cortico-hippocampal correlations and uncover important parameters and coupling mechanisms controlling them. The cortical oscillatory output entrains the CA3 network via connections representing the mossy fiber input, and the CA1 network via the temporoammonic pathway (TA). The spiking activity in CA3 and CA1 is shown to depend on the excitation-to-inhibition ratio, induced by combining the two hippocampal inputs, with mossy fiber input controlling the UP-state correlation of CA3 population bursts and corresponding SWRs, whereas the temporoammonic input affects the overall CA1 spiking activity. Ripple characteristics and pyramidal spiking participation to SWRs are shaped by the strength of the Schaffer collateral drive. A set of in vivo recordings from the rat hippocampus confirms a model-predicted segregation of pyramidal cells into subgroups according to the SO state where they preferentially fire and their response to SWRs. These groups can potentially play distinct functional roles in the replay of spike sequences. PMID:23386827

  9. Inhibitory control of intrinsic hippocampal oscillations?

    PubMed

    Fischer, Yacov; Dürr, Roland

    2003-08-22

    An oscillatory mode of activity is a basic operational mode of the hippocampus. Such activity involves the concurrent expression of several rhythmic processes, of which theta (4-15 Hz) and gamma (20-80 Hz) oscillations are prominent and considered to be important for cognitive processing. In an experimental model that preserves the intrinsic network oscillator, exhibiting the dependency on cholinergic inputs and consequent expression of concurrent theta and gamma oscillations, we investigate the intrinsic mechanisms underlying such integrated hippocampal network responses. This experimental framework is used here to examine the currently prevailing dogma, that interneurons control hippocampal oscillations. The spontaneous response of individual pyramidal cells (in areas CA3 and CA1) and interneurons (area CA3), during oscillatory activity, was monitored intracellularly. Particular attention was given to the initiation of interneuron discharge during oscillations, to the impact of the synaptic output of discharging interneurons on the oscillatory activity, and to the time at which interneurons discharge in relation to the oscillatory cycles. Analysis of the spontaneous patterns of activity in individual interneurons and their outcome, during the oscillatory activity, revealed that interneuron activity is incompatible with initiating, pacing or determining the oscillatory frequencies, although contributing to the apparent rhythmic patterns. Moreover, our results show that non-interneuronal members of the network control interneuron activity. We therefore suggest that the activity of the excitatory cells, i.e., principle cells, is critical toward the initiation, pacing and synchronization of intrinsic hippocampal network oscillations.

  10. 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

  11. CA3 Synaptic Silencing Attenuates Kainic Acid-Induced Seizures and Hippocampal Network Oscillations.

    PubMed

    Yu, Lily M Y; Polygalov, Denis; Wintzer, Marie E; Chiang, Ming-Ching; McHugh, Thomas J

    2016-01-01

    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.

  12. Ablation of neuropsin-neuregulin 1 signaling imbalances ErbB4 inhibitory networks and disrupts hippocampal gamma oscillation.

    PubMed

    Kawata, M; Morikawa, S; Shiosaka, S; Tamura, H

    2017-03-07

    Parvalbumin-expressing interneurons are pivotal for the processing of information in healthy brain, whereas the coordination of these functions is seriously disrupted in diseased brain. How these interneurons in the hippocampus participate in pathological functions remains unclear. We previously reported that neuregulin 1 (NRG1)-ErbB4 signaling, which is actuated by neuropsin, is important for coordinating brain plasticity. Neuropsin cleaves mature NRG1 (bound to extracellular glycosaminoglycans) in response to long-term potentiation or depression, liberating a soluble ligand that activates its receptor, ErbB4. Here, we show in mice that kainate-induced status epilepticus transiently elevates the proteolytic activity of neuropsin and stimulates cFos expression with a time course suggesting that activation of ErbB4- and parvalbumin-expressing interneurons follows the excitation and subsequent silencing of pyramidal neurons. In neuropsin-deficient mice, kainate administration impaired signaling and disrupted the neuronal excitation-inhibition balance (E/I balance) in hippocampal networks, by decreasing the activity of parvalbumin-positive interneurons while increasing that of pyramidal neurons, resulting in the progression of status epilepticus. Slow, but not fast, gamma oscillations in neuropsin-deficient mice showed reduced power. Intracerebroventricular infusion of the soluble NRG1 ligand moiety restored the E/I balance, status epilepticus and gamma oscillations to normal levels. These results suggest that the neuropsin-NRG1 signaling system has a role in pathological processes underlying temporal lobe epilepsy by regulating the activity of parvalbumin-expressing interneurons, and that neuropsin regulates E/I balance and gamma oscillations through NRG1-ErbB4 signaling toward parvalbumin-expressing interneurons. This neuronal system may be a useful target of pharmacological therapies against cognitive disorders.

  13. Nonspecific effects of the gap junction blocker mefloquine on fast hippocampal network oscillations in the adult rat in vitro.

    PubMed

    Behrens, C J; Ul Haq, R; Liotta, A; Anderson, M L; Heinemann, U

    2011-09-29

    It has been suggested that gap junctions are involved in the synchronization during high frequency oscillations as observed during sharp wave-ripple complexes (SPW-Rs) and during recurrent epileptiform discharges (REDs). Ripple oscillations during SPW-Rs, possibly involved in memory replay and memory consolidation, reach frequencies of up to 200 Hz while ripple oscillations during REDs display frequencies up to 500 Hz. These fast oscillations may be synchronized by intercellular interactions through gap junctions. In area CA3, connexin 36 (Cx36) proteins are present and potentially sensitive to mefloquine. Here, we used hippocampal slices of adult rats to investigate the effects of mefloquine, which blocks Cx36, Cx43 and Cx50 gap junctions on both SPW-Rs and REDs. SPW-Rs were induced by high frequency stimulation in the CA3 region while REDs were recorded in the presence of the GABA(A) receptor blocker bicuculline (5 μM). Both, SPW-Rs and REDs were blocked by the gap junction blocker carbenoxolone. Mefloquine (50 μM), which did not affect stimulus-induced responses in area CA3, neither changed SPW-Rs nor superimposed ripple oscillations. During REDs, 25 and 50 μM mefloquine exerted only minor effects on the expression of REDs but significantly reduced the amplitude of superimposed ripples by ∼17 and ∼54%, respectively. Intracellular recordings of CA3 pyramidal cells revealed that mefloquine did not change their resting membrane potential and input resistance but significantly increased the afterhyperpolarization following evoked action potentials (APs) resulting in reduced probability of AP firing during depolarizing current injection. Similarly, mefloquine caused a reduction in AP generation during REDs. Together, our data suggest that mefloquine depressed RED-related ripple oscillations by reducing high frequency discharges and not necessarily by blocking electrical coupling.

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

    PubMed

    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

  15. 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

  16. 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

  17. 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

  18. Rhythms of the hippocampal network

    PubMed Central

    Colgin, Laura Lee

    2016-01-01

    The hippocampal local field potential (LFP) exhibits three major types of rhythms, theta, sharp wave-ripples and gamma. These rhythms are defined by their frequencies, have behavioral correlates in several species including rats and humans, and have been proposed to perform distinct functions in hippocampal memory processing. However, recent findings have challenged traditional views on these behavioral functions. Here I review our current understanding of the origins and mnemonic functions of hippocampal theta, sharp-wave ripples and gamma rhythms based on findings from rodent studies, and present an updated, synthesized view of their roles and interactions within the hippocampal network. PMID:26961163

  19. 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.

  20. 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

  1. 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.

  2. Network synchronization in hippocampal neurons

    PubMed Central

    Penn, Yaron; Segal, Menahem; Moses, Elisha

    2016-01-01

    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

  3. 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.

  4. Nonlinear Neural Network Oscillator.

    DTIC Science & Technology

    A nonlinear oscillator (10) includes a neural network (12) having at least one output (12a) for outputting a one dimensional vector. The neural ... neural network and the input of the input layer for modifying a magnitude and/or a polarity of the one dimensional output vector prior to the sample of...first or a second direction. Connection weights of the neural network are trained on a deterministic sequence of data from a chaotic source or may be a

  5. Decreased rhythmic GABAergic septal activity and memory-associated theta oscillations after hippocampal amyloid-beta pathology in the rat.

    PubMed

    Villette, Vincent; Poindessous-Jazat, Frédérique; Simon, Axelle; Léna, Clément; Roullot, Elodie; Bellessort, Brice; Epelbaum, Jacques; Dutar, Patrick; Stéphan, Aline

    2010-08-18

    The memory deficits associated with Alzheimer's disease result to a great extent from hippocampal network dysfunction. The coordination of this network relies on theta (symbol) oscillations generated in the medial septum. Here, we investigated in rats the impact of hippocampal amyloid beta (Abeta) injections on the physiological and cognitive functions that depend on the septohippocampal system. Hippocampal Abeta injections progressively impaired behavioral performances, the associated hippocampal theta power, and theta frequency response in a visuospatial recognition test. These alterations were associated with a specific reduction in the firing of the identified rhythmic bursting GABAergic neurons responsible for the propagation of the theta rhythm to the hippocampus, but without loss of medial septal neurons. Such results indicate that hippocampal Abeta treatment leads to a specific functional depression of inhibitory projection neurons of the medial septum, resulting in the functional impairment of the temporal network.

  6. Relationships between hippocampal sharp waves, ripples and fast gamma oscillation: influence of dentate and entorhinal cortical activity

    PubMed Central

    Sullivan, David; Csicsvari, Jozsef; Mizuseki, Kenji; Montgomery, Sean; Diba, Kamran; Buzsáki, György

    2011-01-01

    Summary Hippocampal sharp waves (SPW) and associated fast (‘ripple’) oscillations in the CA1 region are among the most synchronous physiological patterns in the mammalian brain. Using two-dimensional arrays of electrodes for recording local field potentials and unit discharges in freely moving rats, we studied the emergence of ripple oscillations (140–220 Hz) and compared their origin and cellular-synaptic mechanisms with fast gamma oscillations (90–140 Hz). We show that (a) hippocampal SPW-Rs and fast gamma oscillations are quantitatively distinct patterns but involve the same networks and share similar mechanisms, (b) both the frequency and magnitude of fast oscillations is positively correlated with the magnitude of SPWs, (c) during both ripples and fast gamma oscillations the frequency of network oscillation is higher in CA1 than in CA3, (d) SPWs and associated firing of neurons are synchronous in the dorsal hippocampus and dorso-medial entorhinal cortex but ripples are confined to the CA1 pyramidal layer and its downstream targets and (e) the emergence of CA3 population bursts, a prerequisite for SPW-ripples, is biased by activity patterns in the dentate gyrus and entorhinal cortex, with highest probability of ripples associated with an ‘optimum’ level of dentate gamma power. We hypothesize that each hippocampal subnetwork possesses distinct resonant properties, tuned by the magnitude of the excitatory drive. PMID:21653864

  7. Coupled oscillators on evolving networks

    NASA Astrophysics Data System (ADS)

    Singh, R. K.; Bagarti, Trilochan

    2016-12-01

    In this work we study coupled oscillators on evolving networks. We find that the steady state behavior of the system is governed by the relative values of the spread in natural frequencies and the global coupling strength. For coupling strong in comparison to the spread in frequencies, the system of oscillators synchronize and when coupling strength and spread in frequencies are large, a phenomenon similar to amplitude death is observed. The network evolution provides a mechanism to build inter-oscillator connections and once a dynamic equilibrium is achieved, oscillators evolve according to their local interactions. We also find that the steady state properties change by the presence of additional time scales. We demonstrate these results based on numerical calculations studying dynamical evolution of limit-cycle and van der Pol oscillators.

  8. Hippocampal theta rhythm and its coupling with gamma oscillations require fast inhibition onto parvalbumin-positive interneurons.

    PubMed

    Wulff, Peer; Ponomarenko, Alexey A; Bartos, Marlene; Korotkova, Tatiana M; Fuchs, Elke C; Bähner, Florian; Both, Martin; Tort, Adriano B L; Kopell, Nancy J; Wisden, William; Monyer, Hannah

    2009-03-03

    Hippocampal theta (5-10 Hz) and gamma (35-85 Hz) oscillations depend on an inhibitory network of GABAergic interneurons. However, the lack of methods for direct and cell-type-specific interference with inhibition has prevented better insights that help link synaptic and cellular properties with network function. Here, we generated genetically modified mice (PV-Deltagamma(2)) in which synaptic inhibition was ablated in parvalbumin-positive (PV+) interneurons. Hippocampal local field potential and unit recordings in the CA1 area of freely behaving mice revealed that theta rhythm was strongly reduced in these mice. The characteristic coupling of theta and gamma oscillations was strongly altered in PV-Deltagamma(2) mice more than could be accounted for by the reduction in theta rhythm only. Surprisingly, gamma oscillations were not altered. These data indicate that synaptic inhibition onto PV+ interneurons is indispensable for theta- and its coupling to gamma oscillations but not for rhythmic gamma-activity in the hippocampus. Similar alterations in rhythmic activity were obtained in a computational hippocampal network model mimicking the genetic modification, suggesting that intrahippocampal networks might contribute to these effects.

  9. Mesopontine median raphe regulates hippocampal ripple oscillation and memory consolidation

    PubMed Central

    Wang, Dong V.; Yau, Hau-Jie; Broker, Carl J.; Tsou, Jen-Hui; Bonci, Antonello; Ikemoto, Satoshi

    2015-01-01

    Sharp-wave associated field-oscillations (~200 Hz) of the hippocampus, referred to as “ripples”, are believed to be important for consolidation of explicit memory. Little is known about how ripples are regulated by other brain regions. Here we show that the median raphe region (MnR) plays a key role in regulating hippocampal ripple activity and memory consolidation. We performed in vivo simultaneous recording in the MnR and hippocampus, and found that when a group of MnR neurons were active, ripples were absent. Consistently, optogenetic stimulation of MnR neurons suppressed ripple activity, while inhibition of these neurons increased ripple activity. Importantly, using a fear conditioning procedure, we provided evidence that photostimulation of MnR neurons interfered with memory consolidation. Our results demonstrate a critical role of the MnR in regulating ripples and memory consolidation. PMID:25867120

  10. Transient depression of excitatory synapses on interneurons contributes to epileptiform bursts during gamma oscillations in the mouse hippocampal slice.

    PubMed

    Traub, Roger D; Pais, Isabel; Bibbig, Andrea; Lebeau, Fiona E N; Buhl, Eberhard H; Garner, Helen; Monyer, Hannah; Whittington, Miles A

    2005-08-01

    Persistent gamma frequency (30-70 Hz) network oscillations occur in hippocampal slices under conditions of metabotropic glutamate receptor (mGluR) activation. Excessive mGluR activation generated a bistable pattern of network activity during which epochs of gamma oscillations of increasing amplitude were terminated by synchronized bursts and very fast oscillations (>70 Hz). We provide experimental evidence that, during this behavior, pyramidal cell-to-interneuron synaptic depression takes place, occurring spontaneously during the gamma rhythm and associated with the onset of epileptiform bursts. We further provide evidence that excitatory postsynaptic potentials (EPSPs) in pyramidal cells are potentiated during the interburst gamma oscillation. When these two types of synaptic plasticity are incorporated, phenomenologically, into a network model previously shown to account for many features of persistent gamma oscillations, we find that epochs of gamma do indeed alternate with epochs of very fast oscillations and epileptiform bursts. Thus the same neuronal network can generate either gamma oscillations or epileptiform bursts, in a manner depending on the degree of network drive and network-induced fluctuations in synaptic efficacies.

  11. Control of hippocampal gamma oscillation frequency by tonic inhibition and excitation of interneurons.

    PubMed

    Mann, Edward O; Mody, Istvan

    2010-02-01

    Gamma-frequency oscillations depend on phasic synaptic GABA(A) receptor (GABA(A)R)-mediated inhibition to synchronize spike timing. The spillover of synaptically released GABA can also activate extrasynaptic GABA(A)Rs, and such tonic inhibition may also contribute to modulating network dynamics. In many neuronal cell types, tonic inhibition is mediated by delta subunit-containing GABA(A)Rs. We found that the frequency of in vitro cholinergically induced gamma oscillations in the mouse hippocampal CA3 region was increased by the activation of NMDA receptors (NMDARs) on interneurons. The NMDAR-dependent increase of gamma oscillation frequency was counteracted by the tonic inhibition of the interneurons mediated by delta subunit-containing GABA(A)Rs. Recordings of synaptic currents during gamma activity revealed that NMDAR-mediated increases in oscillation frequency correlated with a progressive synchronization of phasic excitation and inhibition in the network. Thus, the balance between tonic excitation and tonic inhibition of interneurons may modulate gamma frequency by shaping interneuronal synchronization.

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

    PubMed

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

    2016-07-14

    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.

  13. 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

  14. Induction of long-term oscillations in the γ frequency band by nAChR activation in rat hippocampal CA3 area.

    PubMed

    Zhang, X; Ge, X Y; Wang, J G; Wang, Y L; Wang, Y; Yu, Y; Li, P P; Lu, C B

    2015-08-20

    The hippocampal neuronal network oscillation at γ frequency band (γ oscillation) is generated by the precise interaction between interneurons and principle cells. γ oscillation is associated with attention, learning and memory and is impaired in the diseased conditions such as Alzheimer's disease (AD) and schizophrenia. Nicotinic acetylcholine receptor (nAChR) plays an important role in the regulation of hippocampal neurotransmission and network activity. It is not known whether nicotine modulates plasticity of network activity at γ oscillations in the hippocampus. In this study we investigated the effects of nicotine on the long-term changes of KA-induced γ oscillations. We found that hippocampal γ oscillations can be enhanced by a low concentration of nicotine (1μM), such an enhancement lasts for hours after washing out of nicotine, suggesting a form of synaptic plasticity, named as long-term oscillation at γ frequency band (LTOγ). Nicotine-induced LTOγ was mimicked by the selective α4β2 but not by α7 nAChR agonist and was involved in N-methyl-d-aspartate (NMDA) receptor activation as well as depended on excitatory and inhibitory neurotransmission. Our results indicate that nAChR activation induced plasticity in γ oscillation, which may be beneficial for the improvement of cognitive deficiency in AD and schizophrenia.

  15. GABAergic contributions to gating, timing, and phase precession of hippocampal neuronal activity during theta oscillations.

    PubMed

    Cutsuridis, Vassilis; Hasselmo, Michael

    2012-07-01

    Successful spatial exploration requires gating, storage, and retrieval of spatial memories in the correct order. The hippocampus is known to play an important role in the temporal organization of spatial information. Temporally ordered spatial memories are encoded and retrieved by the firing rate and phase of hippocampal pyramidal cells and inhibitory interneurons with respect to ongoing network theta oscillations paced by intra- and extrahippocampal areas. Much is known about the anatomical, physiological, and molecular characteristics as well as the connectivity and synaptic properties of various cell types in the hippocampal microcircuits, but how these detailed properties of individual neurons give rise to temporal organization of spatial memories remains unclear. We present a model of the hippocampal CA1 microcircuit based on observed biophysical properties of pyramidal cells and six types of inhibitory interneurons: axo-axonic, basket, bistratistified, neurogliaform, ivy, and oriens lacunosum-moleculare cells. The model simulates a virtual rat running on a linear track. Excitatory transient inputs come from the entorhinal cortex (EC) and the CA3 Schaffer collaterals and impinge on both the pyramidal cells and inhibitory interneurons, whereas inhibitory inputs from the medial septum impinge only on the inhibitory interneurons. Dopamine operates as a gate-keeper modulating the spatial memory flow to the PC distal dendrites in a frequency-dependent manner. A mechanism for spike-timing-dependent plasticity in distal and proximal PC dendrites consisting of three calcium detectors, which responds to the instantaneous calcium level and its time course in the dendrite, is used to model the plasticity effects. The model simulates the timing of firing of different hippocampal cell types relative to theta oscillations, and proposes functional roles for the different classes of the hippocampal and septal inhibitory interneurons in the correct ordering of spatial memories

  16. Energy substrates that fuel fast neuronal network oscillations.

    PubMed

    Galow, Lukas V; Schneider, Justus; Lewen, Andrea; Ta, Thuy-Truc; Papageorgiou, Ismini E; Kann, Oliver

    2014-01-01

    Fast neuronal network oscillations in the gamma-frequency band (30--100 Hz) provide a fundamental mechanism of complex neuronal information processing in the hippocampus and neocortex of mammals. Gamma oscillations have been implicated in higher brain functions such as sensory perception, motor activity, and memory formation. The oscillations emerge from precise synapse interactions between excitatory principal neurons such as pyramidal cells and inhibitory GABAergic interneurons, and they are associated with high energy expenditure. However, both energy substrates and metabolic pathways that are capable to power cortical gamma oscillations have been less defined. Here, we investigated the energy sources fueling persistent gamma oscillations in the CA3 subfield of organotypic hippocampal slice cultures of the rat. This preparation permits superior oxygen supply as well as fast application of glucose, glycolytic metabolites or drugs such as glycogen phosphorylase inhibitor during extracellular recordings of the local field potential. Our findings are: (i) gamma oscillations persist in the presence of glucose (10 mmol/L) for greater than 60 min in slice cultures while (ii) lowering glucose levels (2.5 mmol/L) significantly reduces the amplitude of the oscillation. (iii) Gamma oscillations are absent at low concentration of lactate (2 mmol/L). (iv) Gamma oscillations persist at high concentration (20 mmol/L) of either lactate or pyruvate, albeit showing significant reductions in the amplitude. (v) The breakdown of glycogen significantly delays the decay of gamma oscillations during glucose deprivation. However, when glucose is present, the turnover of glycogen is not essential to sustain gamma oscillations. Our study shows that fast neuronal network oscillations can be fueled by different energy-rich substrates, with glucose being most effective.

  17. Energy substrates that fuel fast neuronal network oscillations

    PubMed Central

    Galow, Lukas V.; Schneider, Justus; Lewen, Andrea; Ta, Thuy-Truc; Papageorgiou, Ismini E.; Kann, Oliver

    2014-01-01

    Fast neuronal network oscillations in the gamma-frequency band (30–−100 Hz) provide a fundamental mechanism of complex neuronal information processing in the hippocampus and neocortex of mammals. Gamma oscillations have been implicated in higher brain functions such as sensory perception, motor activity, and memory formation. The oscillations emerge from precise synapse interactions between excitatory principal neurons such as pyramidal cells and inhibitory GABAergic interneurons, and they are associated with high energy expenditure. However, both energy substrates and metabolic pathways that are capable to power cortical gamma oscillations have been less defined. Here, we investigated the energy sources fueling persistent gamma oscillations in the CA3 subfield of organotypic hippocampal slice cultures of the rat. This preparation permits superior oxygen supply as well as fast application of glucose, glycolytic metabolites or drugs such as glycogen phosphorylase inhibitor during extracellular recordings of the local field potential. Our findings are: (i) gamma oscillations persist in the presence of glucose (10 mmol/L) for greater than 60 min in slice cultures while (ii) lowering glucose levels (2.5 mmol/L) significantly reduces the amplitude of the oscillation. (iii) Gamma oscillations are absent at low concentration of lactate (2 mmol/L). (iv) Gamma oscillations persist at high concentration (20 mmol/L) of either lactate or pyruvate, albeit showing significant reductions in the amplitude. (v) The breakdown of glycogen significantly delays the decay of gamma oscillations during glucose deprivation. However, when glucose is present, the turnover of glycogen is not essential to sustain gamma oscillations. Our study shows that fast neuronal network oscillations can be fueled by different energy-rich substrates, with glucose being most effective. PMID:25538552

  18. A distinctive subpopulation of medial septal slow-firing neurons promote hippocampal activation and theta oscillations

    PubMed Central

    Lin, Shih-Chieh; Nicolelis, Miguel A. L.

    2011-01-01

    The medial septum-vertical limb of the diagonal band of Broca (MSvDB) is important for normal hippocampal functions and theta oscillations. Although many previous studies have focused on understanding how MSVDB neurons fire rhythmic bursts to pace hippocampal theta oscillations, a significant portion of MSVDB neurons are slow-firing and thus do not pace theta oscillations. The function of these MSVDB neurons, especially their role in modulating hippocampal activity, remains unknown. We recorded MSVDB neuronal ensembles in behaving rats, and identified a distinct physiologically homogeneous subpopulation of slow-firing neurons (overall firing <4 Hz) that shared three features: 1) much higher firing rate during rapid eye movement sleep than during slow-wave (SW) sleep; 2) temporary activation associated with transient arousals during SW sleep; 3) brief responses (latency 15∼30 ms) to auditory stimuli. Analysis of the fine temporal relationship of their spiking and theta oscillations showed that unlike the theta-pacing neurons, the firing of these “pro-arousal” neurons follows theta oscillations. However, their activity precedes short-term increases in hippocampal oscillation power in the theta and gamma range lasting for a few seconds. Together, these results suggest that these pro-arousal slow-firing MSvDB neurons may function collectively to promote hippocampal activation. PMID:21865435

  19. Hippocampal strata theta oscillations change their frequency and coupling during spatial learning.

    PubMed

    Hernández-Pérez, J Jesús; Gutiérrez-Guzmán, Blanca E; Olvera-Cortés, María E

    2016-11-19

    The theta rhythm is necessary for hippocampal-dependent spatial learning. It has been proposed that each hippocampal stratum can generate a current theta dipole. Therefore, considering that each hippocampal circuit (CA1, CA3, and Dentate Gyrus (DG)) contributes differently to distinct aspects of a spatial memory, the theta oscillations on each stratum and their couplings may exhibit oscillatory dynamics associated with different stages of learning. To test this hypothesis, the theta oscillations from five hippocampal strata were recorded in the rat during different stages of learning in a Morris maze. The peak power, the relative power (RP) and the coherence between hippocampal strata were analyzed. The early acquisition stage of the Morris task was characterized by the predominance of slow frequency theta activity and high coupling between specific hippocampal strata at slow frequencies. However, on the last training day, the theta oscillations were faster in all hippocampal strata, with tighter coupling at fast frequencies between the CA3 pyramidal stratum and other strata. Our results suggest that modifications to the theta frequency and its coupling can be a means by which the hippocampus differentially operates during acquisition and retrieval states.

  20. Cerebellar theta oscillations are synchronized during hippocampal theta-contingent trace conditioning

    PubMed Central

    Hoffmann, Loren C.; Berry, Stephen D.

    2009-01-01

    The hippocampus and cerebellum are critically involved in trace eyeblink classical conditioning (EBCC). The mechanisms underlying the hippocampal-cerebellar interaction during this task are not well-understood, although hippocampal theta (3–7 Hz) oscillations are known to reflect a favorable state for EBCC. Two groups of rabbits received trace EBCC in which a brain-computer interface administered trials in either the explicit presence or absence of naturally occurring hippocampal theta. A high percentage of robust theta led to a striking enhancement of learning accompanied by rhythmic theta-band (6–7 Hz) oscillations in the interpositus nucleus (IPN) and cerebellar cortex that were time-locked both to hippocampal rhythms and sensory stimuli during training. Rhythmic oscillations were absent in the cerebellum of the non-theta group. These data strongly suggest a beneficial impact of theta-based coordination of hippocampus and cerebellum and, importantly, demonstrate that hippocampal theta oscillations can be used to index, and perhaps modulate, the functional properties of the cerebellum. PMID:19940240

  1. Hippocampal gamma-slow oscillation coupling in macaques during sedation and sleep.

    PubMed

    Richardson, Andrew G; Liu, Xilin; Weigand, Pauline K; Hudgins, Eric D; Stein, Joel M; Das, Sandhitsu R; Proekt, Alexander; Kelz, Max B; Zhang, Milin; Van der Spiegel, Jan; Lucas, Timothy H

    2017-07-01

    Behavioral and neurophysiological evidence suggests that the slow (≤1 Hz) oscillation (SO) during sleep plays a role in consolidating hippocampal (HIPP)-dependent memories. The effects of the SO on HIPP activity have been studied in rodents and cats both during natural sleep and during anesthetic administration titrated to mimic sleep-like slow rhythms. In this study, we sought to document these effects in primates. First, HIPP field potentials were recorded during ketamine-dexmedetomidine sedation and during natural sleep in three rhesus macaques. Sedation produced regionally-specific slow and gamma (∼40 Hz) oscillations with strong coupling between the SO phase and gamma amplitude. These same features were seen in slow-wave sleep (SWS), but the coupling was weaker and the coupled gamma oscillation had a higher frequency (∼70 Hz) during SWS. Second, electrical stimuli were delivered to HIPP afferents in the parahippocampal gyrus (PHG) during sedation to assess the effects of sleep-like SO on excitability. Gamma bursts after the peak of SO cycles corresponded to periods of increased gain of monosynaptic connections between the PHG and HIPP. However, the two PHG-HIPP connectivity gains during sedation were both substantially lower than when the animal was awake. We conclude that the SO is correlated with rhythmic excitation and inhibition of the PHG-HIPP network, modulating connectivity and gamma generators intrinsic to this network. Ketamine-dexmedetomidine sedation produces a similar effect, but with a decreased contribution of the PHG to HIPP activity and gamma generation. © 2017 Wiley Periodicals, Inc.

  2. Hippocampal synaptic and neural network deficits in young mice carrying the human APOE4 gene.

    PubMed

    Sun, Guo-Zhu; He, Yong-Chang; Ma, Xiao Kuang; Li, Shuang-Tao; Chen, De-Jie; Gao, Ming; Qiu, Shen-Feng; Yin, Jun-Xiang; Shi, Jiong; Wu, Jie

    2017-09-01

    Apolipoprotein E4 (APOE4) is a major genetic risk factor for late-onset sporadic Alzheimer disease. Emerging evidence demonstrates a hippocampus-associated learning and memory deficit in aged APOE4 human carriers and also in aged mice carrying human APOE4 gene. This suggests that either exogenous APOE4 or endogenous APOE4 alters the cognitive profile and hippocampal structure and function. However, little is known regarding how Apoe4 modulates hippocampal dendritic morphology, synaptic function, and neural network activity in young mice. In this study, we compared hippocampal dendritic and spine morphology and synaptic function of young (4 months) mice with transgenic expression of the human APOE4 and APOE3 genes. Hippocampal dendritic and spine morphology and synaptic function were assessed by neuronal imaging and electrophysiological approaches. Morphology results showed that shortened dendritic length and reduced spine density occurred at hippocampal CA1 neurons in Apoe4 mice compared to Apoe3 mice. Electrophysiological results demonstrated that in the hippocampal CA3-CA1 synapses of young Apoe4 mice, basic synaptic transmission, and paired-pulse facilitation were enhanced but long-term potentiation and carbachol-induced hippocampal theta oscillations were impaired compared to young Apoe3 mice. However, both Apoe genotypes responded similarly to persistent stimulations (4, 10, and 40 Hz for 4 seconds). Our results suggest significant alterations in hippocampal dendritic structure and synaptic function in Apoe4 mice, even at an early age. © 2017 John Wiley & Sons Ltd.

  3. 5-HT3a Receptors Modulate Hippocampal Gamma Oscillations by Regulating Synchrony of Parvalbumin-Positive Interneurons.

    PubMed

    Huang, Ying; Yoon, Kristopher; Ko, Ho; Jiao, Song; Ito, Wataru; Wu, Jian-Young; Yung, Wing-Ho; Lu, Bai; Morozov, Alexei

    2016-02-01

    Gamma-frequency oscillatory activity plays an important role in information integration across brain areas. Disruption in gamma oscillations is implicated in cognitive impairments in psychiatric disorders, and 5-HT3 receptors (5-HT3Rs) are suggested as therapeutic targets for cognitive dysfunction in psychiatric disorders. Using a 5-HT3aR-EGFP transgenic mouse line and inducing gamma oscillations by carbachol in hippocampal slices, we show that activation of 5-HT3aRs, which are exclusively expressed in cholecystokinin (CCK)-containing interneurons, selectively suppressed and desynchronized firings in these interneurons by enhancing spike-frequency accommodation in a small conductance potassium (SK)-channel-dependent manner. Parvalbumin-positive interneurons therefore received diminished inhibitory input leading to increased but desynchronized firings of PV cells. As a consequence, the firing of pyramidal neurons was desynchronized and gamma oscillations were impaired. These effects were independent of 5-HT3aR-mediated CCK release. Our results therefore revealed an important role of 5-HT3aRs in gamma oscillations and identified a novel crosstalk among different types of interneurons for regulation of network oscillations. The functional link between 5-HT3aR and gamma oscillations may have implications for understanding the cognitive impairments in psychiatric disorders.

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

    PubMed

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

    2011-10-15

    CB(1) cannabinoid receptor (CB(1)R) 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 CB(1)Rs. 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 CB(1)R 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 CB(1)R 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 CB(1)R activation suggesting that cannabinoids profoundly reduce the intrinsically generated oscillatory activities at distinct frequencies in CA3 networks by reducing synaptic neurotransmission.

  5. Synaptic currents in anatomically identified CA3 neurons during hippocampal gamma oscillations in vitro.

    PubMed

    Oren, Iris; Mann, Edward O; Paulsen, Ole; Hájos, Norbert

    2006-09-27

    Gamma-frequency oscillations are prominent during active network states in the hippocampus. An intrahippocampal gamma generator has been identified in the CA3 region. To better understand the synaptic mechanisms involved in gamma oscillogenesis, we recorded action potentials and synaptic currents in distinct types of anatomically identified CA3 neurons during carbachol-induced (20-25 microM) gamma oscillations in rat hippocampal slices. We wanted to compare and contrast the relationship between excitatory and inhibitory postsynaptic currents in pyramidal cells and perisomatic-targeting interneurons, cell types implicated in gamma oscillogenesis, as well as in other interneuron subtypes, and to relate synaptic currents to the firing properties of the cells. We found that phasic synaptic input differed between cell classes. Most strikingly, the dominant phasic input to pyramidal neurons was inhibitory, whereas phase-coupled perisomatic-targeting interneurons often received a strong phasic excitatory input. Differences in synaptic input could account for some of the differences in firing rate, action potential phase precision, and mean action potential phase angle, both between individual cells and between cell types. There was a strong positive correlation between the ratio of phasic synaptic excitation to inhibition and firing rate over all neurons and between the phase precision of excitation and action potentials in interneurons. Moreover, mean action potential phase angle correlated with the phase of the peak of the net-estimated synaptic reversal potential in all phase-coupled neurons. The data support a recurrent mechanism of gamma oscillations, whereby spike timing is controlled primarily by inhibition in pyramidal cells and by excitation in interneurons.

  6. Network mechanisms of gamma oscillations in the CA3 region of the hippocampus.

    PubMed

    Hájos, Norbert; Paulsen, Ole

    2009-10-01

    Neural networks of the brain display multiple patterns of oscillatory activity. Some of these rhythms are generated intrinsically within the local network, and can therefore be studied in isolated preparations. Here we discuss local-circuit mechanisms involved in hippocampal CA3 gamma oscillations, one of the best understood locally generated network patterns in the mammalian brain. Perisomatic inhibitory cells are crucial players in gamma oscillogenesis. They provide prominent rhythmic inhibition to CA3 pyramidal cells and are themselves synchronized primarily by excitatory synaptic inputs derived from the local collaterals of CA3 pyramidal cells. The recruitment of this recurrent excitatory-inhibitory feedback loop during hippocampal gamma oscillations suggests that local gamma oscillations not only control when, but also how many and which pyramidal cells will fire during each gamma cycle.

  7. 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

  8. Quantitative prediction of intermittent high-frequency oscillations in neural networks with supralinear dendritic interactions

    PubMed Central

    Memmesheimer, Raoul-Martin

    2010-01-01

    The explanation of higher neural processes requires an understanding of the dynamics of complex, spiking neural networks. So far, modeling studies have focused on networks with linear or sublinear dendritic input summation. However, recent single-neuron experiments have demonstrated strongly supralinear dendritic enhancement of synchronous inputs. What are the implications of this amplification for networks of neurons? Here, I show numerically and analytically that such networks can generate intermittent, strong increases of activity with high-frequency oscillations; the models developed predict the shape of these events and the oscillation frequency. As an example, for the hippocampal region CA1, events with 200-Hz oscillations are predicted. I argue that these dynamics provide a plausible explanation for experimentally observed sharp-wave/ripple events. High-frequency oscillations can involve the replay of spike patterns. The models suggest that these patterns may reflect underlying network structures. PMID:20511534

  9. Input-output features of anatomically identified CA3 neurons during hippocampal sharp wave/ripple oscillation in vitro.

    PubMed

    Hájos, Norbert; Karlócai, Mária R; Németh, Beáta; Ulbert, István; Monyer, Hannah; Szabó, Gábor; Erdélyi, Ferenc; Freund, Tamás F; Gulyás, Attila I

    2013-07-10

    Hippocampal sharp waves and the associated ripple oscillations (SWRs) are implicated in memory processes. These network events emerge intrinsically in the CA3 network. To understand cellular interactions that generate SWRs, we detected first spiking activity followed by recording of synaptic currents in distinct types of anatomically identified CA3 neurons during SWRs that occurred spontaneously in mouse hippocampal slices. We observed that the vast majority of interneurons fired during SWRs, whereas only a small portion of pyramidal cells was found to spike. There were substantial differences in the firing behavior among interneuron groups; parvalbumin-expressing basket cells were one of the most active GABAergic cells during SWRs, whereas ivy cells were silent. Analysis of the synaptic currents during SWRs uncovered that the dominant synaptic input to the pyramidal cell was inhibitory, whereas spiking interneurons received larger synaptic excitation than inhibition. The discharge of all interneurons was primarily determined by the magnitude and the timing of synaptic excitation. Strikingly, we observed that the temporal structure of synaptic excitation and inhibition during SWRs significantly differed between parvalbumin-containing basket cells, axoaxonic cells, and type 1 cannabinoid receptor (CB1)-expressing basket cells, which might explain their distinct recruitment to these synchronous events. Our data support the hypothesis that the active current sources restricted to the stratum pyramidale during SWRs originate from the synaptic output of parvalbumin-expressing basket cells. Thus, in addition to gamma oscillation, these GABAergic cells play a central role in SWR generation.

  10. Estradiol and raloxifene modulate hippocampal gamma oscillations during a spatial memory task.

    PubMed

    Schroeder, Anna; Hudson, Matthew; Du, Xin; Wu, Yee Wen Candace; Nakamura, Jay; van den Buuse, Maarten; Jones, Nigel C; Hill, Rachel A

    2017-04-01

    Previous work suggests that estradiol regulates the expression of hippocampal parvalbumin as well as hippocampus-dependent spatial memory in mice. Parvalbumin interneurons generate neuronal oscillatory activity in the gamma frequency range (30-80Hz) and gamma oscillations are closely linked with higher cognitive functions. Raloxifene, a selective estrogen receptor modulator, shows beneficial effects on human cognitive performance, and has few peripheral side effects unlike estradiol, but the biological mechanisms which underpin these benefits are not clear. This study aimed to investigate whether estradiol and raloxifene modulate hippocampal gamma-band oscillations during spatial memory performance. Prepubescent female mice were ovariectomized (OVX) and implanted with a subcutaneous pellet of either estradiol (E2), raloxifene or placebo. During adulthood, local field potentials were recorded from the dorsal hippocampus while mice were performing the Y-maze hippocampus-dependent spatial memory task. Ovariectomy caused deficits in spatial memory, accompanied by a significant reduction in hippocampal gamma oscillations, specifically during decision making. Estradiol as well as raloxifene rescued both behavioural and electrophysiological deficits. These data have significant implications for disorders of cognitive impairment where altered gamma oscillations are apparent, such as schizophrenia.

  11. Changes in Neuronal Oscillations Accompany the Loss of Hippocampal LTP that Occurs in an Animal Model of Psychosis

    PubMed Central

    Kalweit, Alexander N.; Amanpour-Gharaei, Bezhad; Colitti-Klausnitzer, Jens; Manahan-Vaughan, Denise

    2017-01-01

    The first-episode of psychosis is followed by a transient time-window of ca. 60 days during which therapeutic interventions have a higher likelihood of being effective than interventions that are started with a greater latency. This suggests that, in the immediate time-period after first-episode psychosis, functional changes occur in the brain that render it increasingly resistant to intervention. The precise mechanistic nature of these changes is unclear, but at the cognitive level, sensory and hippocampus-based dysfunctions become increasingly manifest. In an animal model of first-episode psychosis that comprises acute treatment of rats with the irreversible N-methyl-D-aspartate receptor (NMDAR)-antagonist, MK801, acute but also chronic deficits in long-term potentiation (LTP) and spatial memory occur. Neuronal oscillations, especially in the form of information transfer through θ and γ frequency oscillations are an intrinsic component of normal information processing in the hippocampus. Changes in θ-γ coupling and power are known to accompany deficits in hippocampal plasticity. Here, we examined whether changes in δ, θ, α, β and γ oscillations, or θ-γ coupling accompany the chronic loss of LTP that is observed in the MK801-animal model of psychosis. One and 4 weeks after acute systemic treatment of adult rats with MK801, a potent loss of hippocampal in vivo LTP was evident compared to vehicle-treated controls. Overall, the typical pattern of θ-γ oscillations that are characteristic for the successful induction of LTP was altered. In particular, θ-power was lower and an uncoupling of θ-γ oscillations was evident in MK801-treated rats. The alterations in network oscillations that accompany LTP deficits in this animal model may comprise a mechanism through which disturbances in sensory information processing and hippocampal function occur in psychosis. These data suggest that the hippocampus is likely to comprise a very early locus of functional

  12. PAN hollow fiber membranes elicit functional hippocampal neuronal network.

    PubMed

    Morelli, Sabrina; Piscioneri, Antonella; Salerno, Simona; Tasselli, Franco; Di Vito, Anna; Giusi, Giuseppina; Canonaco, Marcello; Drioli, Enrico; De Bartolo, Loredana

    2012-01-01

    This study focuses on the development of an advanced in vitro biohybrid culture model system based on the use of hollow fibre membranes (HFMs) and hippocampal neurons in order to promote the formation of a high density neuronal network. Polyacrylonitrile (PAN) and modified polyetheretherketone (PEEK-WC) membranes were prepared in hollow fibre configuration. The morphological and metabolic behaviour of hippocampal neurons cultured on PAN HF membranes were compared with those cultured on PEEK-WC HF. The differences of cell behaviour between HFMs were evidenced by the morphometric analysis in terms of axon length and also by the investigation of metabolic activity in terms of neurotrophin secretion. These findings suggested that PAN HFMs induced the in vitro reconstruction of very highly functional and complex neuronal networks. Thus, these biomaterials could potentially be used for the in vitro realization of a functional hippocampal tissue analogue for the study of neurobiological functions and/or neurodegenerative diseases.

  13. 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.

  14. 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.

  15. Asymmetry-induced synchronization in oscillator networks

    NASA Astrophysics Data System (ADS)

    Zhang, Yuanzhao; Nishikawa, Takashi; Motter, Adilson E.

    2017-06-01

    A scenario has recently been reported in which in order to stabilize complete synchronization of an oscillator network—a symmetric state—the symmetry of the system itself has to be broken by making the oscillators nonidentical. But how often does such behavior—which we term asymmetry-induced synchronization (AISync)—occur in oscillator networks? Here we present the first general scheme for constructing AISync systems and demonstrate that this behavior is the norm rather than the exception in a wide class of physical systems that can be seen as multilayer networks. Since a symmetric network in complete synchrony is the basic building block of cluster synchronization in more general networks, AISync should be common also in facilitating cluster synchronization by breaking the symmetry of the cluster subnetworks.

  16. Coupling functions in networks of oscillators

    NASA Astrophysics Data System (ADS)

    Stankovski, Tomislav; Ticcinelli, Valentina; McClintock, Peter V. E.; Stefanovska, Aneta

    2015-03-01

    Networks of interacting oscillators abound in nature, and one of the prevailing challenges in science is how to characterize and reconstruct them from measured data. We present a method of reconstruction based on dynamical Bayesian inference that is capable of detecting the effective phase connectivity within networks of time-evolving coupled phase oscillators subject to noise. It not only reconstructs pairwise, but also encompasses couplings of higher degree, including triplets and quadruplets of interacting oscillators. Thus inference of a multivariate network enables one to reconstruct the coupling functions that specify possible causal interactions, together with the functional mechanisms that underlie them. The characteristic features of the method are illustrated by the analysis of a numerically generated example: a network of noisy phase oscillators with time-dependent coupling parameters. To demonstrate its potential, the method is also applied to neuronal coupling functions from single- and multi-channel electroencephalograph recordings. The cross-frequency δ, α to α coupling function, and the θ, α, γ to γ triplet are computed, and their coupling strengths, forms of coupling function, and predominant coupling components, are analysed. The results demonstrate the applicability of the method to multivariate networks of oscillators, quite generally.

  17. 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.

  18. Driven synchronization in random networks of oscillators

    NASA Astrophysics Data System (ADS)

    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.

  19. Dedicated Hippocampal Inhibitory Networks for Locomotion and Immobility.

    PubMed

    Arriaga, Moises; Han, Edward B

    2017-09-20

    Network activity is strongly tied to animal movement; however, hippocampal circuits selectively engaged during locomotion or immobility remain poorly characterized. Here we examined whether distinct locomotor states are encoded differentially in genetically defined classes of hippocampal interneurons. To characterize the relationship between interneuron activity and movement, we used in vivo, two-photon calcium imaging in CA1 of male and female mice, as animals performed a virtual-reality (VR) track running task. We found that activity in most somatostatin-expressing and parvalbumin-expressing interneurons positively correlated with locomotion. Surprisingly, nearly one in five somatostatin or one in seven parvalbumin interneurons were inhibited during locomotion and activated during periods of immobility. Anatomically, the somata of somatostatin immobility-activated neurons were smaller than those of movement-activated neurons. Furthermore, immobility-activated interneurons were distributed across cell layers, with somatostatin-expressing cells predominantly in stratum oriens and parvalbumin-expressing cells mostly in stratum pyramidale. Importantly, each cell's correlation between activity and movement was stable both over time and across VR environments. Our findings suggest that hippocampal interneuronal microcircuits are preferentially active during either movement or immobility periods. These inhibitory networks may regulate information flow in "labeled lines" within the hippocampus to process information during distinct behavioral states.SIGNIFICANCE STATEMENT The hippocampus is required for learning and memory. Movement controls network activity in the hippocampus but it's unclear how hippocampal neurons encode movement state. We investigated neural circuits active during locomotion and immobility and found interneurons were selectively active during movement or stopped periods, but not both. Each cell's response to locomotion was consistent across time and

  20. The Influence of Cold Temperature on Cellular Excitability of Hippocampal Networks

    PubMed Central

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

    2012-01-01

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

  1. Cell type-specific tuning of hippocampal interneuron firing during gamma oscillations in vivo.

    PubMed

    Tukker, John J; Fuentealba, Pablo; Hartwich, Katja; Somogyi, Peter; Klausberger, Thomas

    2007-08-01

    Cortical gamma oscillations contribute to cognitive processing and are thought to be supported by perisomatic-innervating GABAergic interneurons. We performed extracellular recordings of identified interneurons in the hippocampal CA1 area of anesthetized rats, revealing that the firing patterns of five distinct interneuron types are differentially correlated to spontaneous gamma oscillations. The firing of bistratified cells, which target dendrites of pyramidal cells coaligned with the glutamatergic input from hippocampal area CA3, is strongly phase locked to field gamma oscillations. Parvalbumin-expressing basket, axo-axonic, and cholecystokinin-expressing interneurons exhibit moderate gamma modulation, whereas the spike timing of distal dendrite-innervating oriens-lacunosum moleculare interneurons is not correlated to field gamma oscillations. Cholecystokinin-expressing interneurons fire earliest in the gamma cycle, a finding that is consistent with their suggested function of thresholding individual pyramidal cells. Furthermore, we show that field gamma amplitude correlates with interneuronal spike-timing precision and firing rate. Overall, our recordings suggest that gamma synchronization in vivo is assisted by temporal- and domain-specific GABAergic inputs to pyramidal cells and is initiated in pyramidal cell dendrites in addition to somata and axon initial segments.

  2. 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

  3. Activation of 5-HT6 receptors modulates sleep-wake activity and hippocampal theta oscillation.

    PubMed

    Ly, Susanna; Pishdari, Bano; Lok, Ling Ling; Hajos, Mihaly; Kocsis, Bernat

    2013-01-16

    The modulatory role of 5-HT neurons and a number of different 5-HT receptor subtypes has been well documented in the regulation of sleep-wake cycles and hippocampal activity. A high level of 5-HT(6) receptor expression is present in the rat hippocampus. Further, hippocampal function has been shown to be modulated by both 5-HT(6) agonists and antagonists. In the current study, the potential involvement of 5-HT(6) receptors in the control of hippocampal theta rhythms and sleep-wake cycles has been investigated. Hippocampal activity was recorded by intracranial hippocampal electrodes both in anesthetized (n = 22) and in freely moving rats (n = 9). Theta rhythm was monitored in different sleep-wake states in freely moving rats and was elicited by stimulation of the brainstem reticular formation under anesthesia. Changes in theta frequency and power were analyzed before and after injection of the 5-HT(6) antagonist (SAM-531) and the 5-HT(6) agonist (EMD386088). In freely moving rats, EMD386088 suppressed sleep for several hours and significantly decreased theta peak frequency, while, in anesthetized rats, EMD386088 had no effect on theta power but significantly decreased theta frequency, which could be blocked by coadministration of SAM-531. SAM-531 alone did not change sleep-wake patterns and had no effect on theta parameters in both unanesthetized and anesthetized rats. Decreases in theta frequency induced by the 5-HT(6) receptor agonist correspond to previously described electrophysiological patterns shared by all anxiolytic drugs, and it is in line with its behavioral anxiolytic profile. The 5-HT(6) antagonist, however, failed to potentiate theta power, which is characteristic of many pro-cognitive substances, indicating that 5-HT(6) receptors might not tonically modulate hippocampal oscillations and sleep-wake patterns.

  4. 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.

  5. Hyperbolic geometry of Kuramoto oscillator networks

    NASA Astrophysics Data System (ADS)

    Chen, Bolun; Engelbrecht, Jan R.; Mirollo, Renato

    2017-09-01

    Kuramoto oscillator networks have the special property that their trajectories are constrained to lie on the (at most) 3D orbits of the Möbius group acting on the state space T N (the N-fold torus). This result has been used to explain the existence of the N-3 constants of motion discovered by Watanabe and Strogatz for Kuramoto oscillator networks. In this work we investigate geometric consequences of this Möbius group action. The dynamics of Kuramoto phase models can be further reduced to 2D reduced group orbits, which have a natural geometry equivalent to the unit disk \

  6. 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

  7. Organization of prefrontal network activity by respiration-related oscillations

    PubMed Central

    Biskamp, Jonatan; Bartos, Marlene; Sauer, Jonas-Frederic

    2017-01-01

    The medial prefrontal cortex (mPFC) integrates information from cortical and sub-cortical areas and contributes to the planning and initiation of behaviour. A potential mechanism for signal integration in the mPFC lies in the synchronization of neuronal discharges by theta (6–12 Hz) activity patterns. Here we show, using in vivo local field potential (LFP) and single-unit recordings from awake mice, that prominent oscillations in the sub-theta frequency band (1–5 Hz) emerge during awake immobility in the mPFC. These oscillation patterns are distinct from but phase-locked to hippocampal theta activity and occur synchronized with nasal respiration (hence termed prefrontal respiration rhythm [PRR]). PRR activity modulates the amplitude of prefrontal gamma rhythms with greater efficacy than theta oscillations. Furthermore, single-unit discharges of putative pyramidal cells and GABAergic interneurons are entrained by prefrontal PRR and nasal respiration. Our data thus suggest that PRR activity contributes to information processing in the prefrontal neuronal network. PMID:28349959

  8. Synchronization in Networks of Coupled Chemical Oscillators

    NASA Astrophysics Data System (ADS)

    Showalter, Kenneth; Tinsley, Mark; Nkomo, Simbarashe; Ke, Hua

    2014-03-01

    We have studied networks of coupled photosensitive chemical oscillators. Experiments and simulations are carried out on networks with different topologies and modes of coupling. We describe experimental and modeling studies of chimera and phase-cluster states and their relation to other synchronization states. Networks of integrate-and-fire oscillators are also studied in which sustained coordinated activity is exhibited. Individual nodes display incoherent firing events; however, a dominant frequency within the collective signal is exhibited. The introduction of spike-timing-dependent plasticity allows the network to evolve and leads to a stable unimodal link-weight distribution. M. R. Tinsley et al., Nature Physics 8, 662 (2012); S. Nkomo et al., Phys. Rev. Lett. 110, 244102 (2013); H. Ke et al., in preparation.

  9. Parvalbumin-expressing interneurons coordinate hippocampal network dynamics required for memory consolidation

    NASA Astrophysics Data System (ADS)

    Ognjanovski, Nicolette; Schaeffer, Samantha; Wu, Jiaxing; Mofakham, Sima; Maruyama, Daniel; Zochowski, Michal; Aton, Sara J.

    2017-04-01

    Activity in hippocampal area CA1 is essential for consolidating episodic memories, but it is unclear how CA1 activity patterns drive memory formation. We find that in the hours following single-trial contextual fear conditioning (CFC), fast-spiking interneurons (which typically express parvalbumin (PV)) show greater firing coherence with CA1 network oscillations. Post-CFC inhibition of PV+ interneurons blocks fear memory consolidation. This effect is associated with loss of two network changes associated with normal consolidation: (1) augmented sleep-associated delta (0.5-4 Hz), theta (4-12 Hz) and ripple (150-250 Hz) oscillations; and (2) stabilization of CA1 neurons' functional connectivity patterns. Rhythmic activation of PV+ interneurons increases CA1 network coherence and leads to a sustained increase in the strength and stability of functional connections between neurons. Our results suggest that immediately following learning, PV+ interneurons drive CA1 oscillations and reactivation of CA1 ensembles, which directly promotes network plasticity and long-term memory formation.

  10. Altered Network Timing in the CA3-CA1 Circuit of Hippocampal Slices from Aged Mice

    PubMed Central

    Kanak, Daniel J.; Rose, Gregory M.; Zaveri, Hitten P.; Patrylo, Peter R.

    2013-01-01

    Network patterns are believed to provide unique temporal contexts for coordinating neuronal activity within and across different regions of the brain. Some of the characteristics of network patterns modeled in vitro are altered in the CA3 or CA1 subregions of hippocampal slices from aged mice. CA3–CA1 network interactions have not been examined previously. We used slices from aged and adult mice to model spontaneous sharp wave ripples and carbachol-induced gamma oscillations, and compared measures of CA3–CA1 network timing between age groups. Coherent sharp wave ripples and gamma oscillations were evident in the CA3–CA1 circuit in both age groups, but the relative timing of activity in CA1 stratum pyramidale was delayed in the aged. In another sample of aged slices, evoked Schaffer collateral responses were attenuated in CA3 (antidromic spike amplitude) and CA1 (orthodromic field EPSP slope). However, the amplitude and timing of spontaneous sharp waves recorded in CA1 stratum radiatum were similar to adults. In both age groups unit activity recorded juxtacellularly from unidentified neurons in CA1 stratum pyramidale and stratum oriens was temporally modulated by CA3 ripples. However, aged neurons exhibited reduced spike probability during the early cycles of the CA3 ripple oscillation. These findings suggest that aging disrupts the coordination of patterned activity in the CA3–CA1 circuit. PMID:23593474

  11. Parvalbumin-expressing interneurons coordinate hippocampal network dynamics required for memory consolidation.

    PubMed

    Ognjanovski, Nicolette; Schaeffer, Samantha; Wu, Jiaxing; Mofakham, Sima; Maruyama, Daniel; Zochowski, Michal; Aton, Sara J

    2017-04-06

    Activity in hippocampal area CA1 is essential for consolidating episodic memories, but it is unclear how CA1 activity patterns drive memory formation. We find that in the hours following single-trial contextual fear conditioning (CFC), fast-spiking interneurons (which typically express parvalbumin (PV)) show greater firing coherence with CA1 network oscillations. Post-CFC inhibition of PV+ interneurons blocks fear memory consolidation. This effect is associated with loss of two network changes associated with normal consolidation: (1) augmented sleep-associated delta (0.5-4 Hz), theta (4-12 Hz) and ripple (150-250 Hz) oscillations; and (2) stabilization of CA1 neurons' functional connectivity patterns. Rhythmic activation of PV+ interneurons increases CA1 network coherence and leads to a sustained increase in the strength and stability of functional connections between neurons. Our results suggest that immediately following learning, PV+ interneurons drive CA1 oscillations and reactivation of CA1 ensembles, which directly promotes network plasticity and long-term memory formation.

  12. Parvalbumin-expressing interneurons coordinate hippocampal network dynamics required for memory consolidation

    PubMed Central

    Ognjanovski, Nicolette; Schaeffer, Samantha; Wu, Jiaxing; Mofakham, Sima; Maruyama, Daniel; Zochowski, Michal; Aton, Sara J.

    2017-01-01

    Activity in hippocampal area CA1 is essential for consolidating episodic memories, but it is unclear how CA1 activity patterns drive memory formation. We find that in the hours following single-trial contextual fear conditioning (CFC), fast-spiking interneurons (which typically express parvalbumin (PV)) show greater firing coherence with CA1 network oscillations. Post-CFC inhibition of PV+ interneurons blocks fear memory consolidation. This effect is associated with loss of two network changes associated with normal consolidation: (1) augmented sleep-associated delta (0.5–4 Hz), theta (4–12 Hz) and ripple (150–250 Hz) oscillations; and (2) stabilization of CA1 neurons’ functional connectivity patterns. Rhythmic activation of PV+ interneurons increases CA1 network coherence and leads to a sustained increase in the strength and stability of functional connections between neurons. Our results suggest that immediately following learning, PV+ interneurons drive CA1 oscillations and reactivation of CA1 ensembles, which directly promotes network plasticity and long-term memory formation. PMID:28382952

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

    PubMed Central

    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

  14. 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

  15. Fast network oscillations in vitro exhibit a slow decay of temporal auto-correlations.

    PubMed

    Poil, Simon-Shlomo; Jansen, Rick; van Aerde, Karlijn; Timmerman, Jaap; Brussaard, Arjen B; Mansvelder, Huibert D; Linkenkaer-Hansen, Klaus

    2011-08-01

    Ongoing neuronal oscillations in vivo exhibit non-random amplitude fluctuations as reflected in a slow decay of temporal auto-correlations that persist for tens of seconds. Interestingly, the decay of auto-correlations is altered in several brain-related disorders, including epilepsy, depression and Alzheimer's disease, suggesting that the temporal structure of oscillations depends on intact neuronal networks in the brain. Whether structured amplitude modulation occurs only in the intact brain or whether isolated neuronal networks can also give rise to amplitude modulation with a slow decay is not known. Here, we examined the temporal structure of cholinergic fast network oscillations in acute hippocampal slices. For the first time, we show that a slow decay of temporal correlations can emerge from synchronized activity in isolated hippocampal networks from mice, and is maximal at intermediate concentrations of the cholinergic agonist carbachol. Using zolpidem, a positive allosteric modulator of GABA(A) receptor function, we found that increased inhibition leads to longer oscillation bursts and more persistent temporal correlations. In addition, we asked if these findings were unique for mouse hippocampus, and we therefore analysed cholinergic fast network oscillations in rat prefrontal cortex slices. We observed significant temporal correlations, which were similar in strength to those found in mouse hippocampus and human cortex. Taken together, our data indicate that fast network oscillations with temporal correlations can be induced in isolated networks in vitro in different species and brain areas, and therefore may serve as model systems to investigate how altered temporal correlations in disease may be rescued with pharmacology. © 2011 The Authors. European Journal of Neuroscience © 2011 Federation of European Neuroscience Societies and Blackwell Publishing Ltd.

  16. Stochastic neural network model for spontaneous bursting in hippocampal slices.

    PubMed

    Biswal, B; Dasgupta, C

    2002-11-01

    A biologically plausible, stochastic, neural network model that exhibits spontaneous transitions between a low-activity (normal) state and a high-activity (epileptic) state is studied by computer simulation. Brief excursions of the network to the high-activity state lead to spontaneous population bursting similar to the behavior observed in hippocampal slices bathed in a high-potassium medium. Although the variability of interburst intervals in this model is due to stochasticity, first return maps of successive interburst intervals show trajectories that resemble the behavior expected near unstable periodic orbits (UPOs) of systems exhibiting deterministic chaos. Simulations of the effects of the application of chaos control, periodic pacing, and anticontrol to the network model yield results that are qualitatively similar to those obtained in experiments on hippocampal slices. Estimation of the statistical significance of UPOs through surrogate data analysis also leads to results that resemble those of similar analysis of data obtained from slice experiments and human epileptic activity. These results suggest that spontaneous population bursting in hippocampal slices may be a manifestation of stochastic bistable dynamics, rather than of deterministic chaos. Our results also question the reliability of some of the recently proposed, UPO-based, statistical methods for detecting determinism and chaos in experimental time-series data.

  17. 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

  18. Stability of amplitude chimeras in oscillator networks

    NASA Astrophysics Data System (ADS)

    Tumash, L.; Zakharova, A.; Lehnert, J.; Just, W.; Schöll, E.

    2017-01-01

    We show that amplitude chimeras in ring networks of Stuart-Landau oscillators with symmetry-breaking nonlocal coupling represent saddle-states in the underlying phase space of the network. Chimera states are composed of coexisting spatial domains of coherent and of incoherent oscillations. We calculate the Floquet exponents and the corresponding eigenvectors in dependence upon the coupling strength and range, and discuss the implications for the phase-space structure. The existence of at least one positive real part of the Floquet exponents indicates an unstable manifold in phase space, which explains the nature of these states as long-living transients. Additionally, we find a Stuart-Landau network of minimum size N = 12 exhibiting amplitude chimeras.

  19. Self-organized synchronous oscillations in a network of excitable cells coupled by gap junctions.

    PubMed

    Lewis, T J; Rinzel, J

    2000-11-01

    Recent evidence suggests that electrical coupling plays a role in generating oscillatory behaviour in networks of neurons; however, the underlying mechanisms have not been identified. Using a cellular automata model proposed by Traub et al (Traub R D, Schmitz D, Jefferys J G and Draguhn A 1999 High-frequency population oscillations are predicted to occur in hippocampal pyramidal neural networks interconnected by axo-axonal gap junctions Neuroscience 92 407-26), we describe a novel mechanism for self-organized oscillations in networks that have strong, sparse random electrical coupling via gap junctions. The network activity is generated by random spontaneous activity that is moulded into regular population oscillations by the propagation of activity through the network. We explain how this activity gives rise to particular dependences of mean oscillation frequency on network connectivity parameters and on the rate of spontaneous activity, and we derive analytical expressions to approximate the mean frequency and variance of the oscillations. In doing so, we provide insight into possible mechanisms for frequency control and modulation in networks of neurons.

  20. GABAergic hub neurons orchestrate synchrony in developing hippocampal networks.

    PubMed

    Bonifazi, P; Goldin, M; Picardo, M A; Jorquera, I; Cattani, A; Bianconi, G; Represa, A; Ben-Ari, Y; Cossart, R

    2009-12-04

    Brain function operates through the coordinated activation of neuronal assemblies. Graph theory predicts that scale-free topologies, which include "hubs" (superconnected nodes), are an effective design to orchestrate synchronization. Whether hubs are present in neuronal assemblies and coordinate network activity remains unknown. Using network dynamics imaging, online reconstruction of functional connectivity, and targeted whole-cell recordings in rats and mice, we found that developing hippocampal networks follow a scale-free topology, and we demonstrated the existence of functional hubs. Perturbation of a single hub influenced the entire network dynamics. Morphophysiological analysis revealed that hub cells are a subpopulation of gamma-aminobutyric acid-releasing (GABAergic) interneurons possessing widespread axonal arborizations. These findings establish a central role for GABAergic interneurons in shaping developing networks and help provide a conceptual framework for studying neuronal synchrony.

  1. 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.

  2. Synchronization of mobile chaotic oscillator networks

    SciTech Connect

    Fujiwara, Naoya; Kurths, Jürgen; Díaz-Guilera, Albert

    2016-09-15

    We study synchronization of systems in which agents holding chaotic oscillators move in a two-dimensional plane and interact with nearby ones forming a time dependent network. Due to the uncertainty in observing other agents' states, we assume that the interaction contains a certain amount of noise that turns out to be relevant for chaotic dynamics. We find that a synchronization transition takes place by changing a control parameter. But this transition depends on the relative dynamic scale of motion and interaction. When the topology change is slow, we observe an intermittent switching between laminar and burst states close to the transition due to small noise. This novel type of synchronization transition and intermittency can happen even when complete synchronization is linearly stable in the absence of noise. We show that the linear stability of the synchronized state is not a sufficient condition for its stability due to strong fluctuations of the transverse Lyapunov exponent associated with a slow network topology change. Since this effect can be observed within the linearized dynamics, we can expect such an effect in the temporal networks with noisy chaotic oscillators, irrespective of the details of the oscillator dynamics. When the topology change is fast, a linearized approximation describes well the dynamics towards synchrony. These results imply that the fluctuations of the finite-time transverse Lyapunov exponent should also be taken into account to estimate synchronization of the mobile contact networks.

  3. Synchronization of mobile chaotic oscillator networks

    NASA Astrophysics Data System (ADS)

    Fujiwara, Naoya; Kurths, Jürgen; Díaz-Guilera, Albert

    2016-09-01

    We study synchronization of systems in which agents holding chaotic oscillators move in a two-dimensional plane and interact with nearby ones forming a time dependent network. Due to the uncertainty in observing other agents' states, we assume that the interaction contains a certain amount of noise that turns out to be relevant for chaotic dynamics. We find that a synchronization transition takes place by changing a control parameter. But this transition depends on the relative dynamic scale of motion and interaction. When the topology change is slow, we observe an intermittent switching between laminar and burst states close to the transition due to small noise. This novel type of synchronization transition and intermittency can happen even when complete synchronization is linearly stable in the absence of noise. We show that the linear stability of the synchronized state is not a sufficient condition for its stability due to strong fluctuations of the transverse Lyapunov exponent associated with a slow network topology change. Since this effect can be observed within the linearized dynamics, we can expect such an effect in the temporal networks with noisy chaotic oscillators, irrespective of the details of the oscillator dynamics. When the topology change is fast, a linearized approximation describes well the dynamics towards synchrony. These results imply that the fluctuations of the finite-time transverse Lyapunov exponent should also be taken into account to estimate synchronization of the mobile contact networks.

  4. Network state-dependent inhibition of identified hippocampal CA3 axo-axonic cells in vivo.

    PubMed

    Viney, Tim J; Lasztoczi, Balint; Katona, Linda; Crump, Michael G; Tukker, John J; Klausberger, Thomas; Somogyi, Peter

    2013-12-01

    Hippocampal sharp waves are population discharges initiated by an unknown mechanism in pyramidal cell networks of CA3. Axo-axonic cells (AACs) regulate action potential generation through GABAergic synapses on the axon initial segment. We found that CA3 AACs in anesthetized rats and AACs in freely moving rats stopped firing during sharp waves, when pyramidal cells fire most. AACs fired strongly and rhythmically around the peak of theta oscillations, when pyramidal cells fire at low probability. Distinguishing AACs from other parvalbumin-expressing interneurons by their lack of detectable SATB1 transcription factor immunoreactivity, we discovered a somatic GABAergic input originating from the medial septum that preferentially targets AACs. We recorded septo-hippocampal GABAergic cells that were activated during hippocampal sharp waves and projected to CA3. We hypothesize that inhibition of AACs, and the resulting subcellular redistribution of inhibition from the axon initial segment to other pyramidal cell domains, is a necessary condition for the emergence of sharp waves promoting memory consolidation.

  5. Effects of Selective M1 Muscarinic Receptor Activation on Hippocampal Spatial Representations and Neuronal Oscillations.

    PubMed

    Lebois, Evan P; Trimper, John B; Hu, Chun; Levey, Allan I; Manns, Joseph R

    2016-10-19

    The muscarinic M1 acetylcholine receptor is a key target for drugs aimed at treating cognitive dysfunction, including the memory impairment in Alzheimer's disease. The overall question of the current study was to ask how systemic administration of the bitopic M1 agonist VU0364572, the M1 positive allosteric modulator BQCA, and the acetylcholinesterase inhibitor donepezil (current standard of care for Alzheimer's disease), would impact spatial memory-related hippocampal function in rats. Hippocampal pyramidal neuron spiking and local field potentials were recorded from regions CA1 and CA3 as rats freely foraged in a recording enclosure. To assess the relative stability versus flexibility of the rats' spatial representations, the walls of the recording enclosure were reshaped in 15-m intervals. As compared to the control condition, systemic administration of VU0364572 increased spatial correlations of CA1 and CA3 pyramidal neuron spiking across all enclosure shape comparisons, whereas BQCA and donepezil appeared to decrease these spatial correlations. Further, both VU0364572 and BQCA increased intrahippocampal synchrony as measured by CA3-CA1 field-field coherence in frequency ranges that tended to align with the prominence of those oscillations for the behavioral state (i.e., theta during locomotion and slow gamma during stationary moments). The results indicated that VU0364572 and BQCA influenced hippocampal function differently but in ways that might both be beneficial for treating memory dysfunction.

  6. 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

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

    PubMed Central

    Kay, K.; Sosa, M.; Chung, J.E.; Karlsson, M.P.; Larkin, M.C.; Frank, L.M.

    2016-01-01

    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 stood unresolved. Here we report that a distinct population of hippocampal neurons, located in the CA2 subregion, signals current location during immobility, and furthermore does so in association with a previously unidentified hippocampus-wide network pattern. In addition, signaling 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

  8. 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

  9. Chimera states in mechanical oscillator networks.

    PubMed

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

    2013-06-25

    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.

  10. Traumatic alterations in GABA signaling disrupt hippocampal network activity in the developing brain

    PubMed Central

    Dzhala, Volodymyr; Valeeva, Guzel; Glykys, Joseph; Khazipov, Rustem; Staley, Kevin

    2012-01-01

    Severe head trauma causes widespread neuronal shear injuries and acute seizures. Shearing of neural processes might contribute to seizures by disrupting the transmembrane ion gradients that subserve normal synaptic signaling. To test this possibility, we investigated changes in intracellular chloride concentration ([Cl−]i) associated with the widespread neural shear injury induced during preparation of acute brain slices. In hippocampal slices and intact hippocampal preparations from immature CLM-1 mice, increases in [Cl−]i correlated with disruption of neural processes and biomarkers of cell injury. Traumatized neurons with higher [Cl−]i demonstrated excitatory GABA signaling, remained synaptically active, and facilitated network activity as assayed by the frequency of extracellular action potentials and spontaneous network-driven oscillations. These data support a more inhibitory role for GABA in the unperturbed immature brain, demonstrate the utility of the acute brain slice preparation for the study of the consequences of trauma, and provide potential mechanisms for both GABA-mediated excitatory network events in the slice preparation and early post-traumatic seizures. PMID:22442068

  11. Collective oscillations in disordered neural networks.

    PubMed

    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-->infinity , 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/N{2}, analogously to the scaling found for the "splay state."

  12. 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.

  13. Spatio-temporal characterization imaging of Ca2+ oscillations in rat hippocampal neurons

    NASA Astrophysics Data System (ADS)

    Zhang, Zhihong; Lu, Jinling; Zhou, Wei; Liu, Rengang; Zeng, Shaoqun; Luo, Qingming

    2001-08-01

    Ca2+ is the most common signal transduction element in cells and plays critical rolls in neuronal development and plasticity. Ca2+ signals encode information in their oscillation frequency or amplitude and response time to regular cellular function. In this study, in order to reveal the spatio-temporal characterization of Ca2+ oscillations in rat hippocampal neurons, two kinds of Ca2+ fluorescent probes, yellow cameleons 2.1 (YC2.1) and Fluo-3, were used to monitor the change of the intracellular free Ca2+ concentration (]Ca2+[i). Spontaneous Ca2+ oscillations and glutamate elicited Ca2+ oscillations were observed with multi-photon excitation laser scan microscope (MPELSM) and confocal laser scan microscope (CLSM). The observation showed that the spatio- temporal characterization of either spontaneous or glutamate provoked Ca2+ oscillations had difference between the neurites and somata in individual nerons, especially in some distal end of neurites. The result indicated that Ca2+ oscillations were most important signal transduction pattern in neuronal development and activation. The spatio-temporal characterization of difference of Ca2+ signals between the distal endo of neurites and the somata might be associated with the distribution of ionotropic receptor and metabotropic glutamate receptors, and Ca2+ response mechanism mediated by two kinds of glutamate receptor. Ca2+ signal elicited by glutamate in the distal end of neurites appeared more complex and generated faster than that in the somata. It was suggested that Ca2+ signal in glutamate stimulated hippacamal neurons first generated from the distal end of neurites and then transduted to the somata. The complicated Ca2+ signal characterization in the distal end of neurites might be associated with neuronal activitation, neurotransmitter releasing, and other functions of neurons.

  14. Energy deprivation transiently enhances rhythmic inhibitory events in the CA3 hippocampal network in vitro.

    PubMed

    Gee, C E; Benquet, P; Demont-Guignard, S; Wendling, F; Gerber, U

    2010-07-14

    Oxygen glucose deprivation (OGD) leads to rapid suppression of synaptic transmission. Here we describe an emergence of rhythmic activity at 8 to 20 Hz in the CA3 subfield of hippocampal slice cultures occurring for a few minutes prior to the OGD-induced cessation of evoked responses. These oscillations, dominated by inhibitory events, represent network activity, as they were abolished by tetrodotoxin. They were also completely blocked by the GABAergic antagonist picrotoxin, and strongly reduced by the glutamatergic antagonist NBQX. Applying CPP to block NMDA receptors had no effect and neither did UBP302, an antagonist of GluK1-containing kainate receptors. The gap junction blocker mefloquine disrupted rhythmicity. Simultaneous whole-cell voltage-clamp recordings from neighboring or distant CA3 pyramidal cells revealed strong cross-correlation of the incoming rhythmic activity. Interneurons in the CA3 area received similar correlated activity. Interestingly, oscillations were much less frequently observed in the CA1 area. These data, together with the observation that the recorded activity consists primarily of inhibitory events, suggest that CA3 interneurons are important for generating these oscillations. This transient increase in inhibitory network activity during OGD may represent a mechanism contributing to the lower vulnerability to ischemic insults of the CA3 area as compared to the CA1 area.

  15. 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.

  16. Multiple Kinases Involved in the Nicotinic Modulation of Gamma Oscillations in the Rat Hippocampal CA3 Area

    PubMed Central

    Wang, JianGang; He, XiaoLong; Guo, Fangli; Cheng, XiangLin; Wang, Yali; Wang, XiaoFang; Feng, ZhiWei; Vreugdenhil, Martin; Lu, ChengBiao

    2017-01-01

    Neuronal synchronization at gamma band frequency (20–80 Hz, γ oscillations) is closely associated with higher brain function, such as learning, memory and attention. Nicotinic acetylcholine receptors (nAChRs) are highly expressed in the hippocampus, and modulate hippocampal γ oscillations, but the intracellular mechanism underlying such modulation remains elusive. We explored multiple kinases by which nicotine can modulate γ oscillations induced by kainate in rat hippocampal area CA3 in vitro. We found that inhibitors of cyclic AMP dependent kinase (protein kinase A, PKA), protein kinase C (PKC), N-methyl-D-aspartate receptor (NMDA) receptors, Phosphoinositide 3-kinase (PI3K) and extracellular signal-related kinases (ERK), each individually could prevent the γ oscillation-enhancing effect of 1 μM nicotine, whereas none of them affected baseline γ oscillation strength. Inhibition of the serine/threonine kinase Akt increased baseline γ oscillations and partially blocked its nicotinic enhancement. We propose that the PKA-NMDAR-PI3K-ERK pathway modifies cellular properties required for the nicotinic enhancement of γ oscillations, dependent on a PKC-ERK mediated pathway. These signaling pathways provide clues for restoring γ oscillations in pathological conditions affecting cognition. The suppression of γ oscillations at 100 μM nicotine was only dependent on PKA-NMDAR activation and may be due to very high intracellular calcium levels. PMID:28321180

  17. Predicting synchronous and asynchronous network groupings of hippocampal interneurons coupled with dendritic gap junctions.

    PubMed

    Zahid, Tariq; Skinner, Frances K

    2009-03-25

    Direct electrical communication between central nervous system (CNS) neurons including those in the hippocampus is well-established. This form of communication is mediated by gap junctions and it is known that this coupling is important for brain rhythms such as gamma (20-80 Hz) which occur during active behavioural states. It is also known that gap junctions are present at several locations along the dendrites of hippocampal interneurons including parvalbumin-positive basket cell types. Weakly coupled oscillator theory, which uses phase response curves (PRCs), has been used to understand and predict the dynamics of electrically coupled networks. Here we use compartmental models of hippocampal basket cells with different levels of basal and apical spike attenuation together with the theory to show that network output can be broken down into three groupings: synchronous, asynchronous and antiphase-like patterns. Moreover, quantified PRCs can be used as a rule of thumb to determine the occurrence of a particular grouping under weak coupling conditions, which in turn implies that spike delays are critical factors in determining network output. In moving beyond weak coupling to encompass the full physiological regime of coupling strengths with network simulations, we note that it is important to be able to differentiate between these different groupings as it affects how the network responds with modulation. Specifically, an asynchronous grouping provides more dynamic richness as a larger range of phase-locked states can be expressed with strength changes. From a functional viewpoint it may be that modulation of electrically coupled networks are key to controlling cell assemblies that contribute to information coding brain substrates.

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

    PubMed

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

    2011-06-14

    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.

  19. Reorganization of anterior and posterior hippocampal networks associated with memory performance in mesial temporal lobe epilepsy.

    PubMed

    Li, Hong; Ji, Caihong; Zhu, Lujia; Huang, Peiyu; Jiang, Biao; Xu, Xiaojun; Sun, Jianzhong; Chen, Zhong; Ding, Meiping; Zhang, Minming; Wang, Shuang

    2017-05-01

    To investigate the pattern of functional demarcation of hippocampal network and its relationship with memory performance in mesial temporal lobe epilepsy (mTLE) with unilateral hippocampal sclerosis. Resting state fMRI data were acquired from fifteen left mTLE patients, fourteen right mTLE patients and twenty healthy subjects. We explore the hippocampal-cortical alterations and corresponding inter-hemispheric functional connectivity (FC) across anterior and posterior hippocampal networks. The association between FC and memory performance was assessed. Left mTLE showed increased intra-hemispheric FC in anterior hippocampal networks, including left anterior hippocampal-entorhinal cortex and right anterior hippocampal-orbitofrontal cortex, and decreased inter-hemispheric FC between anterior hippocampus, entorhinal cortex and posterior cingulate cortex. Right mTLE was associated with extensive reduction in inter-hemispheric FC along the areas of anterior and posterior hippocampal networks. Intra-hemispheric FC between left anterior hippocampus and entorhinal cortex was positively correlated with verbal memory in left mTLE. Inter-hemispheric FC between posterior parahippocampal gyrus was negatively correlated with verbal memory in right mTLE. Our findings suggested that left and right mTLE exhibit different neural reorganization patterns of anterior and posterior hippocampal networks associated with verbal memory. The findings may facilitate the characterization of mTLE associated with memory deficit. Copyright © 2017 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

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

    PubMed

    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.

  1. 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

  2. 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.

  3. 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

  4. Subthreshold membrane-potential oscillations in immature rat CA3 hippocampal neurones.

    PubMed

    Psarropoulou, C; Avoli, M

    1995-12-15

    Subthreshold membrane potential oscillations (MPOs) were recorded intracellularly in 31 of 43 (>70%) immature CA3 hippocampal neurones (from 3-17 days postnatally). MPOs (3-5 mV, 3-15 Hz) occurred at resting membrane potential (RMP) in 20 of 31 neurones, or following depolarization (11 of 31 neurones); with sufficient depolarization spontaneous action potentials (APs) were generated from the positive-going phase of MPOs. In all cells, MPOs were blocked by steady membrane hyperpolarization. Tetrodotoxin abolished MPOs (n = 4); Co(2+) markedly reduced them (n = 3), and tetraethylammonium, added in the presence of TTX, revealed lower frequency oscillatory activity (n = 2). We conclude that subthreshold MPOs in immature hippocampus, possibly linked to theta rhythm generation and memory acquisition, depend on voltage-dependent Na+ electrogenesis and they might be additionally controlled by Ca(2+) and K+ conductances.

  5. Orexin signaling regulates both the hippocampal clock and the circadian oscillation of Alzheimer’s disease-risk genes

    PubMed Central

    Ma, Zhixiong; Jiang, Weiliang; Zhang, Eric Erquan

    2016-01-01

    Alzheimer’s disease (AD) is a circadian clock-related disease. However, it is not very clear whether pre-symptomatic AD leads to circadian disruption or whether malfunction of circadian rhythms exerts influence on development of AD. Here, we report a functional clock that exists in the hippocampus. This oscillator both receives input signals and maintains the cycling of the hippocampal Per2 gene. One of the potential inputs to the oscillator is orexin signaling, which can shorten the hippocampal clock period and thereby regulate the expression of clock-controlled-genes (CCGs). A 24-h time course qPCR analysis followed by a JTK_CYCLE algorithm analysis indicated that a number of AD-risk genes are potential CCGs in the hippocampus. Specifically, we found that Bace1 and Bace2, which are related to the production of the amyloid-beta peptide, are CCGs. BACE1 is inhibited by E4BP4, a repressor of D-box genes, while BACE2 is activated by CLOCK:BMAL1. Finally, we observed alterations in the rhythmic expression patterns of Bace2 and ApoE in the hippocampus of aged APP/PS1dE9 mice. Our results therefore indicate that there is a circadian oscillator in the hippocampus whose oscillation could be regulated by orexins. Hence, orexin signaling regulates both the hippocampal clock and the circadian oscillation of AD-risk genes. PMID:27796320

  6. Orexin signaling regulates both the hippocampal clock and the circadian oscillation of Alzheimer's disease-risk genes.

    PubMed

    Ma, Zhixiong; Jiang, Weiliang; Zhang, Eric Erquan

    2016-10-31

    Alzheimer's disease (AD) is a circadian clock-related disease. However, it is not very clear whether pre-symptomatic AD leads to circadian disruption or whether malfunction of circadian rhythms exerts influence on development of AD. Here, we report a functional clock that exists in the hippocampus. This oscillator both receives input signals and maintains the cycling of the hippocampal Per2 gene. One of the potential inputs to the oscillator is orexin signaling, which can shorten the hippocampal clock period and thereby regulate the expression of clock-controlled-genes (CCGs). A 24-h time course qPCR analysis followed by a JTK_CYCLE algorithm analysis indicated that a number of AD-risk genes are potential CCGs in the hippocampus. Specifically, we found that Bace1 and Bace2, which are related to the production of the amyloid-beta peptide, are CCGs. BACE1 is inhibited by E4BP4, a repressor of D-box genes, while BACE2 is activated by CLOCK:BMAL1. Finally, we observed alterations in the rhythmic expression patterns of Bace2 and ApoE in the hippocampus of aged APP/PS1dE9 mice. Our results therefore indicate that there is a circadian oscillator in the hippocampus whose oscillation could be regulated by orexins. Hence, orexin signaling regulates both the hippocampal clock and the circadian oscillation of AD-risk genes.

  7. Restoration of oscillation in network of oscillators in presence of direct and indirect interactions

    NASA Astrophysics Data System (ADS)

    Majhi, Soumen; Bera, Bidesh K.; Bhowmick, Sourav K.; Ghosh, Dibakar

    2016-10-01

    The suppression of oscillations in coupled systems may lead to several unwanted situations, which requires a suitable treatment to overcome the suppression. In this paper, we show that the environmental coupling in the presence of direct interaction, which can suppress oscillation even in a network of identical oscillators, can be modified by introducing a feedback factor in the coupling scheme in order to restore the oscillation. We inspect how the introduction of the feedback factor helps to resurrect oscillation from various kinds of death states. We numerically verify the resurrection of oscillations for two paradigmatic limit cycle systems, namely Landau-Stuart and Van der Pol oscillators and also in generic chaotic Lorenz oscillator. We also study the effect of parameter mismatch in the process of restoring oscillation for coupled oscillators.

  8. Synchronization in hybrid neuronal networks of the hippocampal formation.

    PubMed

    Netoff, Theoden I; Banks, Matthew I; Dorval, Alan D; Acker, Corey D; Haas, Julie S; Kopell, Nancy; White, John A

    2005-03-01

    Understanding the mechanistic bases of neuronal synchronization is a current challenge in quantitative neuroscience. We studied this problem in two putative cellular pacemakers of the mammalian hippocampal theta rhythm: glutamatergic stellate cells (SCs) of the medial entorhinal cortex and GABAergic oriens-lacunosum-molecular (O-LM) interneurons of hippocampal region CA1. We used two experimental methods. First, we measured changes in spike timing induced by artificial synaptic inputs applied to individual neurons. We then measured responses of free-running hybrid neuronal networks, consisting of biological neurons coupled (via dynamic clamp) to biological or virtual counterparts. Results from the single-cell experiments predicted network behaviors well and are compatible with previous model-based predictions of how specific membrane mechanisms give rise to empirically measured synchronization behavior. Both cell types phase lock stably when connected via homogeneous excitatory-excitatory (E-E) or inhibitory-inhibitory (I-I) connections. Phase-locked firing is consistently synchronous for either cell type with E-E connections and nearly anti-synchronous with I-I connections. With heterogeneous connections (e.g., excitatory-inhibitory, as might be expected if members of a given population had heterogeneous connections involving intermediate interneurons), networks often settled into phase locking that was either stable or unstable, depending on the order of firing of the two cells in the hybrid network. Our results imply that excitatory SCs, but not inhibitory O-LM interneurons, are capable of synchronizing in phase via monosynaptic mutual connections of the biologically appropriate polarity. Results are largely independent of synaptic strength and synaptic kinetics, implying that our conclusions are robust and largely unaffected by synaptic plasticity.

  9. Anxious and nonanxious mice show similar hippocampal sensory evoked oscillations under urethane anesthesia: difference in the effect of buspirone.

    PubMed

    Horváth, János; Barkóczi, Balázs; Müller, Géza; Szegedi, Viktor

    2015-01-01

    Hippocampal oscillations recorded under urethane anesthesia are proposed to be modulated by anxiolytics. All classes of clinically effective anxiolytics were reported to decrease the frequency of urethane theta; however, recent findings raise concerns about the direct correlation of anxiolysis and the frequency of hippocampal theta. Here, we took advantage of our two inbred mouse strains displaying extremes of anxiety (anxious (AX) and nonanxious (nAX)) to compare the properties of hippocampal activity and to test the effect of an anxiolytic drugs. No difference was observed in the peak frequency or in the peak power between AX and nAX strains. Buspirone (Bus) applied in 2.5 mg/kg decreased anxiety of AX but did not have any effect on nAX as was tested by elevated plus maze and open field. Interestingly, Bus treatment increased hippocampal oscillatory frequency in the AX but left it unaltered in nAX mice. Saline injection did not have any effect on the oscillation. Paired-pulse facilitation was enhanced by Bus in the nAX, but not in the AX strain. Collectively, these results do not support the hypothesis that hippocampal activity under urethane may serve as a marker for potential anxiolytic drugs. Moreover, we could not confirm the decrease of frequency after anxiolytic treatment.

  10. Anxious and Nonanxious Mice Show Similar Hippocampal Sensory Evoked Oscillations under Urethane Anesthesia: Difference in the Effect of Buspirone

    PubMed Central

    Horváth, János; Barkóczi, Balázs; Müller, Géza

    2015-01-01

    Hippocampal oscillations recorded under urethane anesthesia are proposed to be modulated by anxiolytics. All classes of clinically effective anxiolytics were reported to decrease the frequency of urethane theta; however, recent findings raise concerns about the direct correlation of anxiolysis and the frequency of hippocampal theta. Here, we took advantage of our two inbred mouse strains displaying extremes of anxiety (anxious (AX) and nonanxious (nAX)) to compare the properties of hippocampal activity and to test the effect of an anxiolytic drugs. No difference was observed in the peak frequency or in the peak power between AX and nAX strains. Buspirone (Bus) applied in 2.5 mg/kg decreased anxiety of AX but did not have any effect on nAX as was tested by elevated plus maze and open field. Interestingly, Bus treatment increased hippocampal oscillatory frequency in the AX but left it unaltered in nAX mice. Saline injection did not have any effect on the oscillation. Paired-pulse facilitation was enhanced by Bus in the nAX, but not in the AX strain. Collectively, these results do not support the hypothesis that hippocampal activity under urethane may serve as a marker for potential anxiolytic drugs. Moreover, we could not confirm the decrease of frequency after anxiolytic treatment. PMID:25949829

  11. 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.

  12. Dynamics of a network of phase oscillators with plastic couplings

    SciTech Connect

    Nekorkin, V. I.; Kasatkin, D. V.

    2016-06-08

    The processes of synchronization and phase cluster formation are investigated in a complex network of dynamically coupled phase oscillators. Coupling weights evolve dynamically depending on the phase relations between the oscillators. It is shown that the network exhibits several types of behavior: the globally synchronized state, two-cluster and multi-cluster states, different synchronous states with a fixed phase relationship between the oscillators and chaotic desynchronized state.

  13. The Energy Demand of Fast Neuronal Network Oscillations: Insights from Brain Slice Preparations

    PubMed Central

    Kann, Oliver

    2012-01-01

    Fast neuronal network oscillations in the gamma range (30–100 Hz) in the cerebral cortex have been implicated in higher cognitive functions such as sensual perception, working memory, and, perhaps, consciousness. However, little is known about the energy demand of gamma oscillations. This is mainly caused by technical limitations that are associated with simultaneous recordings of neuronal activity and energy metabolism in small neuronal networks and at the level of mitochondria in vivo. Thus recent studies have focused on brain slice preparations to address the energy demand of gamma oscillations in vitro. Here, reports will be summarized and discussed that combined electrophysiological recordings, oxygen sensor microelectrodes, and live-cell fluorescence imaging in acutely prepared slices and organotypic slice cultures of the hippocampus from both, mouse and rat. These reports consistently show that gamma oscillations can be reliably induced in hippocampal slice preparations by different pharmacological tools. They suggest that gamma oscillations are associated with high energy demand, requiring both rapid adaptation of oxidative energy metabolism and sufficient supply with oxygen and nutrients. These findings might help to explain the exceptional vulnerability of higher cognitive functions during pathological processes of the brain, such as circulatory disturbances, genetic mitochondrial diseases, and neurodegeneration. PMID:22291647

  14. Weak chimeras in minimal networks of coupled phase oscillators

    NASA Astrophysics Data System (ADS)

    Ashwin, Peter; Burylko, Oleksandr

    2015-01-01

    We suggest a definition for a type of chimera state that appears in networks of indistinguishable phase oscillators. Defining a "weak chimera" as a type of invariant set showing partial frequency synchronization, we show that this means they cannot appear in phase oscillator networks that are either globally coupled or too small. We exhibit various networks of four, six, and ten indistinguishable oscillators, where weak chimeras exist with various dynamics and stabilities. We examine the role of Kuramoto-Sakaguchi coupling in giving degenerate (neutrally stable) families of weak chimera states in these example networks.

  15. Link weight evolution in a network of coupled chemical oscillators

    NASA Astrophysics Data System (ADS)

    Ke, Hua; Tinsley, Mark R.; Steele, Aaron; Wang, Fang; Showalter, Kenneth

    2014-05-01

    Link weight evolution is studied in a network of coupled chemical oscillators. Oscillators are perturbed by adjustments in imposed light intensity based on excitatory or inhibitory links to other oscillators undergoing excitation. Experimental and modeling studies demonstrate that the network is capable of producing sustained coordinated activity. The individual nodes of the network exhibit incoherent firing events; however, a dominant frequency can be discerned within the collective signal by Fourier analysis. The introduction of spike-timing-dependent plasticity yields a network that evolves to a stable unimodal link weight distribution.

  16. Hippocampal theta oscillations are slower in humans than in rodents: implications for models of spatial navigation and memory.

    PubMed

    Jacobs, Joshua

    2014-02-05

    The theta oscillation is a neuroscience enigma. When a rat runs through an environment, large-amplitude theta oscillations (4-10 Hz) reliably appear in the hippocampus's electrical activity. The consistency of this pattern led to theta playing a central role in theories on the neural basis of mammalian spatial navigation and memory. However, in fact, hippocampal oscillations at 4-10 Hz are rare in humans and in some other species. This presents a challenge for theories proposing theta as an essential component of the mammalian brain, including models of place and grid cells. Here, I examine this issue by reviewing recent research on human hippocampal oscillations using direct brain recordings from neurosurgical patients. This work indicates that the human hippocampus does indeed exhibit rhythms that are functionally similar to theta oscillations found in rodents, but that these signals have a slower frequency of approximately 1-4 Hz. I argue that oscillatory models of navigation and memory derived from rodent data are relevant for humans, but that they should be modified to account for the slower frequency of the human theta rhythm.

  17. Feedforward inhibition underlies the propagation of cholinergically induced gamma oscillations from hippocampal CA3 to CA1.

    PubMed

    Zemankovics, Rita; Veres, Judit M; Oren, Iris; Hájos, Norbert

    2013-07-24

    Gamma frequency (30-80 Hz) oscillations are implicated in memory processing. Such rhythmic activity can be generated intrinsically in the CA3 region of the hippocampus from where it can propagate to the CA1 area. To uncover the synaptic mechanisms underlying the intrahippocampal spread of gamma oscillations, we recorded local field potentials, as well as action potentials and synaptic currents in anatomically identified CA1 and CA3 neurons during carbachol-induced gamma oscillations in mouse hippocampal slices. The firing of the vast majority of CA1 neurons and all CA3 neurons was phase-coupled to the oscillations recorded in the stratum pyramidale of the CA1 region. The predominant synaptic input to CA1 interneurons was excitatory, and their discharge followed the firing of CA3 pyramidal cells at a latency indicative of monosynaptic connections. Correlation analysis of the input-output characteristics of the neurons and local pharmacological block of inhibition both agree with a model in which glutamatergic CA3 input controls the firing of CA1 interneurons, with local pyramidal cell activity having a minimal role. The firing of phase-coupled CA1 pyramidal cells was controlled principally by their inhibitory inputs, which dominated over excitation. Our results indicate that the synchronous firing of CA3 pyramidal cells rhythmically recruits CA1 interneurons and that this feedforward inhibition generates the oscillatory activity in CA1. These findings identify distinct synaptic mechanisms underlying the generation of gamma frequency oscillations in neighboring hippocampal subregions.

  18. Hippocampal theta oscillations are slower in humans than in rodents: implications for models of spatial navigation and memory

    PubMed Central

    Jacobs, Joshua

    2014-01-01

    The theta oscillation is a neuroscience enigma. When a rat runs through an environment, large-amplitude theta oscillations (4–10 Hz) reliably appear in the hippocampus's electrical activity. The consistency of this pattern led to theta playing a central role in theories on the neural basis of mammalian spatial navigation and memory. However, in fact, hippocampal oscillations at 4–10 Hz are rare in humans and in some other species. This presents a challenge for theories proposing theta as an essential component of the mammalian brain, including models of place and grid cells. Here, I examine this issue by reviewing recent research on human hippocampal oscillations using direct brain recordings from neurosurgical patients. This work indicates that the human hippocampus does indeed exhibit rhythms that are functionally similar to theta oscillations found in rodents, but that these signals have a slower frequency of approximately 1–4 Hz. I argue that oscillatory models of navigation and memory derived from rodent data are relevant for humans, but that they should be modified to account for the slower frequency of the human theta rhythm. PMID:24366145

  19. Spontaneous recurrent network activity in organotypic rat hippocampal slices.

    PubMed

    Mohajerani, Majid H; Cherubini, Enrico

    2005-07-01

    Organotypic hippocampal slices were prepared from postnatal day 4 rats and maintained in culture for >6 weeks. Cultured slices exhibited from 12 days in vitro spontaneous events which closely resembled giant depolarizing potentials (GDPs) recorded in neonatal hippocampal slices. GDP-like events occurred over the entire hippocampus with a delay of 30-60 ms between two adjacent regions as demonstrated by pair recordings from CA3-CA3, CA3-CA1 and interneurone-CA3 pyramidal cells. As in acute slices, spontaneous recurrent events were generated by the interplay of GABA and glutamate acting on AMPA receptors as they were reversibly blocked by bicuculline and 6,7-dinitroquinoxaline-2,3-dione but not by dl-2-amino-5-phosphonopentaoic acid. The equilibrium potentials for GABA measured in whole cell and gramicidin-perforated patch from interconnected interneurones-CA3 pyramidal cells were -70 and -56 mV, respectively. The resting membrane potential estimated from the reversal of N-methyl-D-aspartate-induced single-channel currents in cell-attach experiments was -75 mV. In spite of its depolarizing action, in the majority of cases GABA was still inhibitory as it blocked the firing of principal cells. The increased level of glutamatergic connectivity certainly contributed to network synchronization and to the development of interictal discharges after prolonged exposure to bicuculline. In spite of its inhibitory action, in a minority of cells GABA was still depolarizing and excitatory as it was able to bring principal cells to fire, suggesting that a certain degree of immaturity is still present in cultured slices. This was in line with the transient bicuculline-induced block of GDPs and with the isoguvacine-induced increase of GDP frequency.

  20. Creation and perturbation of planar networks of chemical oscillators

    NASA Astrophysics Data System (ADS)

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

    2015-06-01

    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.

  1. 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

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

    SciTech Connect

    Bick, Christian; Ashwin, Peter; Rodrigues, Ana

    2016-09-15

    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.

  3. 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.

  4. 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.

  5. Early-life stress impairs recognition memory and perturbs the functional maturation of prefrontal-hippocampal-perirhinal networks.

    PubMed

    Reincke, Samuel A J; Hanganu-Opatz, Ileana L

    2017-02-07

    Early life exposure to stressful situations impairs cognitive performance of adults and contributes to the etiology of several psychiatric disorders. Most of affected cognitive abilities rely on coupling by synchrony within complex neuronal networks, including prefrontal cortex (PFC), hippocampus (HP), and perirhinal cortex (PRH). Yet it remains poorly understood how early life stress (ELS) induces dysfunction within these networks during the course of development. Here we used intermittent maternal separation during the first 2 postnatal weeks to mimic ELS and monitored the recognition memory and functional coupling within prefrontal-hippocampal-perirhinal circuits in juvenile rats. While maternally-separated female rats showed largely normal behavior, male rats experiencing this form of ELS had poorer location and recency recognition memory. Simultaneous multi-site extracellular recordings of network oscillations and neuronal spiking from PFC, HP, and PRH in vivo revealed corresponding decrease of oscillatory activity in theta and beta frequency bands in the PFC of male but not female rats experiencing maternal separation. This deficit was accompanied by weaker cross-frequency coupling within juvenile prefrontal-hippocampal networks. These results indicate that already at juvenile age ELS mimicked by maternal separation induces sex-specific deficits in recognition memory that might have as underlying mechanism a disturbed communication between PFC and HP.

  6. Early-life stress impairs recognition memory and perturbs the functional maturation of prefrontal-hippocampal-perirhinal networks

    PubMed Central

    Reincke, Samuel A. J.; Hanganu-Opatz, Ileana L.

    2017-01-01

    Early life exposure to stressful situations impairs cognitive performance of adults and contributes to the etiology of several psychiatric disorders. Most of affected cognitive abilities rely on coupling by synchrony within complex neuronal networks, including prefrontal cortex (PFC), hippocampus (HP), and perirhinal cortex (PRH). Yet it remains poorly understood how early life stress (ELS) induces dysfunction within these networks during the course of development. Here we used intermittent maternal separation during the first 2 postnatal weeks to mimic ELS and monitored the recognition memory and functional coupling within prefrontal-hippocampal-perirhinal circuits in juvenile rats. While maternally-separated female rats showed largely normal behavior, male rats experiencing this form of ELS had poorer location and recency recognition memory. Simultaneous multi-site extracellular recordings of network oscillations and neuronal spiking from PFC, HP, and PRH in vivo revealed corresponding decrease of oscillatory activity in theta and beta frequency bands in the PFC of male but not female rats experiencing maternal separation. This deficit was accompanied by weaker cross-frequency coupling within juvenile prefrontal-hippocampal networks. These results indicate that already at juvenile age ELS mimicked by maternal separation induces sex-specific deficits in recognition memory that might have as underlying mechanism a disturbed communication between PFC and HP. PMID:28169319

  7. On controlling networks of limit-cycle oscillators.

    PubMed

    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.

  8. 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.

  9. Interneuronal mechanisms of hippocampal theta oscillations in a full-scale model of the rodent CA1 circuit.

    PubMed

    Bezaire, Marianne J; Raikov, Ivan; Burk, Kelly; Vyas, Dhrumil; Soltesz, Ivan

    2016-12-23

    The hippocampal theta rhythm plays important roles in information processing; however, the mechanisms of its generation are not well understood. We developed a data-driven, supercomputer-based, full-scale (1:1) model of the rodent CA1 area and studied its interneurons during theta oscillations. Theta rhythm with phase-locked gamma oscillations and phase-preferential discharges of distinct interneuronal types spontaneously emerged from the isolated CA1 circuit without rhythmic inputs. Perturbation experiments identified parvalbumin-expressing interneurons and neurogliaform cells, as well as interneuronal diversity itself, as important factors in theta generation. These simulations reveal new insights into the spatiotemporal organization of the CA1 circuit during theta oscillations.

  10. Interneuronal mechanisms of hippocampal theta oscillations in a full-scale model of the rodent CA1 circuit

    PubMed Central

    Bezaire, Marianne J; Raikov, Ivan; Burk, Kelly; Vyas, Dhrumil; Soltesz, Ivan

    2016-01-01

    The hippocampal theta rhythm plays important roles in information processing; however, the mechanisms of its generation are not well understood. We developed a data-driven, supercomputer-based, full-scale (1:1) model of the rodent CA1 area and studied its interneurons during theta oscillations. Theta rhythm with phase-locked gamma oscillations and phase-preferential discharges of distinct interneuronal types spontaneously emerged from the isolated CA1 circuit without rhythmic inputs. Perturbation experiments identified parvalbumin-expressing interneurons and neurogliaform cells, as well as interneuronal diversity itself, as important factors in theta generation. These simulations reveal new insights into the spatiotemporal organization of the CA1 circuit during theta oscillations. DOI: http://dx.doi.org/10.7554/eLife.18566.001 PMID:28009257

  11. Synaptic connectivity in hippocampal neuronal networks cultured on micropatterned surfaces.

    PubMed

    Liu, Q Y; Coulombe, M; Dumm, J; Shaffer, K M; Schaffner, A E; Barker, J L; Pancrazio, J J; Stenger, D A; Ma, W

    2000-04-14

    Embryonic rat hippocampal neurons were grown on patterned silane surface in order to organize synapse formations in a controlled manner. The surface patterns were composed of trimethoxysilylpropyl-diethylenetriamine (DETA) lines separated by tridecafluoro-1,1,2,2-tetrahydrooctyl-1-dimethylchlorosilane (13F) spaces. Pre- and post-synaptic specializations were identified by immunostaining for synapsin I and microtubule-associated protein-2 (MAP-2). Functional synaptic connections were examined by recording simultaneously from pairs of neurons using the whole-cell configuration of the patch-clamp technique. Spontaneous and evoked synaptic currents were recorded in neurons cultured for 2-14 days. The formation of functional connections was accompanied by the appearance of spontaneous synaptic currents (SSCs), which could be detected after approximately 3 days in culture in the absence of evoked synaptic currents (ESCs). ESCs were detected only after approximately 7 days in culture, mostly in the form of unidirectional synaptic connections. Other forms of synaptic connectivity, such as bidirectional and autaptic connections, were also identified. Both transient GABAergic and glutamatergic signals mediated the transmissions between communicating cells. These results demonstrate the combination of various types of synaptic connections forming simple and complex networks in neurons cultured on line (DETA)-space (13F) patterns. Finally, precisely synchronized SSCs were recorded in neuron pairs cultured on pattern indicating the existence of a fast-acting feedback mechanism mediated by pre-synaptic GABA(A) receptors.

  12. Network Models Predict that Reduced Excitatory Fluctuations Can Give Rise to Hippocampal Network Hyper-Excitability in MeCP2-Null Mice

    PubMed Central

    Ho, Ernest C. Y.; Eubanks, James H.; Zhang, Liang; Skinner, Frances K.

    2014-01-01

    Rett syndrome is a severe pediatric neurological disorder caused by loss of function mutations within the gene encoding methyl CpG-binding protein 2 (MeCP2). Although MeCP2 is expressed near ubiquitously, the primary pathophysiology of Rett syndrome stems from impairments of nervous system function. One alteration within different regions of the MeCP2-deficient brain is the presence of hyper-excitable network responses. In the hippocampus, such responses exist despite there being an overall decrease in spontaneous excitatory drive within the network. In this study, we generated and used mathematical, neuronal network models to resolve this apparent paradox. We did this by taking advantage of previous mathematical modelling insights that indicated that decreased excitatory fluctuations, but not mean excitatory drive, more critically explain observed changes in hippocampal network oscillations from MeCP2-null mouse slices. Importantly, reduced excitatory fluctuations could also bring about hyper-excitable responses in our network models. Therefore, these results indicate that diminished excitatory fluctuations may be responsible for the hyper-excitable state of MeCP2-deficient hippocampal circuitry. PMID:24642514

  13. Effective connectivity of hippocampal neural network and its alteration in Mg2+-free epilepsy model.

    PubMed

    Gong, Xin-Wei; Li, Jing-Bo; Lu, Qin-Chi; Liang, Pei-Ji; Zhang, Pu-Ming

    2014-01-01

    Understanding the connectivity of the brain neural network and its evolution in epileptiform discharges is meaningful in the epilepsy researches and treatments. In the present study, epileptiform discharges were induced in rat hippocampal slices perfused with Mg2+-free artificial cerebrospinal fluid. The effective connectivity of the hippocampal neural network was studied by comparing the normal and epileptiform discharges recorded by a microelectrode array. The neural network connectivity was constructed by using partial directed coherence and analyzed by graph theory. The transition of the hippocampal network topology from control to epileptiform discharges was demonstrated. Firstly, differences existed in both the averaged in- and out-degree between nodes in the pyramidal cell layer and the granule cell layer, which indicated an information flow from the pyramidal cell layer to the granule cell layer during epileptiform discharges, whereas no consistent information flow was observed in control. Secondly, the neural network showed different small-worldness in the early, middle and late stages of the epileptiform discharges, whereas the control network did not show the small-world property. Thirdly, the network connectivity began to change earlier than the appearance of epileptiform discharges and lasted several seconds after the epileptiform discharges disappeared. These results revealed the important network bases underlying the transition from normal to epileptiform discharges in hippocampal slices. Additionally, this work indicated that the network analysis might provide a useful tool to evaluate the neural network and help to improve the prediction of seizures.

  14. GABAergic neurons of the medial septum lead the hippocampal network during theta activity.

    PubMed

    Hangya, Balázs; Borhegyi, Zsolt; Szilágyi, Nóra; Freund, Tamás F; Varga, Viktor

    2009-06-24

    Information processing in the hippocampus critically relies on its reciprocal interaction with the medial septum (MS). Synchronization of the septo-hippocampal system was demonstrated during both major hippocampal activity states, the regular theta rhythm and the large amplitude irregular activity. Previous experimental and modeling data suggest that the MS provides rhythmic drive to the hippocampus, and hippocampo-septal feedback synchronizes septal pacemaker units. However, this view has recently been questioned based on the possibility of intrahippocampal theta genesis. Previously, we identified putative pacemaker neurons expressing parvalbumin (PV) and/or the pacemaker hyperpolarization-activated and cyclic nucleotide-gated nonselective cation channel (HCN) in the MS. In this study, by analyzing the temporal relationship of activity between the PV/HCN-containing medial septal neurons and hippocampal local field potential, we aimed to uncover whether the sequence of events during theta formation supports the classic view of septal drive or the challenging theory of hippocampal pacing of theta. Importantly, by implementing a circular statistical method, a temporal lead of these septal neurons over the hippocampus was observed on the course of theta synchronization. Moreover, the activity of putative hippocampal interneurons also preceded hippocampal local field theta, but by a shorter time period compared with PV/HCN-containing septal neurons. Using the concept of mutual information, the action potential series of PV/HCN-containing neurons shared higher amount of information with hippocampal field oscillation than PV/HCN-immunonegative cells. Thus, a pacemaker neuron population of the MS leads hippocampal activity, presumably via the synchronization of hippocampal interneurons.

  15. 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.

  16. 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

  17. Synchronization in complex oscillator networks and smart grids.

    PubMed

    Dörfler, Florian; Chertkov, Michael; Bullo, Francesco

    2013-02-05

    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.

  18. Local complexity predicts global synchronization of hierarchically networked oscillators

    NASA Astrophysics Data System (ADS)

    Xu, Jin; Park, Dong-Ho; Jo, Junghyo

    2017-07-01

    We study the global synchronization of hierarchically-organized Stuart-Landau oscillators, where each subsystem consists of three oscillators with activity-dependent couplings. We considered all possible coupling signs between the three oscillators, and found that they can generate different numbers of phase attractors depending on the network motif. Here, the subsystems are coupled through mean activities of total oscillators. Under weak inter-subsystem couplings, we demonstrate that the synchronization between subsystems is highly correlated with the number of attractors in uncoupled subsystems. Among the network motifs, perfect anti-symmetric ones are unique to generate both single and multiple attractors depending on the activities of oscillators. The flexible local complexity can make global synchronization controllable.

  19. 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

  20. 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.

  1. Amplitude death and resurgence of oscillation in networks of mobile oscillators

    NASA Astrophysics Data System (ADS)

    Majhi, Soumen; Ghosh, Dibakar

    2017-05-01

    The phenomenon of amplitude death has been explored using a variety of different coupling strategies in the last two decades. In most of the works, the basic coupling arrangement is considered to be static over time, although many realistic systems exhibit significant changes in the interaction pattern as time varies. In this article, we study the emergence of amplitude death in a dynamical network composed of time-varying interaction amidst a collection of random walkers in a finite region of three-dimensional space. We consider an oscillator for each walker and demonstrate that depending upon the network parameters and hence the interaction between them, the global oscillation in the network gets suppressed. In this framework, the vision range of each oscillator decides the number of oscillators with which it interacts. In addition, with the use of an appropriate feedback parameter in the coupling strategy, we articulate how the suppressed oscillation can be resurrected in the systems' parameter space. The phenomenon of amplitude death and the resurgence of oscillation is investigated taking limit cycle and chaotic oscillators for broad ranges of the parameters, like the interaction strength k between the entities, the vision range r and the speed of movement v.

  2. Amplitude death of identical oscillators in networks with direct coupling

    NASA Astrophysics Data System (ADS)

    Illing, Lucas

    2016-08-01

    It is known that amplitude death can occur in networks of coupled identical oscillators if they interact via diffusive time-delayed coupling links. Here we consider networks of oscillators that interact via direct time-delayed coupling links. It is shown analytically that amplitude death is impossible for directly coupled Stuart-Landau oscillators, in contradistinction to the case of diffusive coupling. We demonstrate that amplitude death in the strict sense does become possible in directly coupled networks if the node dynamics is governed by second-order delay differential equations. Finally, we analyze in detail directly coupled nodes whose dynamics are described by first-order delay differential equations and find that, while amplitude death in the strict sense is impossible, other interesting oscillation quenching scenarios exist.

  3. 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

  4. 5-Hydroxytryptamine1A receptor-activation hyperpolarizes pyramidal cells and suppresses hippocampal gamma oscillations via Kir3 channel activation.

    PubMed

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

    2014-10-01

    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.

  5. Hippocampal neuro-networks and dendritic spine perturbations in epileptogenesis are attenuated by neuroprotectin d1.

    PubMed

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

    2015-01-01

    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. 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. 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. 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.

  6. The CAN-In network: A biologically inspired model for self-sustained theta oscillations and memory maintenance in the hippocampus.

    PubMed

    Giovannini, Francesco; Knauer, Beate; Yoshida, Motoharu; Buhry, Laure

    2017-04-01

    During working memory tasks, the hippocampus exhibits synchronous theta-band activity, which is thought to be correlated with the short-term memory maintenance of salient stimuli. Recent studies indicate that the hippocampus contains the necessary circuitry allowing it to generate and sustain theta oscillations without the need of extrinsic drive. However, the cellular and network mechanisms supporting synchronous rhythmic activity are far from being fully understood. Based on electrophysiological recordings from hippocampal pyramidal CA1 cells, we present a possible mechanism for the maintenance of such rhythmic theta-band activity in the isolated hippocampus. Our model network, based on the Hodgkin-Huxley formalism, comprising pyramidal neurons equipped with calcium-activated nonspecific cationic (CAN) ion channels, is able to generate and sustain synchronized theta oscillations (4-12 Hz), following a transient stimulation. The synchronous network activity is maintained by an intrinsic CAN current (ICAN ), in the absence of constant external input. When connecting the pyramidal-CAN network to fast-spiking inhibitory interneurons, the dynamics of the model reveal that feedback inhibition improves the robustness of fast theta oscillations, by tightening the synchronization of the pyramidal CAN neurons. The frequency and power of the theta oscillations are both modulated by the intensity of the ICAN , which allows for a wide range of oscillation rates within the theta band. This biologically plausible mechanism for the maintenance of synchronous theta oscillations in the hippocampus aims at extending the traditional models of septum-driven hippocampal rhythmic activity. © 2017 Wiley Periodicals, Inc.

  7. 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.

  8. Synchronization, quantum correlations and entanglement in oscillator networks.

    PubMed

    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.

  9. 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.

  10. 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

  11. The Organization of Mouse and Human Cortico-Hippocampal Networks Estimated by Intrinsic Functional Connectivity

    PubMed Central

    Bergmann, Eyal; Zur, Gil; Bershadsky, Guy; Kahn, Itamar

    2016-01-01

    While the hippocampal memory system has been relatively conserved across mammals, the cerebral cortex has undergone massive expansion. A central question in brain evolution is how cortical development affected the nature of cortical inputs to the hippocampus. To address this question, we compared cortico-hippocampal connectivity using intrinsic functional connectivity MRI (fcMRI) in awake mice and humans. We found that fcMRI recapitulates anatomical connectivity, demonstrating sensory mapping within the mouse parahippocampal region. Moreover, we identified a similar topographical modality-specific organization along the longitudinal axis of the mouse hippocampus, indicating that sensory information arriving at the hippocampus is only partly integrated. Finally, comparing cortico-hippocampal connectivity across species, we discovered preferential hippocampal connectivity of sensory cortical networks in mice compared with preferential connectivity of association cortical networks in humans. Supporting this observation in humans but not in mice, sensory and association cortical networks are connected to spatially distinct subregions within the parahippocampal region. Collectively, these findings indicate that sensory cortical networks are coupled to the mouse but not the human hippocampal memory system, suggesting that the emergence of expanded and new association areas in humans resulted in the rerouting of cortical information flow and dissociation of primary sensory cortices from the hippocampus. PMID:27797832

  12. Exercise Prevents Amyloid-β-Induced Hippocampal Network Disruption by Inhibiting GSK3β Activation.

    PubMed

    Isla, Arturo G; Vázquez-Cuevas, Francisco Gabriel; Peña-Ortega, Fernando

    2016-03-16

    Exercise is becoming a promising therapeutic approach to prevent alterations both in Alzheimer's disease (AD) patients and in transgenic models of AD. This neuroprotection has been associated with changes in hippocampal structure and function, as well as with the reduction of amyloid-β (Aβ) production and accumulation. However, whether exercise produces lasting changes in hippocampal population activity and renders it resistant to Aβ-induced network dysfunction is still unknown. Thus, we tested whether voluntary exercise changes hippocampal population activity and prevents its alteration in the presence of Aβ, which has been associated to glycogen synthase kinase-3β (GSK3β) activation. We found that the hippocampal population activity recorded in slices obtained from mice that exercised voluntarily (with free access to a running wheel for 21 days) exhibits higher power and faster frequency composition than slices obtained from sedentary animals. Moreover, the hippocampal network of mice that exercised becomes insensitive to Aβ-induced inhibition of spontaneous population activity. This protective effect correlates with the inability of Aβ to activate GSK3β, is mimicked by GSK3β inhibition with SB126763 (in slices obtained from sedentary mice), and is abolished by the inhibition of PI3K with LY294002 (in slices obtained from mice that exercised). We conclude that voluntary exercise produces a lasting protective state in the hippocampus, maintained in hippocampal slices by a PI3K-dependent mechanism that precludes its functional disruption in the presence of Aβ by avoiding GSK3β activation.

  13. Network mechanisms of hippocampal laterality, place coding, and goal-directed navigation.

    PubMed

    Kitanishi, Takuma; Ito, Hiroshi T; Hayashi, Yuichiro; Shinohara, Yoshiaki; Mizuseki, Kenji; Hikida, Takatoshi

    2017-03-01

    The hippocampus and associated structures are responsible for episodic memory in humans. In rodents, the most prominent behavioral correlate of hippocampal neural activity is place coding, which is thought to underlie spatial navigation. While episodic memory is considered to be unique to humans in a restricted context, it has been proposed that the same neural circuitry and algorithms that enable spatial coding and navigation also support episodic memory. Here we review the recent progress in neural circuit mechanisms of hippocampal activity by introducing several topics: (1) cooperation and specialization of the bilateral hippocampi, (2) the role of synaptic plasticity in gamma phase-locking of spikes and place cell formation, (3) impaired goal-related activity and oscillations in a mouse model of mental disorders, and (4) a prefrontal-thalamo-hippocampal circuit for goal-directed spatial navigation.

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

    PubMed

    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 cannabinoid and

  15. 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.

  16. 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.

  17. Experimental observation of dynamical behaviors of four, five and six oscillators in rings and nine oscillators in a branched network

    NASA Astrophysics Data System (ADS)

    Nishiyama, Nobuaki

    1995-01-01

    Cation-exchange beads loaded with ferroin were immersed in the Belousov-Zabotinsky reaction mixture and used as chemical oscillators. Four, five and six chemical oscillators were spatially distributed in rings. Coupling among the oscillators was due to mass diffusion. Spontaneous switching between two out-of-phase modes was observed in the ring oscillator systems. In the case of ring with three or four oscillators, transient extinction of oscillations was also observed. In addition, dynamical behaviors of a branched network with nine oscillators were reported.

  18. Observations of spontaneous oscillations in simple two-fluid networks

    NASA Astrophysics Data System (ADS)

    Storey, Brian D.; Hellen, Deborah V.; Karst, Nathaniel J.; Geddes, John B.

    2015-02-01

    We investigate the laminar flow of two-fluid mixtures inside a simple network of interconnected tubes. The fluid system is composed of two miscible Newtonian fluids of different viscosity which do not mix and remain as nearly distinct phases. Downstream of a diverging network junction the two fluids do not necessarily split in equal fraction and thus heterogeneity is introduced into network. We find that in the simplest network, a single loop with one inlet and one outlet, under steady inlet conditions, the flow rates and distribution of the two fluids within the network loop can undergo persistent spontaneous oscillations. We develop a simple model which highlights the basic mechanism of the instability and we demonstrate that the model can predict the region of parameter space where oscillations exist. The model predictions are in good agreement with experimental observations.

  19. 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.

  20. Oscillation propagation in neural networks with different topologies

    NASA Astrophysics Data System (ADS)

    Gao, Yang; Wang, Jianjun

    2011-03-01

    In light of the issue of oscillation propagation in neural networks, various topologies of FitzHugh-Nagumo neuron populations are investigated. External Gaussian white noise is injected into the first neuron only. Before the oscillation spreads to the other neurons in the network, some of the inherent stochasticity within the noise-induced oscillation of the first neuron is filtered out due to the neuron's nonlinear dynamics. Both the temporal and the spatial coherence of the evoked activity's propagation are analyzed in conjunction with the network topology randomness p, the coupling strength between neurons g, and the noise amplitude D. The temporal periodicity of the global neural network presents a typical coherence biresonance (CBR) characteristic with regard to the noise intensity. The network topology randomness exerts different influences on the resonance effects for different coupling strength regimes. At an intermediate coupling strength, the random shortcuts reinforce the interactions between the neurons, and then more stochasticity in the firings of the first neuron spreads within the network. Consequently, CBR is decreased with the increase of the network topology randomness. At a large coupling strength, the random shortcuts assist the nonlinearity in impairing the stochastic components, and consequently help to enhance the resonance effects, which differed significantly from previous related work. However, the degree of the spatial synchronization of the systems increases monotonically as the network topology randomness increases at any coupling strength.

  1. The Many Tunes of Perisomatic Targeting Interneurons in the Hippocampal Network

    PubMed Central

    Ellender, Tommas J.; Paulsen, Ole

    2010-01-01

    The axonal targets of perisomatic targeting interneurons make them ideally suited to synchronize excitatory neurons. As such they have been implicated in rhythm generation of network activity in many brain regions including the hippocampus. However, several recent publications indicate that their roles extend beyond that of rhythm generation. Firstly, it has been shown that, in addition to rhythm generation, GABAergic perisomatic inhibition also serves as a current generator contributing significantly to hippocampal oscillatory EEG signals. Furthermore, GABAergic interneurons have a previously unrecognized role in the initiation of hippocampal population bursts, both in the developing and adult hippocampus. In this review, we describe these new observations in detail and discuss the implications they have for our understanding of the mechanisms underlying physiological and pathological hippocampal network activities. This review is part of the Frontiers in Cellular Neuroscience's special topic entitled “GABA signaling in health and disease” based on the meeting at the CNCR Amsterdam. PMID:20740069

  2. 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.

  3. Brain State Is a Major Factor in Preseizure Hippocampal Network Activity and Influences Success of Seizure Intervention

    PubMed Central

    Ewell, Laura A.; Liang, Liang; Armstrong, Caren; Soltész, Ivan; Leutgeb, Stefan

    2015-01-01

    Neural dynamics preceding seizures are of interest because they may shed light on mechanisms of seizure generation and could be predictive. In healthy animals, hippocampal network activity is shaped by behavioral brain state and, in epilepsy, seizures selectively emerge during specific brain states. To determine the degree to which changes in network dynamics before seizure are pathological or reflect ongoing fluctuations in brain state, dorsal hippocampal neurons were recorded during spontaneous seizures in a rat model of temporal lobe epilepsy. Seizures emerged from all brain states, but with a greater likelihood after REM sleep, potentially due to an observed increase in baseline excitability during periods of REM compared with other brains states also characterized by sustained theta oscillations. When comparing the firing patterns of the same neurons across brain states associated with and without seizures, activity dynamics before seizures followed patterns typical of the ongoing brain state, or brain state transitions, and did not differ until the onset of the electrographic seizure. Next, we tested whether disparate activity patterns during distinct brain states would influence the effectiveness of optogenetic curtailment of hippocampal seizures in a mouse model of temporal lobe epilepsy. Optogenetic curtailment was significantly more effective for seizures preceded by non-theta states compared with seizures that emerged from theta states. Our results indicate that consideration of behavioral brain state preceding a seizure is important for the appropriate interpretation of network dynamics leading up to a seizure and for designing effective seizure intervention. SIGNIFICANCE STATEMENT Hippocampal single-unit activity is strongly shaped by behavioral brain state, yet this relationship has been largely ignored when studying activity dynamics before spontaneous seizures in medial temporal lobe epilepsy. In light of the increased attention on using single

  4. 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.

  5. Spontaneous Local Gamma Oscillation Selectively Enhances Neural Network Responsiveness

    PubMed Central

    Paik, Se-Bum; Kumar, Tribhawan; Glaser, Donald A.

    2009-01-01

    Synchronized oscillation is very commonly observed in many neuronal systems and might play an important role in the response properties of the system. We have studied how the spontaneous oscillatory activity affects the responsiveness of a neuronal network, using a neural network model of the visual cortex built from Hodgkin-Huxley type excitatory (E-) and inhibitory (I-) neurons. When the isotropic local E-I and I-E synaptic connections were sufficiently strong, the network commonly generated gamma frequency oscillatory firing patterns in response to random feed-forward (FF) input spikes. This spontaneous oscillatory network activity injects a periodic local current that could amplify a weak synaptic input and enhance the network's responsiveness. When E-E connections were added, we found that the strength of oscillation can be modulated by varying the FF input strength without any changes in single neuron properties or interneuron connectivity. The response modulation is proportional to the oscillation strength, which leads to self-regulation such that the cortical network selectively amplifies various FF inputs according to its strength, without requiring any adaptation mechanism. We show that this selective cortical amplification is controlled by E-E cell interactions. We also found that this response amplification is spatially localized, which suggests that the responsiveness modulation may also be spatially selective. This suggests a generalized mechanism by which neural oscillatory activity can enhance the selectivity of a neural network to FF inputs. PMID:19343222

  6. Cerebellar network plasticity: from genes to fast oscillation.

    PubMed

    Cheron, G; Servais, L; Dan, B

    2008-04-22

    The role of the cerebellum has been increasingly recognized not only in motor control but in sensory, cognitive and emotional learning and regulation. Purkinje cells, being the sole output from the cerebellar cortex, occupy an integrative position in this network. Plasticity at this level is known to critically involve calcium signaling. In the last few years, electrophysiological study of genetically engineered mice has demonstrated the topical role of several genes encoding calcium-binding proteins (calretinin, calbindin, parvalbumin). Specific inactivation of these genes results in the emergence of a fast network oscillation (ca. 160 Hz) throughout the cerebellar cortex in alert animals, associated with ataxia. This oscillation is produced by synchronization of Purkinje cells along the parallel fiber beam. It behaves as an electrophysiological arrest rhythm, being blocked by sensorimotor stimulation. Pharmacological manipulations showed that the oscillation is blocked by GABA(A) and NMDA antagonists as well as gap junction blockers. This cerebellar network oscillation has also been documented in mouse models of human conditions with complex developmental cerebellar dysfunction, such as Angelman syndrome and fetal alcohol syndrome. Recent evidence suggests a relationship between fast oscillation and cerebellar long term depression (LTD). This may have major implications for future therapeutic targeting.

  7. 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…

  8. 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…

  9. 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.

  10. Flow version of statistical neurodynamics for oscillator neural networks

    NASA Astrophysics Data System (ADS)

    Uchiyama, Satoki

    2012-04-01

    We consider a neural network of Stuart-Landau oscillators as an associative memory. This oscillator network with N elements is a system of an N-dimensional differential equation, works as an attractor neural network, and is expected to have no Lyapunov functions. Therefore, the technique of equilibrium statistical physics is not applicable to the study of this system in the thermodynamic limit. However, the simplicity of this system allows us to extend statistical neurodynamics [S. Amari, K. Maginu, Neural Netw. 1 (1988) 63-73], which was originally developed to analyse the discrete time evolution of the Hopfield model, into the version for continuous time evolution. We have developed and attempted to apply this method in the analysis of the phase transition of our model network.

  11. Coupled Oscillations and Circadian Rhythms in Molecular Replication Networks.

    PubMed

    Wagner, Nathaniel; Alasibi, Samaa; Peacock-Lopez, Enrique; Ashkenasy, Gonen

    2015-01-02

    Living organisms often display rhythmic and oscillatory behavior. We investigate here a challenge in contemporary Systems Chemistry, that is, to construct "bottom-up" molecular networks that display such complex behavior. We first describe oscillations during self-replication by applying kinetic parameters relevant to peptide replication in an open environment. Small networks of coupled oscillators are then constructed in silico, producing various functions such as logic gates, integrators, counters, triggers, and detectors. These networks are finally utilized to simulate the connectivity and network topology of the Kai proteins circadian clocks from the S. elongatus cyanobacteria, thus producing rhythms whose constant frequency is independent of the input intake rate and robust toward concentration fluctuations. We suggest that this study helps further reveal the underlying principles of biological clocks and may provide clues into their emergence in early molecular evolution.

  12. Reconciling the different faces of hippocampal theta: The role of theta oscillations in cognitive, emotional and innate behaviors.

    PubMed

    Korotkova, Tatiana; Ponomarenko, Alexey; Monaghan, Caitlin K; Poulter, Steven L; Cacucci, Francesca; Wills, Tom; Hasselmo, Michael E; Lever, Colin

    2017-09-05

    The theta oscillation (5-10Hz) is a prominent behavior-specific brain rhythm. This review summarizes studies showing the multifaceted role of theta rhythm in cognitive functions, including spatial coding, time coding and memory, exploratory locomotion and anxiety-related behaviors. We describe how activity of hippocampal theta rhythm generators - medial septum, nucleus incertus and entorhinal cortex, links theta with specific behaviors. We review evidence for functions of the theta-rhythmic signaling to subcortical targets, including lateral septum. Further, we describe functional associations of theta oscillation properties - phase, frequency and amplitude - with memory, locomotion and anxiety, and outline how manipulations of these features, using optogenetics or pharmacology, affect associative and innate behaviors. We discuss work linking cognition to the slope of the theta frequency to running speed regression, and emotion-sensitivity (anxiolysis) to its y-intercept. Finally, we describe parallel emergence of theta oscillations, theta-mediated neuronal activity and behaviors during development. This review highlights a complex interplay of neuronal circuits and synchronization features, which enables an adaptive regulation of multiple behaviors by theta-rhythmic signaling. Copyright © 2017 Elsevier Ltd. All rights reserved.

  13. Regulating Cortical Oscillations in an Inhibition-Stabilized Network

    PubMed Central

    Jadi, Monika P.; Sejnowski, Terrence J.

    2014-01-01

    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

  14. 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.

  15. 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

  16. Synchronization of Lienard-Type Oscillators in Uniform Electrical Networks

    SciTech Connect

    Sinha, Mohit; Dorfler, Florian; Johnson, Brian B.; Dhople, Sairaj V.

    2016-08-01

    This paper presents a condition for global asymptotic synchronization of Lienard-type nonlinear oscillators in uniform LTI electrical networks with series R-L circuits modeling interconnections. By uniform electrical networks, we mean that the per-unit-length impedances are identical for the interconnecting lines. We derive conditions for global asymptotic synchronization for a particular feedback architecture where the derivative of the oscillator output current supplements the innate current feedback induced by simply interconnecting the oscillator to the network. Our proof leverages a coordinate transformation to a set of differential coordinates that emphasizes signal differences and the particular form of feedback permits the formulation of a quadratic Lyapunov function for this class of networks. This approach is particularly interesting since synchronization conditions are difficult to obtain by means of quadratic Lyapunov functions when only current feedback is used and for networks composed of series R-L circuits. Our synchronization condition depends on the algebraic connectivity of the underlying network, and reiterates the conventional wisdom from Lyapunov- and passivity-based arguments that strong coupling is required to ensure synchronization.

  17. Graph partitions and cluster synchronization in networks of oscillators

    PubMed Central

    Schaub, Michael T.; O’Clery, Neave; Billeh, Yazan N.; Delvenne, Jean-Charles; Lambiotte, Renaud; Barahona, Mauricio

    2017-01-01

    Synchronization over networks depends strongly on the structure of the coupling between the oscillators. When the coupling presents certain regularities, the dynamics can be coarse-grained into clusters by means of External Equitable Partitions of the network graph and their associated quotient graphs. We exploit this graph-theoretical concept to study the phenomenon of cluster synchronization, in which different groups of nodes converge to distinct behaviors. We derive conditions and properties of networks in which such clustered behavior emerges, and show that the ensuing dynamics is the result of the localization of the eigenvectors of the associated graph Laplacians linked to the existence of invariant subspaces. The framework is applied to both linear and non-linear models, first for the standard case of networks with positive edges, before being generalized to the case of signed networks with both positive and negative interactions. We illustrate our results with examples of both signed and unsigned graphs for consensus dynamics and for partial synchronization of oscillator networks under the master stability function as well as Kuramoto oscillators. PMID:27781454

  18. Rapid eye movement sleep and hippocampal theta oscillations precede seizure onset in the tetanus toxin model of temporal lobe epilepsy.

    PubMed

    Sedigh-Sarvestani, Madineh; Thuku, Godfrey I; Sunderam, Sridhar; Parkar, Anjum; Weinstein, Steven L; Schiff, Steven J; Gluckman, Bruce J

    2014-01-22

    Improved understanding of the interaction between state of vigilance (SOV) and seizure onset has therapeutic potential. Six rats received injections of tetanus toxin (TeTX) in the ventral hippocampus that resulted in chronic spontaneous seizures. The distribution of SOV before 486 seizures was analyzed for a total of 19 d of recording. Rapid eye movement sleep (REM) and exploratory wake, both of which express prominent hippocampal theta rhythm, preceded 47 and 34%, for a total of 81%, of all seizures. Nonrapid eye movement sleep (NREM) and nonexploratory wake, neither of which expresses prominent theta, preceded 6.8 and 13% of seizures. We demonstrate that identification of SOV yields significant differentiation of seizure susceptibilities, with the instantaneous seizure rate during REM nearly 10 times higher than baseline and the rate for NREM less than half of baseline. Survival analysis indicated a shorter duration of preseizure REM bouts, with a maximum transition to seizure at ∼90 s after the onset of REM. This study provides the first analysis of a correlation between SOV and seizure onset in the TeTX model of temporal lobe epilepsy, as well as the first demonstration that hippocampal theta rhythms associated with natural behavioral states can serve a seizure-promoting role. Our findings are in contrast with previous studies suggesting that the correlations between SOV and seizures are primarily governed by circadian oscillations and the notion that hippocampal theta rhythms inhibit seizures. The documentation of significant SOV-dependent seizure susceptibilities indicates the potential utility of SOV and its time course in seizure prediction and control.

  19. Hippocampal and prefrontal processing of network topology to simulate the future

    PubMed Central

    Javadi, Amir-Homayoun; Emo, Beatrix; Howard, Lorelei R.; Zisch, Fiona E.; Yu, Yichao; Knight, Rebecca; Pinelo Silva, Joao; Spiers, Hugo J.

    2017-01-01

    Topological networks lie at the heart of our cities and social milieu. However, it remains unclear how and when the brain processes topological structures to guide future behaviour during everyday life. Using fMRI in humans and a simulation of London (UK), here we show that, specifically when new streets are entered during navigation of the city, right posterior hippocampal activity indexes the change in the number of local topological connections available for future travel and right anterior hippocampal activity reflects global properties of the street entered. When forced detours require re-planning of the route to the goal, bilateral inferior lateral prefrontal activity scales with the planning demands of a breadth-first search of future paths. These results help shape models of how hippocampal and prefrontal regions support navigation, planning and future simulation. PMID:28323817

  20. Hippocampal and prefrontal processing of network topology to simulate the future.

    PubMed

    Javadi, Amir-Homayoun; Emo, Beatrix; Howard, Lorelei R; Zisch, Fiona E; Yu, Yichao; Knight, Rebecca; Pinelo Silva, Joao; Spiers, Hugo J

    2017-03-21

    Topological networks lie at the heart of our cities and social milieu. However, it remains unclear how and when the brain processes topological structures to guide future behaviour during everyday life. Using fMRI in humans and a simulation of London (UK), here we show that, specifically when new streets are entered during navigation of the city, right posterior hippocampal activity indexes the change in the number of local topological connections available for future travel and right anterior hippocampal activity reflects global properties of the street entered. When forced detours require re-planning of the route to the goal, bilateral inferior lateral prefrontal activity scales with the planning demands of a breadth-first search of future paths. These results help shape models of how hippocampal and prefrontal regions support navigation, planning and future simulation.

  1. 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.

  2. Stimulation of the Posterior Cortical-Hippocampal Network Enhances Precision of Memory Recollection.

    PubMed

    Nilakantan, Aneesha S; Bridge, Donna J; Gagnon, Elise P; VanHaerents, Stephen A; Voss, Joel L

    2017-02-06

    Episodic memory is thought to critically depend on interaction of the hippocampus with distributed brain regions [1-3]. Specific contributions of distinct networks have been hypothesized, with the hippocampal posterior-medial (HPM) network implicated in the recollection of highly precise contextual and spatial information [3-6]. Current evidence for HPM specialization is mostly indirect, derived from correlative measures such as neural activity recordings. Here we tested the causal role of the HPM network in recollection using network-targeted noninvasive brain stimulation in humans, which has previously been shown to increase functional connectivity within the HPM network [7]. Effects of multiple-day electromagnetic stimulation were assessed using an object-location memory task that segregated recollection precision from general recollection success. HPM network-targeted stimulation produced lasting (∼24 hr) enhancement of recollection precision, without effects on general success. Canonical neural correlates of recollection [8-10] were also modulated by stimulation. Late-positive evoked potential amplitude and theta-alpha oscillatory power were reduced, suggesting that stimulation can improve memory through enhanced reactivation of detailed visuospatial information at retrieval. The HPM network was thus specifically implicated in the processing of fine-grained memory detail, supporting functional specialization of hippocampal-cortical networks. These findings demonstrate that brain networks can be causally linked to distinct and specific neurocognitive functions and suggest mechanisms for long-lasting changes in memory due to network-targeted stimulation.

  3. 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

  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. Intensity oscillations in chromospheric bright points and network elements

    NASA Astrophysics Data System (ADS)

    Kariyappa, R.

    1994-09-01

    From a 35-min time series of photographic spectra in the Ca II H-line obtained at the Vacuum Tower Telescope (VTT) of the Sacramento Peak Observatory under high spatial, spectral, and temporal resolution, we have derived a large number of H-line profiles at the sites of the bright points in the interior of the supergranulation cells, and at the network elements, on a quiet region at the center of the solar disc. It is shown that the bright points are associated with 3-min periodicity in their intensity oscillations whereas the network elements exhibit approximately 7-min periodicity. It is surmised that the large difference in periods of the intensity oscillations, the strength of the magnetic fields, and the intensity enhancements at the sites of the bright points and the network elements themselves may probably be taken as evidence to argue that the mechanisms of heating in the two cases are dissimilar, irrespective of the sizes of these structures.

  6. Hierarchical synchrony of phase oscillators in modular networks

    NASA Astrophysics Data System (ADS)

    Skardal, Per Sebastian; Restrepo, Juan G.

    2012-01-01

    We study synchronization of sinusoidally coupled phase oscillators on networks with modular structure and a large number of oscillators in each community. Of particular interest is the hierarchy of local and global synchrony, i.e., synchrony within and between communities, respectively. Using the recent ansatz of Ott and Antonsen [ChaosCHAOEH1054-150010.1063/1.2930766 18, 037113 (2008)], we find that the degree of local synchrony can be determined from a set of coupled low-dimensional equations. If the number of communities in the network is large, a low-dimensional description of global synchrony can be also found. Using these results, we study bifurcations between different types of synchrony. We find that, depending on the relative strength of local and global coupling, the transition to synchrony in the network can be mediated by local or global effects.

  7. Hierarchical synchrony of phase oscillators in modular networks.

    PubMed

    Skardal, Per Sebastian; Restrepo, Juan G

    2012-01-01

    We study synchronization of sinusoidally coupled phase oscillators on networks with modular structure and a large number of oscillators in each community. Of particular interest is the hierarchy of local and global synchrony, i.e., synchrony within and between communities, respectively. Using the recent ansatz of Ott and Antonsen [Chaos 18, 037113 (2008)], we find that the degree of local synchrony can be determined from a set of coupled low-dimensional equations. If the number of communities in the network is large, a low-dimensional description of global synchrony can be also found. Using these results, we study bifurcations between different types of synchrony. We find that, depending on the relative strength of local and global coupling, the transition to synchrony in the network can be mediated by local or global effects.

  8. Synchronization of networks of oscillators with distributed delay coupling

    NASA Astrophysics Data System (ADS)

    Kyrychko, Y. N.; Blyuss, K. B.; Schöll, E.

    2014-12-01

    This paper studies the stability of synchronized states in networks, where couplings between nodes are characterized by some distributed time delay, and develops a generalized master stability function approach. Using a generic example of Stuart-Landau oscillators, it is shown how the stability of synchronized solutions in networks with distributed delay coupling can be determined through a semi-analytic computation of Floquet exponents. The analysis of stability of fully synchronized and of cluster or splay states is illustrated for several practically important choices of delay distributions and network topologies.

  9. Mean-field theory of assortative networks of phase oscillators

    NASA Astrophysics Data System (ADS)

    Restrepo, Juan G.; Ott, Edward

    2014-09-01

    Employing the Kuramoto model as an illustrative example, we show how the use of the mean-field approximation can be applied to large networks of phase oscillators with assortativity. We then use the ansatz of Ott and Antonsen (Chaos, 19 (2008) 037113) to reduce the mean-field kinetic equations to a system of ordinary differential equations. The resulting formulation is illustrated by application to a network Kuramoto problem with degree assortativity and correlation between the node degrees and the natural oscillation frequencies. Good agreement is found between the solutions of the reduced set of ordinary differential equations obtained from our theory and full simulations of the system. These results highlight the ability of our method to capture all the phase transitions (bifurcations) and system attractors. One interesting result is that degree assortativity can induce transitions from a steady macroscopic state to a temporally oscillating macroscopic state through both (presumed) Hopf and SNIPER (saddle-node, infinite period) bifurcations. Possible use of these techniques to a broad class of phase oscillator network problems is discussed.

  10. 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.

  11. Phase-lag synchronization in networks of coupled chemical oscillators.

    PubMed

    Totz, Jan F; Snari, Razan; Yengi, Desmond; Tinsley, Mark R; Engel, Harald; Showalter, Kenneth

    2015-08-01

    Chemical oscillators with a broad frequency distribution are photochemically coupled in network topologies. Experiments and simulations show that the network synchronization occurs by phase-lag synchronization of clusters of oscillators with zero- or nearly zero-lag synchronization. Symmetry also plays a role in the synchronization, the extent of which is explored as a function of coupling strength, frequency distribution, and the highest frequency oscillator location. The phase-lag synchronization occurs through connected synchronized clusters, with the highest frequency node or nodes setting the frequency of the entire network. The synchronized clusters successively "fire," with a constant phase difference between them. For low heterogeneity and high coupling strength, the synchronized clusters are made up of one or more clusters of nodes with the same permutation symmetries. As heterogeneity is increased or coupling strength decreased, the phase-lag synchronization occurs partially through clusters of nodes sharing the same permutation symmetries. As heterogeneity is further increased or coupling strength decreased, partial synchronization and, finally, independent unsynchronized oscillations are observed. The relationships between these classes of behavior are explored with numerical simulations, which agree well with the experimentally observed behavior.

  12. Oscillator networks with tissue-specific circadian clocks in plants.

    PubMed

    Inoue, Keisuke; Araki, Takashi; Endo, Motomu

    2017-09-08

    Many organisms rely on circadian clocks to synchronize their biological processes with the 24-h rotation of the earth. In mammals, the circadian clock consists of a central clock in the suprachiasmatic nucleus and peripheral clocks in other tissues. The central clock is tightly coupled to synchronize rhythmicity and can organize peripheral clocks through neural and hormonal signals. In contrast to mammals, it has long been assumed that the circadian clocks in each plant cell is able to be entrained by external light, and they are only weakly coupled to each other. Recently, however, several reports have demonstrated that plants have unique oscillator networks with tissue-specific circadian clocks. Here, we introduce our current view regarding tissue-specific properties and oscillator networks of plant circadian clocks. Accumulating evidence suggests that plants have multiple oscillators, which show distinct properties and reside in different tissues. A direct tissue-isolation technique and micrografting have clearly demonstrated that plants have hierarchical oscillator networks consisting of multiple tissue-specific clocks. Copyright © 2017. Published by Elsevier Ltd.

  13. Synchronization in networks of mobile oscillators.

    PubMed

    Fujiwara, Naoya; Kurths, Jürgen; Díaz-Guilera, Albert

    2011-02-01

    We present a model of synchronization in networks of autonomous agents where the topology changes due to agents motion. We introduce two timescales, one for the topological change and another one for local synchronization. If the former scale is much shorter, an approximation that averages out the effect of motion is available. Here we show, however, that the time required for synchronization achievement is larger than the prediction of the approximation in the opposite case, especially close to the continuum percolation transition point. The simulation results are confirmed by means of spectral analysis of the time-dependent Laplacian matrix. Our results show that the tradeoff between these two timescales, which have opposite effects on synchronization, should be taken into account for the design of mobile device networks.

  14. Data Synchronization in a Network of Coupled Phase Oscillators

    NASA Astrophysics Data System (ADS)

    Miyano, Takaya; Tsutsui, Takako

    2007-01-01

    We devised a new method of data mining for a large-scale database. In the method, a network of locally coupled phase oscillators subject to Kuramoto’s model substitutes for given multivariate data to generate major features through phase locking of the oscillators, i.e., phase transition of the data set. We applied the method to the national database of care needs certification for the Japanese public long-term care insurance program, and found three major patterns in the aging process of the frail elderly. This work revealed the latent utility of Kuramoto’s model for data processing.

  15. Chronic exposure to alcohol alters network activity and morphology of cultured hippocampal neurons.

    PubMed

    Korkotian, Eduard; Botalova, Alena; Odegova, Tatiana; Segal, Menahem

    2015-03-01

    The effects of chronic exposure to moderate concentrations of ethanol were studied in cultured hippocampal neurons. Network activity, assessed by imaging of [Ca(2+)]i variations, was markedly suppressed following 5 days of exposure to 0.25-1% ethanol. The reduced activity was sustained following extensive washout of ethanol, but the activity recovered by blockade of inhibition with bicuculline. This reduction of network activity was associated with a reduction in rates of mEPSCs, but not in a change in inhibitory synaptic activity. Chronic exposure to ethanol caused a significant reduction in the density of mature dendritic spines, without an effect on dendritic length or arborization. These results indicate that chronic exposure to ethanol causes a reduction in excitatory network drive in hippocampal neurons adding another dimension to the chronic effects of alcohol abuse.

  16. Disruption of amygdala-entorhinal-hippocampal network in late-life depression.

    PubMed

    Leal, Stephanie L; Noche, Jessica A; Murray, Elizabeth A; Yassa, Michael A

    2017-04-01

    Episodic memory deficits are evident in late-life depression (LLD) and are associated with subtle synaptic and neurochemical changes in the medial temporal lobes (MTL). However, the particular mechanisms by which memory impairment occurs in LLD are currently unknown. We tested older adults with (DS+) and without (DS-) depressive symptoms using high-resolution fMRI that is capable of discerning signals in hippocampal subfields and amygdala nuclei. Scanning was conducted during performance of an emotional discrimination task used previously to examine the relationship between depressive symptoms and amygdala-mediated emotional modulation of hippocampal pattern separation in young adults. We found that hippocampal dentate gyrus (DG)/CA3 activity was reduced during correct discrimination of negative stimuli and increased during correct discrimination of neutral items in DS+ compared to DS- adults. The extent of the latter increase was correlated with symptom severity. Furthermore, DG/CA3 and basolateral amygdala (BLA) activity predicted discrimination performance on negative trials, a relationship that depended on symptom severity. The impact of the BLA on depressive symptom severity was mediated by the DG/CA3 during discrimination of neutral items, and by the lateral entorhinal cortex (LEC) during false recognition of positive items. These results shed light on a novel mechanistic account for amygdala-hippocampal network changes and concurrent alterations in emotional episodic memory in LLD. The BLA-LEC-DG/CA3 network, which comprises a key pathway by which emotion modulates memory, is specifically implicated in LLD. © 2017 Wiley Periodicals, Inc.

  17. Phase-Locked Inhibition, but Not Excitation, Underlies Hippocampal Ripple Oscillations in Awake Mice In Vivo.

    PubMed

    Gan, Jian; Weng, Shih-Ming; Pernía-Andrade, Alejandro J; Csicsvari, Jozsef; Jonas, Peter

    2017-01-18

    Sharp wave-ripple (SWR) oscillations play a key role in memory consolidation during non-rapid eye movement sleep, immobility, and consummatory behavior. However, whether temporally modulated synaptic excitation or inhibition underlies the ripples is controversial. To address this question, we performed simultaneous recordings of excitatory and inhibitory postsynaptic currents (EPSCs and IPSCs) and local field potentials (LFPs) in the CA1 region of awake mice in vivo. During SWRs, inhibition dominated over excitation, with a peak conductance ratio of 4.1 ± 0.5. Furthermore, the amplitude of SWR-associated IPSCs was positively correlated with SWR magnitude, whereas that of EPSCs was not. Finally, phase analysis indicated that IPSCs were phase-locked to individual ripple cycles, whereas EPSCs were uniformly distributed in phase space. Optogenetic inhibition indicated that PV(+) interneurons provided a major contribution to SWR-associated IPSCs. Thus, phasic inhibition, but not excitation, shapes SWR oscillations in the hippocampal CA1 region in vivo.

  18. Synchrony-optimized networks of Kuramoto oscillators with inertia

    NASA Astrophysics Data System (ADS)

    Pinto, Rafael S.; Saa, Alberto

    2016-12-01

    We investigate synchronization in networks of Kuramoto oscillators with inertia. More specifically, we introduce a rewiring algorithm consisting basically in a hill climb scheme in which the edges of the network are swapped in order to enhance its synchronization capacity. We show that the synchrony-optimized networks generated by our algorithm have some interesting topological and dynamical properties. In particular, they typically exhibit an anticipation of the synchronization onset and are more robust against certain types of perturbations. We consider synthetic random networks and also a network with a topology based on an approximated model of the (high voltage) power grid of Spain, since networks of Kuramoto oscillators with inertia have been used recently as simplified models for power grids, for which synchronization is obviously a crucial issue. Despite the extreme simplifications adopted in these models, our results, among others recently obtained in the literature, may provide interesting principles to guide the future growth and development of real-world grids, specially in the case of a change of the current paradigm of centralized towards distributed generation power grids.

  19. Efficacy of nonselective optogenetic control of the medial septum over hippocampal oscillations: the influence of speed and implications for cognitive enhancement.

    PubMed

    Blumberg, Benjamin J; Flynn, Sean P; Barriere, Sylvain J; Mouchati, Philippe R; Scott, Rod C; Holmes, Gregory L; Barry, Jeremy M

    2016-12-01

    Optogenetics holds great promise for both the dissection of neural circuits and the evaluation of theories centered on the temporal organizing properties of oscillations that underpin cognition. To date, no studies have examined the efficacy of optogenetic stimulation for altering hippocampal oscillations in freely moving wild-type rats, or how these alterations would affect performance on behavioral tasks. Here, we used an AAV virus to express ChR2 in the medial septum (MS) of wild-type rats, and optically stimulated septal neurons at 6 Hz and 30 Hz. We measured the corresponding effects of these stimulations on the oscillations of the MS and hippocampal subfields CA1 and CA3 in three different contexts: (1) With minimal movement while the rats sat in a confined chamber; (2) Explored a novel open field; and (3) Learned and performed a T-maze behavioral task. While control yellow light stimulation did not affect oscillations, 6-Hz blue light septal stimulations altered hippocampal theta oscillations in a manner that depended on the animal's mobility and speed. While the 30 Hz blue light septal stimulations only altered theta frequency in CA1 while the rat had limited mobility, it robustly increased the amplitude of hippocampal signals at 30 Hz in both regions in all three recording contexts. We found that animals were more likely to make a correct choice during Day 1 of T-maze training during both MS stimulation protocols than during control stimulation, and that improved performance was independent of theta frequency alterations.

  20. Reconstructing networks of pulse-coupled oscillators from spike trains

    NASA Astrophysics Data System (ADS)

    Cestnik, Rok; Rosenblum, Michael

    2017-07-01

    We present an approach for reconstructing networks of pulse-coupled neuronlike oscillators from passive observation of pulse trains of all nodes. It is assumed that units are described by their phase response curves and that their phases are instantaneously reset by incoming pulses. Using an iterative procedure, we recover the properties of all nodes, namely their phase response curves and natural frequencies, as well as strengths of all directed connections.

  1. Functional network changes in hippocampal CA1 after status epilepticus predict spatial memory deficits in rats.

    PubMed

    Tyler, Anna L; Mahoney, J Matthew; Richard, Gregory R; Holmes, Gregory L; Lenck-Santini, Pierre-Pascal; Scott, Rod C

    2012-08-15

    Status epilepticus (SE) is a common neurological emergency, which has been associated with subsequent cognitive impairments. Neuronal death in hippocampal CA1 is thought to be an important mechanism of these impairments. However, it is also possible that functional interactions between surviving neurons are important. In this study we recorded in vivo single-unit activity in the CA1 hippocampal region of rats while they performed a spatial memory task. From these data we constructed functional networks describing pyramidal cell interactions. To build the networks, we used maximum entropy algorithms previously applied only to in vitro data. We show that several months following SE pyramidal neurons display excessive neuronal synchrony and less neuronal reactivation during rest compared with those in healthy controls. Both effects predict rat performance in a spatial memory task. These results provide a physiological mechanism for SE-induced cognitive impairment and highlight the importance of the systems-level perspective in investigating spatial cognition.

  2. Synchronization of networks of chaotic oscillators: Structural and dynamical datasets.

    PubMed

    Sevilla-Escoboza, Ricardo; Buldú, Javier M

    2016-06-01

    We provide the topological structure of a series of N=28 Rössler chaotic oscillators diffusively coupled through one of its variables. The dynamics of the y variable describing the evolution of the individual nodes of the network are given for a wide range of coupling strengths. Datasets capture the transition from the unsynchronized behavior to the synchronized one, as a function of the coupling strength between oscillators. The fact that both the underlying topology of the system and the dynamics of the nodes are given together makes this dataset a suitable candidate to evaluate the interplay between functional and structural networks and serve as a benchmark to quantify the ability of a given algorithm to extract the structural network of connections from the observation of the dynamics of the nodes. At the same time, it is possible to use the dataset to analyze the different dynamical properties (randomness, complexity, reproducibility, etc.) of an ensemble of oscillators as a function of the coupling strength.

  3. Network bursting using experimentally constrained single compartment CA3 hippocampal neuron models with adaptation.

    PubMed

    Dur-e-Ahmad, Muhammad; Nicola, Wilten; Campbell, Sue Ann; Skinner, Frances K

    2012-08-01

    The hippocampus is a brain structure critical for memory functioning. Its network dynamics include several patterns such as sharp waves that are generated in the CA3 region. To understand how population outputs are generated, models need to consider aspects of network size, cellular and synaptic characteristics and context, which are necessarily 'balanced' in appropriate ways to produce particular outputs. Thick slice hippocampal preparations spontaneously produce sharp waves that are initiated in CA3 regions and depend on the right balance of glutamatergic activities. As a step toward developing network models that can explain important balances in the generation of hippocampal output, we develop models of CA3 pyramidal cells. Our models are single compartment in nature, use an Izhikevich-type structure and involve parameter values that are specifically designed to encompass CA3 intrinsic properties. Importantly, they incorporate spike frequency adaptation characteristics that are directly comparable to those measured experimentally. Excitatory networks using these model cells are able to produce bursting suggesting that the amount of spike frequency adaptation expressed in the biological cells is an essential contributor to network bursting, and as such, may be important for sharp wave generation. The network bursting mechanism is numerically dissected showing the critical balance between adaptation and excitatory drive. The compact nature of our models allows large network simulations to be efficiently computed. This, together with the linkage of our models to cellular characteristics, will allow us to develop an understanding of population output of CA3 hippocampus with direct biological comparisons.

  4. Robust network topologies for generating oscillations with temperature-independent periods

    PubMed Central

    Wu, Lili; Ouyang, Qi; Wang, Hongli

    2017-01-01

    Nearly all living systems feature a temperature-independent oscillation period in circadian clocks. This ubiquitous property occurs at the system level and is rooted in the network architecture of the clock machinery. To investigate the mechanism of this prominent property of the circadian clock and provide general guidance for generating robust genetic oscillators with temperature-compensated oscillations, we theoretically explored the design principle and core network topologies preferred by oscillations with a temperature-independent period. By enumerating all topologies of genetic regulatory circuits with three genes, we obtained four network motifs, namely, a delayed negative feedback oscillator, repressilator, activator-inhibitor oscillator and substrate-depletion oscillator; hybrids of these motifs constitute the vast majority of target network topologies. These motifs are biased in their capacities for achieving oscillations and the temperature sensitivity of the period. The delayed negative feedback oscillator and repressilator are more robust for oscillations, whereas the activator-inhibitor and substrate-depletion oscillators are superior for maintaining a temperature-independent oscillation period. These results suggest that thermally robust oscillation can be more plausibly achieved by hybridizing these two categories of network motifs. Antagonistic balance and temperature insulation mechanisms for achieving temperature compensation are typically found in these topologies with temperature robustness. In the temperature insulation approach, the oscillation period relies on very few parameters, and these parameters are influenced only slightly by temperature. This approach prevents the temperature from affecting the oscillation period and generates circadian rhythms that are robust against environmental perturbations. PMID:28152061

  5. Neuronal mechanisms of the anoxia-induced network oscillations in the rat hippocampus in vitro.

    PubMed

    Dzhala, V; Khalilov, I; Ben-Ari, Y; Khazipov, R

    2001-10-15

    1. A spindle of fast network oscillations precedes the ischaemia-induced rapid depolarisation in the rat hippocampus in vivo. However, this oscillatory pattern could not be reproduced in slices and the underlying mechanisms remain poorly understood. We have found that anoxia-induced network oscillations (ANOs, 20-40 Hz, lasting for 1-2 min) can be reproduced in the intact hippocampi of postnatal day P7-10 rats in vitro, and we have examined the underlying mechanisms using whole-cell and extracellular field potential recordings in a CA3 pyramidal layer. 2. ANOs were generated at the beginning of the anoxic depolarisation, when pyramidal cells depolarised to subthreshold values. Maximal power of the ANOs was attained when pyramidal cells depolarised to -56 mV; depolarisation above -47 mV resulted in a depolarisation block of pyramidal cells and a waning of ANOs. 3. A multiple unit activity in extracellular field recordings was phase locked to the negative and ascending phases of ANOs. Pyramidal cells recorded in current-clamp mode generated action potentials with an average probability of about 0.05 per cycle. The AMPA receptor-mediated EPSCs and the GABA receptor-mediated IPSCs in CA3 pyramidal cells were also phase locked with ANOs. 4. ANOs were prevented by tetrodotoxin and glutamate receptor antagonists CNQX and APV, and were slowed down by the allosteric GABA(A) receptor modulator diazepam. In the presence of the GABA(A) receptor antagonist bicuculline, ANOs were transformed to epileptiform discharges. 5. In the presence of the A1 adenosine receptor antagonist 8-cyclopentyl-1,3-dipropylxanthine (DPCPX), the anoxia induced an epileptiform activity and no ANOs were observed. 6. In normoxic conditions, a rise of extracellular potassium to 10 mM induced an epileptiform activity. Increasing extracellular potassium in conjunction with a bath application of the adenosine A1 receptor agonist cyclopentyladenosine induced oscillations similar to ANOs. 7. Multisite

  6. Neuronal mechanisms of the anoxia-induced network oscillations in the rat hippocampus in vitro

    PubMed Central

    Dzhala, Volodymyr; Khalilov, Ilgam; Ben-Ari, Yehezkiel; Khazipov, Roustem

    2001-01-01

    A spindle of fast network oscillations precedes the ischaemia-induced rapid depolarisation in the rat hippocampus in vivo. However, this oscillatory pattern could not be reproduced in slices and the underlying mechanisms remain poorly understood. We have found that anoxia-induced network oscillations (ANOs, 20–40 Hz, lasting for 1–2 min) can be reproduced in the intact hippocampi of postnatal day P7–10 rats in vitro, and we have examined the underlying mechanisms using whole-cell and extracellular field potential recordings in a CA3 pyramidal layer.ANOs were generated at the beginning of the anoxic depolarisation, when pyramidal cells depolarised to subthreshold values. Maximal power of the ANOs was attained when pyramidal cells depolarised to −56 mV; depolarisation above −47 mV resulted in a depolarisation block of pyramidal cells and a waning of ANOs.A multiple unit activity in extracellular field recordings was phase locked to the negative and ascending phases of ANOs. Pyramidal cells recorded in current-clamp mode generated action potentials with an average probability of about 0.05 per cycle. The AMPA receptor-mediated EPSCs and the GABA receptor-mediated IPSCs in CA3 pyramidal cells were also phase locked with ANOs.ANOs were prevented by tetrodotoxin and glutamate receptor antagonists CNQX and APV, and were slowed down by the allosteric GABAA receptor modulator diazepam. In the presence of the GABAA receptor antagonist bicuculline, ANOs were transformed to epileptiform discharges.In the presence of the A1 adenosine receptor antagonist 8-cyclopentyl-1,3-dipropylxanthine (DPCPX), the anoxia induced an epileptiform activity and no ANOs were observed.In normoxic conditions, a rise of extracellular potassium to 10 mm induced an epileptiform activity. Increasing extracellular potassium in conjunction with a bath application of the adenosine A1 receptor agonist cyclopentyladenosine induced oscillations similar to ANOs.Multisite recordings along the septo

  7. 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.

  8. 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

  9. Astrocytes regulate heterogeneity of presynaptic strengths in hippocampal networks

    PubMed Central

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

    2016-01-01

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

  10. 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.

  11. Topological Influence On Network Of Coupled Chemical Oscillators

    NASA Astrophysics Data System (ADS)

    Zhao, Jie; Rericha, Erin; Vanderbilt Biophysics Collaboration

    2013-03-01

    Networks of interacting nodes are ubiquitous in biological and communication systems. Recently the manner of the network connections, be it through of activator or inhibitor signals, and the topology of the network has received theoretical attention with the goal of finding networks with optimal synchronization and information transmission properties. In preparation for building an experimental system to examine these predictions, we numerically explore networks of Belousov-Zhabotinsky oscillatory nodes connected through unidirectional links of activator species. We measure the time required for the nodes to synchronize as a function of the network topology. While we observe a trend of smaller synchronization times with increasing first non-zero eigen values, we find that the most important factor in determining synchronization time is the initial phase difference between the oscillators. We find that the synchronization times for a given network topology, as determined from a uniform distribution of initial phase differences, is best described with a skewed Gaussian. To better understand the factors underlying this distribution, we look at the synchronization times in a three-node network as a function of both initial conditions and model parameters.

  12. 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

  13. Spontaneous oscillations of capillary blood flow in artificial microvascular networks.

    PubMed

    Forouzan, Omid; Yang, Xiaoxi; Sosa, Jose M; Burns, Jennie M; Shevkoplyas, Sergey S

    2012-09-01

    Previous computational studies have suggested that the capillary blood flow oscillations frequently observed in vivo can originate spontaneously from the non-linear rheological properties of blood, without any regulatory input. Testing this hypothesis definitively in experiments involving real microvasculature has been difficult because in vivo the blood flow in capillaries is always actively controlled by the host. The objective of this study was to test the hypothesis experimentally and to investigate the relative contribution of different blood cells to the capillary blood flow dynamics under static boundary conditions and in complete isolation from the active regulatory mechanisms mediated by the blood vessels in vivo. To accomplish this objective, we passed whole blood and re-constituted blood samples (purified red blood cells suspended in buffer or in autologous plasma) through an artificial microvascular network (AMVN) comprising completely inert, microfabricated vessels with the architecture inspired by the real microvasculature. We found that the flow of blood in capillaries of the AMVN indeed oscillates with characteristic frequencies in the range of 0-0.6 Hz, which is in a very good agreement with previous computational studies and in vivo observations. We also found that the traffic of leukocytes through the network (typically neglected in computational modeling) plays an important role in generating the oscillations. This study represents the key piece of experimental evidence in support of the hypothesis that spontaneous, self-sustained oscillations of capillary blood flow can be generated solely by the non-linear rheological properties of blood flowing through microvascular networks, and provides an insight into the mechanism of this fundamentally important microcirculatory phenomenon. Copyright © 2012 Elsevier Inc. All rights reserved.

  14. Dynamics of finite-size networks of coupled oscillators

    NASA Astrophysics Data System (ADS)

    Buice, Michael; Chow, Carson

    2010-03-01

    Mean field models of coupled oscillators do not adequately capture the dynamics of large but finite size networks. For example, the incoherent state of the Kuramoto model of coupled oscillators exhibits marginal modes in mean field theory. We demonstrate that corrections due to finite size effects render these modes stable in the subcritical case, i.e. when the population is not synchronous. This demonstration is facilitated by the construction of a non-equilibrium statistical field theoretic formulation of a generic model of coupled oscillators. This theory is consistent with previous results. In the all-to-all case, the fluctuations in this theory are due completely to finite size corrections, which can be calculated in an expansion in 1/N, where N is the number of oscillators. The N -> infinity limit of this theory is what is traditionally called mean field theory for the Kuramoto model. We also demonstrate this approach with a system of pulse coupled theta neurons and describe the stability of the population activity.

  15. Circadian oscillation of hippocampal MAPK activity and cAMP: implications for memory persistence

    PubMed Central

    Eckel-Mahan, Kristin L; Phan, Trongha; Han, Sung; Wang, Hongbing; Chan, Guy C-K; Scheiner, Zachary S

    2008-01-01

    The mitogen-activated protein kinase (MAPK) and cyclic adenosine monophosphate (cAMP) signal transduction pathways have critical roles in the consolidation of hippocampus-dependent memory. We found that extracellular regulated kinase 1/2 MAPK phosphorylation and cAMP underwent a circadian oscillation in the hippocampus that was paralleled by changes in Ras activity and the phosphorylation of MAPK kinase and cAMP response element-binding protein (CREB). The nadir of this activation cycle corresponded with severe deficits in hippocampus-dependent fear conditioning under both light-dark and free-running conditions. Circadian oscillations in cAMP and MAPK activity were absent in memory-deficient transgenic mice that lacked Ca2+-stimulated adenylyl cyclases. Furthermore, physiological and pharmacological interference with oscillations in MAPK phosphorylation after the cellular memory consolidation period impaired the persistence of hippocampus-dependent memory. These data suggest that the persistence of long-term memories may depend on reactivation of the cAMP/MAPK/CREB transcriptional pathway in the hippocampus during the circadian cycle. PMID:19160506

  16. Loss of the Kv1.1 potassium channel promotes pathologic sharp waves and high frequency oscillations in in vitro hippocampal slices

    PubMed Central

    Simeone, Timothy A.; Simeone, Kristina A.; Samson, Kaeli K.; Kim, Do Young; Rho, Jong M.

    2013-01-01

    In human disease, channelopathies involving functional reduction of the delayed rectifier potassium channel α-subunit Kv1.1 – either by mutation or autoimmune inhibition – result in temporal lobe epilepsy. Kv1.1 is prominently expressed in the axons of the hippocampal tri-synaptic pathway, suggesting its absence will result in widespread effects on normal network oscillatory activity. Here, we performed in vitro extracellular recordings using a multielectrode array to determine the effects of loss of Kv1.1 on spontaneous sharp waves (SPWs) and high frequency oscillations (HFOs). We found that Kcna1-null hippocampi generate SPWs and ripples (80–200 Hz bandwidth) with a 50% increased rate of incidence and 50% longer duration, and that epilepsy-associated pathologic HFOs in the fast ripple bandwidth (200–600 Hz) are also present. Furthermore, Kcna1-null CA3 has enhanced coupling of excitatory inputs and population spike generation and CA3 principal cells have reduced spike timing reliability. Removing the influence of mossy fiber and perforant path inputs by microdissecting the Kcna1-null CA3 region mostly rescued the oscillatory behavior and improved spike timing. We found that Kcna1-null mossy fibers and medial perforant path axons are hyperexcitable and produce greater pre- and post-synaptic responses with reduced paired-pulse ratios suggesting increased neurotransmitter release at these terminals. These findings were recapitulated in wild-type slices exposed to the Kv1.1 inhibitor dendrotoxin-κ. Collectively, these data indicate that loss of Kv1.1 enhances synaptic release in the CA3 region, which reduces spike timing precision of individual neurons leading to disorganization of network oscillatory activity and promotes the emergence of fast ripples. PMID:23466697

  17. Voluntary control of intracortical oscillations for reconfiguration of network activity

    PubMed Central

    Corlier, Juliana; Valderrama, Mario; Navarrete, Miguel; Lehongre, Katia; Hasboun, Dominique; Adam, Claude; Belaid, Hayat; Clémenceau, Stéphane; Baulac, Michel; Charpier, Stéphane; Navarro, Vincent; Le Van Quyen, Michel

    2016-01-01

    Voluntary control of oscillatory activity represents a key target in the self-regulation of brain function. Using a real-time closed-loop paradigm and simultaneous macro- and micro-electrode recordings, we studied the effects of self-induced intracortical oscillatory activity (4–8 Hz) in seven neurosurgical patients. Subjects learned to robustly and specifically induce oscillations in the target frequency, confirmed by increased oscillatory event density. We have found that the session-to-session variability in performance was explained by the functional long-range decoupling of the target area suggesting a training-induced network reorganization. Downstream effects on more local activities included progressive cross-frequency-coupling with gamma oscillations (30–120 Hz), and the dynamic modulation of neuronal firing rates and spike timing, indicating an improved temporal coordination of local circuits. These findings suggest that effects of voluntary control of intracortical oscillations can be exploited to specifically target plasticity processes to reconfigure network activity, with a particular relevance for memory function or skill acquisition. PMID:27808225

  18. Chimeras and clusters in networks of hyperbolic chaotic oscillators

    NASA Astrophysics Data System (ADS)

    Cano, A. V.; Cosenza, M. G.

    2017-03-01

    We show that chimera states, where differentiated subsets of synchronized and desynchronized dynamical elements coexist, can emerge in networks of hyperbolic chaotic oscillators subject to global interactions. As local dynamics we employ Lozi maps, which possess hyperbolic chaotic attractors. We consider a globally coupled system of these maps and use two statistical quantities to describe its collective behavior: the average fraction of elements belonging to clusters and the average standard deviation of state variables. Chimera states, clusters, complete synchronization, and incoherence are thus characterized on the space of parameters of the system. We find that chimera states are related to the formation of clusters in the system. In addition, we show that chimera states arise for a sufficiently long range of interactions in nonlocally coupled networks of these maps. Our results reveal that, under some circumstances, hyperbolicity does not impede the formation of chimera states in networks of coupled chaotic systems, as it had been previously hypothesized.

  19. Altered resting-state hippocampal functional networks associated with chemotherapy-induced prospective memory impairment in breast cancer survivors

    PubMed Central

    Cheng, Huaidong; Li, Wen; Gong, Liang; Xuan, Han; Huang, Zhonglian; Zhao, Hong; Wang, Long Sheng; Wang, Kai

    2017-01-01

    In this study, we aimed to investigate the intrinsic hippocampal functional connectivity (FC) network and its relationship with prospective memory in patients with breast cancer suffering from chemotherapy-induced cognitive impairment (CICI). Thirty-four breast cancer patients before and after adjuvant chemotherapy (CB and CC, respectively) and 31 age- and education-matched cognitively normal (CN) women were recruited and subjected to a prospective memory task and a resting-state functional magnetic resonance imaging scan. Seed-based functional connectivity analysis was used to compare the hippocampal FC networks between CC and CN groups. Partial correction analysis was used to examine the association between the hippocampal FC network and prospective memory in the CC group. The cancer group that underwent chemotherapy obtained significantly poorer scores than the CN group on mini-mental state examination, verbal fluency test, digit span, and prospective memory examination. Compared to the CN group, CC group showed increased hippocampal connectivity in the frontal and parietal cortex, precuneus, posterior cingulate cortex, and the cerebellum. In addition, the increasing hippocampal FC networks were negatively correlated with prospective memory performance in the CC group. These findings suggest maladaptive hippocampal functioning as a mechanism underlying the impairment of prospective memory in patients experiencing CICI. PMID:28327626

  20. Altered resting-state hippocampal functional networks associated with chemotherapy-induced prospective memory impairment in breast cancer survivors.

    PubMed

    Cheng, Huaidong; Li, Wen; Gong, Liang; Xuan, Han; Huang, Zhonglian; Zhao, Hong; Wang, Long Sheng; Wang, Kai

    2017-03-22

    In this study, we aimed to investigate the intrinsic hippocampal functional connectivity (FC) network and its relationship with prospective memory in patients with breast cancer suffering from chemotherapy-induced cognitive impairment (CICI). Thirty-four breast cancer patients before and after adjuvant chemotherapy (CB and CC, respectively) and 31 age- and education-matched cognitively normal (CN) women were recruited and subjected to a prospective memory task and a resting-state functional magnetic resonance imaging scan. Seed-based functional connectivity analysis was used to compare the hippocampal FC networks between CC and CN groups. Partial correction analysis was used to examine the association between the hippocampal FC network and prospective memory in the CC group. The cancer group that underwent chemotherapy obtained significantly poorer scores than the CN group on mini-mental state examination, verbal fluency test, digit span, and prospective memory examination. Compared to the CN group, CC group showed increased hippocampal connectivity in the frontal and parietal cortex, precuneus, posterior cingulate cortex, and the cerebellum. In addition, the increasing hippocampal FC networks were negatively correlated with prospective memory performance in the CC group. These findings suggest maladaptive hippocampal functioning as a mechanism underlying the impairment of prospective memory in patients experiencing CICI.

  1. 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

  2. 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.

  3. Megamap: flexible representation of a large space embedded with nonspatial information by a hippocampal attractor network

    PubMed Central

    Zhang, Kechen

    2016-01-01

    The problem of how the hippocampus encodes both spatial and nonspatial information at the cellular network level remains largely unresolved. Spatial memory is widely modeled through the theoretical framework of attractor networks, but standard computational models can only represent spaces that are much smaller than the natural habitat of an animal. We propose that hippocampal networks are built on a basic unit called a “megamap,” or a cognitive attractor map in which place cells are flexibly recombined to represent a large space. Its inherent flexibility gives the megamap a huge representational capacity and enables the hippocampus to simultaneously represent multiple learned memories and naturally carry nonspatial information at no additional cost. On the other hand, the megamap is dynamically stable, because the underlying network of place cells robustly encodes any location in a large environment given a weak or incomplete input signal from the upstream entorhinal cortex. Our results suggest a general computational strategy by which a hippocampal network enjoys the stability of attractor dynamics without sacrificing the flexibility needed to represent a complex, changing world. PMID:27193320

  4. 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

  5. Attractor neural networks storing multiple space representations: A model for hippocampal place fields

    NASA Astrophysics Data System (ADS)

    Battaglia, F. P.; Treves, A.

    1998-12-01

    A recurrent neural network model storing multiple spatial maps, or ``charts,'' is analyzed. A network of this type has been suggested as a model for the origin of place cells in the hippocampus of rodents. The extremely diluted and fully connected limits are studied, and the storage capacity and the information capacity are found. The important parameters determining the performance of the network are the sparsity of the spatial representations and the degree of connectivity, as found already for the storage of individual memory patterns in the general theory of autoassociative networks. Such results suggest a quantitative parallel between theories of hippocampal function in different animal species, such as primates (episodic memory) and rodents (memory for space).

  6. Chaotic itinerancy in the oscillator neural network without Lyapunov functions

    NASA Astrophysics Data System (ADS)

    Uchiyama, Satoki; Fujisaka, Hirokazu

    2004-09-01

    Chaotic itinerancy (CI), which is defined as an incessant spontaneous switching phenomenon among attractor ruins in deterministic dynamical systems without Lyapunov functions, is numerically studied in the case of an oscillator neural network model. The model is the pseudoinverse-matrix version of the previous model [S. Uchiyama and H. Fujisaka, Phys. Rev. E 65, 061912 (2002)] that was studied theoretically with the aid of statistical neurodynamics. It is found that CI in neural nets can be understood as the intermittent dynamics of weakly destabilized chaotic retrieval solutions.

  7. 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.

  8. Converting genetic network oscillations into somite spatial patterns

    NASA Astrophysics Data System (ADS)

    Mazzitello, K. I.; Arizmendi, C. M.; Hentschel, H. G. E.

    2008-08-01

    The segmentation of vertebrate embryos, a process known as somitogenesis, depends on a complex genetic network that generates highly dynamic gene expression in an oscillatory manner. A recent proposal for the mechanism underlying these oscillations involves negative-feedback regulation at transcriptional translational levels, also known as the “delay model” [J. Lewis Curr. Biol. 13, 1398 (2003)]. In addition, in the zebrafish a longitudinal positional information signal in the form of an Fgf8 gradient constitutes a determination front that could be used to transform these coupled intracellular temporal oscillations into the observed spatial periodicity of somites. Here we consider an extension of the delay model by taking into account the interaction of the oscillation clock with the determination front. Comparison is made with the known properties of somite formation in the zebrafish embryo. We also show that the model can mimic the anomalies formed when progression of the determination wave front is perturbed and make an experimental prediction that can be used to test the model.

  9. Phase-locked regimes in delay-coupled oscillator networks

    NASA Astrophysics Data System (ADS)

    Punetha, Nirmal; Prasad, Awadhesh; Ramaswamy, Ramakrishna

    2014-12-01

    For an ensemble of globally coupled oscillators with time-delayed interactions, an explicit relation for the frequency of synchronized dynamics corresponding to different phase behaviors is obtained. One class of solutions corresponds to globally synchronized in-phase oscillations. The other class of solutions have mixed phases, and these can be either randomly distributed or can be a splay state, namely with phases distributed uniformly on a circle. In the strong coupling limit and for larger networks, the in-phase synchronized configuration alone remains. Upon variation of the coupling strength or the size of the system, the frequency can change discontinuously, when there is a transition from one class of solutions to another. This can be from the in-phase state to a mixed-phase state, but can also occur between two in-phase configurations of different frequency. Analytical and numerical results are presented for coupled Landau-Stuart oscillators, while numerical results are shown for Rössler and FitzHugh-Nagumo systems.

  10. Collective signaling behavior in a networked-oscillator model

    NASA Astrophysics Data System (ADS)

    Liu, Z.-H.; Hui, P. M.

    2007-09-01

    We propose and study the collective behavior of a model of networked signaling objects that incorporates several ingredients of real-life systems. These ingredients include spatial inhomogeneity with grouping of signaling objects, signal attenuation with distance, and delayed and impulsive coupling between non-identical signaling objects. Depending on the coupling strength and/or time-delay effect, the model exhibits completely, partially, and locally collective signaling behavior. In particular, a correlated signaling (CS) behavior is observed in which there exist time durations when nearly a constant fraction of oscillators in the system are in the signaling state. These time durations are much longer than the duration of a spike when a single oscillator signals, and they are separated by regular intervals in which nearly all oscillators are silent. Such CS behavior is similar to that observed in biological systems such as fireflies, cicadas, crickets, and frogs. The robustness of the CS behavior against noise is also studied. It is found that properly adjusting the coupling strength and noise level could enhance the correlated behavior.

  11. Oscillations and chaos in neural networks: an exactly solvable model.

    PubMed Central

    Wang, L P; Pichler, E E; Ross, J

    1990-01-01

    We consider a randomly diluted higher-order network with noise, consisting of McCulloch-Pitts neurons that interact by Hebbian-type connections. For this model, exact dynamical equations are derived and solved for both parallel and random sequential updating algorithms. For parallel dynamics, we find a rich spectrum of different behaviors including static retrieving and oscillatory and chaotic phenomena in different parts of the parameter space. The bifurcation parameters include first- and second-order neuronal interaction coefficients and a rescaled noise level, which represents the combined effects of the random synaptic dilution, interference between stored patterns, and additional background noise. We show that a marked difference in terms of the occurrence of oscillations or chaos exists between neural networks with parallel and random sequential dynamics. Images PMID:2251287

  12. Isochronous dynamics in pulse coupled oscillator networks with delay

    NASA Astrophysics Data System (ADS)

    Li, Pan; Lin, Wei; Efstathiou, Konstantinos

    2017-05-01

    We consider a network of identical pulse-coupled oscillators with delay and all-to-all coupling. We demonstrate that the discontinuous nature of the dynamics induces the appearance of isochronous regions—subsets of the phase space filled with periodic orbits having the same period. For each fixed value of the network parameters, such an isochronous region corresponds to a subset of initial states on an appropriate surface of section with non-zero dimensions such that all periodic orbits in this set have qualitatively similar dynamical behaviour. We analytically and numerically study in detail such an isochronous region, give proof of its existence, and describe its properties. We further describe other isochronous regions that appear in the system.

  13. Content-based retrieval using MPEG-7 visual descriptor and hippocampal neural network

    NASA Astrophysics Data System (ADS)

    Kim, Young Ho; Joung, Lyang-Jae; Kang, Dae-Seong

    2005-12-01

    As development of digital technology, many kinds of multimedia data are used variously and requirements for effective use by user are increasing. In order to transfer information fast and precisely what user wants, effective retrieval method is required. As existing multimedia data are impossible to apply the MPEG-1, MPEG-2 and MPEG-4 technologies which are aimed at compression, store and transmission. So MPEG-7 is introduced as a new technology for effective management and retrieval for multimedia data. In this paper, we extract content-based features using color descriptor among the MPEG-7 standardization visual descriptor, and reduce feature data applying PCA(Principal Components Analysis) technique. We remodel the cerebral cortex and hippocampal neural networks as a principle of a human's brain and it can label the features of the image-data which are inputted according to the order of hippocampal neuron structure to reaction-pattern according to the adjustment of a good impression in Dentate gyrus region and remove the noise through the auto-associate- memory step in the CA3 region. In the CA1 region receiving the information of the CA3, it can make long-term or short-term memory learned by neuron. Hippocampal neural network makes neuron of the neural network separate and combine dynamically, expand the neuron attaching additional information using the synapse and add new features according to the situation by user's demand. When user is querying, it compares feature value stored in long-term memory first and it learns feature vector fast and construct optimized feature. So the speed of index and retrieval is fast. Also, it uses MPEG-7 standard visual descriptors as content-based feature value, it improves retrieval efficiency.

  14. Hippocampal Contributions to the Large-Scale Episodic Memory Network Predict Vivid Visual Memories.

    PubMed

    Geib, Benjamin R; Stanley, Matthew L; Wing, Erik A; Laurienti, Paul J; Cabeza, Roberto

    2017-01-01

    A common approach in memory research is to isolate the function(s) of individual brain regions, such as the hippocampus, without addressing how those regions interact with the larger network. To investigate the properties of the hippocampus embedded within large-scale networks, we used functional magnetic resonance imaging and graph theory to characterize complex hippocampal interactions during the active retrieval of vivid versus dim visual memories. The study yielded 4 main findings. First, the right hippocampus displayed greater communication efficiency with the network (shorter path length) and became a more convergent structure for information integration (higher centrality measures) for vivid than dim memories. Second, vivid minus dim differences in our graph theory measures of interest were greater in magnitude for the right hippocampus than for any other region in the 90-region network. Moreover, the right hippocampus significantly reorganized its set of direct connections from dim to vivid memory retrieval. Finally, beyond the hippocampus, communication throughout the whole-brain network was more efficient (shorter global path length) for vivid than dim memories. In sum, our findings illustrate how multivariate network analyses can be used to investigate the roles of specific regions within the large-scale network, while also accounting for global network changes.

  15. Hippocampal network dynamics constrain the time lag between pyramidal cells across modified environments

    PubMed Central

    Diba, Kamran; Buzsáki, György

    2008-01-01

    The hippocampus provides a spatial map of the environment. Changes in the environment alter the firing patterns of hippocampal neurons, but are presumably constrained by elements of the network dynamics. We compared the neural activity in CA1 and CA3 regions of the hippocampus in rats running for water reward on a linear track, before and after the track length was shortened. A fraction of cells lost their place-fields and new sets of cells with fields emerged, indicating distinct representation of the two tracks. Cells active in both environments shifted their place-fields in a location dependent manner, most notably at the beginning and the end of the track. Furthermore, peak firing rates and place-field sizes decreased, while place-field overlap and co-activity increased. Power in the theta-frequency band of the local field potentials also decreased in both CA1 and CA3, along with the coherence between the two structures. In contrast, the theta-scale (0–150 ms) time lags between cell pairs, representing distances on the tracks, were conserved, and the activity of the inhibitory neuron population was maintained across environments. We interpret these observations as reflecting the freedoms and constraints of the hippocampal network dynamics. The freedoms permit the necessary flexibility for the network to distinctly represent unique patterns, while the dynamics constrain the speed at which activity propagates between the cell assemblies representing the patterns. PMID:19074018

  16. 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

    2015-01-03

    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.

  17. 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

  18. Dopamine-dependent effects on basal and glutamate stimulated network dynamics in cultured hippocampal neurons.

    PubMed

    Li, Yan; Chen, Xin; Dzakpasu, Rhonda; Conant, Katherine

    2017-02-01

    Oscillatory activity occurs in cortical and hippocampal networks with specific frequency ranges thought to be critical to working memory, attention, differentiation of neuronal precursors, and memory trace replay. Synchronized activity within relatively large neuronal populations is influenced by firing and bursting frequency within individual cells, and the latter is modulated by changes in intrinsic membrane excitability and synaptic transmission. Published work suggests that dopamine, a potent modulator of learning and memory, acts on dopamine receptor 1-like dopamine receptors to influence the phosphorylation and trafficking of glutamate receptor subunits, along with long-term potentiation of excitatory synaptic transmission in striatum and prefrontal cortex. Prior studies also suggest that dopamine can influence voltage gated ion channel function and membrane excitability in these regions. Fewer studies have examined dopamine's effect on related endpoints in hippocampus, or potential consequences in terms of network burst dynamics. In this study, we record action potential activity using a microelectrode array system to examine the ability of dopamine to modulate baseline and glutamate-stimulated bursting activity in an in vitro network of cultured murine hippocampal neurons. We show that dopamine stimulates a dopamine type-1 receptor-dependent increase in number of overall bursts within minutes of its application. Notably, however, at the concentration used herein, dopamine did not increase the overall synchrony of bursts between electrodes. Although the number of bursts normalizes by 40 min, bursting in response to a subsequent glutamate challenge is enhanced by dopamine pretreatment. Dopamine-dependent potentiation of glutamate-stimulated bursting was not observed when the two modulators were administered concurrently. In parallel, pretreatment of murine hippocampal cultures with dopamine stimulated lasting increases in the phosphorylation of the

  19. Neonatal hypoxia-ischemia impairs juvenile recognition memory by disrupting the maturation of prefrontal-hippocampal networks.

    PubMed

    Domnick, Nina-Kristin; Gretenkord, Sabine; De Feo, Vito; Sedlacik, Jan; Brockmann, Marco D; Hanganu-Opatz, Ileana L

    2015-11-01

    High-prevalence/low-severity cognitive deficits represent the life-long burden of a perinatal hypoxic–ischemic (HI) insult. They have been proposed to result from dysmaturation of prelimbic-hippocampal networks, which account for mnemonic and executive performance. Already at neonatal age the communication within these networks is largely reduced after an early HI insult with mild/moderate structural outcome. However, the longlasting consequences of the neonatal network dysfunction remain unknown. Here,we combine MRI and electrophysiology in vivo with behavioral testing to assess the effects of an early HI insult on the structure and function of prelimbic-hippocampal networks and on related cognitive abilities of juvenile rats. Despite the absence of lesions over the prelimbic cortex (PL) and hippocampus (HP), juvenile rats experiencing an early HI have lower performance in item and temporal order recognition memory. These cognitive deficits do not result from delayed somatic development or increased locomotion or anxiety. More likely, abnormal activity patterns and interactions within prelimbic-hippocampal networks account for behavioral impairment. The early HI insult causes power reduction of the fast (12–48 Hz) network activity and diminishment of neuronal firing in the PL and HP. This weaker entrainment of local circuits at juvenile age emerges in the absence of sufficiently strong directed interactions within neonatal prelimbic-hippocampal networks. Similar developmental mechanisms may account for poorer academic achievements of HI-injured infants.

  20. Generation of slow network oscillations in the developing rat hippocampus after blockade of glutamate uptake.

    PubMed

    Cattani, Adriano Augusto; Bonfardin, Valérie Delphine; Represa, Alfonso; Ben-Ari, Yehezkel; Aniksztejn, Laurent

    2007-10-01

    Cell-surface glutamate transporters are essential for the proper function of early cortical networks because their dysfunction induces seizures in the newborn rat in vivo. We have now analyzed the consequences of their inhibition by DL-TBOA on the activity of the developing CA1 rat hippocampal network in vitro. DL-TBOA generated a pattern of recurrent depolarization with an onset and decay of several seconds' duration in interneurons and pyramidal cells. These slow network oscillations (SNOs) were mostly mediated by gamma-aminobutyric acid (GABA) in pyramidal cells and by GABA and N-methyl-D-aspartate (NMDA) receptors in interneurons. However, in both cell types SNOs were blocked by NMDA receptor antagonists, suggesting that their generation requires a glutamatergic drive. Moreover, in interneurons, SNOs were still generated after the blockade of NMDA-mediated synaptic currents with MK-801, suggesting that SNOs are expressed by the activation of extrasynaptic NMDA receptors. Long-lasting bath application of glutamate or NMDA failed to induce SNOs, indicating that they are generated by periodic but not sustained activation of NMDA receptors. In addition, SNOs were observed in interneurons recorded in slices with or without the strata pyramidale and oriens, suggesting that the glutamatergic drive may originate from the radiatum and pyramidale strata. We propose that in the absence of an efficient transport of glutamate, the transmitter diffuses in the extracellular space to activate extrasynaptic NMDA receptors preferentially present on interneurons that in turn activate other interneurons and pyramidal cells. This periodic neuronal coactivation may contribute to the generation of seizures when glutamate transport dysfunction is present.

  1. 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

  2. Multiple-scale dynamics in neural systems: learning, synchronization and network oscillations

    NASA Astrophysics Data System (ADS)

    Zhigulin, Valentin P.

    Many dynamical processes that take place in neural systems involve interactions between multiple temporal and/or spatial scales which lead to the emergence of new dynamical phenomena. Two of them are studied in this thesis: learning-induced robustness and enhancement of synchronization in small neural circuits; and emergence of global spatio-temporal dynamics from local interactions in neural networks.Chapter 2 presents the study of synchronization of two model neurons coupled through a synapse with spike-timing dependent plasticity (STDP). It shows that this form of learning leads to the enlargement of frequency locking zones and makes synchronization much more robust to noise than classical synchronization mediated by non-plastic synapses. A simple discrete-time map model is presented that enables deep understanding of this phenomenon and demonstrates its generality. Chapter 3 extends these results by demonstrating enhancement of synchronization in a hybrid circuit with living postsynaptic neuron. The robustness of STDP-mediated synchronization is further confirmed with simulations of stochastic plasticity.Chapter 4 studies the entrainment of a heterogeneous network of electrically coupled neurons by periodic stimulation. It demonstrates that, when compared to the case of non-plastic input synapses, inputs with STDP enhance coherence of network oscillations and improve robustness of synchronization to the variability of network properties. The observed mechanism may play a role in synchronization of hippocampal neural ensembles.Chapter 5 proposes a new type of artificial synaptic connection that combines fast reaction of an electrical synapse with plasticity of a chemical synapse. It shows that such synapse mediates regularization of chaos in a circuit of two chaotic bursting neurons and leads to structural stability of the regularized state. Such plastic electrical synapse may be used in the development of robust neural prosthetics.Chapter 6 suggests a new

  3. Synchronized oscillations in interneuron networks driven by metabotropic glutamate receptor activation

    NASA Astrophysics Data System (ADS)

    Whittington, Miles A.; Traub, Roger D.; Jefferys, John G. R.

    1995-02-01

    PARTIALLY synchronous 40-Hz oscillations of cortical neurons have been implicated in cognitive function. Specifically, coherence of these oscillations between different parts of the cortex may provide conjunctive properties1,2 to solve the 'binding problem' associating features detected by the cortex into unified perceived objects. Here we report an emergent 40-Hz oscillation in networks of inhibitory neurons connected by synapses using GABAA (γ-aminobutyric acid) receptors in slices of rat hippocampus and neocortex. These network inhibitory postsynaptic potential oscillations occur in response to the activation of metabotropic glutamate receptors. The oscillations can entrain pyramidal cell discharges. The oscillation frequency is determined both by the net excitation of interneurons and by the kinetics of the inhibitory postsynaptic potentials between them. We propose that interneuron network oscillations, in conjunction with intrinsic membrane resonances and long-loop (such as thalamocortical) interactions, contribute to 40-Hz rhythms in vivo.

  4. Maintaining network activity in submerged hippocampal slices: importance of oxygen supply.

    PubMed

    Hájos, Norbert; Ellender, Tommas J; Zemankovics, Rita; Mann, Edward O; Exley, Richard; Cragg, Stephanie J; Freund, Tamás F; Paulsen, Ole

    2009-01-01

    Studies in brain slices have provided a wealth of data on the basic features of neurons and synapses. In the intact brain, these properties may be strongly influenced by ongoing network activity. Although physiologically realistic patterns of network activity have been successfully induced in brain slices maintained in interface-type recording chambers, they have been harder to obtain in submerged-type chambers, which offer significant experimental advantages, including fast exchange of pharmacological agents, visually guided patch-clamp recordings, and imaging techniques. Here, we investigated conditions for the emergence of network oscillations in submerged slices prepared from the hippocampus of rats and mice. We found that the local oxygen level is critical for generation and propagation of both spontaneously occurring sharp wave-ripple oscillations and cholinergically induced fast oscillations. We suggest three ways to improve the oxygen supply to slices under submerged conditions: (i) optimizing chamber design for laminar flow of superfusion fluid; (ii) increasing the flow rate of superfusion fluid; and (iii) superfusing both surfaces of the slice. These improvements to the recording conditions enable detailed studies of neurons under more realistic conditions of network activity, which are essential for a better understanding of neuronal network operation.

  5. A study of epileptogenic network structures in rat hippocampal cultures using first spike latencies during synchronization events.

    PubMed

    Raghavan, Mohan; Amrutur, Bharadwaj; Srinivas, Kalyan V; Sikdar, Sujit K

    2012-10-01

    Study of hypersynchronous activity is of prime importance for combating epilepsy. Studies on network structure typically reconstruct the network by measuring various aspects of the interaction between neurons and subsequently measure the properties of the reconstructed network. In sub-sampled networks such methods lead to significant errors in reconstruction. Using rat hippocampal neurons cultured on a multi-electrode array dish and a glutamate injury model of epilepsy in vitro, we studied synchronous activity in neuronal networks. Using the first spike latencies in various neurons during a network burst, we extract various recurring spatio-temporal onset patterns in the networks. Comparing the patterns seen in control and injured networks, we observe that injured networks express a wide diversity in their foci (origin) and activation pattern, while control networks show limited diversity. Furthermore, we note that onset patterns in glutamate injured networks show a positive correlation between synchronization delay and physical distance between neurons, while control networks do not.

  6. Young adult born neurons enhance hippocampal dependent performance via influences on bilateral networks

    PubMed Central

    Zhuo, Jia-Min; Tseng, Hua-an; Desai, Mitul; Bucklin, Mark E; Mohammed, Ali I; Robinson, Nick TM; Boyden, Edward S; Rangel, Lara M; Jasanoff, Alan P; Gritton, Howard J; Han, Xue

    2016-01-01

    Adult neurogenesis supports performance in many hippocampal dependent tasks. Considering the small number of adult-born neurons generated at any given time, it is surprising that this sparse population of cells can substantially influence behavior. Recent studies have demonstrated that heightened excitability and plasticity may be critical for the contribution of young adult-born cells for certain tasks. What is not well understood is how these unique biophysical and synaptic properties may translate to networks that support behavioral function. Here we employed a location discrimination task in mice while using optogenetics to transiently silence adult-born neurons at different ages. We discovered that adult-born neurons promote location discrimination during early stages of development but only if they undergo maturation during task acquisition. Silencing of young adult-born neurons also produced changes extending to the contralateral hippocampus, detectable by both electrophysiology and fMRI measurements, suggesting young neurons may modulate location discrimination through influences on bilateral hippocampal networks. DOI: http://dx.doi.org/10.7554/eLife.22429.001 PMID:27914197

  7. 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.

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

    PubMed

    Amoroso, N; Errico, R; Bruno, S; Chincarini, A; Garuccio, E; Sensi, F; Tangaro, S; Tateo, A; Bellotti, R

    2015-11-21

    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[Formula: see text] and Dice[Formula: see text]). 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.

  9. 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.

  10. Waves and Oscillations in Networks of Coupled Neurons

    NASA Astrophysics Data System (ADS)

    Ermentrout, B.

    Neural systems are characterized by the interactions of thousands of individual cells called neurons. Individual neurons vary in their properties with some of them spontaneously active and others active only when given a sufficient perturbation. In this note, I will describe work that has been done on the mathematical analysis of waves and synchronous oscillations in spatially distributed networks of neurons. These classes of behavior are observed both in vivo (that is, in the living brain) and in vitro (isolated networks, such as slices of brain tissue.) We focus on these simple behaviors rather than on the possible computations that networks of neurons can do (such as filtering sensory inputs and producing precise motor output) mainly because they are mathematically tractable. The chapter is organized as follows. First, I will introduce the kinds of equations that are of interest and from these abstract some simplified models. I will consider several different types of connectivity - from "all-to-all" to spatially organized. Typically (although not in every case), each individual neuron is represented by a scalar equation for its dynamics. These individuals can be coupled together directly or indirectly and in spatially discrete or continuous arrays.

  11. H-Channels Affect Frequency, Power and Amplitude Fluctuations of Neuronal Network Oscillations

    PubMed Central

    Avella Gonzalez, Oscar J.; Mansvelder, Huibert D.; van Pelt, Jaap; van Ooyen, Arjen

    2015-01-01

    Oscillations in network activity are ubiquitous in the brain and are involved in diverse cognitive functions. Oscillation characteristics, such as power, frequency, and temporal structure, depend on both network connectivity and intrinsic cellular properties, such as ion channel composition. An important class of channels, with key roles in regulating cell excitability, are h-channels. The h-current (Ih) is a slow, hyperpolarization-activated, depolarizing current that contributes to neuronal resonance and membrane potential. The impact of Ih on network oscillations, however, remains poorly understood. To elucidate the network effects of Ih, we used a computational model of a generic oscillatory neuronal network consisting of inhibitory and excitatory cells that were externally driven by excitatory action potentials and sustained depolarizing currents. We found that Ih increased the oscillation frequency and, in combination with external action potentials, representing input from areas outside the network, strongly decreased the synchrony of firing. As a consequence, the oscillation power and the duration of episodes during which the network exhibited high-amplitude oscillations were greatly reduced in the presence of Ih. Our results suggest that modulation of Ih or impaired expression of h-channels, as observed in epilepsy, could, by affecting oscillation dynamics, markedly alter network-level activity and potentially influence oscillation-dependent cognitive processes such as learning, memory and attention. PMID:26635594

  12. Synchrony arising from a balanced synaptic plasticity in a network of heterogeneous neural oscillators

    NASA Astrophysics Data System (ADS)

    Karbowski, Jan; Ermentrout, G. Bard

    2002-03-01

    We investigate the dynamics of a recurrent network of coupled heterogeneous neural oscillators with experimentally observed spike-timing-dependent synaptic plasticity. We show both theoretically and by computer simulations that, in a regime of a balance between synaptic potentiation and depression, the network of such oscillators converges to a stable synchronous state. The stability of this state is fostered by flexible synaptic weights which adjust themselves based on the relative timing of firing of pre- and postsynaptic oscillators.

  13. Control of amplitude chimeras by time delay in oscillator networks

    NASA Astrophysics Data System (ADS)

    Gjurchinovski, Aleksandar; Schöll, Eckehard; Zakharova, Anna

    2017-04-01

    We investigate the influence of time-delayed coupling in a ring network of nonlocally coupled Stuart-Landau oscillators upon chimera states, i.e., space-time patterns with coexisting partially coherent and partially incoherent domains. We focus on amplitude chimeras, which exhibit incoherent behavior with respect to the amplitude rather than the phase and are transient patterns, and we show that their lifetime can be significantly enhanced by coupling delay. To characterize their transition to phase-lag synchronization (coherent traveling waves) and other coherent structures, we generalize the Kuramoto order parameter. Contrasting the results for instantaneous coupling with those for constant coupling delay, for time-varying delay, and for distributed-delay coupling, we demonstrate that the lifetime of amplitude chimera states and related partially incoherent states can be controlled, i.e., deliberately reduced or increased, depending upon the type of coupling delay.

  14. 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.

  15. CA1 hippocampal network activity changes during sleep-dependent memory consolidation

    PubMed Central

    Ognjanovski, Nicolette; Maruyama, Daniel; Lashner, Nora; Zochowski, Michal; Aton, Sara J.

    2014-01-01

    A period of sleep over the first few hours following single-trial contextual fear conditioning (CFC) is essential for hippocampally-mediated memory consolidation. Recent studies have uncovered intracellular mechanisms required for memory formation which are affected by post-conditioning sleep and sleep deprivation. However, almost nothing is known about the circuit-level activity changes during sleep that underlie activation of these intracellular pathways. Here we continuously recorded from the CA1 region of freely-behaving mice to characterize neuronal and network activity changes occurring during active memory consolidation. C57BL/6J mice were implanted with custom stereotrode recording arrays to monitor activity of individual CA1 neurons, local field potentials (LFPs), and electromyographic activity. Sleep architecture and state-specific CA1 activity patterns were assessed during a 24 h baseline recording period, and for 24 h following either single-trial CFC or Sham conditioning. We find that consolidation of CFC is not associated with significant sleep architecture changes, but is accompanied by long-lasting increases in CA1 neuronal firing, as well as increases in delta, theta, and gamma-frequency CA1 LFP activity. These changes occurred in both sleep and wakefulness, and may drive synaptic plasticity within the hippocampus during memory formation. We also find that functional connectivity within the CA1 network, assessed through functional clustering algorithm (FCA) analysis of spike timing relationships among recorded neurons, becomes more stable during consolidation of CFC. This increase in network stability was not present following Sham conditioning, was most evident during post-CFC slow wave sleep (SWS), and was negligible during post-CFC wakefulness. Thus in the interval between encoding and recall, SWS may stabilize the hippocampal contextual fear memory (CFM) trace by promoting CA1 network stability. PMID:24860440

  16. Synchronization in networks of networks: the onset of coherent collective behavior in systems of interacting populations of heterogeneous oscillators.

    PubMed

    Barreto, Ernest; Hunt, Brian; Ott, Edward; So, Paul

    2008-03-01

    The onset of synchronization in networks of networks is investigated. Specifically, we consider networks of interacting phase oscillators in which the set of oscillators is composed of several distinct populations. The oscillators in a given population are heterogeneous in that their natural frequencies are drawn from a given distribution, and each population has its own such distribution. The coupling among the oscillators is global, however, we permit the coupling strengths between the members of different populations to be separately specified. We determine the critical condition for the onset of coherent collective behavior, and develop the illustrative case in which the oscillator frequencies are drawn from a set of (possibly different) Cauchy-Lorentz distributions. One motivation is drawn from neurobiology, in which the collective dynamics of several interacting populations of oscillators (such as excitatory and inhibitory neurons and glia) are of interest.

  17. Synchronization in networks of networks: The onset of coherent collective behavior in systems of interacting populations of heterogeneous oscillators

    NASA Astrophysics Data System (ADS)

    Barreto, Ernest; Hunt, Brian; Ott, Edward; So, Paul

    2008-03-01

    The onset of synchronization in networks of networks is investigated. Specifically, we consider networks of interacting phase oscillators in which the set of oscillators is composed of several distinct populations. The oscillators in a given population are heterogeneous in that their natural frequencies are drawn from a given distribution, and each population has its own such distribution. The coupling among the oscillators is global, however, we permit the coupling strengths between the members of different populations to be separately specified. We determine the critical condition for the onset of coherent collective behavior, and develop the illustrative case in which the oscillator frequencies are drawn from a set of (possibly different) Cauchy-Lorentz distributions. One motivation is drawn from neurobiology, in which the collective dynamics of several interacting populations of oscillators (such as excitatory and inhibitory neurons and glia) are of interest.

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

    PubMed Central

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

    2012-01-01

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

  19. Face-name association task reveals memory networks in patients with left and right hippocampal sclerosis.

    PubMed

    Klamer, Silke; Milian, Monika; Erb, Michael; Rona, Sabine; Lerche, Holger; Ethofer, Thomas

    2017-01-01

    We aimed to identify reorganization processes of episodic memory networks in patients with left and right temporal lobe epilepsy (TLE) due to hippocampal sclerosis as well as their relations to neuropsychological memory performance. We investigated 28 healthy subjects, 12 patients with left TLE (LTLE) and 9 patients with right TLE (RTLE) with hippocampal sclerosis by means of functional magnetic resonance imaging (fMRI) using a face-name association task, which combines verbal and non-verbal memory functions. Regions-of-interest (ROIs) were defined based on the group results of the healthy subjects. In each ROI, fMRI activations were compared across groups and correlated with verbal and non-verbal memory scores. The face-name association task yielded activations in bilateral hippocampus (HC), left inferior frontal gyrus (IFG), left superior frontal gyrus (SFG), left superior temporal gyrus, bilateral angular gyrus (AG), bilateral medial prefrontal cortex and right anterior temporal lobe (ATL). LTLE patients demonstrated significantly less activation in the left HC and left SFG, whereas RTLE patients showed significantly less activation in the HC bilaterally, the left SFG and right AG. Verbal memory scores correlated with activations in the left and right HC, left SFG and right ATL and non-verbal memory scores with fMRI activations in the left and right HC and left SFG. The face-name association task can be employed to examine functional alterations of hippocampal activation during encoding of both verbal and non-verbal material in one fMRI paradigm. Further, the left SFG seems to be a convergence region for encoding of verbal and non-verbal material.

  20. 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.

  1. 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.

  2. Analysis of oscillator neural networks for sparsely coded phase patterns

    NASA Astrophysics Data System (ADS)

    Nomura, Masaki; Aoyagi, Toshio

    2000-12-01

    We study a simple extended model of oscillator neural networks capable of storing sparsely coded phase patterns, in which information is encoded both in the mean activity level and in the timing of spikes. Applying the methods of statistical neurodynamics to our model, we investigate theoretically the model's associative memory capability by evaluating its maximum storage capacities and deriving its basins of attraction. It is shown that, as in the Hopfield model, the storage capacity diverges as the activity level decreases. We consider various practically and theoretically important cases. For example, it is revealed that a dynamically adjusted threshold mechanism enhances the retrieval ability of the associative memory. It is also found that, under suitable conditions, the network can recall patterns even in the case that patterns with different activity levels are stored at the same time. In addition, we examine the robustness with respect to damage of the synaptic connections. The validity of these theoretical results is confirmed by reasonable agreement with numerical simulations.

  3. Multimodal approaches to define network oscillations in depression.

    PubMed

    Smart, Otis Lkuwamy; Tiruvadi, Vineet Ravi; Mayberg, Helen S

    2015-06-15

    The renaissance in the use of encephalography-based research methods to probe the pathophysiology of neuropsychiatric disorders is well afoot and continues to advance. Building on the platform of neuroimaging evidence on brain circuit models, magnetoencephalography, scalp electroencephalography, and even invasive electroencephalography are now being used to characterize brain network dysfunctions that underlie major depressive disorder using brain oscillation measurements and associated treatment responses. Such multiple encephalography modalities provide avenues to study pathologic network dynamics with high temporal resolution and over long time courses, opportunities to complement neuroimaging methods and findings, and new approaches to identify quantitative biomarkers that indicate critical targets for brain therapy. Such goals have been facilitated by the ongoing testing of novel invasive neuromodulation therapies, notably, deep brain stimulation, where clinically relevant treatment effects can be monitored at multiple brain sites in a time-locked causal manner. We review key brain rhythms identified in major depressive disorder as foundation for development of putative biomarkers for objectively evaluating neuromodulation success and for guiding deep brain stimulation or other target-based neuromodulation strategies for treatment-resistant depression patients.

  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. Recovery of network-driven glutamatergic activity in rat hippocampal neurons during chronic glutamate receptor blockade.

    PubMed

    Leininger, Eric; Belousov, Andrei B

    2009-01-28

    Previous studies indicated that a long-term decrease in the activity of ionotropic glutamate receptors induces cholinergic activity in rat and mouse hypothalamic neuronal cultures. Here we studied whether a prolonged inactivation of ionotropic glutamate receptors also induces cholinergic activity in hippocampal neurons. Receptor activity was chronically suppressed in rat hippocampal primary neuronal cultures with two proportionally increasing sets of concentrations of NMDA plus non-NMDA receptor antagonists: 100 microM/10 microM AP5/CNQX (1X cultures) and 200 microM/20 microM AP5/CNQX (2X cultures). Using calcium imaging we demonstrate that cholinergic activity does not develop in these cultures. Instead, network-driven glutamate-dependent activity, that normally is detected in hyper-excitable conditions, reappears in each culture group in the presence of these antagonists and can be reversibly suppressed by higher concentrations of AP5/CNQX. This activity is mediated by non-NMDA receptors and is modulated by NMDA receptors. Further, non-NMDA receptors, the general level of glutamate receptor activity and CaMK-dependent signaling are critical for development of this network-driven glutamatergic activity in the presence of receptor antagonists. Using electrophysiology, western blotting and calcium imaging we show that some neuronal parameters are either reduced or not affected by chronic glutamate receptor blockade. However, other parameters (including neuronal excitability, mEPSC frequency, and expression of GluR1, NR1 and betaCaMKII) become up-regulated and, in some cases, proportionally between the non-treated, 1X and 2X cultures. Our data suggest recovery of the network-driven glutamatergic activity after chronic glutamate receptor blockade. This recovery may represent a form of neuronal plasticity that compensates for the prolonged suppression of the activity of glutamate receptors.

  6. 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.

  7. Impulsive synchronization of coupled dynamical networks with nonidentical Duffing oscillators and coupling delays.

    PubMed

    Wang, Zhengxin; Duan, Zhisheng; Cao, Jinde

    2012-03-01

    This paper aims to investigate the synchronization problem of coupled dynamical networks with nonidentical Duffing-type oscillators without or with coupling delays. Different from cluster synchronization of nonidentical dynamical networks in the previous literature, this paper focuses on the problem of complete synchronization, which is more challenging than cluster synchronization. By applying an impulsive controller, some sufficient criteria are obtained for complete synchronization of the coupled dynamical networks of nonidentical oscillators. Furthermore, numerical simulations are given to verify the theoretical results.

  8. Synaptic Potentiation Facilitates Memory-like Attractor Dynamics in Cultured In Vitro Hippocampal Networks

    PubMed Central

    Conant, Katherine; Dzakpasu, Rhonda

    2013-01-01

    Collective rhythmic dynamics from neurons is vital for cognitive functions such as memory formation but how neurons self-organize to produce such activity is not well understood. Attractor-based computational models have been successfully implemented as a theoretical framework for memory storage in networks of neurons. Additionally, activity-dependent modification of synaptic transmission is thought to be the physiological basis of learning and memory. The goal of this study is to demonstrate that using a pharmacological treatment that has been shown to increase synaptic strength within in vitro networks of hippocampal neurons follows the dynamical postulates theorized by attractor models. We use a grid of extracellular electrodes to study changes in network activity after this perturbation and show that there is a persistent increase in overall spiking and bursting activity after treatment. This increase in activity appears to recruit more “errant” spikes into bursts. Phase plots indicate a conserved activity pattern suggesting that a synaptic potentiation perturbation to the attractor leaves it unchanged. Lastly, we construct a computational model to demonstrate that these synaptic perturbations can account for the dynamical changes seen within the network. PMID:23526935

  9. Emergence of localized patterns in globally coupled networks of relaxation oscillators with heterogeneous connectivity

    NASA Astrophysics Data System (ADS)

    Leiser, Randolph J.; Rotstein, Horacio G.

    2017-08-01

    Oscillations in far-from-equilibrium systems (e.g., chemical, biochemical, biological) are generated by the nonlinear interplay of positive and negative feedback effects operating at different time scales. Relaxation oscillations emerge when the time scales between the activators and the inhibitors are well separated. In addition to the large-amplitude oscillations (LAOs) or relaxation type, these systems exhibit small-amplitude oscillations (SAOs) as well as abrupt transitions between them (canard phenomenon). Localized cluster patterns in networks of relaxation oscillators consist of one cluster oscillating in the LAO regime or exhibiting mixed-mode oscillations (LAOs interspersed with SAOs), while the other oscillates in the SAO regime. Because the individual oscillators are monostable, localized patterns are a network phenomenon that involves the interplay of the connectivity and the intrinsic dynamic properties of the individual nodes. Motivated by experimental and theoretical results on the Belousov-Zhabotinsky reaction, we investigate the mechanisms underlying the generation of localized patterns in globally coupled networks of piecewise-linear relaxation oscillators where the global feedback term affects the rate of change of the activator (fast variable) and depends on the weighted sum of the inhibitor (slow variable) at any given time. We also investigate whether these patterns are affected by the presence of a diffusive type of coupling whose synchronizing effects compete with the symmetry-breaking global feedback effects.

  10. Scanless functional imaging of hippocampal networks using patterned two-photon illumination through GRIN lenses

    PubMed Central

    Moretti, Claudio; Antonini, Andrea; Bovetti, Serena; Liberale, Carlo; Fellin, Tommaso

    2016-01-01

    Patterned illumination through the phase modulation of light is increasingly recognized as a powerful tool to investigate biological tissues in combination with two-photon excitation and light-sensitive molecules. However, to date two-photon patterned illumination has only been coupled to traditional microscope objectives, thus limiting the applicability of these methods to superficial biological structures. Here, we show that phase modulation can be used to efficiently project complex two-photon light patterns, including arrays of points and large shapes, in the focal plane of graded index (GRIN) lenses. Moreover, using this approach in combination with the genetically encoded calcium indicator GCaMP6, we validate our system performing scanless functional imaging in rodent hippocampal networks in vivo ~1.2 mm below the brain surface. Our results open the way to the application of patterned illumination approaches to deep regions of highly scattering biological tissues, such as the mammalian brain. PMID:27867707

  11. 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

  12. Dynamic changes in interneuron morpho-physiological properties mark the maturation of hippocampal network activity

    PubMed Central

    Allene, C.; Picardo, M. A.; Becq, H.; Miyoshi, G.; Fishell, G.; Cossart, R.

    2012-01-01

    During early postnatal development, neuronal networks successively produce various forms of spontaneous patterned activity that provide key signals for circuit maturation. Initially, in both rodent hippocampus and neocortex, coordinated activity emerges in the form of Synchronous Plateau Assemblies (SPAs) that are initiated by sparse groups of gap-junction coupled oscillating neurons. Subsequently, SPAs are replaced by synapse-driven Giant Depolarizing Potentials (GDPs). Whether these sequential changes in mechanistically distinct network activities correlate with modifications in single-cell properties is unknown. To understand this, we have studied the morpho-physiological fate of single SPA-cells as a function of development. We focused on CA3 GABAergic interneurons, which are centrally involved in generating GDPs in the hippocampus. As the network matures, GABAergic neurons are engaged more in GDPs and less in SPAs. Using inducible genetic fate mapping, we show that the individual involvement of GABAergic neurons in SPAs is correlated to their temporal origin. In addition, we demonstrate that the SPA to GDP transition is paralleled by a remarkable maturation in the morpho-physiological properties of GABAergic neurons. Compared to those involved in GDPs, interneurons participating in SPAs possess immature intrinsic properties, receive synaptic inputs spanning a wide amplitude range, and display large somata as well as membrane protrusions. Thus, a developmental switch in the morpho-physiological properties of GABAergic interneurons as they progress from SPA to GDPs marks the emergence of synapse-driven network oscillations. PMID:22573691

  13. 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.

  14. Immune network behavior: Oscillations, chaos and stationary states

    SciTech Connect

    De Boer, R.J.; Perelson, A.S.; Kevrekidis, I.G.

    1994-04-01

    The authors report two types of behavior in models of immune networks. The typical behavior of simple models, which involve B cells only, consists of several coexisting steady states. Finite amplitude perturbations may cause the model to switch between different equilibria. The typical behavior of more realistic models, which involve both B cells and antibody, consists of autonomous oscillations and/or chaos. While steady-state behavior leads to easy interpretations in terms of immune memory, oscillatory behavior seems to be in better agreement with experimental data obtained in unimmunized animals. The stability of the steady states, and the structure and interactions of the stable and unstable manifolds of the saddle-type equilibria turn out to be factors influencing the model`s behavior. Whether or not the model is able to attain any form of sustained oscillatory behavior, i.e., limit cycles or chaos, seems to be determined by (global) bifurcations involving the stable and unstable manifolds of the steady states.

  15. 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

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

    NASA Astrophysics Data System (ADS)

    Tchumatchenko, Tatjana; Clopath, Claudia

    2014-11-01

    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.

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

    PubMed

    Tchumatchenko, Tatjana; Clopath, Claudia

    2014-11-18

    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.

  18. Synergy and redundancy in timescale dependent multiplex networks of hippocampal and cortical neurons

    NASA Astrophysics Data System (ADS)

    Timme, Nicholas; Ito, Shinya; Myroshnychenko, Maxym; Yeh, Fang-Chin; Hiolski, Emma; Litke, Alan; Beggs, John

    2015-03-01

    Understanding the types of computations small groups of neurons perform is of great importance in neuroscience. To investigate these computations, we used tools from information theory (transfer entropy and the partial information decomposition) to study information processing in time scale dependent effective connectivity networks (i.e. multiplex neural networks). These networks were derived from the spiking activity of thousands of neurons recorded from 60 cortico-hippocampal slice cultures using a high density 512-electrode array with 60 μm inter-electrode spacing and 50 μs temporal resolution. To the best of our knowledge, this preparation and recording method represents a combination of number of recorded neurons and temporal and spatial recording resolutions that is not currently available in any in vivo recording system. We found that neurons that received many connections tended to not processes as much information as neurons that received few connections, but neurons that sent out many connections tended to process more information than neurons that sent out few connections. Also, for slow interactions, we found that neurons that were physically distant tended to participate in more interesting computations than neurons that were more proximally located. NSF Grants 090813 (JMB), 1058291 (JMB), and IIS-0904413 (A.L.).

  19. Synchronization of Plant Circadian Oscillators with a Phase Delay Effect of the Vein Network

    NASA Astrophysics Data System (ADS)

    Fukuda, Hirokazu; Nakamichi, Norihito; Hisatsune, Mihoe; Murase, Haruhiko; Mizuno, Takeshi

    2007-08-01

    Synchronization phenomena in coupled circadian oscillators of plant leaves were investigated experimentally using bioluminescence technology for a clock gene. Analyzing the phase of circadian oscillation, the phase-wave propagations and the phase delay caused by the vein network were observed. We describe these phase dynamics using a two-layer model with coupled Stuart-Landau equations. Global synchronization of circadian oscillators in the leaf is also investigated.

  20. Experimental investigation of a unidirectional network of four chemical oscillators pulse-coupled through an inhibitor

    NASA Astrophysics Data System (ADS)

    Smelov, P. S.; Vanag, V. K.

    2017-06-01

    Dynamical synchronous modes in a network of four nearly identical chemical oscillators unidirectionally coupled via inhibitory pulse coupling with time delay τ (when a spike in one oscillator inhibits the next oscillator in the circle after time delay τ), are obtained experimentally. The Belousov-Zhabotinsky reaction is used as a chemical oscillator. The existence of four main modes is confirmed experimentally: in-phase (IP) oscillations; an anti-phase (AP) mode, in which any two neighboring oscillators have a phase shift equal to half of global period T; a walk mode (W), in which oscillators produce consecutive spikes in the direction of the connection with a phase shift between neighboring oscillators equal to T/4; and a walk-reverse mode (WR), when the oscillators produce consecutive spikes (with phase shift T/4), but in the direction opposite the connections (the mode opposite to the W mode). In addition to the main modes, OS modes in which at least one of the four oscillators is suppressed, and "2+1+1" modes in which two neighboring oscillators produce spikes simultaneously and the phases of the third and the fourth oscillators are shifted by T/3 and 2 T/3, respectively, are found. It is shown that the modes found experimentally correspond to those found in simulations.

  1. Impaired cerebral blood flow networks in temporal lobe epilepsy with hippocampal sclerosis: A graph theoretical approach.

    PubMed

    Sone, Daichi; Matsuda, Hiroshi; Ota, Miho; Maikusa, Norihide; Kimura, Yukio; Sumida, Kaoru; Yokoyama, Kota; Imabayashi, Etsuko; Watanabe, Masako; Watanabe, Yutaka; Okazaki, Mitsutoshi; Sato, Noriko

    2016-09-01

    Graph theory is an emerging method to investigate brain networks. Altered cerebral blood flow (CBF) has frequently been reported in temporal lobe epilepsy (TLE), but graph theoretical findings of CBF are poorly understood. Here, we explored graph theoretical networks of CBF in TLE using arterial spin labeling imaging. We recruited patients with TLE and unilateral hippocampal sclerosis (HS) (19 patients with left TLE, and 21 with right TLE) and 20 gender- and age-matched healthy control subjects. We obtained all participants' CBF maps using pseudo-continuous arterial spin labeling and analyzed them using the Graph Analysis Toolbox (GAT) software program. As a result, compared to the controls, the patients with left TLE showed a significantly low clustering coefficient (p=0.024), local efficiency (p=0.001), global efficiency (p=0.010), and high transitivity (p=0.015), whereas the patients with right TLE showed significantly high assortativity (p=0.046) and transitivity (p=0.011). The group with right TLE also had high characteristic path length values (p=0.085), low global efficiency (p=0.078), and low resilience to targeted attack (p=0.101) at a trend level. Lower normalized clustering coefficient (p=0.081) in the left TLE and higher normalized characteristic path length (p=0.089) in the right TLE were found also at a trend level. Both the patients with left and right TLE showed significantly decreased clustering in similar areas, i.e., the cingulate gyri, precuneus, and occipital lobe. Our findings revealed differing left-right network metrics in which an inefficient CBF network in left TLE and vulnerability to irritation in right TLE are suggested. The left-right common finding of regional decreased clustering might reflect impaired default-mode networks in TLE.

  2. 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.

  3. 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.

  4. 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

  5. Factors Underlying Bursting Behavior in a Network of Cultured Hippocampal Neurons Exposed to Zero Magnesium

    PubMed Central

    Mangan, Patrick S.; Kapur, Jaideep

    2010-01-01

    Factors contributing to reduced magnesium-induced neuronal action potential bursting were investigated in primary hippocampal cell culture at high and low culture density. In nominally zero external magnesium medium, pyramidal neurons from high-density cultures produced recurrent spontaneous action potential bursts superimposed on prolonged depolarizations. These bursts were partially attenuated by the NMDA receptor antagonist D-APV. Pharmacological analysis of miniature excitatory postsynaptic currents (EPSCs) revealed 2 components: one sensitive to D-APV and another to the AMPA receptor antagonist DNQX. The components were kinetically distinct. Participation of NMDA receptors in reduced magnesium-induced synaptic events was supported by the localization of the NR1 subunit of the NMDA receptor with the presynaptic vesicular protein synaptophysin. Presynaptically, zero magnesium induced a significant increase in EPSC frequency likely attributable to increased neuronal hyperexcitability induced by reduced membrane surface charge screening. Mean quantal content was significantly increased in zero magnesium. Cells from low-density cultures did not exhibit action potential bursting in zero magnesium but did show increased EPSC frequency. Low-density neurons had less synaptophysin immunofluorescence and fewer active synapses as determined by FM1-43 analysis. These results demonstrate that multiple factors are involved in network bursting. Increased probability of transmitter release presynaptically, enhanced NMDA receptor-mediated excitability postsynaptically, and extent of neuronal interconnectivity contribute to initiation and maintenance of elevated network excitability. PMID:14534286

  6. Bubbling effect in the electro-optic delayed feedback oscillator coupled network

    NASA Astrophysics Data System (ADS)

    Liu, Lingfeng; Lin, Jun; Miao, Suoxia

    2017-03-01

    Synchronization in the optical systems coupled network always suffers from bubbling events. In this paper, we numerically investigate the statistical properties of the synchronization characteristics and bubbling effects in the electro-optic delayed feedback oscillator coupled network with different coupling strength, delay time and gain coefficient. Furthermore, we compare our results with the synchronization properties of semiconductor laser (SL) coupled network, which indicates that the electro-optic delayed feedback oscillator can be better to suppress the bubbling effects in the synchronization of coupled network under the same conditions.

  7. Edge Event-Triggered Synchronization in Networks of Coupled Harmonic Oscillators.

    PubMed

    Wei, Bo; Xiao, Feng; Dai, Ming-Zhe

    2016-08-30

    The synchronization problems of networks of coupled harmonic oscillators are addressed by the edge event-triggered approach in this paper. The network dynamics with respect to edge states are presented and a new edge event-triggered control protocol is designed. Combined with the periodic event-detecting and edge event-triggered approach, sufficient conditions that guarantee the synchronization of coupled harmonic oscillators are presented. Two event-detecting rules are given to achieve the synchronization of coupled harmonic oscillators with low resource consumption. Finally, simulations are conducted to illustrate the effectiveness of the edge event-triggered control algorithm.

  8. Ultra Low-Frequency Oscillations of a Solar Filament Observed by the GONG Network

    NASA Astrophysics Data System (ADS)

    Efremov, V. I.; Parfinenko, L. D.; Solov'ev, A. A.

    2016-11-01

    The data of ground-based telescopes of the Global Oscillation Network Group (GONG) obtained in the Hα line provide an opportunity to study the long-period oscillations of chromospheric filaments (quiescent prominences). For the first time, on the basis of time series of 5 days duration that we combined from the observations of three observatories of the GONG network, a new ultra-low mode with a period of between 20 and 30 hours was reliably detected in oscillations of a long-lived dark filament on the solar disk.

  9. Variation of critical point of aging transition in a networked oscillators system.

    PubMed

    Huang, Wenwen; Zhang, Xiyun; Hu, Xin; Zou, Yong; Liu, Zonghua; Guan, Shuguang

    2014-06-01

    In this work, we study the variation of critical point in aging transition in a networked system consisting of both active and inactive oscillators. By theoretical analysis and numerical simulations, we show that the critical point of aging transition actually is determined by the (normalized) cross links between active and inactive subpopulations of oscillators. This reveals how specific configuration of active and inactive oscillators in the network can lead to the variation of transition point. In particular, we investigate how different strategies of targeted inactivation influence the transition point based on the theory. Our results theoretically explain why the low-degree nodes are crucial regarding dynamical robustness in such systems.

  10. Structural hippocampal network alterations during healthy aging: a multi-modal MRI study

    PubMed Central

    Pelletier, Amandine; Periot, Olivier; Dilharreguy, Bixente; Hiba, Bassem; Bordessoules, Martine; Pérès, Karine; Amieva, Hélène; Dartigues, Jean-François; Allard, Michèle; Catheline, Gwénaëlle

    2013-01-01

    While hippocampal atrophy has been described during healthy aging, few studies have examined its relationship with the integrity of White Matter (WM) connecting tracts of the limbic system. This investigation examined WM structural damage specifically related to hippocampal atrophy in healthy aging subjects (n = 129), using morphological MRI to assess hippocampal volume and Diffusion Tensor Imaging (DTI) to assess WM integrity. Subjects with Mild Cognitive Impairment (MCI) or dementia were excluded from the analysis. In our sample, increasing age was significantly associated with reduced hippocampal volume and reduced Fractional Anisotropy (FA) at the level of the fornix and the cingulum bundle. The findings also demonstrate that hippocampal atrophy was specifically associated with reduced FA of the fornix bundle, but it was not related to alteration of the cingulum bundle. Our results indicate that the relationship between hippocampal atrophy and fornix FA values is not due to an independent effect of age on both structures. A recursive regression procedure was applied to evaluate sequential relationships between the alterations of these two brain structures. When both hippocampal atrophy and fornix FA values were included in the same model to predict age, fornix FA values remained significant whereas hippocampal atrophy was no longer significantly associated with age. According to this latter finding, hippocampal atrophy in healthy aging could be mediated by a loss of fornix connections. Structural alterations of this part of the limbic system, which have been associated with neurodegeneration in Alzheimer's disease, result at least in part from the aging process. PMID:24367331

  11. Dynamics of the solar chromosphere. I - Long-period network oscillations

    NASA Technical Reports Server (NTRS)

    Lites, B. W.; Rutten, R. J.; Kalkofen, W.

    1993-01-01

    We analyze differences in solar oscillations between the chromospheric network and internetwork regions from a 1 hr sequence of spectrograms of a quiet region near disk center. The spectrograms contain Ca II H, Ca I 422.7 nm, and various Fe I blends in the Ca II H wing. They permit vertical tracing of oscillations throughout the photosphere and into the low chromosphere. We find that the rms amplitude of Ca II H line center Doppler fluctuations is about 1.5 km/s for both network and internetwork, but that the character of the oscillations differs markedly in these two regions. Within internetwork areas the chromospheric velocity power spectrum is dominated by oscillations with frequencies at and above the acoustic cutoff frequency. They are well correlated with the oscillations in the underlying photosphere, but they are much reduced in the network. In contrast, the network Ca II H line center velocity and intensity power spectra are dominated by low-frequency oscillations with periods of 5-20 min. Their signature is much clearer in our Ca II H line center measurements than in previously used diagnostics which are contaminated by signals from deeper layers. We find that these long-period oscillations are not correlated with underlying photospheric disturbances, and we discuss their nature.

  12. Oscillations of the p53-Akt Network: Implications on Cell Survival and Death

    PubMed Central

    Wee, Keng Boon; Surana, Uttam; Aguda, Baltazar D.

    2009-01-01

    Intracellular protein levels of p53 and MDM2 have been shown to oscillate in response to ionizing radiation (IR), but the physiological significance of these oscillations remains unclear. The p53-MDM2 negative feedback loop – the putative cause of the oscillations – is embedded in a network involving a mutual antagonism (or positive feedback loop) between p53 and AKT. We have shown earlier that this p53-AKT network predicts an all-or-none switching behavior between a pro-survival cellular state (low p53 and high AKT levels) and a pro-apoptotic state (high p53 and low AKT levels). Here, we show that upon exposure to IR, the p53-AKT network can also reproduce the experimentally observed p53 and MDM2 oscillations. The present work is based on the hypothesis that the physiological significance of the experimentally observed oscillations could be found in their role in regulating the switching behavior of the p53-AKT network between pro-survival and pro-apoptotic states. It is shown here that these oscillations are associated with a significant decrease in the threshold level of IR at which switching from a pro-survival to a pro-apoptotic state occurs. Moreover, oscillations in p53 protein levels induce higher levels of expression of p53-target genes compared to non-oscillatory p53, and thus influence cell-fate decisions between cell cycle arrest/DNA damage repair versus apoptosis. PMID:19197384

  13. Synchronization transition in networked chaotic oscillators: the viewpoint from partial synchronization.

    PubMed

    Fu, Chenbo; Lin, Weijie; Huang, Liang; Wang, Xingang

    2014-05-01

    Synchronization transition in networks of nonlocally coupled chaotic oscillators is investigated. It is found that in reaching the state of global synchronization the networks can stay in various states of partial synchronization. The stability of the partial synchronization states is analyzed by the method of eigenvalue analysis, in which the important roles of the network topological symmetry on synchronization transition are identified. Moreover, for networks possessing multiple topological symmetries, it is found that the synchronization transition can be divided into different stages, with each stage characterized by a unique synchronous pattern of the oscillators. Synchronization transitions in networks of nonsymmetric topology and nonidentical oscillators are also investigated, where the partial synchronization states, although unstable, are found to be still playing important roles in the transitions.

  14. Synchronization of GABAergic interneuronal network in CA3 subfield of neonatal rat hippocampal slices.

    PubMed

    Khazipov, R; Leinekugel, X; Khalilov, I; Gaiarsa, J L; Ben-Ari, Y

    1997-02-01

    1. Cell-attached and whole-cell recordings from interneurons localized in the stratum radiatum of the CA3 subfield (SR-CA3) of neonatal (postnatal days 2-5) rat hippocampal slices were performed to study their activity during the generation of GABAergic giant depolarizing potentials (GDPs) in CA3 pyramidal cells. 2. Dual recordings revealed that during the generation of GDPs in CA3 pyramidal cells, the interneurons fire bursts of spikes, on average 4.5 +/- 1.4 spikes per burst (cell-attached mode). There bursts were induced by periodical large inward currents (interneuronal GDPs) recorded in whole-cell mode. 3. Interneuronal GDPs revealed typical features of polysynaptic neuronal network-driven events: they were blocked by TTX and by high divalent cation medium and they could be evoked in an all-or-none manner by electrical stimulation in different regions of the hippocampus. The network elements required for the generation of GDPs are present in local CA3 circuits since spontaneous GDPs were present in the isolated CA3 subfield of the hippocampal slice. 4. Interneuronal GDPs were mediated by GABAA and glutamate receptors, since: (i) their reversal potential strongly depended on [Cl-]i; (ii) at the reversal potential of GABAA postsynaptic currents an inward component of GDPs was composed of events with the same kinetics as alpha-amino-3-hydroxy-5-methylisoxazole-4-propionate (AMPA) receptor-mediated EPSCs; and (iii) once GABAA receptors were blocked intracellularly by dialysis with F(-)-MgATP-free solution, the remaining component of interneuronal GDPs reversed near 0 mV and rectified at membrane potentials more negative than -20 mV, suggesting an important contribution of NMDA receptors in addition to AMPA receptors. 5. In cell-attached recordings from interneurons, electrical stimulation in the stratum radiatum evoked a burst of spikes that corresponded to evoked GDPs. Pharmacological study of this response revealed that excitation of SR-CA3 interneurons during

  15. Synchronization of GABAergic interneuronal network in CA3 subfield of neonatal rat hippocampal slices.

    PubMed Central

    Khazipov, R; Leinekugel, X; Khalilov, I; Gaiarsa, J L; Ben-Ari, Y

    1997-01-01

    1. Cell-attached and whole-cell recordings from interneurons localized in the stratum radiatum of the CA3 subfield (SR-CA3) of neonatal (postnatal days 2-5) rat hippocampal slices were performed to study their activity during the generation of GABAergic giant depolarizing potentials (GDPs) in CA3 pyramidal cells. 2. Dual recordings revealed that during the generation of GDPs in CA3 pyramidal cells, the interneurons fire bursts of spikes, on average 4.5 +/- 1.4 spikes per burst (cell-attached mode). There bursts were induced by periodical large inward currents (interneuronal GDPs) recorded in whole-cell mode. 3. Interneuronal GDPs revealed typical features of polysynaptic neuronal network-driven events: they were blocked by TTX and by high divalent cation medium and they could be evoked in an all-or-none manner by electrical stimulation in different regions of the hippocampus. The network elements required for the generation of GDPs are present in local CA3 circuits since spontaneous GDPs were present in the isolated CA3 subfield of the hippocampal slice. 4. Interneuronal GDPs were mediated by GABAA and glutamate receptors, since: (i) their reversal potential strongly depended on [Cl-]i; (ii) at the reversal potential of GABAA postsynaptic currents an inward component of GDPs was composed of events with the same kinetics as alpha-amino-3-hydroxy-5-methylisoxazole-4-propionate (AMPA) receptor-mediated EPSCs; and (iii) once GABAA receptors were blocked intracellularly by dialysis with F(-)-MgATP-free solution, the remaining component of interneuronal GDPs reversed near 0 mV and rectified at membrane potentials more negative than -20 mV, suggesting an important contribution of NMDA receptors in addition to AMPA receptors. 5. In cell-attached recordings from interneurons, electrical stimulation in the stratum radiatum evoked a burst of spikes that corresponded to evoked GDPs. Pharmacological study of this response revealed that excitation of SR-CA3 interneurons during

  16. Spatiotemporal dynamics in excitable homogeneous random networks composed of periodically self-sustained oscillation.

    PubMed

    Qian, Yu; Liu, Fei; Yang, Keli; Zhang, Ge; Yao, Chenggui; Ma, Jun

    2017-09-19

    The collective behaviors of networks are often dependent on the network connections and bifurcation parameters, also the local kinetics plays an important role in contributing the consensus of coupled oscillators. In this paper, we systematically investigate the influence of network structures and system parameters on the spatiotemporal dynamics in excitable homogeneous random networks (EHRNs) composed of periodically self-sustained oscillation (PSO). By using the dominant phase-advanced driving (DPAD) method, the one-dimensional (1D) Winfree loop is exposed as the oscillation source supporting the PSO, and the accurate wave propagation pathways from the oscillation source to the whole network are uncovered. Then, an order parameter is introduced to quantitatively study the influence of network structures and system parameters on the spatiotemporal dynamics of PSO in EHRNs. Distinct results induced by the network structures and the system parameters are observed. Importantly, the corresponding mechanisms are revealed. PSO influenced by the network structures are induced not only by the change of average path length (APL) of network, but also by the invasion of 1D Winfree loop from the outside linking nodes. Moreover, PSO influenced by the system parameters are determined by the excitation threshold and the minimum 1D Winfree loop. Finally, we confirmed that the excitation threshold and the minimum 1D Winfree loop determined PSO will degenerate as the system size is expanded.

  17. Recruitment of an inhibitory hippocampal network after bursting in a single granule cell.

    PubMed

    Mori, Masahiro; Gähwiler, Beat H; Gerber, Urs

    2007-05-01

    The hippocampal CA3 area, an associational network implicated in memory function, receives monosynaptic excitatory as well as disynaptic inhibitory input through the mossy-fiber axons of the dentate granule cells. Synapses made by mossy fibers exhibit low release probability, resulting in high failure rates at resting discharge frequencies of 0.1 Hz. In recordings from functionally connected pairs of neurons, burst firing of a granule cell increased the probability of glutamate release onto both CA3 pyramidal cells and inhibitory interneurons, such that subsequent low-frequency stimulation evoked biphasic excitatory/inhibitory responses in a CA3 pyramidal cell, an effect lasting for minutes. Analysis of the unitary connections in the circuit revealed that granule cell bursting caused powerful activation of an inhibitory network, thereby transiently suppressing excitatory input to CA3 pyramidal cells. This phenomenon reflects the high incidence of spike-to-spike transmission at granule cell to interneuron synapses, the numerically much greater targeting by mossy fibers of inhibitory interneurons versus principal cells, and the extensively divergent output of interneurons targeting CA3 pyramidal cells. Thus, mossy-fiber input to CA3 pyramidal cells appears to function in three distinct modes: a resting mode, in which synaptic transmission is ineffectual because of high failure rates; a bursting mode, in which excitation predominates; and a postbursting mode, in which inhibitory input to the CA3 pyramidal cells is greatly enhanced. A mechanism allowing the transient recruitment of inhibitory input may be important for controlling network activity in the highly interconnected CA3 pyramidal cell region.

  18. 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.

  19. 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

  20. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2016-02-01

    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.

  2. 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

  3. 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

  4. Interaction of chimera states in a multilayered network of nonlocally coupled oscillators

    NASA Astrophysics Data System (ADS)

    Goremyko, M. V.; Maksimenko, V. A.; Makarov, V. V.; Ghosh, D.; Bera, B.; Dana, S. K.; Hramov, A. E.

    2017-08-01

    The processes of formation and evolution of chimera states in the model of a multilayered network of nonlinear elements with complex coupling topology are studied. A two-layered network of nonlocally intralayer-coupled Kuramoto-Sakaguchi phase oscillators is taken as the object of investigation. Different modes implemented in this system upon variation of the degree of interlayer interaction are demonstrated.

  5. 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

  6. 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

  7. Hippocampal-neocortical networks differ during encoding and retrieval of relational memory: functional and effective connectivity analyses.

    PubMed

    McCormick, C; Moscovitch, M; Protzner, A B; Huber, C G; McAndrews, M P

    2010-09-01

    Encoding and retrieval of relational information requires interaction between the hippocampus and various neocortical regions, but it is unknown whether the connectivity of hippocampal-neocortical networks is different at input and output stages. To examine this, we conducted a network analysis of event-related fMRI data collected during a face-recognition, remember/know paradigm. Directed analyses in the medial temporal lobe identified a small region in the left hippocampus that showed differential activation for encoding and retrieval of recollected versus familiar items. Multivariate seed partial least squares (PLS) analysis was used to identify brain regions that were functionally connected to this hippocampal region at encoding and retrieval of 'remembered' items. Anatomically based structural equation modeling (SEM) was then used to test for differences in effective connectivity of network nodes between these two memory stages. The SEM analysis revealed a reversal of directionality between the left hippocampus (LHC) and left inferior parietal cortex (LIPC) at encoding and retrieval. During encoding, activation of the LHC had a positive influence on the LIPC, whereas during retrieval the reverse pattern was found, i.e., the LIPC activation positively influenced LHC activation. These findings emphasize the importance of hippocampal-parietal connections and underscore the complexity of their interactions in initial binding and retrieval/reintegration of relational memory. We also found that, during encoding, the right hippocampus had a positive influence on the right retrospenial cortex, whereas during retrieval this influence was significantly weaker. We submit that examining patterns of connectivity can be important both to elaborate and constrain models of memory involving hippocampal-neocortical interactions. Copyright 2010 Elsevier Ltd. All rights reserved.

  8. 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

  9. 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

    2015-11-27

    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.

  10. Transsynaptic progression of amyloid-β-induced neuronal dysfunction within the entorhinal-hippocampal network

    PubMed Central

    Harris, Julie A.; Devidze, Nino; Verret, Laure; Ho, Kaitlyn; Halabisky, Brian; Thwin, Myo T.; Kim, Daniel; Hamto, Patricia; Lo, Iris; Yu, Gui-Qiu; Palop, Jorge J.; Masliah, Eliezer; Mucke, Lennart

    2011-01-01

    SUMMARY The entorhinal cortex (EC) is one of the earliest affected and most vulnerable brain regions in Alzheimer’s disease (AD), which is associated with amyloid-β (Aβ) accumulation in many brain areas. We show selective overexpression of mutant amyloid precursor protein (APP) predominantly in layer II/III neurons of the EC causes cognitive and behavioral abnormalities characteristic of mouse models with widespread neuronal APP overexpression, including hyperactivity, disinhibition, and spatial learning and memory deficits. Overexpression of APP/Aβ in the EC elicited abnormalities in synaptic functions and activity-related molecules in the dentate gyrus and CA1, as well as epileptiform activity in parietal cortex. Soluble Aβ was observed in the dentate gyrus and Aβ deposits in the hippocampus were localized to perforant pathway terminal fields. Thus, APP/Aβ expression in EC neurons can cause transsynaptic deficits, which could initiate the cortical-hippocampal network dysfunction observed in mouse models and human patients with AD. PMID:21040845

  11. Inhibition dominates in shaping spontaneous CA3 hippocampal network activities in vitro.

    PubMed

    Ho, Ernest C Y; Zhang, Liang; Skinner, Frances K

    2009-02-01

    We have assessed the balance of excitation and inhibition in in vitro rodent hippocampal slices exhibiting spontaneous, basal sharp waves (bSPWs). A defining signature of a network exhibiting bSPWs is the rise and fall in local field activities with frequencies ranging from 0.5 to 4.5 Hz. This variation of extracellular local field activities manifests at the intracellular level as postsynaptic potentials (PSPs). In correspondence with the local field bSPWs, we consider "sparse" and "synchronous" parts of bSPWs at the intracellular level. We have used intracellular data of bSPW-associated PSPs together with mathematical extraction techniques to quantify the mean and variance of synaptic conductances that a neuron experiences during bSPW episodes. We find that inhibitory conductances dominate in pyramidal cells and in a putative interneuron, and that inhibitory variances are much greater than excitatory ones during synchronous parts of bSPWs. Specifically, we find that there is at least a twofold increase in inhibitory conductance dominance from "sparse" to "synchronous" bSPW states and that this transition is associated with inhibitory fluctuations of greater than 10% of the change in mean inhibitory conductance. On the basis of our findings, we suggest that such inhibitory fluctuations during transition may be a physiological feature of systems expressing such population activities. In summary, our results provide a quantified basis for understanding the interaction of excitatory and inhibitory neuronal subpopulations in bSPW activities.

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

    PubMed

    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.

  13. Breakdown of order preservation in symmetric oscillator networks with pulse-coupling.

    PubMed

    Kielblock, Hinrich; Kirst, Christoph; Timme, Marc

    2011-06-01

    Symmetric networks of coupled dynamical units exhibit invariant subspaces with two or more units synchronized. In time-continuously coupled systems, these invariant sets constitute barriers for the dynamics. For networks of units with local dynamics defined on the real line, this implies that the units' ordering is preserved and that their winding number is identical. Here, we show that in permutation-symmetric networks with pulse-coupling, the order is often no longer preserved. We analytically study a class of pulse-coupled oscillators (characterizing for instance the dynamics of spiking neural networks) and derive quantitative conditions for the breakdown of order preservation. We find that in general pulse-coupling yields additional dimensions to the state space such that units may change their order by avoiding the invariant sets. We identify a system of two symmetrically pulse-coupled identical oscillators where, contrary to intuition, the oscillators' average frequencies and thus their winding numbers are different.

  14. 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

  15. Synchronized patterns in hierarchical networks of neuronal oscillators with D3 × D3 symmetry

    NASA Astrophysics Data System (ADS)

    Wegelin, Michael; Oppenländer, Jörg; Tomes, Jörg; Güttinger, Werner; Dangelmayr, Gerhard

    1998-10-01

    The spatiotemporal patterns generated by systems of nine coupled nonlinear oscillators which are equivariant under the permutation symmetry group D3 × D3 are determined. This system can be interpreted as a hierarchically organized network composed of three interacting systems each of which consists of three coupled oscillators. We determine generic synchronized oscillation patterns and transitions between these analytically, by numerical simulations, and experimentally with an electronic analog-network. In the theoretical analysis the representative nonlinear ordinary differential equations are reduced to the normal form equations for coupled Hopf bifurcations in an eight-dimensional center eigenspace, whose generic states have been classified previously. The results are applied to a specific model system in which the network is formed by a class of oscillators, each composed of two asymmetrically coupled Hopfield neurons. Experiments performed on an analog-electronic network of such nonlinear oscillators show that most of the states predicted by the theory of the Hopf bifurcation with D3 × D3- symmetry appear in a stable way. We find a great variety of periodic and quasiperiodic oscillation patterns of maximal and submaximal symmetry which can be classified in a two-level pattern hierarchy. In addition to these states we find in simulations homoclinic cycles within the same isotropy class as well as heteroclinic switchings between such cycles.

  16. Odour-modulated collective network oscillations of olfactory interneurons in a terrestrial mollusc

    NASA Astrophysics Data System (ADS)

    Gelperin, Alan; Tank, David W.

    1990-05-01

    DETERMINATION of the dynamical structure of neural circuits—the general principles of how neural activity varies with time and manipulates information—is a prerequisite to understanding their computational function1. Rhythmically active or oscillating neural circuits are particularly interesting dynamical structures, as rhythms and oscillations are a prominent feature of mammalian central nervous system electrophysiology. Coherent oscillations by networks of interneurons are observed in the vertebrate olfactory system2,3 and have recently been described in mammalian visual cortex4-6. These interneuronal networks display oscillations in local field potential (LFP) and probability of producing action potentials that are highly correlated between subcircuits sharing the same stimulus features. Much less is known about the existence and importance of network oscillations in the higher centres of invertebrates7. Here we report that a network of olfactory inter-neurons in the cerebral ganglion of the terrestrial mollusc Limax maximus also displays coherent oscillations in LFP which are modified by odour input. This dynamical structure could be central to the odour recognition and odour learning ability of Limax8,9.

  17. Immature Hippocampal Neuronal Networks do not Develop Tolerance to the Excitatory Actions of Ethanol

    PubMed Central

    Galindo, Rafael; Valenzuela, C. Fernando

    2007-01-01

    EtOH (ethanol) 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 hr. 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 4 hours/day for 1 or 3 days (neonatal peak blood EtOH concentration = 40–45 mM). We then performed slice electrophysiological studies 24 hours 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

  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. 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. Copyright © 2015 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

  20. Development of structural correlations and synchronization from adaptive rewiring in networks of Kuramoto oscillators

    NASA Astrophysics Data System (ADS)

    Papadopoulos, Lia; Kim, Jason Z.; Kurths, Jürgen; Bassett, Danielle S.

    2017-07-01

    Synchronization of non-identical oscillators coupled through complex networks is an important example of collective behavior, and it is interesting to ask how the structural organization of network interactions influences this process. Several studies have explored and uncovered optimal topologies for synchronization by making purposeful alterations to a network. On the other hand, the connectivity patterns of many natural systems are often not static, but are rather modulated over time according to their dynamics. However, this co-evolution and the extent to which the dynamics of the individual units can shape the organization of the network itself are less well understood. Here, we study initially randomly connected but locally adaptive networks of Kuramoto oscillators. In particular, the system employs a co-evolutionary rewiring strategy that depends only on the instantaneous, pairwise phase differences of neighboring oscillators, and that conserves the total number of edges, allowing the effects of local reorganization to be isolated. We find that a simple rule—which preserves connections between more out-of-phase oscillators while rewiring connections between more in-phase oscillators—can cause initially disordered networks to organize into more structured topologies that support enhanced synchronization dynamics. We examine how this process unfolds over time, finding a dependence on the intrinsic frequencies of the oscillators, the global coupling, and the network density, in terms of how the adaptive mechanism reorganizes the network and influences the dynamics. Importantly, for large enough coupling and after sufficient adaptation, the resulting networks exhibit interesting characteristics, including degree-frequency and frequency-neighbor frequency correlations. These properties have previously been associated with optimal synchronization or explosive transitions in which the networks were constructed using global information. On the contrary, by

  1. A universal order parameter for synchrony in networks of limit cycle oscillators

    NASA Astrophysics Data System (ADS)

    Schröder, Malte; Timme, Marc; Witthaut, Dirk

    2017-07-01

    We analyze the properties of order parameters measuring synchronization and phase locking in complex oscillator networks. First, we review network order parameters previously introduced and reveal several shortcomings: none of the introduced order parameters capture all transitions from incoherence over phase locking to full synchrony for arbitrary, finite networks. We then introduce an alternative, universal order parameter that accurately tracks the degree of partial phase locking and synchronization, adapting the traditional definition to account for the network topology and its influence on the phase coherence of the oscillators. We rigorously prove that this order parameter is strictly monotonously increasing with the coupling strength in the phase locked state, directly reflecting the dynamic stability of the network. Furthermore, it indicates the onset of full phase locking by a diverging slope at the critical coupling strength. The order parameter may find applications across systems where different types of synchrony are possible, including biological networks and power grids.

  2. 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

  3. 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.

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

    PubMed

    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.

  5. 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.

  6. Functional connectivity of hippocampal and prefrontal networks during episodic and spatial memory based on real-world environments.

    PubMed

    Robin, Jessica; Hirshhorn, Marnie; Rosenbaum, R Shayna; Winocur, Gordon; Moscovitch, Morris; Grady, Cheryl L

    2015-01-01

    Several recent studies have compared episodic and spatial memory in neuroimaging paradigms in order to understand better the contribution of the hippocampus to each of these tasks. In the present study, we build on previous findings showing common neural activation in default network areas during episodic and spatial memory tasks based on familiar, real-world environments (Hirshhorn et al. (2012) Neuropsychologia 50:3094-3106). Following previous demonstrations of the presence of functionally connected sub-networks within the default network, we performed seed-based functional connectivity analyses to determine how, depending on the task, the hippocampus and prefrontal cortex differentially couple with one another and with distinct whole-brain networks. We found evidence for a medial prefrontal-parietal network and a medial temporal lobe network, which were functionally connected to the prefrontal and hippocampal seeds, respectively, regardless of the nature of the memory task. However, these two networks were functionally connected with one another during the episodic memory task, but not during spatial memory tasks. Replicating previous reports of fractionation of the default network into stable sub-networks, this study also shows how these sub-networks may flexibly couple and uncouple with one another based on task demands. These findings support the hypothesis that episodic memory and spatial memory share a common medial temporal lobe-based neural substrate, with episodic memory recruiting additional prefrontal sub-networks.

  7. Spatially organized dynamical states in chemical oscillator networks: synchronization, dynamical differentiation, and chimera patterns.

    PubMed

    Wickramasinghe, Mahesh; Kiss, István Z

    2013-01-01

    Dynamical processes in many engineered and living systems take place on complex networks of discrete dynamical units. We present laboratory experiments with a networked chemical system of nickel electrodissolution in which synchronization patterns are recorded in systems with smooth periodic, relaxation periodic, and chaotic oscillators organized in networks composed of up to twenty dynamical units and 140 connections. The reaction system formed domains of synchronization patterns that are strongly affected by the architecture of the network. Spatially organized partial synchronization could be observed either due to densely connected network nodes or through the 'chimera' symmetry breaking mechanism. Relaxation periodic and chaotic oscillators formed structures by dynamical differentiation. We have identified effects of network structure on pattern selection (through permutation symmetry and coupling directness) and on formation of hierarchical and 'fuzzy' clusters. With chaotic oscillators we provide experimental evidence that critical coupling strengths at which transition to identical synchronization occurs can be interpreted by experiments with a pair of oscillators and analysis of the eigenvalues of the Laplacian connectivity matrix. The experiments thus provide an insight into the extent of the impact of the architecture of a network on self-organized synchronization patterns.

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

    PubMed

    Goto, Hayato

    2016-02-22

    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.

  9. 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.

  10. Globally attracting synchrony in a network of oscillators with all-to-all inhibitory pulse coupling

    NASA Astrophysics Data System (ADS)

    Canavier, Carmen C.; Tikidji-Hamburyan, Ruben A.

    2017-03-01

    The synchronization tendencies of networks of oscillators have been studied intensely. We assume a network of all-to-all pulse-coupled oscillators in which the effect of a pulse is independent of the number of oscillators that simultaneously emit a pulse and the normalized delay (the phase resetting) is a monotonically increasing function of oscillator phase with the slope everywhere less than 1 and a value greater than 2 φ -1 , where φ is the normalized phase. Order switching cannot occur; the only possible solutions are globally attracting synchrony and cluster solutions with a fixed firing order. For small conduction delays, we prove the former stable and all other possible attractors nonexistent due to the destabilizing discontinuity of the phase resetting at a phase of 0.

  11. 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

  12. 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.

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

    PubMed

    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.

  14. Coherence of biochemical oscillations is bounded by driving force and network topology

    NASA Astrophysics Data System (ADS)

    Barato, Andre C.; Seifert, Udo

    2017-06-01

    Biochemical oscillations are prevalent in living organisms. Systems with a small number of constituents cannot sustain coherent oscillations for an indefinite time because of fluctuations in the period of oscillation. We show that the number of coherent oscillations that quantifies the precision of the oscillator is universally bounded by the thermodynamic force that drives the system out of equilibrium and by the topology of the underlying biochemical network of states. Our results are valid for arbitrary Markov processes, which are commonly used to model biochemical reactions. We apply our results to a model for a single KaiC protein and to an activator-inhibitor model that consists of several molecules. From a mathematical perspective, based on strong numerical evidence, we conjecture a universal constraint relating the imaginary and real parts of the first nontrivial eigenvalue of a stochastic matrix.

  15. Landscape, Flux, Correlation, Resonance, Coherence, Stability, and Key Network Wirings of Stochastic Circadian Oscillation

    PubMed Central

    Li, Chunhe; Wang, Erkang; Wang, Jin

    2011-01-01

    Circadian rhythms with a period of ∼24 h, are natural timing machines. They are broadly distributed in living organisms, such as Neurospora, Drosophila, and mammals. The underlying natures of the rhythmic behavior have been explored by experimental and theoretical approaches. However, the global and physical natures of the oscillation under fluctuations are still not very clear. We developed a landscape and flux framework to explore the global stability and robustness of a circadian oscillation system. The potential landscape of the network is uncovered and has a global Mexican-hat shape. The height of the Mexican-hat provides a quantitative measure to evaluate the robustness and coherence of the oscillation. We found that in nonequilibrium dynamic systems, not only the potential landscape but also the probability flux are important to the dynamics of the system under intrinsic noise. Landscape attracts the systems down to the oscillation ring while flux drives the coherent oscillation on the ring. We also investigated the phase coherence and the entropy production rate of the system at different fluctuations and found that dissipations are less and the coherence is higher for larger number of molecules. We also found that the power spectrum of autocorrelation functions show resonance peak at the frequency of coherent oscillations. The peak is less prominent for smaller number of molecules and less barrier height and therefore can be used as another measure of stability of oscillations. As a consequence of nonzero probability flux, we show that the three-point correlations from the time traces show irreversibility, providing a possible way to explore the flux from the observations. Furthermore, we explored the escape time from the oscillation ring to outside at different molecular number. We found that when barrier height is higher, escape time is longer and phase coherence of oscillation is higher. Finally, we performed the global sensitivity analysis of the

  16. Coexistence of Regular and Irregular Dynamics in Complex Networks of Pulse-Coupled Oscillators

    NASA Astrophysics Data System (ADS)

    Timme, Marc; Wolf, Fred; Geisel, Theo

    2002-11-01

    For general networks of pulse-coupled oscillators, including regular, random, and more complex networks, we develop an exact stability analysis of synchronous states. As opposed to conventional stability analysis, here stability is determined by a multitude of linear operators. We treat this multioperator problem exactly and show that for inhibitory interactions the synchronous state is stable, independent of the parameters and the network connectivity. In randomly connected networks with strong interactions this synchronous state, displaying regular dynamics, coexists with a balanced state exhibiting irregular dynamics. External signals may switch the network between qualitatively distinct states.

  17. Evolutionary design of non-frustrated networks of phase-repulsive oscillators

    PubMed Central

    Levnajić, Zoran

    2012-01-01

    Evolutionary optimisation algorithm is employed to design networks of phase-repulsive oscillators that achieve an anti-phase synchronised state. By introducing the link frustration, the evolutionary process is implemented by rewiring the links with probability proportional to their frustration, until the final network displaying a unique non-frustrated dynamical state is reached. Resulting networks are bipartite and with zero clustering. In addition, the designed non-frustrated anti-phase synchronised networks display a clear topological scale. This contrasts usually studied cases of networks with phase-attractive dynamics, whose performance towards full synchronisation is typically enhanced by the presence of a topological hierarchy. PMID:23243494

  18. Onset of chaotic phase synchronization in complex networks of coupled heterogeneous oscillators.

    PubMed

    Ricci, Francesco; Tonelli, Roberto; Huang, Liang; Lai, Ying-Cheng

    2012-08-01

    Existing studies on network synchronization focused on complex networks possessing either identical or nonidentical but simple nodal dynamics. We consider networks of both complex topologies and heterogeneous but chaotic oscillators, and investigate the onset of global phase synchronization. Based on a heuristic analysis and by developing an efficient numerical procedure to detect the onset of phase synchronization, we uncover a general scaling law, revealing that chaotic phase synchronization can be facilitated by making the network more densely connected. Our methodology can find applications in probing the fundamental network dynamics in realistic situations, where both complex topology and complicated, heterogeneous nodal dynamics are expected.

  19. Two different modes of oscillation in a gene transcription regulatory network with interlinked positive and negative feedback loops

    NASA Astrophysics Data System (ADS)

    Karmakar, Rajesh

    2016-12-01

    We study the oscillatory behavior of a gene regulatory network with interlinked positive and negative feedback loop. The frequency and amplitude are two important properties of oscillation. The studied network produces two different modes of oscillation. In one mode (mode-I), frequency of oscillation remains constant over a wide range of amplitude and in the other mode (mode-II) the amplitude of oscillation remains constant over a wide range of frequency. Our study reproduces both features of oscillations in a single gene regulatory network and shows that the negative plus positive feedback loops in gene regulatory network offer additional advantage. We identified the key parameters/variables responsible for different modes of oscillation. The network is flexible in switching between different modes by choosing appropriately the required parameters/variables.

  20. The 5-hydroxytryptamine4 receptor agonists prucalopride and PRX-03140 increase acetylcholine and histamine levels in the rat prefrontal cortex and the power of stimulated hippocampal θ oscillations.

    PubMed

    Johnson, David E; Drummond, Elena; Grimwood, Sarah; Sawant-Basak, Aarti; Miller, Emily; Tseng, Elaine; McDowell, Laura L; Vanase-Frawley, Michelle A; Fisher, Katherine E; Rubitski, David M; Stutzman-Engwall, Kim J; Nelson, Robin T; Horner, Weldon E; Gorczyca, Roxanne R; Hajos, Mihaly; Siok, Chester J

    2012-06-01

    5-Hydroxytryptamine (5-HT)(4) receptor agonists reportedly stimulate brain acetylcholine (ACh) release, a property that might provide a new pharmacological approach for treating cognitive deficits associated with Alzheimer's disease. The purpose of this study was to compare the binding affinities, functional activities, and effects on neuropharmacological responses associated with cognition of two highly selective 5-HT(4) receptor agonists, prucalopride and 6,7-dihydro-4-hydroxy-7-isopropyl-6-oxo-N-[3-(piperidin-1-yl)propyl]thieno[2,3-b]pyridine-5-carboxamide (PRX-03140). In vitro, prucalopride and PRX-03140 bound to native rat brain 5-HT(4) receptors with K(i) values of 30 nM and 110 nM, respectively, and increased cAMP production in human embryonic kidney-293 cells expressing recombinant rat 5-HT(4) receptors. In vivo receptor occupancy studies established that prucalopride and PRX-03140 were able to penetrate the brain and bound to 5-HT(4) receptors in rat brain, achieving 50% receptor occupancy at free brain exposures of 330 nM and 130 nM, respectively. Rat microdialysis studies revealed that prucalopride maximally increased ACh and histamine levels in the prefrontal cortex at 5 and 10 mg/kg, whereas PRX-03140 significantly increased cortical histamine levels at 50 mg/kg, failing to affect ACh release at doses lower than 150 mg/kg. In combination studies, donepezil-induced increases in cortical ACh levels were potentiated by prucalopride and PRX-03140. Electrophysiological studies in rats demonstrated that both compounds increased the power of brainstem-stimulated hippocampal θ oscillations at 5.6 mg/kg. These findings show for the first time that the 5-HT(4) receptor agonists prucalopride and PRX-03140 can increase cortical ACh and histamine levels, augment donepezil-induced ACh increases, and increase stimulated-hippocampal θ power, all neuropharmacological parameters consistent with potential positive effects on cognitive processes.

  1. Bipartite networks of oscillators with distributed delays: Synchronization branches and multistability

    NASA Astrophysics Data System (ADS)

    Punetha, Nirmal; Ramaswamy, Ramakrishna; Atay, Fatihcan M.

    2015-04-01

    We study synchronization in bipartite networks of phase oscillators with general nonlinear coupling and distributed time delays. Phase-locked solutions are shown to arise, where the oscillators in each partition are perfectly synchronized among themselves but can have a phase difference with the other partition, with the phase difference necessarily being either zero or π radians. Analytical conditions for the stability of both types of solutions are obtained and solution branches are explicitly calculated, revealing that the network can have several coexisting stable solutions. With increasing value of the mean delay, the system exhibits hysteresis, phase flips, final state sensitivity, and an extreme form of multistability where the numbers of stable in-phase and antiphase synchronous solutions with distinct frequencies grow without bound. The theory is applied to networks of Landau-Stuart and Rössler oscillators and shown to accurately predict both in-phase and antiphase synchronous behavior in appropriate parameter ranges.

  2. 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.

  3. Network hyperexcitability in hippocampal slices from Mecp2 mutant mice revealed by voltage-sensitive dye imaging

    PubMed Central

    Calfa, Gaston; Hablitz, John J.

    2011-01-01

    Dysfunctions of neuronal and network excitability have emerged as common features in disorders associated with intellectual disabilities, autism, and seizure activity, all common clinical manifestations of Rett syndrome (RTT), a neurodevelopmental disorder caused by loss-of-function mutations in the transcriptional regulator methyl-CpG-binding protein 2 (MeCP2). Here, we evaluated the consequences of Mecp2 mutation on hippocampal network excitability, as well as synapse structure and function using a combination of imaging and electrophysiological approaches in acute slices. Imaging the amplitude and spatiotemporal spread of neuronal depolarizations with voltage-sensitive dyes (VSD) revealed that the CA1 and CA3 regions of hippocampal slices from symptomatic male Mecp2 mutant mice are highly hyperexcitable. However, only the density of docked synaptic vesicles and the rate of release from the readily releasable pool are impaired in Mecp2 mutant mice, while synapse density and morphology are unaffected. The differences in network excitability were not observed in surgically isolated CA1 minislices, and blockade of GABAergic inhibition enhanced VSD signals to the same extent in Mecp2 mutant and wild-type mice, suggesting that network excitability originates in area CA3. Indeed, extracellular multiunit recordings revealed a higher level of spontaneous firing of CA3 pyramidal neurons in slices from symptomatic Mecp2 mutant mice. The neuromodulator adenosine reduced the amplitude and spatiotemporal spread of VSD signals evoked in CA1 of Mecp2 mutant slices to wild-type levels, suggesting its potential use as an anticonvulsant in RTT individuals. The present results suggest that hyperactive CA3 pyramidal neurons contribute to hippocampal dysfunction and possibly to limbic seizures observed in Mecp2 mutant mice and RTT individuals. PMID:21307327

  4. 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.

  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.

  6. Cannabinoids inhibit network-driven synapse loss between hippocampal neurons in culture

    PubMed Central

    Kim, Hee Jung; Waataja, Jonathan J.; Thayer, Stanley A.

    2008-01-01

    Dendritic pruning and loss of synaptic contacts are early events in many neurodegenerative diseases. These effects are dynamic and appear to differ mechanistically from the cell death process. Cannabinoids modulate synaptic activity and afford protection in some neurotoxicity models. We investigated the effects of cannabinoids on activity-induced changes in the number of synapses between rat hippocampal neurons in culture. Morphology and synapses were visualized by confocal imaging of neurons expressing DsRed2 and postsynaptic density protein 95 fused to enhanced green fluorescent protein (PSD95-GFP). Reducing the extracellular Mg2+ concentration to 0.1 mM for 4 hr induced intense synaptic activity that decreased the number of PSD95-GFP puncta by 45 ± 13 %. Synapse loss was an early event, required activation of NMDA receptors and was mediated by the ubiquitin-proteasome pathway. The cannabinoid receptor full agonist (R)-(+)-[2,3-dihydro-5-methyl-3-[(4-morpholinyl)methyl] pyrrolo-[1,2,3-de]-1,4-benzoxazin-6-yl](1-napthalenyl)methanone monomethanesulfonate (WIN55,212-2; EC50=2.5±0.5 nM) and the partial agonist Δ9-tetrahydrocannabinol (THC; EC50=9±3 nM) inhibited PSD loss in a manner reversed by the CB1 receptor antagonist rimonabant. The protection was mimicked by inhibition of presynaptic Ca2+ channels and WIN55,212-2 did not prevent PSD loss elicited by direct application of glutamate, suggesting a presynaptic mechanism. Prolonged exposure to WIN55,212-2, but not THC, desensitized the protective effect. Treating cells that had undergone PSD loss with WIN55,212-2 reversed the loss and enabled recovery of a full compliment of synapses. The modulation of synaptic number by acute and prolonged exposure to cannabinoids may account for some of the effects of these drugs on the plasticity, survival and function of neural networks. PMID:18310474

  7. Synchronization of chaotic optoelectronic oscillators: Adaptive techniques and the design of optimal networks

    NASA Astrophysics Data System (ADS)

    Ravoori, Bhargava

    Synchronization in networks of chaotic systems is an interesting phenomenon with potential applications to sensing, parameter estimation and communications. Synchronization of chaos, in addition to being influenced by the dynamical nature of the constituent network units, is critically dependent upon the maintenance of a proper coupling between the systems. In practical situations, however, synchronization in chaotic networks is negatively affected by perturbations in the coupling channels. Here, using a fiber-optic network of chaotic optoelectronic oscillators, we experimentally demonstrate an adaptive algorithm that maintains global network synchrony even when the coupling strengths are unknown and time-varying. Our adaptive algorithm operates by generating real-time estimates of the coupling perturbations which are subsequently used to suitably adjust internal node parameters in order to compensate for external disturbances. In our work, we also examine the influence of network configuration on synchronization. Through measurements of the convergence rate to synchronization in networks of optoelectronic systems, we show that having more network links does not necessarily imply faster or better synchronization as is generally thought. We find that the convergence rate is maximized for certain network configurations, called optimal networks, which are identified based on the eigenvalues of the coupling matrix. Further, based on an analysis of the eigenvectors of the coupling matrix, we introduce a classification system that categorizes networks according to their sensitivity to coupling perturbations as sensitive and nonsensitive configurations. Though our experiments are performed on networks consisting of specific nonlinear optoelectronic oscillators, the theoretical basis of our studies is general and consequently many of our results are applicable to networks of arbitrary dynamical oscillators.

  8. Afferent inputs to cortical fast-spiking interneurons organize pyramidal cell network oscillations at high-gamma frequencies (60–200 Hz)

    PubMed Central

    Crone, Nathan E.; Franaszczuk, Piotr J.

    2014-01-01

    High-gamma activity, ranging in frequency between ∼60 Hz and 200 Hz, has been observed in local field potential, electrocorticography, EEG and magnetoencephalography signals during cortical activation, in a variety of functional brain systems. The origin of these signals is yet unknown. Using computational modeling, we show that a cortical network model receiving thalamic input generates high-gamma responses comparable to those observed in local field potential recorded in monkey somatosensory cortex during vibrotactile stimulation. These high-gamma oscillations appear to be mediated mostly by an excited population of inhibitory fast-spiking interneurons firing at high-gamma frequencies and pacing excitatory regular-spiking pyramidal cells, which fire at lower rates but in phase with the population rhythm. The physiological correlates of high-gamma activity, in this model of local cortical circuits, appear to be similar to those proposed for hippocampal ripples generated by subsets of interneurons that regulate the discharge of principal cells. PMID:25210164

  9. Synchrony and chaos in coupled oscillators and neural networks

    NASA Astrophysics Data System (ADS)

    Raghavachari, Sridhar

    1999-09-01

    This dissertation studies the dynamics of ensembles of coupled, dynamical elements with discrete and continuous time dynamics. Specific problems include the appearance of synchronous behavior in an ensemble of dynamical elements. We show that the dynamics of coupled map lattices with connectivity that scales with inter-site distance exhibit a transition from spatial disorder to spatially uniform temporal chaos as the scaling varies. We investigate the eigenvalue spectrum of the stochastic matrix characterizing fluctuations from the uniform state numerically and show that the spectrum is bounded, real and the largest eigenvalue (corresponding to the uniform solution) has a gap separating it from the remaining N-1 eigenvalues which correspond to non-uniform solutions. The width of this gap depends on the scaling exponent. We relate the stability of the uniform state to this gap and show that the state is globally stable even in a strongly chaotic region of the uncoupled map. Bursting is a prototypical pattern of voltage oscillations of membrane potentials of biological cells, where the membrane potential alternates between fast oscillations and a slow drift. These complex oscillations arise as a result of interactions between the kinetics of fast and slow ion channels. While bursting in isolated cells Is, well understood, the study of populations of interacting bursters is less developed. We study a one- dimensional continuum model of bursting and show that a spatial wave of bursting separating active and quiescent cells extinguishes synchronous bursting when the coupling is weak. This result places bounds on the measured values of coupling strength between secretory cells in the pancreas. The interactions of cellular and synaptic mechanisms acting on several timescales control rhythmic behavior in animals, such as locomotion, digestion and respiration. We explore a simple rhythmic circuit model with two cells reciprocally inhibiting each other with fast and slow

  10. Dynamical Bayesian inference of time-evolving interactions: From a pair of coupled oscillators to networks of oscillators

    NASA Astrophysics Data System (ADS)

    Duggento, Andrea; Stankovski, Tomislav; McClintock, Peter V. E.; Stefanovska, Aneta

    2012-12-01

    Living systems have time-evolving interactions that, until recently, could not be identified accurately from recorded time series in the presence of noise. Stankovski [Phys. Rev. Lett.PRLTAO0031-900710.1103/PhysRevLett.109.024101 109, 024101 (2012)] introduced a method based on dynamical Bayesian inference that facilitates the simultaneous detection of time-varying synchronization, directionality of influence, and coupling functions. It can distinguish unsynchronized dynamics from noise-induced phase slips. The method is based on phase dynamics, with Bayesian inference of the time-evolving parameters being achieved by shaping the prior densities to incorporate knowledge of previous samples. We now present the method in detail using numerically generated data, data from an analog electronic circuit, and cardiorespiratory data. We also generalize the method to encompass networks of interacting oscillators and thus demonstrate its applicability to small-scale networks.

  11. Fast and robust image segmentation by small-world neural oscillator networks.

    PubMed

    Li, Chunguang; Li, Yuke

    2011-06-01

    Inspired by the temporal correlation theory of brain functions, researchers have presented a number of neural oscillator networks to implement visual scene segmentation problems. Recently, it is shown that many biological neural networks are typical small-world networks. In this paper, we propose and investigate two small-world models derived from the well-known LEGION (locally excitatory and globally inhibitory oscillator network) model. To form a small-world network, we add a proper proportion of unidirectional shortcuts (random long-range connections) to the original LEGION model. With local connections and shortcuts, the neural oscillators can not only communicate with neighbors but also exchange phase information with remote partners. Model 1 introduces excitatory shortcuts to enhance the synchronization within an oscillator group representing the same object. Model 2 goes further to replace the global inhibitor with a sparse set of inhibitory shortcuts. Simulation results indicate that the proposed small-world models could achieve synchronization faster than the original LEGION model and are more likely to bind disconnected image regions belonging together. In addition, we argue that these two models are more biologically plausible.

  12. Synchronization, stickiness effects and intermittent oscillations in coupled nonlinear stochastic networks

    NASA Astrophysics Data System (ADS)

    Kouvaris, N.; Provata, A.

    2009-08-01

    Long distance reactive and diffusive coupling is introduced in a spatially extended nonlinear stochastic network of interacting particles. The network serves as a substrate for Lotka-Volterra dynamics with 3rd order nonlinearities. If the network includes only local nearest neighbour interactions, the system organizes into a number of local asynchronous oscillators. It is shown that (a) Introduction of all-to-all coupling in the network leads the system into global, center-type, conservative oscillations as dictated by the mean-field dynamics. (b) Introduction of reactive coupling to the network leads the system to intermittent oscillations where the trajectories stick for short times in bounded regions of space, with subsequent jumps between different bounded regions. (c) Introduction of diffusive coupling to the system does not alter the dynamics for small values of the diffusive coupling pdiff, while after a critical value pdiff c the system synchronizes into a limit cycle with specific frequency, deviating non-trivially from the mean-field center-type behaviour. The frequency of the limit cycle oscillations depends on the reaction rates and on the diffusion coupling. The amplitude σ of the limit cycle depends on the control parameter pdiff.

  13. Autapses and networks of hippocampal neurons exhibit distinct synaptic transmission phenotypes in the absence of synaptotagmin I

    PubMed Central

    Liu, Huisheng; Dean, Camin; Arthur, Christopher P.; Dong, Min; Chapman, Edwin R.

    2009-01-01

    Synaptotagmin-I (syt-I) is required for rapid neurotransmitter release in mouse hippocampal neurons. However, contradictory results have been reported regarding evoked and spontaneous secretion from syt-I knockout (KO) neurons. Here, we compared synaptic transmission in two different hippocampal neuron preparations: autaptic cultures in which a single isolated cell innervates itself, and dissociated mass cultures in which individual cells are innervated by neighboring cells. In autaptic cultures, the total extent of evoked release, size of readily releasable pool of synaptic vesicles, and release probability, were unchanged in syt-I KO neurons. In contrast, in cultures containing multiple interconnected neurons, total evoked release, the number of docked vesicles, and release probability, were significantly reduced in syt-I KO neurons. Using a micro-network system in which we varied the number of cells on an island, we found that the frequency of spontaneous synaptic vesicle fusion events (minis) was unchanged in syt-I KO neurons when ≤ 2 cells were present on an island. However, in micro-networks composed of ≥ 3 neurons, mini frequency was increased three to five-fold in syt-I KO neurons compared to wild-type. Moreover, inter-neuronal synapses exhibited higher rates of spontaneous release than autaptic synapses. This higher rate was due to an increase in release probability because excitatory hippocampal neurons in micro-networks formed a set number of synapses per cell regardless of the number of connected neurons. Thus, aspects of synaptic transmission differ between autaptic and dissociated cultures and the synaptic transmission phenotype, due to loss of syt-I, is dictated by the connectivity of neurons. PMID:19515907

  14. Self-organized network of phase oscillators coupled by activity-dependent interactions.

    PubMed

    Aoki, Takaaki; Aoyagi, Toshio

    2011-12-01

    We investigate a network of coupled phase oscillators whose interactions evolve dynamically depending on the relative phases between the oscillators. We found that this coevolving dynamical system robustly yields three basic states of collective behavior with their self-organized interactions. The first is the two-cluster state, in which the oscillators are organized into two synchronized groups. The second is the coherent state, in which the oscillators are arranged sequentially in time. The third is the chaotic state, in which the relative phases between oscillators and their coupling weights are chaotically shuffled. Furthermore, we demonstrate that self-assembled multiclusters can be designed by controlling the weight dynamics. Note that the phase patterns of the oscillators and the weighted network of interactions between them are simultaneously organized through this coevolving dynamics. We expect that these results will provide new insight into self-assembly mechanisms by which the collective behavior of a rhythmic system emerges as a result of the dynamics of adaptive interactions.

  15. A Nanotechnology-Ready Computing Scheme based on a Weakly Coupled Oscillator Network

    PubMed Central

    Vodenicarevic, Damir; Locatelli, Nicolas; Abreu Araujo, Flavio; Grollier, Julie; Querlioz, Damien

    2017-01-01

    With conventional transistor technologies reaching their limits, alternative computing schemes based on novel technologies are currently gaining considerable interest. Notably, promising computing approaches have proposed to leverage the complex dynamics emerging in networks of coupled oscillators based on nanotechnologies. The physical implementation of such architectures remains a true challenge, however, as most proposed ideas are not robust to nanotechnology devices’ non-idealities. In this work, we propose and investigate the implementation of an oscillator-based architecture, which can be used to carry out pattern recognition tasks, and which is tailored to the specificities of nanotechnologies. This scheme relies on a weak coupling between oscillators, and does not require a fine tuning of the coupling values. After evaluating its reliability under the severe constraints associated to nanotechnologies, we explore the scalability of such an architecture, suggesting its potential to realize pattern recognition tasks using limited resources. We show that it is robust to issues like noise, variability and oscillator non-linearity. Defining network optimization design rules, we show that nano-oscillator networks could be used for efficient cognitive processing. PMID:28322262

  16. A Nanotechnology-Ready Computing Scheme based on a Weakly Coupled Oscillator Network.

    PubMed

    Vodenicarevic, Damir; Locatelli, Nicolas; Abreu Araujo, Flavio; Grollier, Julie; Querlioz, Damien

    2017-03-21

    With conventional transistor technologies reaching their limits, alternative computing schemes based on novel technologies are currently gaining considerable interest. Notably, promising computing approaches have proposed to leverage the complex dynamics emerging in networks of coupled oscillators based on nanotechnologies. The physical implementation of such architectures remains a true challenge, however, as most proposed ideas are not robust to nanotechnology devices' non-idealities. In this work, we propose and investigate the implementation of an oscillator-based architecture, which can be used to carry out pattern recognition tasks, and which is tailored to the specificities of nanotechnologies. This scheme relies on a weak coupling between oscillators, and does not require a fine tuning of the coupling values. After evaluating its reliability under the severe constraints associated to nanotechnologies, we explore the scalability of such an architecture, suggesting its potential to realize pattern recognition tasks using limited resources. We show that it is robust to issues like noise, variability and oscillator non-linearity. Defining network optimization design rules, we show that nano-oscillator networks could be used for efficient cognitive processing.

  17. A Nanotechnology-Ready Computing Scheme based on a Weakly Coupled Oscillator Network

    NASA Astrophysics Data System (ADS)

    Vodenicarevic, Damir; Locatelli, Nicolas; Abreu Araujo, Flavio; Grollier, Julie; Querlioz, Damien

    2017-03-01

    With conventional transistor technologies reaching their limits, alternative computing schemes based on novel technologies are currently gaining considerable interest. Notably, promising computing approaches have proposed to leverage the complex dynamics emerging in networks of coupled oscillators based on nanotechnologies. The physical implementation of such architectures remains a true challenge, however, as most proposed ideas are not robust to nanotechnology devices’ non-idealities. In this work, we propose and investigate the implementation of an oscillator-based architecture, which can be used to carry out pattern recognition tasks, and which is tailored to the specificities of nanotechnologies. This scheme relies on a weak coupling between oscillators, and does not require a fine tuning of the coupling values. After evaluating its reliability under the severe constraints associated to nanotechnologies, we explore the scalability of such an architecture, suggesting its potential to realize pattern recognition tasks using limited resources. We show that it is robust to issues like noise, variability and oscillator non-linearity. Defining network optimization design rules, we show that nano-oscillator networks could be used for efficient cognitive processing.

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

    PubMed Central

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

    2015-01-01

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

  19. Analysis of firing behaviors in networks of pulse-coupled oscillators with delayed excitatory coupling.

    PubMed

    Wu, Wei; Liu, Bo; Chen, Tianping

    2010-09-01

    In this paper, we investigate the firing behaviors in networks of pulse-coupled oscillators with delayed excitatory coupling according to the coupling strength epsilon and delay tau. We find out that the parameter space A={(epsilon,tau)|0network will have apparently different firing properties on them. In A(1), the firing behavior is relatively simple for rigorous analysis, while it is more complicated on A(2). First, we show that the delay tau is a lower bound for the inter-spike intervals of each oscillator on A(1). Using this lower bound, three important properties of the firing on A(1) are obtained: (a) Any complete synchronized solution is a solution with period 1; (b) If two oscillators fire at same time, and they have the same coupling strength from each other and from other oscillators, then, they will be synchronized forever; (c) The firing order of two oscillators is always preserved. However, examples can be provided to show that these properties do not hold for the region A(2). Yet, numerical simulation still reveals some interesting phenomenon on A(2): (a) Completely synchronized solutions are prevalent; (b) Given (tau,epsilon)inA(2), the fraction of the initial values that will lead to complete synchronization will converge along with increasing network size.

  20. 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.

  1. 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

  2. Conditions for the generation of beta oscillations in the subthalamic nucleus-globus pallidus network.

    PubMed

    Holgado, Alejo J Nevado; Terry, John R; Bogacz, Rafal

    2010-09-15

    The advance of Parkinson's disease is associated with the existence of abnormal oscillations within the basal ganglia with frequencies in the beta band (13-30 Hz). While the origin of these oscillations remains unknown, there is some evidence suggesting that oscillations observed in the basal ganglia arise due to interactions of two nuclei: the subthalamic nucleus (STN) and the globus pallidus pars externa (GPe). To investigate this hypothesis, we develop a computational model of the STN-GPe network based upon anatomical and electrophysiological studies. Significantly, our study shows that for certain parameter regimes, the model intrinsically oscillates in the beta range. Through an analytical study of the model, we identify a simple set of necessary conditions on model parameters that guarantees the existence of beta oscillations. These conditions for generation of oscillations are described by a set of simple inequalities and can be summarized as follows: (1) The excitatory connections from STN to GPe and the inhibitory connections from GPe to STN need to be sufficiently strong. (2) The time required by neurons to react to their inputs needs to be short relative to synaptic transmission delays. (3) The excitatory input from the cortex to STN needs to be high relative to the inhibition from striatum to GPe. We confirmed the validity of these conditions via numerical simulation. These conditions describe changes in parameters that are consistent with those expected as a result of the development of Parkinson's disease, and predict manipulations that could inhibit the pathological oscillations.

  3. 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.

  4. Stationary oscillation of an impulsive delayed system and its application to chaotic neural networks.

    PubMed

    Sun, Jitao; Lin, Hai

    2008-09-01

    This paper investigates the stationary oscillation for an impulsive delayed system which represents a class of nonlinear hybrid systems. First, a new concept of S-stability is introduced for nonlinear impulsive delayed systems. Based on this new concept and fixed point theorem, the relationship between S-stability and stationary oscillation (i.e., existence, uniqueness and global stability of periodic solutions) for the nonlinear impulsive delayed system is explored. It is shown that the nonlinear impulsive delayed system has a stationary oscillation if the system is S-stable. Second, an easily verifiable sufficient condition is then obtained for stationary oscillations of nonautonomous neural networks with both time delays and impulses by using the new criterion. Finally, an illustrative example is given to demonstrate the effectiveness of the proposed method.

  5. 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.

  6. Grouping synchronization in a pulse-coupled network of chaotic spiking oscillators.

    PubMed

    Nakano, H; Saito, T

    2004-09-01

    This paper studies a pulse-coupled network consisting of simple chaotic spiking oscillators (CSOs). If a unit oscillator and its neighbor(s) have (almost) the same parameter values, they exhibit in-phase synchronization of chaos. As the parameter values differ, they exhibit asynchronous phenomena. Based on such behavior, some synchronous groups appear partially in the network. Typical phenomena are verified in the laboratory via a simple test circuit. These phenomena can be evaluated numerically by using an effective mapping procedure. We then apply the proposed network to image segmentation. Using a lattice pulse-coupled network via grouping synchronous phenomena, the input image data can be segmented into some sub-regions.

  7. Sustained Activity in Hierarchical Modular Neural Networks: Self-Organized Criticality and Oscillations

    PubMed Central

    Wang, Sheng-Jun; Hilgetag, Claus C.; Zhou, Changsong

    2010-01-01

    Cerebral cortical brain networks possess a number of conspicuous features of structure and dynamics. First, these networks have an intricate, non-random organization. In particular, they are structured in a hierarchical modular fashion, from large-scale regions of the whole brain, via cortical areas and area subcompartments organized as structural and functional maps to cortical columns, and finally circuits made up of individual neurons. Second, the networks display self-organized sustained activity, which is persistent in the absence of external stimuli. At the systems level, such activity is characterized by complex rhythmical oscillations over a broadband background, while at the cellular level, neuronal discharges have been observed to display avalanches, indicating that cortical networks are at the state of self-organized criticality (SOC). We explored the relationship between hierarchical neural network organization and sustained dynamics using large-scale network modeling. Previously, it was shown that sparse random networks with balanced excitation and inhibition can sustain neural activity without external stimulation. We found that a hierarchical modular architecture can generate sustained activity better than random networks. Moreover, the system can simultaneously support rhythmical oscillations and SOC, which are not present in the respective random networks. The mechanism underlying the sustained activity is that each dense module cannot sustain activity on its own, but displays SOC in the presence of weak perturbations. Therefore, the hierarchical modular networks provide the coupling among subsystems with SOC. These results imply that the hierarchical modular architecture of cortical networks plays an important role in shaping the ongoing spontaneous activity of the brain, potentially allowing the system to take advantage of both the sensitivity of critical states and the predictability and timing of oscillations for efficient information

  8. Sustained activity in hierarchical modular neural networks: self-organized criticality and oscillations.

    PubMed

    Wang, Sheng-Jun; Hilgetag, Claus C; Zhou, Changsong

    2011-01-01

    Cerebral cortical brain networks possess a number of conspicuous features of structure and dynamics. First, these networks have an intricate, non-random organization. In particular, they are structured in a hierarchical modular fashion, from large-scale regions of the whole brain, via cortical areas and area subcompartments organized as structural and functional maps to cortical columns, and finally circuits made up of individual neurons. Second, the networks display self-organized sustained activity, which is persistent in the absence of external stimuli. At the systems level, such activity is characterized by complex rhythmical oscillations over a broadband background, while at the cellular level, neuronal discharges have been observed to display avalanches, indicating that cortical networks are at the state of self-organized criticality (SOC). We explored the relationship between hierarchical neural network organization and sustained dynamics using large-scale network modeling. Previously, it was shown that sparse random networks with balanced excitation and inhibition can sustain neural activity without external stimulation. We found that a hierarchical modular architecture can generate sustained activity better than random networks. Moreover, the system can simultaneously support rhythmical oscillations and SOC, which are not present in the respective random networks. The mechanism underlying the sustained activity is that each dense module cannot sustain activity on its own, but displays SOC in the presence of weak perturbations. Therefore, the hierarchical modular networks provide the coupling among subsystems with SOC. These results imply that the hierarchical modular architecture of cortical networks plays an important role in shaping the ongoing spontaneous activity of the brain, potentially allowing the system to take advantage of both the sensitivity of critical states and the predictability and timing of oscillations for efficient information

  9. Effect of random synaptic dilution on recalling dynamics in an oscillator neural network

    NASA Astrophysics Data System (ADS)

    Kitano, Katsunori; Aoyagi, Toshio

    1998-05-01

    In the present paper, we study the effect of random synaptic dilution in an oscillator neural network in which information is encoded by the relative timing of neuronal firing. In order to analyze the recalling process in this oscillator network, we apply the method of statistical neurodynamics. The results show that the dynamical equations are described by some macroscopic order parameters, such as that representing the overlap with the retrieved pattern. We also present the phase diagram showing both the basin of attraction and the equilibrium overlap in the retrieval state. Our results are supported by numerical simulation. Consequently, it is found that both the attractor and the basin are preserved even though dilution is promoted. Moreover, as compared with the basin of attraction in the traditional binary model, it is suggested that the oscillator model is more robust against the synaptic dilution. Taking into account the fact that oscillator networks contain more detailed information than binary networks, the obtained results constitute significant support for the plausibility of temporal coding.

  10. Control design for sustained oscillation in a two-gene regulatory network.

    PubMed

    Edwards, Roderick; Kim, Sehjeong; van den Driessche, P

    2011-04-01

    Control strategies for gene regulatory networks have begun to be explored, both experimentally and theoretically, with implications for control of disease as well as for synthetic biology. Recent work has focussed on controls designed to achieve desired stationary states. Another useful objective, however, is the initiation of sustained oscillations in systems where oscillations are normally damped, or even not present. Alternatively, it may be desired to suppress (by damping) oscillations that naturally occur in an uncontrolled network. Here we address these questions in the context of piecewise-affine models of gene regulatory networks with affine controls that match the qualitative nature of the model. In the case of two genes with a single relevant protein concentration threshold per gene, we find that control of production terms (constant control) is effective in generating or suppressing sustained oscillations, while control of decay terms (linear control) is not effective. We derive an easily calculated condition to determine an effective constant control. As an example, we apply our analysis to a model of the carbon response network in Escherichia coli, reduced to the two genes that are essential in understanding its behavior.

  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.

  12. 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

  13. A synthetic multi-cellular network of coupled self-sustained oscillators

    PubMed Central

    Giraldo, Daniel; Gomez-Porras, Judith Lucia; Dreyer, Ingo; González Barrios, Andrés Fernando; Arevalo-Ferro, Catalina

    2017-01-01

    Engineering artificial networks from modular components is a major challenge in synthetic biology. In the past years, single units, such as switches and oscillators, were successfully constructed and implemented. The effective integration of these parts into functional artificial self-regulated networks is currently on the verge of breakthrough. Here, we describe the design of a modular higher-order synthetic genetic network assembled from two independent self-sustained synthetic units: repressilators coupled via a modified quorum-sensing circuit. The isolated communication circuit and the network of coupled oscillators were analysed in mathematical modelling and experimental approaches. We monitored clustering of cells in groups of various sizes. Within each cluster of cells, cells oscillate synchronously, whereas the theoretical modelling predicts complete synchronization of the whole cellular population to be obtained approximately after 30 days. Our data suggest that self-regulated synchronization in biological systems can occur through an intermediate, long term clustering phase. The proposed artificial multicellular network provides a system framework for exploring how a given network generates a specific behaviour. PMID:28662174

  14. A synthetic multi-cellular network of coupled self-sustained oscillators.

    PubMed

    Fernández-Niño, Miguel; Giraldo, Daniel; Gomez-Porras, Judith Lucia; Dreyer, Ingo; González Barrios, Andrés Fernando; Arevalo-Ferro, Catalina

    2017-01-01

    Engineering artificial networks from modular components is a major challenge in synthetic biology. In the past years, single units, such as switches and oscillators, were successfully constructed and implemented. The effective integration of these parts into functional artificial self-regulated networks is currently on the verge of breakthrough. Here, we describe the design of a modular higher-order synthetic genetic network assembled from two independent self-sustained synthetic units: repressilators coupled via a modified quorum-sensing circuit. The isolated communication circuit and the network of coupled oscillators were analysed in mathematical modelling and experimental approaches. We monitored clustering of cells in groups of various sizes. Within each cluster of cells, cells oscillate synchronously, whereas the theoretical modelling predicts complete synchronization of the whole cellular population to be obtained approximately after 30 days. Our data suggest that self-regulated synchronization in biological systems can occur through an intermediate, long term clustering phase. The proposed artificial multicellular network provides a system framework for exploring how a given network generates a specific behaviour.

  15. Detecting effective connectivity in networks of coupled neuronal oscillators.

    PubMed

    Boykin, Erin R; Khargonekar, Pramod P; Carney, Paul R; Ogle, William O; Talathi, Sachin S

    2012-06-01

    The application of data-driven time series analysis techniques such as Granger causality, partial directed coherence and phase dynamics modeling to estimate effective connectivity in brain networks has recently gained significant prominence in the neuroscience community. While these techniques have been useful in determining causal interactions among different regions of brain networks, a thorough analysis of the comparative accuracy and robustness of these methods in identifying patterns of effective connectivity among brain networks is still lacking. In this paper, we systematically address this issue within the context of simple networks of coupled spiking neurons. Specifically, we develop a method to assess the ability of various effective connectivity measures to accurately determine the true effective connectivity of a given neuronal network. Our method is based on decision tree classifiers which are trained using several time series features that can be observed solely from experimentally recorded data. We show that the classifiers constructed in this work provide a general framework for determining whether a particular effective connectivity measure is likely to produce incorrect results when applied to a dataset.

  16. Comparison of the effects of acute and chronic administration of ketamine on hippocampal oscillations. Relevance for the NMDA receptor hypofunction model of schizophrenia

    PubMed Central

    Kittelberger, Kara; Hur, Elizabeth E.; Sazegar, Saba; Keshavan, Vidya; Kocsis, Bernat

    2011-01-01

    The proper organization and function of GABAergic interneuron networks is essential for many cognitive processes and abnormalities in these systems have been documented in schizophrenic patients. The memory function of the hippocampus depends on two major patterns of oscillations in the theta and gamma ranges, both requiring the intact functioning of the network of fast-firing interneurons expressing parvalbumin. We examined the ability of acute and chronic administration of NMDA receptor antagonists to recapitulate the oscillatory dysfunctions observed in schizophrenia. In freely moving rats, acute injection of MK801 or ketamine increased gamma power in both CA1 and dentate gyrus of the hippocampus. Theta peak shifted to higher frequencies whereas the average 5–10 Hz theta power decreased by 24% in CA1 and remained high in the dentate gyrus. Strong increase in CA1 gamma and decrease in theta power triggered by brainstem stimulation were found under urethane anesthesia. In contrast to acute experiments, chronic administration of ketamine caused a steady decline in both gamma and theta oscillations, 2–4 weeks after treatment. A further important difference between the two models was that the effects of acute injection were more robust than the changes after chronic treatment. Chronic administration of ketamine also lead to decrease in the number of detectable parvalbumin interneurons. Histological examination of interindividual differences indicated however that within the ketamine treated group a further decrease in parvalbumin neurons correlated with strengthening of oscillations. The findings are consistent with abnormalities of oscillations in human schizophrenia and further validate the NMDA receptor hypofunction hypothesis. PMID:21979451

  17. Brain oscillations and electroencephalography scalp networks during tempo perception.

    PubMed

    Tian, Yin; Ma, Weiyi; Tian, Chunyang; Xu, Peng; Yao, Dezhong

    2013-12-01

    In the current study we used electroencephalography (EEG) to investigate the relation between musical tempo perception and the oscillatory activity in specific brain regions, and the scalp EEG networks in the theta, alpha, and beta bands. The results showed that the theta power at the frontal midline decreased with increased arousal level related to tempo. The alpha power induced by original music at the bilateral occipital-parietal regions was stronger than that by tempo-transformed music. The beta power did not change with tempo. At the network level, the original music-related alpha network had high global efficiency and the optimal path length. This study was the first to use EEG to investigate multi-oscillatory activities and the data support the tempo-specific timing hypothesis.

  18. Cannabinoids inhibit network-driven synapse loss between hippocampal neurons in culture.

    PubMed

    Kim, Hee Jung; Waataja, Jonathan J; Thayer, Stanley A

    2008-06-01

    Dendritic pruning and loss of synaptic contacts are early events in many neurodegenerative diseases. These effects are dynamic and seem to differ mechanistically from the cell death process. Cannabinoids modulate synaptic activity and afford protection in some neurotoxicity models. We investigated the effects of cannabinoids on activity-induced changes in the number of synapses between rat hippocampal neurons in culture. Morphology and synapses were visualized by confocal imaging of neurons expressing DsRed2 and postsynaptic density protein 95 (PSD95) fused to enhanced green fluorescent protein (GFP). Reducing the extracellular Mg2+ concentration to 0.1 mM for 4 h induced intense synaptic activity, which decreased the number of PSD95-GFP puncta by 45 +/- 13%. Synapse loss was an early event, required activation of N-methyl-D-aspartate receptors, and was mediated by the ubiquitin-proteasome pathway. The cannabinoid receptor full agonist WIN55,212-2 [(R)-(+)-[2,3-dihydro-5-methyl-3-[(4-morpholinyl)-methyl] pyrrolo-[1,2,3-de]-1,4-benzoxazin-6-yl](1-napthalenyl)-methanone monomethanesulfonate] (EC(50) = 2.5 +/- 0.5 nM) and the partial agonist Delta(9)-tetrahydrocannabinol (THC; EC(50) = 9 +/- 3 nM) inhibited PSD loss in a manner reversed by the CB1 receptor antagonist rimonabant [N-piperidino-5-(4-chlorophenyl)-1-(2,4-dichlorophenyl)-4-methyl-3-pyrazole-carboxamide]. The protection was mimicked by inhibition of presynaptic Ca2+ channels, and WIN55,212-2 did not prevent PSD loss elicited by direct application of glutamate, suggesting a presynaptic mechanism. Prolonged exposure to WIN55,212-2, but not THC, desensitized the protective effect. Treating cells that had undergone PSD loss with WIN55,212-2 reversed the loss and enabled recovery of a full compliment of synapses. The modulation of synaptic number by acute and prolonged exposure to cannabinoids may account for some of the effects of these drugs on the plasticity, survival, and function of neural networks.

  19. The Role of Voltage-Dependence of the NMDA Receptor in Cellular and Network Oscillation

    PubMed Central

    Martell, Amber L.; Ramirez, Jan-Marino; Lasky, Robert E.; Dwyer, Jennifer E.; Kohrman, Michael; van Drongelen, Wim

    2012-01-01

    Unraveling the mechanisms underlying oscillatory behavior is critical for understanding normal and pathological brain processes. Here we used electrophysiology in mouse neocortical slices and principles of nonlinear dynamics to demonstrate how an increase in the N-methyl-D-aspartic acid receptor (NMDAR) conductance can create a nonlinear whole-cell current-voltage ( I – V ) relationship, which leads to changes in cellular stability. We discovered two behaviorally and morphologically distinct pyramidal cell populations. Under control conditions, both cell types responded to depolarizing current injection with regular spiking patterns. However, upon NMDAR activation, an intrinsic oscillatory (IO) cell type (n = 44) showed a nonlinear whole-cell I – V relationship, intrinsic voltage-dependent oscillations plus amplification of alternating input current, and these properties persisted after disabling action potential generation with TTX. The other non-oscillatory (NO) neuronal population (n = 24) demonstrated none of these behaviors. Simultaneous intra- and extracellular recordings demonstrated the NMDAR’s capacity to promote low-frequency seizure-like network oscillations via its effects on intrinsic neuronal properties. The two pyramidal cell types demonstrated different relationships with network oscillation: the IO cells were leaders that were activated early in the population activity cycle while the activation of the NO cell type was distributed across network bursts. The properties of IO neurons disappeared in a low magnesium environment where the voltage-dependence of the receptor is abolished; concurrently, the cellular contribution to network oscillation switched to synchronous firing. Thus, depending upon the efficacy of NMDAR in altering the linearity of the whole-cell current-voltage relationship, the two cell populations played different roles in sustaining network oscillation. PMID:22805058

  20. Persistent current oscillations produced by activation of metabotropic glutamate receptors in immature rat CA3 hippocampal neurons.

    PubMed

    Aniksztejn, L; Sciancalepore, M; Ben Ari, Y; Cherubini, E

    1995-04-01

    1. The single-electrode voltage-clamp technique was used to study the effects of the metabotropic glutamate receptors (mGluRs) agonist 1S,3R-1-aminocyclopentane-1,3-dicarboxylic acid (1S,3R-ACPD, ACPD, 3-10 microM) on CA3 hippocampal neurons during the 1st 10 days of postnatal (P) life and in adulthood. 2. Repeated applications of 1S,3R-ACPD, in the presence of tetrodotoxin (TTX, 1 microM), tetraethylammonium chloride (TEACl 10 mM), and CsCl (2 mM), induced in immature but not in adult neurons periodic inward currents (PICs) that persisted for several hours after the last application of the agonist. 3. PICs, which were generated by nonspecific cationic currents, reversed polarity at 2.8 +/- 3 (SD) mV. They were reversibly blocked by kynurenic acid (1 mM), suggesting that they were mediated by glutamate acting on ionotropic receptors. They were also abolished in a nominally Ca(2+)-free medium. 4. PICs were irreversibly abolished by thapsigargin (10 microM) but were unaffected by ryanodine (10-40 microM). Caffeine (2 mM) also reversibly blocked PICs; this effect was independent from adenosine 3',5'-cyclic monophosphate (cAMP) accumulation, inhibition of voltage-dependent Ca2+ current, or blockade of adenosine receptors. 5. We suggest that, in neonatal slices, mGluRs-induced PICs are triggered by elevation of [Ca2+]i, after mobilization of Ca2+ from inositol 1,4,5-trisphosphate (InsP3)-sensitive stores. This will lead to a persistent, pulsatile release of glutamate from presynaptic nerve terminals, a phenomenon that is probably maintained via a calcium-induced-calcium release process.

  1. Synchronization in slowly switching networks of coupled oscillators

    PubMed Central

    Zhou, Jie; Zou, Yong; Guan, Shuguang; Liu, Zonghua; Boccaletti, S.

    2016-01-01

    Networks whose structure of connections evolves in time constitute a big challenge in the study of synchronization, in particular when the time scales for the evolution of the graph topology are comparable with (or even longer than) those pertinent to the units’ dynamics. We here focus on networks with a slow-switching structure, and show that the necessary conditions for synchronization, i.e. the conditions for which synchronization is locally stable, are determined by the time average of the largest Lyapunov exponents of transverse modes of the switching topologies. Comparison between fast- and slow-switching networks allows elucidating that slow-switching processes prompt synchronization in the cases where the Master Stability Function is concave, whereas fast-switching schemes facilitate synchronization for convex curves. Moreover, the condition of slow-switching enables the introduction of a control strategy for inducing synchronization in networks with arbitrary structure and coupling strength, which is of evident relevance for broad applications in real world systems. PMID:27779253

  2. Synchronization in slowly switching networks of coupled oscillators.

    PubMed

    Zhou, Jie; Zou, Yong; Guan, Shuguang; Liu, Zonghua; Boccaletti, S

    2016-10-25

    Networks whose structure of connections evolves in time constitute a big challenge in the study of synchronization, in particular when the time scales for the evolution of the graph topology are comparable with (or even longer than) those pertinent to the units' dynamics. We here focus on networks with a slow-switching structure, and show that the necessary conditions for synchronization, i.e. the conditions for which synchronization is locally stable, are determined by the time average of the largest Lyapunov exponents of transverse modes of the switching topologies. Comparison between fast- and slow-switching networks allows elucidating that slow-switching processes prompt synchronization in the cases where the Master Stability Function is concave, whereas fast-switching schemes facilitate synchronization for convex curves. Moreover, the condition of slow-switching enables the introduction of a control strategy for inducing synchronization in networks with arbitrary structure and coupling strength, which is of evident relevance for broad applications in real world systems.

  3. Synchronization in slowly switching networks of coupled oscillators

    NASA Astrophysics Data System (ADS)

    Zhou, Jie; Zou, Yong; Guan, Shuguang; Liu, Zonghua; Boccaletti, S.

    2016-10-01

    Networks whose structure of connections evolves in time constitute a big challenge in the study of synchronization, in particular when the time scales for the evolution of the graph topology are comparable with (or even longer than) those pertinent to the units’ dynamics. We here focus on networks with a slow-switching structure, and show that the necessary conditions for synchronization, i.e. the conditions for which synchronization is locally stable, are determined by the time average of the largest Lyapunov exponents of transverse modes of the switching topologies. Comparison between fast- and slow-switching networks allows elucidating that slow-switching processes prompt synchronization in the cases where the Master Stability Function is concave, whereas fast-switching schemes facilitate synchronization for convex curves. Moreover, the condition of slow-switching enables the introduction of a control strategy for inducing synchronization in networks with arbitrary structure and coupling strength, which is of evident relevance for broad applications in real world systems.

  4. 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

  5. The Edge of Stability: Response Times and Delta Oscillations in Balanced Networks

    PubMed Central

    Gillary, Grant; Niebur, Ernst

    2016-01-01

    The standard architecture of neocortex is a network with excitation and inhibition in closely maintained balance. These networks respond fast and with high precision to their inputs and they allow selective amplification of patterned signals. The stability of such networks is known to depend on balancing the strengths of positive and negative feedback. We here show that a second condition is required for stability which depends on the relative strengths and time courses of fast (AMPA) and slow (NMDA) currents in the excitatory projections. This condition also determines the response time of the network. We show that networks which respond quickly to an input are necessarily close to an oscillatory instability which resonates in the delta range. This instability explains the existence of neocortical delta oscillations and the emergence of absence epilepsy. Although cortical delta oscillations are a network-level phenomenon, we show that in non-pathological networks, individual neurons receive sufficient information to keep the network in the fast-response regime without sliding into the instability. PMID:27689361

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

    NASA Astrophysics Data System (ADS)

    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.

  7. 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.

  8. Enriched Encoding: Reward Motivation Organizes Cortical Networks for Hippocampal Detection of Unexpected Events

    PubMed Central

    Murty, Vishnu P.; Adcock, R. Alison

    2014-01-01

    Learning how to obtain rewards requires learning about their contexts and likely causes. How do long-term memory mechanisms balance the need to represent potential determinants of reward outcomes with the computational burden of an over-inclusive memory? One solution would be to enhance memory for salient events that occur during reward anticipation, because all such events are potential determinants of reward. We tested whether reward motivation enhances encoding of salient events like expectancy violations. During functional magnetic resonance imaging, participants performed a reaction-time task in which goal-irrelevant expectancy violations were encountered during states of high- or low-reward motivation. Motivation amplified hippocampal activation to and declarative memory for expectancy violations. Connectivity of the ventral tegmental area (VTA) with medial prefrontal, ventrolateral prefrontal, and visual cortices preceded and predicted this increase in hippocampal sensitivity. These findings elucidate a novel mechanism whereby reward motivation can enhance hippocampus-dependent memory: anticipatory VTA-cortical–hippocampal interactions. Further, the findings integrate literatures on dopaminergic neuromodulation of prefrontal function and hippocampus-dependent memory. We conclude that during reward motivation, VTA modulation induces distributed neural changes that amplify hippocampal signals and records of expectancy violations to improve predictions—a potentially unique contribution of the hippocampus to reward learning. PMID:23529005

  9. Enriched encoding: reward motivation organizes cortical networks for hippocampal detection of unexpected events.

    PubMed

    Murty, Vishnu P; Adcock, R Alison

    2014-08-01

    Learning how to obtain rewards requires learning about their contexts and likely causes. How do long-term memory mechanisms balance the need to represent potential determinants of reward outcomes with the computational burden of an over-inclusive memory? One solution would be to enhance memory for salient events that occur during reward anticipation, because all such events are potential determinants of reward. We tested whether reward motivation enhances encoding of salient events like expectancy violations. During functional magnetic resonance imaging, participants performed a reaction-time task in which goal-irrelevant expectancy violations were encountered during states of high- or low-reward motivation. Motivation amplified hippocampal activation to and declarative memory for expectancy violations. Connectivity of the ventral tegmental area (VTA) with medial prefrontal, ventrolateral prefrontal, and visual cortices preceded and predicted this increase in hippocampal sensitivity. These findings elucidate a novel mechanism whereby reward motivation can enhance hippocampus-dependent memory: anticipatory VTA-cortical-hippocampal interactions. Further, the findings integrate literatures on dopaminergic neuromodulation of prefrontal function and hippocampus-dependent memory. We conclude that during reward motivation, VTA modulation induces distributed neural changes that amplify hippocampal signals and records of expectancy violations to improve predictions-a potentially unique contribution of the hippocampus to reward learning. © The Author 2013. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  10. Pacemaker-driven stochastic resonance on diffusive and complex networks of bistable oscillators

    NASA Astrophysics Data System (ADS)

    Perc, Matjaž; Gosak, Marko

    2008-05-01

    We study the phenomenon of stochastic resonance on diffusive, small-world and scale-free networks consisting of bistable overdamped oscillators. Important thereby is the fact that the external subthreshold periodic forcing is introduced only to a single oscillator of the network. Hence, the forcing acts as a pacemaker trying to impose its rhythm on the whole network through the unit to which it is introduced. Without the addition of additive spatiotemporal noise, however, the whole network, including the unit that is directly exposed to the pacemaker, remains trapped forever in one of the two stable steady states of the local dynamics. We show that the correlation between the frequency of subthreshold pacemaker activity and the response of the network is resonantly dependent on the intensity of additive noise. The reported pacemaker-driven stochastic resonance depends most significantly on the coupling strength and the underlying network structure. Namely, the outreach of the pacemaker obeys the classic diffusion law in the case of nearest-neighbor interactions, thus being proportional to the square root of the coupling strength, whereas it becomes superdiffusive by an appropriate small-world or scale-free topology of the interaction network. In particular, the scale-free topology is identified as being optimal for the dissemination of localized rhythmic activity across the whole network. Also, we show that the ratio between the clustering coefficient and the characteristic path length is the crucial quantity defining the ability of a small-world network to facilitate the outreach of the pacemaker-emitted subthreshold rhythm. We additionally confirm these findings by using the FitzHugh-Nagumo excitable system as an alternative to the bistable overdamped oscillator.

  11. A G-Protein Subunit Translocation Embedded Network Motif Underlies GPCR Regulation of Calcium Oscillations

    PubMed Central

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

    2014-01-01

    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

  12. SYNCHRONIZATION OF HETEROGENEOUS OSCILLATORS UNDER NETWORK MODIFICATIONS: PERTURBATION AND OPTIMIZATION OF THE SYNCHRONY ALIGNMENT FUNCTION.

    PubMed

    Taylor, Dane; Skardal, Per Sebastian; Sun, Jie

    2016-01-01

    Synchronization is central to many complex systems in engineering physics (e.g., the power-grid, Josephson junction circuits, and electro-chemical oscillators) and biology (e.g., neuronal, circadian, and cardiac rhythms). Despite these widespread applications-for which proper functionality depends sensitively on the extent of synchronization-there remains a lack of understanding for how systems can best evolve and adapt to enhance or inhibit synchronization. We study how network modifications affect the synchronization properties of network-coupled dynamical systems that have heterogeneous node dynamics (e.g., phase oscillators with non-identical frequencies), which is often the case for real-world systems. Our approach relies on a synchrony alignment function (SAF) that quantifies the interplay between heterogeneity of the network and of the oscillators and provides an objective measure for a system's ability to synchronize. We conduct a spectral perturbation analysis of the SAF for structural network modifications including the addition and removal of edges, which subsequently ranks the edges according to their importance to synchronization. Based on this analysis, we develop gradient-descent algorithms to efficiently solve optimization problems that aim to maximize phase synchronization via network modifications. We support these and other results with numerical experiments.

  13. SYNCHRONIZATION OF HETEROGENEOUS OSCILLATORS UNDER NETWORK MODIFICATIONS: PERTURBATION AND OPTIMIZATION OF THE SYNCHRONY ALIGNMENT FUNCTION

    PubMed Central

    Taylor, Dane; Skardal, Per Sebastian; Sun, Jie

    2016-01-01

    Synchronization is central to many complex systems in engineering physics (e.g., the power-grid, Josephson junction circuits, and electro-chemical oscillators) and biology (e.g., neuronal, circadian, and cardiac rhythms). Despite these widespread applications—for which proper functionality depends sensitively on the extent of synchronization—there remains a lack of understanding for how systems can best evolve and adapt to enhance or inhibit synchronization. We study how network modifications affect the synchronization properties of network-coupled dynamical systems that have heterogeneous node dynamics (e.g., phase oscillators with non-identical frequencies), which is often the case for real-world systems. Our approach relies on a synchrony alignment function (SAF) that quantifies the interplay between heterogeneity of the network and of the oscillators and provides an objective measure for a system’s ability to synchronize. We conduct a spectral perturbation analysis of the SAF for structural network modifications including the addition and removal of edges, which subsequently ranks the edges according to their importance to synchronization. Based on this analysis, we develop gradient-descent algorithms to efficiently solve optimization problems that aim to maximize phase synchronization via network modifications. We support these and other results with numerical experiments. PMID:27872501

  14. Chimera states in networks of Van der Pol oscillators with hierarchical connectivities.

    PubMed

    Ulonska, Stefan; Omelchenko, Iryna; Zakharova, Anna; Schöll, Eckehard

    2016-09-01

    Chimera states are complex spatio-temporal patterns that consist of coexisting domains of coherent and incoherent dynamics. We analyse chimera states in ring networks of Van der Pol oscillators with hierarchical coupling topology. We investigate the stepwise transition from a nonlocal to a hierarchical topology and propose the network clustering coefficient as a measure to establish a link between the existence of chimera states and the compactness of the initial base pattern of a hierarchical topology; we show that a large clustering coefficient promotes the occurrence of chimeras. Depending on the level of hierarchy and base pattern, we obtain chimera states with different numbers of incoherent domains. We investigate the chimera regimes as a function of coupling strength and nonlinearity parameter of the individual oscillators. The analysis of a network with larger base pattern resulting in larger clustering coefficient reveals two different types of chimera states and highlights the increasing role of amplitude dynamics.

  15. Metastability and chimera states in modular delay and pulse-coupled oscillator networks.

    PubMed

    Wildie, Mark; Shanahan, Murray

    2012-12-01

    Modular networks of delay-coupled and pulse-coupled oscillators are presented, which display both transient (metastable) synchronization dynamics and the formation of a large number of "chimera" states characterized by coexistent synchronized and desynchronized subsystems. We consider networks based on both community and small-world topologies. It is shown through simulation that the metastable behaviour of the system is dependent in all cases on connection delay, and a critical region is found that maximizes indices of both metastability and the prevalence of chimera states. We show dependence of phase coherence in synchronous oscillation on the level and strength of external connectivity between communities, and demonstrate that synchronization dynamics are dependent on the modular structure of the network. The long-term behaviour of the system is considered and the relevance of the model briefly discussed with emphasis on biological and neurobiological systems.

  16. Chimera states in networks of Van der Pol oscillators with hierarchical connectivities

    NASA Astrophysics Data System (ADS)

    Ulonska, Stefan; Omelchenko, Iryna; Zakharova, Anna; Schöll, Eckehard

    2016-09-01

    Chimera states are complex spatio-temporal patterns that consist of coexisting domains of coherent and incoherent dynamics. We analyse chimera states in ring networks of Van der Pol oscillators with hierarchical coupling topology. We investigate the stepwise transition from a nonlocal to a hierarchical topology and propose the network clustering coefficient as a measure to establish a link between the existence of chimera states and the compactness of the initial base pattern of a hierarchical topology; we show that a large clustering coefficient promotes the occurrence of chimeras. Depending on the level of hierarchy and base pattern, we obtain chimera states with different numbers of incoherent domains. We investigate the chimera regimes as a function of coupling strength and nonlinearity parameter of the individual oscillators. The analysis of a network with larger base pattern resulting in larger clustering coefficient reveals two different types of chimera states and highlights the increasing role of amplitude dynamics.

  17. Contributions of intrinsic membrane dynamics to fast network oscillations with irregular neuronal discharges.

    PubMed

    Geisler, Caroline; Brunel, Nicolas; Wang, Xiao-Jing

    2005-12-01

    During fast oscillations in the local field potential (40-100 Hz gamma, 100-200 Hz sharp-wave ripples) single cortical neurons typically fire irregularly at rates that are much lower than the oscillation frequency. Recent computational studies have provided a mathematical description of such fast oscillations, using the leaky integrate-and-fire (LIF) neuron model. Here, we extend this theoretical framework to populations of more realistic Hodgkin-Huxley-type conductance-based neurons. In a noisy network of GABAergic neurons that are connected randomly and sparsely by chemical synapses, coherent oscillations emerge with a frequency that depends sensitively on the single cell's membrane dynamics. The population frequency can be predicted analytically from the synaptic time constants and the preferred phase of discharge during the oscillatory cycle of a single cell subjected to noisy sinusoidal input. The latter depends significantly on the single cell's membrane properties and can be understood in the context of the simplified exponential integrate-and-fire (EIF) neuron. We find that 200-Hz oscillations can be generated, provided the effective input conductance of single cells is large, so that the single neuron's phase shift is sufficiently small. In a two-population network of excitatory pyramidal cells and inhibitory neurons, recurrent excitation can either decrease or increase the population rhythmic frequency, depending on whether in a neuron the excitatory synaptic current follows or precedes the inhibitory synaptic current in an oscillatory cycle. Detailed single-cell properties have a substantial impact on population oscillations, even though rhythmicity does not originate from pacemaker neurons and is an emergent network phenomenon.

  18. Robust autoassociative memory with coupled networks of Kuramoto-type oscillators

    NASA Astrophysics Data System (ADS)

    Heger, Daniel; Krischer, Katharina

    2016-08-01

    Uncertain recognition success, unfavorable scaling of connection complexity, or dependence on complex external input impair the usefulness of current oscillatory neural networks for pattern recognition or restrict technical realizations to small networks. We propose a network architecture of coupled oscillators for pattern recognition which shows none of the mentioned flaws. Furthermore we illustrate the recognition process with simulation results and analyze the dynamics analytically: Possible output patterns are isolated attractors of the system. Additionally, simple criteria for recognition success are derived from a lower bound on the basins of attraction.

  19. Dynamic synchronization of a time-evolving optical network of chaotic oscillators.

    PubMed

    Cohen, Adam B; Ravoori, Bhargava; Sorrentino, Francesco; Murphy, Thomas E; Ott, Edward; Roy, Rajarshi

    2010-12-01

    We present and experimentally demonstrate a technique for achieving and maintaining a global state of identical synchrony of an arbitrary network of chaotic oscillators even when the coupling strengths are unknown and time-varying. At each node an adaptive synchronization algorithm dynamically estimates the current strength of the net coupling signal to that node. We experimentally demonstrate this scheme in a network of three bidirectionally coupled chaotic optoelectronic feedback loops and we present numerical simulations showing its application in larger networks. The stability of the synchronous state for arbitrary coupling topologies is analyzed via a master stability function approach. © 2010 American Institute of Physics.

  20. From mechanical to biological oscillator networks: The role of long range interactions

    NASA Astrophysics Data System (ADS)

    Bountis, T.

    2016-09-01

    The study of one-dimensional particle networks of Classical Mechanics, through Hamiltonian models, has taught us a lot about oscillations of particles coupled to each other by nearest neighbor (short range) interactions. Recently, however, a careful analysis of the role of long range interactions (LRI) has shown that several widely accepted notions concerning chaos and the approach to thermal equilibrium need to be modified, since LRI strongly affects the statistics of certain very interesting, long lasting metastable states. On the other hand, when LRI (in the form of non-local or all-to-all coupling) was introduced in systems of biological oscillators, Kuramoto's theory of synchronization was developed and soon thereafter researchers studied amplitude and phase oscillations in networks of FitzHugh Nagumo and Hindmarsh Rose (HR) neuron models. In these models certain fascinating phenomena called chimera states were discovered where populations of synchronous and asynchronous oscillators are seen to coexist in the same system. Currently, their synchronization properties are being widely investigated in HR mathematical models as well as realistic neural networks, similar to what one finds in simple living organisms like the C.elegans worm.

  1. Phase resetting and transient desynchronization in networks of globally coupled phase oscillators with inertia

    NASA Astrophysics Data System (ADS)

    Dolan, Kevin; Majtanik, Milan; Tass, Peter A.

    2005-11-01

    Recently extensive work has been done towards developing methods for effective desynchronization of globally coupled phase oscillators (the Kuramoto model), by means of short stimulation pulses, or sequences of pulses. This is of great importance for the treatment of neurological disorders like Parkinson’s disease and essential tremor. As a progressive step towards the goal of being able to apply these desynchronization and phase-resetting techniques medically as a form of treatment, we demonstrate here how these ideas can be generalized and applied to a network of two-dimensional phase oscillators with inertia. This model has been previously presented as a simplification of a neuron with an axon and dendrite, and can be used to account for intrinsic transient behavior often seen experimentally. The stimulation techniques originally developed for the Kuramoto model work on a network of globally coupled inertial phase oscillators in a qualitatively similar way. In both cases desynchronization can be achieved when the stimulation causes nearby trajectories to diverge from each other. However, the mechanism by which this divergence of trajectories is achieved, is substantially different for the network of inertial oscillators. In particular, the addition of inertia results in a broad range of transient dynamics not present in the Kuramoto model. Nevertheless, the basic principles of phase resetting and desynchronization still apply. This suggests a robustness of these techniques which is of extreme importance to the medical applications.

  2. 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

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

    PubMed

    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.

  4. Oscillations during observations: Dynamic oscillatory networks serving visuospatial attention.

    PubMed

    Wiesman, Alex I; Heinrichs-Graham, Elizabeth; Proskovec, Amy L; McDermott, Timothy J; Wilson, Tony W

    2017-10-01

    The dynamic allocation of neural resources to discrete features within a visual scene enables us to react quickly and accurately to salient environmental circumstances. A network of bilateral cortical regions is known to subserve such visuospatial attention functions; however the oscillatory and functional connectivity dynamics of information coding within this network are not fully understood. Particularly, the coding of information within prototypical attention-network hubs and the subsecond functional connections formed between these hubs have not been adequately characterized. Herein, we use the precise temporal resolution of magnetoencephalography (MEG) to define spectrally specific functional nodes and connections that underlie the deployment of attention in visual space. Twenty-three healthy young adults completed a visuospatial discrimination task designed to elicit multispectral activity in visual cortex during MEG, and the resulting data were preprocessed and reconstructed in the time-frequency domain. Oscillatory responses were projected to the cortical surface using a beamformer, and time series were extracted from peak voxels to examine their temporal evolution. Dynamic functional connectivity was then computed between nodes within each frequency band of interest. We find that visual attention network nodes are defined functionally by oscillatory frequency, that the allocation of attention to the visual space dynamically modulates functional connectivity between these regions on a millisecond timescale, and that these modulations significantly correlate with performance on a spatial discrimination task. We conclude that functional hubs underlying visuospatial attention are segregated not only anatomically but also by oscillatory frequency, and importantly that these oscillatory signatures promote dynamic communication between these hubs. Hum Brain Mapp 38:5128-5140, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

  5. Synchronization in phase-coupled Kuramoto oscillator networks with axonal delay and synaptic plasticity

    NASA Astrophysics Data System (ADS)

    Timms, L.; English, L. Q.

    2014-03-01

    We explore both analytically and numerically an ensemble of coupled phase oscillators governed by a Kuramoto-type system of differential equations. However, we have included the effects of time delay (due to finite signal-propagation speeds) and network plasticity (via dynamic coupling constants) inspired by the Hebbian learning rule in neuroscience. When time delay and learning effects combine, interesting synchronization phenomena are observed. We investigate the formation of spatiotemporal patterns in both one- and two-dimensional oscillator lattices with periodic boundary conditions and comment on the role of dimensionality.

  6. Frequency adjustment and synchrony in networks of delayed pulse-coupled oscillators

    NASA Astrophysics Data System (ADS)

    Nishimura, Joel

    2015-01-01

    We introduce a system of pulse-coupled oscillators that can change both their phases and frequencies and prove that when there is a separation of time scales between phase and frequency adjustment the system converges to exact synchrony on strongly connected graphs with time delays. The analysis involves decomposing the network into a forest of tree-like structures that capture causality. These results provide a robust method of sensor net synchronization as well as demonstrate a new avenue of possible pulse-coupled oscillator research.

  7. Curing critical links in oscillator networks as power flow models

    NASA Astrophysics Data System (ADS)

    Rohden, Martin; Witthaut, Dirk; Timme, Marc; Meyer-Ortmanns, Hildegard

    2017-01-01

    Modern societies crucially depend on the robust supply with electric energy so that blackouts of power grids can have far reaching consequences. Typically, large scale blackouts take place after a cascade of failures: the failure of a single infrastructure component, such as a critical transmission line, results in several subsequent failures that spread across large parts of the network. Improving the robustness of a network to prevent such secondary failures is thus key for assuring a reliable power supply. In this article we analyze the nonlocal rerouting of power flows after transmission line failures for a simplified AC power grid model and compare different strategies to improve network robustness. We identify critical links in the grid and compute alternative pathways to quantify the grid’s redundant capacity and to find bottlenecks along the pathways. Different strategies are developed and tested to increase transmission capacities to restore stability with respect to transmission line failures. We show that local and nonlocal strategies typically perform alike: one can equally well cure critical links by providing backup capacities locally or by extending the capacities of bottleneck links at remote locations.

  8. Dynamics of thalamo-cortical network oscillations and human perception.

    PubMed

    Ribary, Urs

    2005-01-01

    There is increasing evidence that human cognitive functions can be addressed from a robust neuroscience perspective. In particular, the distributed coherent electrical properties of central neuronal ensembles are considered to be a promising avenue of inquiry concerning global brain functions. The intrinsic oscillatory properties of neurons (Llinás, R. (1988) The intrinsic electrophysiological properties of mammalian neurons: Insights into central nervous system function. Science, 242: 1654-1664), supported by a large variety of voltage-gated ionic conductances are recognized to be the central elements in the generation of the temporal binding required for cognition. Research in neuroscience further indicates that oscillatory activity in the gamma band (25-50 Hz) can be correlated with both sensory acquisition and pre-motor planning, which are non-continuous functions in the time domain. From this perspective, gamma-band activity is viewed as serving a broad temporal binding function, where single-cell oscillators and the conduction time of the intervening pathways support large multicellular thalamo-cortical resonance that is closely linked with cognition and subjective experience. Our working hypothesis is that although dedicated units achieve sensory processing, the cognitive binding process is a common mechanism across modalities. Moreover, it is proposed that such time-dependent binding when altered, will result in modifications of the sensory motor integration that will affect and impair cognition and conscious perception.

  9. Chaotic itinerancy within the coupled dynamics between a physical body and neural oscillator networks.

    PubMed

    Park, Jihoon; Mori, Hiroki; Okuyama, Yuji; Asada, Minoru

    2017-01-01

    Chaotic itinerancy is a phenomenon in which the state of a nonlinear dynamical system spontaneously explores and attracts certain states in a state space. From this perspective, the diverse behavior of animals and its spontaneous transitions lead to a complex coupled dynamical system, including a physical body and a brain. Herein, a series of simulations using different types of non-linear oscillator networks (i.e., regular, small-world, scale-free, random) with a musculoskeletal model (i.e., a snake-like robot) as a physical body are conducted to understand how the chaotic itinerancy of bodily behavior emerges from the coupled dynamics between the body and the brain. A behavior analysis (behavior clustering) and network analysis for the classified behavior are then applied. The former consists of feature vector extraction from the motions and classification of the movement patterns that emerged from the coupled dynamics. The network structures behind the classified movement patterns are revealed by estimating the "information networks" different from the given non-linear oscillator networks based on the transfer entropy which finds the information flow among neurons. The experimental results show that: (1) the number of movement patterns and their duration depend on the sensor ratio to control the balance of strength between the body and the brain dynamics and on the type of the given non-linear oscillator networks; and (2) two kinds of information networks are found behind two kinds movement patterns with different durations by utilizing the complex network measures, clustering coefficient and the shortest path length with a negative and a positive relationship with the duration periods of movement patterns. The current results seem promising for a future extension of the method to a more complicated body and environment. Several requirements are also discussed.

  10. 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

  11. Stimulus statistics shape oscillations in nonlinear recurrent neural networks.

    PubMed

    Lefebvre, Jérémie; Hutt, Axel; Knebel, Jean-François; Whittingstall, Kevin; Murray, Micah M

    2015-02-18

    Rhythmic activity plays a central role in neural computations and brain functions ranging from homeostasis to attention, as well as in neurological and neuropsychiatric disorders. Despite this pervasiveness, little is known about the mechanisms whereby the frequency and power of oscillatory activity are modulated, and how they reflect the inputs received by neurons. Numerous studies have reported input-dependent fluctuations in peak frequency and power (as well as couplings across these features). However, it remains unresolved what mediates these spectral shifts among neural populations. Extending previous findings regarding stochastic nonlinear systems and experimental observations, we provide analytical insights regarding oscillatory responses of neural populations to stimulation from either endogenous or exogenous origins. Using a deceptively simple yet sparse and randomly connected network of neurons, we show how spiking inputs can reliably modulate the peak frequency and power expressed by synchronous neural populations without any changes in circuitry. Our results reveal that a generic, non-nonlinear and input-induced mechanism can robustly mediate these spectral fluctuations, and thus provide a framework in which inputs to the neurons bidirectionally regulate both the frequency and power expressed by synchronous populations. Theoretical and computational analysis of the ensuing spectral fluctuations was found to reflect the underlying dynamics of the input stimuli driving the neurons. Our results provide insights regarding a generic mechanism supporting spectral transitions observed across cortical networks and spanning multiple frequency bands.

  12. 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

  13. Hermite Functional Link Neural Network for Solving the Van der Pol-Duffing Oscillator Equation.

    PubMed

    Mall, Susmita; Chakraverty, S

    2016-08-01

    Hermite polynomial-based functional link artificial neural network (FLANN) is proposed here to solve the Van der Pol-Duffing oscillator equation. A single-layer hermite neural network (HeNN) model is used, where a hidden layer is replaced by expansion block of input pattern using Hermite orthogonal polynomials. A feedforward neural network model with the unsupervised error backpropagation principle is used for modifying the network parameters and minimizing the computed error function. The Van der Pol-Duffing and Duffing oscillator equations may not be solved exactly. Here, approximate solutions of these types of equations have been obtained by applying the HeNN model for the first time. Three mathematical example problems and two real-life application problems of Van der Pol-Duffing oscillator equation, extracting the features of early mechanical failure signal and weak signal detection problems, are solved using the proposed HeNN method. HeNN approximate solutions have been compared with results obtained by the well known Runge-Kutta method. Computed results are depicted in term of graphs. After training the HeNN model, we may use it as a black box to get numerical results at any arbitrary point in the domain. Thus, the proposed HeNN method is efficient. The results reveal that this method is reliable and can be applied to other nonlinear problems too.

  14. Symmetry effects on naturally arising chimera states in mechanical oscillator networks

    NASA Astrophysics Data System (ADS)

    Blaha, Karen; Burrus, Ryan J.; Orozco-Mora, Jorge L.; Ruiz-Beltrán, Elvia; Siddique, Abu B.; Hatamipour, V. D.; Sorrentino, Francesco

    2016-11-01

    Coupled oscillators were believed to exclusively exist in a state of synchrony or disorder until Kuramoto theoretically proved that the two states could coexist, called a chimera state, when portions of the population had a spatial dependent coupling. Recent work has demonstrated the spontaneous emergence of chimera states in an experiment involving mechanical oscillators coupled through a two platform swing. We constructed an experimental apparatus with three platforms that each contains a population of mechanical oscillators in order investigate the effects of a network symmetry on naturally arising chimera states. We considered in more detail the case of 15 metronomes per platform and observed that chimera states emerged as a broad range of parameters, namely, the metronomes' nominal frequency and the coupling strength between the platforms. A scalability study shows that chimera states no longer arise when the population size is reduced to three metronomes per platform. Furthermore, many chimera states are seen in the system when the coupling between platforms is asymmetric.

  15. Symmetry effects on naturally arising chimera states in mechanical oscillator networks.

    PubMed

    Blaha, Karen; Burrus, Ryan J; Orozco-Mora, Jorge L; Ruiz-Beltrán, Elvia; Siddique, Abu B; Hatamipour, V D; Sorrentino, Francesco

    2016-11-01

    Coupled oscillators were believed to exclusively exist in a state of synchrony or disorder until Kuramoto theoretically proved that the two states could coexist, called a chimera state, when portions of the population had a spatial dependent coupling. Recent work has demonstrated the spontaneous emergence of chimera states in an experiment involving mechanical oscillators coupled through a two platform swing. We constructed an experimental apparatus with three platforms that each contains a population of mechanical oscillators in order investigate the effects of a network symmetry on naturally arising chimera states. We considered in more detail the case of 15 metronomes per platform and observed that chimera states emerged as a broad range of parameters, namely, the metronomes' nominal frequency and the coupling strength between the platforms. A scalability study shows that chimera states no longer arise when the population size is reduced to three metronomes per platform. Furthermore, many chimera states are seen in the system when the coupling between platforms is asymmetric.

  16. 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

  17. Temporal organization of GABAergic interneurons in the intermediate CA1 hippocampus during network oscillations.

    PubMed

    Forro, Thomas; Valenti, Ornella; Lasztoczi, Balint; Klausberger, Thomas

    2015-05-01

    Travelling theta oscillations and sharp wave-associated ripples (SWRs) provide temporal structures to neural activity in the CA1 hippocampus. The contribution of rhythm-generating GABAergic interneurons to network timing across the septotemporal CA1 axis remains unknown. We recorded the spike-timing of identified parvalbumin (PV)-expressing basket, axo-axonic, oriens-lacunosum moleculare (O-LM) interneurons, and pyramidal cells in the intermediate CA1 (iCA1) of anesthetized rats in relation to simultaneously detected network oscillations in iCA1 and dorsal CA1 (dCA1). Distinct interneuron types were coupled differentially to SWR, and the majority of iCA1 SWR events occurred simultaneously with dCA1 SWR events. In contrast, iCA1 theta oscillations were shifted in time relative to dCA1 theta oscillations. During theta cycles, the highest firing of iCA1 axo-axonic cells was followed by PV-expressing basket cells and subsequently by O-LM together with pyramidal cells, similar to the firing sequence of dCA1 cell types reported previously. However, we observed that this temporal organization of cell types is shifted in time between dCA1 and iCA1, together with the respective shift in theta oscillations. We show that GABAergic activity can be synchronized during SWR but is shifted in time from dCA1 to iCA1 during theta oscillations, highlighting the flexible inhibitory control of excitatory activity across a brain structure.

  18. Representation of time-varying stimuli by a network exhibiting oscillations on a faster time scale.

    PubMed

    Shamir, Maoz; Ghitza, Oded; Epstein, Steven; Kopell, Nancy

    2009-05-01

    Sensory processing is associated with gamma frequency oscillations (30-80 Hz) in sensory cortices. This raises the question whether gamma oscillations can be directly involved in the representation of time-varying stimuli, including stimuli whose time scale is longer than a gamma cycle. We are interested in the ability of the system to reliably distinguish different stimuli while being robust to stimulus variations such as uniform time-warp. We address this issue with a dynamical model of spiking neurons and study the response to an asymmetric sawtooth input current over a range of shape parameters. These parameters describe how fast the input current rises and falls in time. Our network consists of inhibitory and excitatory populations that are sufficient for generating oscillations in the gamma range. The oscillations period is about one-third of the stimulus duration. Embedded in this network is a subpopulation of excitatory cells that respond to the sawtooth stimulus and a subpopulation of cells that respond to an onset cue. The intrinsic gamma oscillations generate a temporally sparse code for the external stimuli. In this code, an excitatory cell may fire a single spike during a gamma cycle, depending on its tuning properties and on the temporal structure of the specific input; the identity of the stimulus is coded by the list of excitatory cells that fire during each cycle. We quantify the properties of this representation in a series of simulations and show that the sparseness of the code makes it robust to uniform warping of the time scale. We find that resetting of the oscillation phase at stimulus onset is important for a reliable representation of the stimulus and that there is a tradeoff between the resolution of the neural representation of the stimulus and robustness to time-warp.

  19. Representation of Time-Varying Stimuli by a Network Exhibiting Oscillations on a Faster Time Scale

    PubMed Central

    Shamir, Maoz; Ghitza, Oded; Epstein, Steven; Kopell, Nancy

    2009-01-01

    Sensory processing is associated with gamma frequency oscillations (30–80 Hz) in sensory cortices. This raises the question whether gamma oscillations can be directly involved in the representation of time-varying stimuli, including stimuli whose time scale is longer than a gamma cycle. We are interested in the ability of the system to reliably distinguish different stimuli while being robust to stimulus variations such as uniform time-warp. We address this issue with a dynamical model of spiking neurons and study the response to an asymmetric sawtooth input current over a range of shape parameters. These parameters describe how fast the input current rises and falls in time. Our network consists of inhibitory and excitatory populations that are sufficient for generating oscillations in the gamma range. The oscillations period is about one-third of the stimulus duration. Embedded in this network is a subpopulation of excitatory cells that respond to the sawtooth stimulus and a subpopulation of cells that respond to an onset cue. The intrinsic gamma oscillations generate a temporally sparse code for the external stimuli. In this code, an excitatory cell may fire a single spike during a gamma cycle, depending on its tuning properties and on the temporal structure of the specific input; the identity of the stimulus is coded by the list of excitatory cells that fire during each cycle. We quantify the properties of this representation in a series of simulations and show that the sparseness of the code makes it robust to uniform warping of the time scale. We find that resetting of the oscillation phase at stimulus onset is important for a reliable representation of the stimulus and that there is a tradeoff between the resolution of the neural representation of the stimulus and robustness to time-warp. PMID:19412531

  20. Characterization of voltage-gated K+ currents contributing to subthreshold membrane potential oscillations in hippocampal CA1 interneurons.

    PubMed

    Morin, France; Haufler, Darrell; Skinner, Frances K; Lacaille, Jean-Claude

    2010-06-01

    CA1 inhibitory interneurons at the stratum lacunosum-moleculare and radiatum junction (LM/RAD-INs) display subthreshold membrane potential oscillations (MPOs) involving voltage-dependent Na(+) and A-type K(+) currents. LM/RAD-INs also express other voltage-gated K(+) currents, although their properties and role in MPOs remain unclear. Here, we characterized these voltage-gated K(+) currents and investigated their role in MPOs. Using outside-out patch recordings from LM/RAD-IN somata, we distinguished four voltage-gated K(+) currents based on their pharmacology and activation/inactivation properties: a fast delayed rectifier current (I(Kfast)), a slow delayed rectifier current (I(Kslow)), a rapidly inactivating A-type current (I(A)), and a slowly inactivating current (I(D)). Their relative contribution to the total K(+) current was I(A) > I(Kfast) > I(Kslow) = I(D). The presence of I(D) and the relative contributions of K(+) currents in LM/RAD-INs are different from those of other CA1 interneurons, suggesting the presence of differential complement of K(+) currents in subgroups of interneurons. We next determined whether these K(+) currents were sufficient for MPO generation using a single-compartment model of LM/RAD-INs. The model captured the subthreshold voltage dependence of MPOs. Moreover, all K(+) currents were active at subthreshold potentials but I(D), I(A), and the persistent sodium current (I(NaP)) were most active near threshold. Using impedance analysis, we found that I(A) and I(NaP) contribute to MPO generation by modulating peak spectral frequency during MPOs and governing the voltage range over which MPOs occur. Our findings uncover a differential expression of a complement of K(+) channels that underlies intrinsic rhythmic activity in inhibitory interneurons.

  1. Chaotic itinerancy within the coupled dynamics between a physical body and neural oscillator networks

    PubMed Central

    Mori, Hiroki; Okuyama, Yuji; Asada, Minoru

    2017-01-01

    Chaotic itinerancy is a phenomenon in which the state of a nonlinear dynamical system spontaneously explores and attracts certain states in a state space. From this perspective, the diverse behavior of animals and its spontaneous transitions lead to a complex coupled dynamical system, including a physical body and a brain. Herein, a series of simulations using different types of non-linear oscillator networks (i.e., regular, small-world, scale-free, random) with a musculoskeletal model (i.e., a snake-like robot) as a physical body are conducted to understand how the chaotic itinerancy of bodily behavior emerges from the coupled dynamics between the body and the brain. A behavior analysis (behavior clustering) and network analysis for the classified behavior are then applied. The former consists of feature vector extraction from the motions and classification of the movement patterns that emerged from the coupled dynamics. The network structures behind the classified movement patterns are revealed by estimating the “information networks” different from the given non-linear oscillator networks based on the transfer entropy which finds the information flow among neurons. The experimental results show that: (1) the number of movement patterns and their duration depend on the sensor ratio to control the balance of strength between the body and the brain dynamics and on the type of the given non-linear oscillator networks; and (2) two kinds of information networks are found behind two kinds movement patterns with different durations by utilizing the complex network measures, clustering coefficient and the shortest path length with a negative and a positive relationship with the duration periods of movement patterns. The current results seem promising for a future extension of the method to a more complicated body and environment. Several requirements are also discussed. PMID:28796797

  2. Inducing isolated-desynchronization states in complex network of coupled chaotic oscillators

    NASA Astrophysics Data System (ADS)

    Lin, Weijie; Li, Huiyan; Ying, Heping; Wang, Xingang

    2016-12-01

    In a recent study about chaos synchronization in complex networks [Nat. Commun. 5, 4079 (2014), 10.1038/ncomms5079], it is shown that a stable synchronous cluster may coexist with vast asynchronous nodes, resembling the phenomenon of a chimera state observed in a regular network of coupled periodic oscillators. Although of practical significance, this new type of state, namely, the isolated-desynchronization state, is hardly observed in practice due to its strict requirements on the network topology. Here, by the strategy of pinning coupling, we propose an effective method for inducing isolated-desynchronization states in symmetric networks of coupled chaotic oscillators. Theoretical analysis based on eigenvalue analysis shows that, by pinning a group of symmetric nodes in the network, there exists a critical pinning strength beyond which the group of pinned nodes can completely be synchronized while the unpinned nodes remain asynchronous. The feasibility and efficiency of the control method are verified by numerical simulations of both artificial and real-world complex networks with the numerical results in good agreement with the theoretical predictions.

  3. 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.

  4. Metastability and Inter-Band Frequency Modulation in Networks of Oscillating Spiking Neuron Populations

    PubMed Central

    Bhowmik, David; Shanahan, Murray

    2013-01-01

    Groups of neurons firing synchronously are hypothesized to underlie many cognitive functions such as attention, associative learning, memory, and sensory selection. Recent theories suggest that transient periods of synchronization and desynchronization provide a mechanism for dynamically integrating and forming coalitions of functionally related neural areas, and that at these times conditions are optimal for information transfer. Oscillating neural populations display a great amount of spectral complexity, with several rhythms temporally coexisting in different structures and interacting with each other. This paper explores inter-band frequency modulation between neural oscillators using models of quadratic integrate-and-fire neurons and Hodgkin-Huxley neurons. We vary the structural connectivity in a network of neural oscillators, assess the spectral complexity, and correlate the inter-band frequency modulation. We contrast this correlation against measures of metastable coalition entropy and synchrony. Our results show that oscillations in different neural populations modulate each other so as to change frequency, and that the interaction of these fluctuating frequencies in the network as a whole is able to drive different neural populations towards episodes of synchrony. Further to this, we locate an area in the connectivity space in which the system directs itself in this way so as to explore a large repertoire of synchronous coalitions. We suggest that such dynamics facilitate versatile exploration, integration, and communication between functionally related neural areas, and thereby supports sophisticated cognitive processing in the brain. PMID:23614040

  5. Metastability and inter-band frequency modulation in networks of oscillating spiking neuron populations.

    PubMed

    Bhowmik, David; Shanahan, Murray

    2013-01-01

    Groups of neurons firing synchronously are hypothesized to underlie many cognitive functions such as attention, associative learning, memory, and sensory selection. Recent theories suggest that transient periods of synchronization and desynchronization provide a mechanism for dynamically integrating and forming coalitions of functionally related neural areas, and that at these times conditions are optimal for information transfer. Oscillating neural populations display a great amount of spectral complexity, with several rhythms temporally coexisting in different structures and interacting with each other. This paper explores inter-band frequency modulation between neural oscillators using models of quadratic integrate-and-fire neurons and Hodgkin-Huxley neurons. We vary the structural connectivity in a network of neural oscillators, assess the spectral complexity, and correlate the inter-band frequency modulation. We contrast this correlation against measures of metastable coalition entropy and synchrony. Our results show that oscillations in different neural populations modulate each other so as to change frequency, and that the interaction of these fluctuating frequencies in the network as a whole is able to drive different neural populations towards episodes of synchrony. Further to this, we locate an area in the connectivity space in which the system directs itself in this way so as to explore a large repertoire of synchronous coalitions. We suggest that such dynamics facilitate versatile exploration, integration, and communication between functionally related neural areas, and thereby supports sophisticated cognitive processing in the brain.

  6. Optimal phase synchronization in networks of phase-coherent chaotic oscillators

    NASA Astrophysics Data System (ADS)

    Skardal, P. S.; Sevilla-Escoboza, R.; Vera-Ávila, V. P.; Buldú, J. M.

    2017-01-01

    We investigate the existence of an optimal interplay between the natural frequencies of a group of chaotic oscillators and the topological properties of the network they are embedded in. We identify the conditions for achieving phase synchronization in the most effective way, i.e., with the lowest possible coupling strength. Specifically, we show by means of numerical and experimental results that it is possible to define a synchrony alignment function J (ω ,L ) linking the natural frequencies ωi of a set of non-identical phase-coherent chaotic oscillators with the topology of the Laplacian matrix L, the latter accounting for the specific organization of the network of interactions between oscillators. We use the classical Rössler system to show that the synchrony alignment function obtained for phase oscillators can be extended to phase-coherent chaotic systems. Finally, we carry out a series of experiments with nonlinear electronic circuits to show the robustness of the theoretical predictions despite the intrinsic noise and parameter mismatch of the electronic components.

  7. Optimal phase synchronization in networks of phase-coherent chaotic oscillators.

    PubMed

    Skardal, P S; Sevilla-Escoboza, R; Vera-Ávila, V P; Buldú, J M

    2017-01-01

    We investigate the existence of an optimal interplay between the natural frequencies of a group of chaotic oscillators and the topological properties of the network they are embedded in. We identify the conditions for achieving phase synchronization in the most effective way, i.e., with the lowest possible coupling strength. Specifically, we show by means of numerical and experimental results that it is possible to define a synchrony alignment function J(ω,L) linking the natural frequencies ωi of a set of non-identical phase-coherent chaotic oscillators with the topology of the Laplacian matrix L, the latter accounting for the specific organization of the network of interactions between oscillators. We use the classical Rössler system to show that the synchrony alignment function obtained for phase oscillators can be extended to phase-coherent chaotic systems. Finally, we carry out a series of experiments with nonlinear electronic circuits to show the robustness of the theoretical predictions despite the intrinsic noise and parameter mismatch of the electronic components.

  8. Network mechanisms of spindle-burst oscillations in the neonatal rat barrel cortex in vivo.

    PubMed

    Minlebaev, Marat; Ben-Ari, Yehezkel; Khazipov, Rustem

    2007-01-01

    Early in development, cortical networks generate particular patterns of activity that participate in cortical development. The dominant pattern of electrical activity in the neonatal rat neocortex in vivo is a spatially confined spindle-burst. Here, we studied network mechanisms of generation of spindle-bursts in the barrel cortex of neonatal rats using a superfused cortex preparation in vivo. Both spontaneous and sensory-evoked spindle-bursts were present in the superfused barrel cortex. Pharmacological analysis revealed that spindle-bursts are driven by glutamatergic synapses with a major contribution of AMPA/kainate receptors, but slight participation of NMDA receptors and gap junctions. Although GABAergic synapses contributed minimally to the pacing the rhythm of spindle-burst oscillations, surround GABAergic inhibition appeared to be crucial for their compartmentalization. We propose that local spindle-burst oscillations, driven by glutamatergic synapses and spatially confined by GABAergic synapses, contribute to the development of barrel cortex during the critical period of developmental plasticity.

  9. Dynamic transitions among multiple oscillators of synchronized bursts in cultured neural networks

    NASA Astrophysics Data System (ADS)

    Hoan Kim, June; Heo, Ryoun; Choi, Joon Ho; Lee, Kyoung J.

    2014-04-01

    Synchronized neural bursts are a salient dynamic feature of biological neural networks, having important roles in brain functions. This report investigates the deterministic nature behind seemingly random temporal sequences of inter-burst intervals generated by cultured networks of cortical cells. We found that the complex sequences were an intricate patchwork of several noisy ‘burst oscillators’, whose periods covered a wide dynamic range, from a few tens of milliseconds to tens of seconds. The transition from one type of oscillator to another favored a particular passage, while the dwelling time between two neighboring transitions followed an exponential distribution showing no memory. With different amounts of bicuculline or picrotoxin application, we could also terminate the oscillators, generate new ones or tune their periods.

  10. Partial Synchronization in Pulse-Coupled Oscillator Networks I: Theory

    NASA Astrophysics Data System (ADS)

    Engelbrecht, Jan; Chen, Bolun; Mirollo, Renato

    We study N identical integrate and fire model neurons coupled in an all to all network through α-function pulses, weighted by a parameter K. Studies of the dynamics of this system often focus on the stability of the fully synchronous and the fully asynchronous splay states, that naturally depend on the sign of K, i.e. excitation vs inhibition. We find that for finite N there is a rich set of other partially synchronized attractors, such as (N - 1 , 1) fixed states and partially synchronized splay states. Our framework exploits the neutrality of the dynamics for K = 0 which allows us to implement a dimensional reduction strategy that replaces the discrete pulses with a continuous flow, with the sign of K determining the flow direction. This framework naturally incorporates a hierarchy of partially synchronized subspaces in which the new states lie. For N = 2 , 3 , 4 , we completely describe the sequence of bifurcations and the stability of all fixed points and limit cycles. Work Supported by NSF DMS 1413020.

  11. Basin stability for burst synchronization in small-world networks of chaotic slow-fast oscillators

    NASA Astrophysics Data System (ADS)

    Maslennikov, Oleg V.; Nekorkin, Vladimir I.; Kurths, Jürgen

    2015-10-01

    The impact of connectivity and individual dynamics on the basin stability of the burst synchronization regime in small-world networks consisting of chaotic slow-fast oscillators is studied. It is shown that there are rewiring probabilities corresponding to the largest basin stabilities, which uncovers a reason for finding small-world topologies in real neuronal networks. The impact of coupling density and strength as well as the nodal parameters of relaxation or excitability are studied. Dynamic mechanisms are uncovered that most strongly influence basin stability of the burst synchronization regime.

  12. Programming an in vitro DNA oscillator using a molecular networking strategy.

    PubMed

    Montagne, Kevin; Plasson, Raphael; Sakai, Yasuyuki; Fujii, Teruo; Rondelez, Yannick

    2011-02-01

    Living organisms perform and control complex behaviours by using webs of chemical reactions organized in precise networks. This powerful system concept, which is at the very core of biology, has recently become a new foundation for bioengineering. Remarkably, however, it is still extremely difficult to rationally create such network architectures in artificial, non-living and well-controlled settings. We introduce here a method for such a purpose, on the basis of standard DNA biochemistry. This approach is demonstrated by assembling de novo an efficient chemical oscillator: we encode the wiring of the corresponding network in the sequence of small DNA templates and obtain the predicted dynamics. Our results show that the rational cascading of standard elements opens the possibility to implement complex behaviours in vitro. Because of the simple and well-controlled environment, the corresponding chemical network is easily amenable to quantitative mathematical analysis. These synthetic systems may thus accelerate our understanding of the underlying principles of biological dynamic modules.

  13. Synchronization, diversity, and topology of networks of integrate and fire oscillators

    PubMed

    Guardiola; Diaz-Guilera; Llas; Perez

    2000-10-01

    We study synchronization dynamics of a population of pulse-coupled oscillators. In particular, we focus our attention on the interplay between topological disorder and synchronization features of networks. First, we analyze synchronization time T in random networks, and find a scaling law which relates T to network connectivity. Then, we compare synchronization time for several other topological configurations, characterized by a different degree of randomness. The analysis shows that regular lattices perform better than a disordered network. This fact can be understood by considering the variability in the number of links between two adjacent neighbors. This phenomenon is equivalent to having a nonrandom topology with a distribution of interactions and it can be removed by an adequate local normalization of the couplings.

  14. Medial temporal lobe structures and hippocampal subfields in psychotic disorders: findings from the Bipolar-Schizophrenia Network on Intermediate Phenotypes (B-SNIP) study.

    PubMed

    Mathew, Ian; Gardin, Tova M; Tandon, Neeraj; Eack, Shaun; Francis, Alan N; Seidman, Larry J; Clementz, Brett; Pearlson, Godfrey D; Sweeney, John A; Tamminga, Carol A; Keshavan, Matcheri S

    2014-07-01

    Structural alterations in the hippocampus and other medial temporal lobe regions have been observed in schizophrenia. How these alterations and hippocampal subfields might differ across the psychosis spectrum remains unclear. To characterize medial temporal lobe structures, including hippocampal subfields, using magnetic resonance imaging and to examine their relation to psychosis and cognitive function across the psychosis spectrum. Case-control, cross-sectional neuroimaging study in a large series of probands with psychotic disorders and healthy volunteers as part of the Bipolar-Schizophrenia Network on Intermediate Phenotypes (B-SNIP). Patients with psychotic disorders (schizophrenia, n = 219; schizoaffective disorder, n = 142; and psychotic bipolar disorder, n = 188) and healthy controls (n = 337) were recruited across ambulatory clinics at university health centers in the B-SNIP consortium. Medial temporal lobe and hippocampal subfields were quantified with an automated parcellation approach using FreeSurfer software. Memory and other cognitive parameters were assessed using standardized neuropsychological tests. Hippocampal volume reductions were seen in all 3 diagnostic groups when compared with healthy controls; alterations in the entorhinal cortex and parahippocampal regions were limited to schizophrenia and schizoaffective disorders (P < .001). Smaller volumes across the hippocampal subfields were seen in all 3 psychotic disorders, with the most prominent differences being in cornu ammonis 2/3 (P < .001). Hippocampal volumes were positively correlated with psychosis severity, declarative memory, and overall cognitive performance (P < .05). Alterations in the hippocampus were evident across psychotic disorders. Hippocampal subfields that participate in memory-related processes supporting pattern separation and pattern completion might be abnormal and may underlie the pathophysiology of psychosis.

  15. Two Distinct Actin Networks Mediate Traction Oscillations to Confer Focal Adhesion Mechanosensing.

    PubMed

    Wu, Zhanghan; Plotnikov, Sergey V; Moalim, Abdiwahab Y; Waterman, Clare M; Liu, Jian

    2017-02-28

    Focal adhesions (FAs) are integrin-based transmembrane assemblies that connect a cell to its extracellular matrix (ECM). They are mechanosensors through which cells exert actin cytoskeleton-mediated traction forces to sense the ECM stiffness. Interestingly, FAs themselves are dynamic structures that adapt their growth in response to mechanical force. It is unclear how the cell manages the plasticity of the FA structure and the associated traction force to accurately sense ECM stiffness. Strikingly, FA traction forces oscillate in time and space, and govern the cell mechanosensing of ECM stiffness. However, precisely how and why the FA traction oscillates is unknown. We developed a model of FA growth that integrates the contributions of the branched actin network and stress fibers (SFs). Using the model in combination with experimental tests, we show that the retrograde flux of the branched actin network promotes the proximal growth of the FA and contributes to a traction peak near the FA's distal tip. The resulting traction gradient within the growing FA favors SF formation near the FA's proximal end. The SF-mediated actomyosin contractility further stabilizes the FA and generates a second traction peak near the center of the FA. Formin-mediated SF elongation negatively feeds back with actomyosin contractility, resulting in central traction peak oscillation. This underpins the observed FA traction oscillation and, importantly, broadens the ECM stiffness range over which FAs can accurately adapt to traction force generation. Actin cytoskeleton-mediated FA growth and maturation thus culminate with FA traction oscillation to drive efficient FA mechanosensing. Published by Elsevier Inc.

  16. 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

  17. 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

  18. Long-period oscillations of sunspot magnetic fields by simultaneous observations of the Global Oscillation Network Group and Solar and Heliospheric Observatory/Michelson Doppler imager

    NASA Astrophysics Data System (ADS)

    Efremov, V. I.; Parfinenko, L. D.; Solov'ev, A. A.; Riehokainen, A.

    2016-12-01

    For the first time, the ultra-low oscillation mode of the sunspot magnetic field strength has been detected with a high degree of confidence by ground-based observations of sunspots with the Global Oscillation Network Group (GONG) network of telescopes. Synchronous series of magnetograms derived from the GONG and Solar and Heliospheric Observatory/Michelson Doppler Imager (SOHO/MDI) have been processed. They were obtained on September 27-30, 2010, for the active region NOAA 11109 with a total duration of 80 h. The periods of magnetic field oscillations found by space data coincide with the periods defined with GONG. This confirms the physical reality of the oscillatory process. The power spectrum contains harmonics with periods of 26 h, 8-10 h, and 3-4 h.

  19. Role of local network oscillations in resting-state functional connectivity.

    PubMed

    Cabral, Joana; Hugues, Etienne; Sporns, Olaf; Deco, Gustavo

    2011-07-01

    Spatio-temporally organized low-frequency fluctuations (<0.1 Hz), observed in BOLD fMRI signal during rest, suggest the existence of underlying network dynamics that emerge spontaneously from intrinsic brain processes. Furthermore, significant correlations between distinct anatomical regions-or functional connectivity (FC)-have led to the identification of several widely distributed resting-state networks (RSNs). This slow dynamics seems to be highly structured by anatomical connectivity but the mechanism behind it and its relationship with neural activity, particularly in the gamma frequency range, remains largely unknown. Indeed, direct measurements of neuronal activity have revealed similar large-scale correlations, particularly in slow power fluctuations of local field potential gamma frequency range oscillations. To address these questions, we investigated neural dynamics in a large-scale model of the human brain's neural activity. A key ingredient of the model was a structural brain network defined by empirically derived long-range brain connectivity together with the corresponding conduction delays. A neural population, assumed to spontaneously oscillate in the gamma frequency range, was placed at each network node. When these oscillatory units are integrated in the network, they behave as weakly coupled oscillators. The time-delayed interaction between nodes is described by the Kuramoto model of phase oscillators, a biologically-based model of coupled oscillatory systems. For a realistic setting of axonal conduction speed, we show that time-delayed network interaction leads to the emergence of slow neural activity fluctuations, whose patterns correlate significantly with the empirically measured FC. The best agreement of the simulated FC with the empirically measured FC is found for a set of parameters where subsets of nodes tend to synchronize although the network is not globally synchronized. Inside such clusters, the simulated BOLD signal between nodes

  20. Neural oscillation, network, eloquent cortex and epileptogenic zone revealed by magnetoencephalography and awake craniotomy

    PubMed Central

    Idris, Zamzuri; Kandasamy, Regunath; Reza, Faruque; Abdullah, Jafri M.

    2014-01-01

    Background: Magnetoencephalography (MEG) is a method of functional neuroimaging. The concomitant use of MEG and electrocorticography has been found to be useful in elucidating neural oscillation and network, and to localize epileptogenic zone and functional cortex. We describe our early experience using MEG in neurosurgical patients, emphasizing on its impact on patient management as well as the enrichment of our knowledge in neurosciences. Materials and Methods: A total of 10 subjects were included; five patients had intraaxial tumors, one with an extraaxial tumor and brain compression, two with arteriovenous malformations, one with cerebral peduncle hemorrhage and one with sensorimotor cortical dysplasia. All patients underwent evoked and spontaneous MEG recordings. MEG data was processed at band-pass filtering frequency of between 0.1 and 300 Hz with a sampling rate of 1 kHz. MEG source localization was performed using either overdetermined equivalent current dipoles or underdetermined inversed solution. Neuromag collection of events software was used to study brain network and epileptogenic zone. The studied data were analyzed for neural oscillation in three patients; brain network and clinical manifestation in five patients; and for the location of epileptogenic zone and eloquent cortex in two patients. Results: We elucidated neural oscillation in three patients. One demonstrated oscillatory phenomenon on stimulation of the motor-cortex during awake surgery, and two had improvement in neural oscillatory parameters after surgery. Brain networks corresponding to clinico-anatomical relationships were depicted in five patients, and two networks were illustrated here. Finally, we demonstrated epilepsy cases in which MEG data was found to be useful in localizing the epileptogenic zones and functional cortices. Conclusion: The application of MEG while enhancing our knowledge in neurosciences also has a useful role in epilepsy and awake surgery. PMID:25685205

  1. Implication of the Slow-5 Oscillations in the Disruption of the Default-Mode Network in Healthy Aging and Stroke

    PubMed Central

    Nair, Veena A.; Mossahebi, Pouria; Young, Brittany M.; Chacon, Marcus; Jensen, Matthew; Birn, Rasmus M.; Meyerand, Mary E.; Prabhakaran, Vivek

    2016-01-01

    Abstract The processes of normal aging and aging-related pathologies subject the brain to an active re-organization of its brain networks. Among these, the default-mode network (DMN) is consistently implicated with a demonstrated reduction in functional connectivity within the network. However, no clear stipulation on the underlying mechanisms of the de-synchronization has yet been provided. In this study, we examined the spectral distribution of the intrinsic low-frequency oscillations (LFOs) of the DMN sub-networks in populations of young normals, older subjects, and acute and subacute ischemic stroke patients. The DMN sub-networks were derived using a mid-order group independent component analysis with 117 eyes-closed resting-state functional magnetic resonance imaging (rs-fMRI) sessions from volunteers in those population groups, isolating three robust components of the DMN among other resting-state networks. The posterior component of the DMN presented noticeable differences. Measures of amplitude of low-frequency fluctuation (ALFF) and fractional ALFF (fALFF) of the network component demonstrated a decrease in resting-state cortical oscillation power in the elderly (normal and patient), specifically in the slow-5 (0.01–0.027 Hz) range of oscillations. Furthermore, the contribution of the slow-5 oscillations during the resting state was diminished for a greater influence of the slow-4 (0.027–0.073 Hz) oscillations in the subacute stroke group, not only suggesting a vulnerability of the slow-5 oscillations to disruption but also indicating a change in the distribution of the oscillations within the resting-state frequencies. The reduction of network slow-5 fALFF in the posterior DMN component was found to present a potential association with behavioral measures, suggesting a brain–behavior relationship to those oscillations, with this change in behavior potentially resulting from an altered network integrity induced by a weakening of the slow-5

  2. Midazolam and Atropine Alter Theta Oscillations in the Hippocampal CA1 Region by Modulating Both the Somatic and Distal Dendritic Dipoles

    PubMed Central

    Balakrishnan, Shilpashree; Pearce, Robert A.

    2014-01-01

    Theta (4-12 Hz) oscillations in the hippocampus play an important role in learning and memory. They are altered by a wide variety of drugs that impair memory, and these effects may underlie or contribute to drug-induced amnesia. However, the network mechanisms linking drug actions with changes in memory formation remain poorly defined. Here, we used a multisite linear electrode array to measure local field potentials simultaneously across the CA1 layers of the hippocampus during active exploration, and employed current source density analysis and computational modeling to investigate how midazolam and atropine – two amnestic drugs that are used clinically and experimentally – change the relative timing and strength of the drivers of θ-oscillations. We found that two dipoles are present, with active inputs that are centered at the soma and the distal apical dendrite and passive return pathways that overlap in the mid-apical dendrite. Both drugs shifted the position of the phase reversal in the local field potential that occurred in the mid-apical dendritic region, but in opposite directions, by changing the strength of the dendritic pole, without altering the somatic pole or relative timing. Computational modeling showed that this constellation of changes, as well as an additional effect on a variably present mid-apical pole, could be produced by simultaneous changes in the active somatic and distal dendritic inputs. These network-level changes, produced by two amnestic drugs that target different types of receptors, may thus serve as a common basis for impaired memory encoding. PMID:24862458

  3. Midazolam and atropine alter theta oscillations in the hippocampal CA1 region by modulating both the somatic and distal dendritic dipoles.

    PubMed

    Balakrishnan, Shilpashree; Pearce, Robert A

    2014-10-01

    Theta (4-12 Hz) oscillations in the hippocampus play an important role in learning and memory. They are altered by a wide variety of drugs that impair memory, and these effects may underlie or contribute to drug-induced amnesia. However, the network mechanisms linking drug actions with changes in memory formation remain poorly defined. Here, we used a multisite linear electrode array to measure local field potentials simultaneously across the CA1 layers of the hippocampus during active exploration, and employed current source density analysis and computational modeling to investigate how midazolam and atropine-two amnestic drugs that are used clinically and experimentally-change the relative timing and strength of the drivers of θ-oscillations. We found that two dipoles are present, with active inputs that are centered at the soma and the distal apical dendrite and passive return pathways that overlap in the mid-apical dendrite. Both drugs shifted the position of the phase reversal in the local field potential that occurred in the mid-apical dendritic region, but in opposite directions, by changing the strength of the dendritic pole, without altering the somatic pole or relative timing. Computational modeling showed that this constellation of changes, as well as an additional effect on a variably present mid-apical pole, could be produced by simultaneous changes in the active somatic and distal dendritic inputs. These network-level changes, produced by two amnestic drugs that target different types of receptors, may thus serve as a common basis for impaired memory encoding.

  4. Disconnection of hippocampal networks contributes to memory dysfunction in individuals with temporal lobe epilepsy.

    PubMed

    Stoub, Travis R; Chicharro, Ada V; Grote, Christopher L; Kanner, Andres M

    2017-09-09

    A deficit in declarative memory function is common among individuals with temporal lobe epilepsy. The purpose of this study is to evaluate the relationship between the volume of the hippocampus, entorhinal cortex along with the surrounding parahippocampal white matter and memory performance in those with temporal lobe epilepsy. T1 weighted MRI scans were acquired using a 3-D pulse sequence in 50 individuals with temporal lobe epilepsy. Hippocampal and entorhinal cortex volumes were derived by manually tracing consecutive coronal slices aligned perpendicular to the long axis of the hippocampus. In addition, parahippocampal white matter volumes were determined using voxel based morphometry. Finally, declarative memory was assessed using immediate and delayed verbal and visual memory tests from the Wechsler Memory Scale third edition. Significant correlations were seen between right and left hippocampal volumes and delayed verbal memory test scores. In addition, left parahippocampal white matter showed positive correlations with immediate and delayed verbal and visual recall. Furthermore, regression models found that the right hippocampus and left parahippocampal white matter were the best predictors of immediate and delayed verbal and visual memory performance. These results show that a decrease in white matter fibers projecting to the hippocampus may cause a disruption of incoming multi-modal sensory information, contributing to the memory decline seen in individuals with temporal lobe epilepsy. © 2017 Wiley Periodicals, Inc.

  5. Switching dynamics of single and coupled VO2-based oscillators as elements of neural networks

    NASA Astrophysics Data System (ADS)

    Velichko, Andrey; Belyaev, Maksim; Putrolaynen, Vadim; Pergament, Alexander; Perminov, Valentin

    2017-01-01

    In the present paper, we report on the switching dynamics of both single and coupled VO2-based oscillators, with resistive and capacitive coupling, and explore the capability of their application in oscillatory neural networks. Based on these results, we further select an adequate SPICE model to describe the modes of operation of coupled oscillator circuits. Physical mechanisms influencing the time of forward and reverse electrical switching, that determine the applicability limits of the proposed model, are identified. For the resistive coupling, it is shown that synchronization takes place at a certain value of the coupling resistance, though it is unstable and a synchronization failure occurs periodically. For the capacitive coupling, two synchronization modes, with weak and strong coupling, are found. The transition between these modes is accompanied by chaotic oscillations. A decrease in the width of the spectrum harmonics in the weak-coupling mode, and its increase in the strong-coupling one, is detected. The dependences of frequencies and phase differences of the coupled oscillatory circuits on the coupling capacitance are found. Examples of operation of coupled VO2 oscillators as a central pattern generator are demonstrated.

  6. On influences of global and local cues on the rate of synchronization of oscillator networks

    PubMed Central

    Wang, Yongqiang; Doyle, Francis J.

    2011-01-01

    Synchronization of connected oscillator networks under global and local cues is ubiquitous in both science and engineering. Over the last few decades, enormous attention has been paid to study synchronization conditions of connected oscillators in chemistry, physics, mechanics, and particularly in biology. However, the influences of global and local cues on the rate of synchronization have not been fully studied. It is widespread that synchronization is achieved in the simultaneous presence of both global and local cues, such as intercellular coupling signals and external entrainment signals in terms of biological oscillators, and inter-neighbor coupling signals between follower nodes and central guiding signals in terms of groups of mobile autonomous agents. We prove in this paper that strength of the global cue is the only determinant of the rate of synchronization. More specifically, we prove that a stronger global cue means a faster rate of synchronization whereas a stronger local cue does not necessarily make the synchronization rate faster. Our results not only apply to the noise free case, but also apply to the case that the oscillator natural frequencies are subject to white noise. The analysis does not require the interplay to be symmetric or balanced. Simulation results are given to illustrate the proposed results. PMID:21607201

  7. Parameter degeneracy in neutrino oscillation — Solution network and structural overview

    NASA Astrophysics Data System (ADS)

    Minakata, Hisakazu; Uchinami, Shoichi

    2010-04-01

    It is known that there is a phenomenon called “parameter degeneracy” in neutrino oscillation measurement of lepton mixing parameters; A set of the oscillation probabilities, e.g., P( ν μ → ν e ) and its CP-conjugate Pleft( {{{bar ν }_μ } to {{bar ν }_e}} right) at a particular neutrino energy does not determine uniquely the values of θ 13 and δ. With use of the approximate form of the oscillation probability á la Cervera et al., a complete analysis of the eightfold parameter degeneracy is presented. We propose a unified view of the various types of the degeneracy as invariance of the oscillation probabilities under discrete mappings of the mixing parameters. Explicit form of the mapping is obtained either by symmetry argument, or by deriving exact analytic expressions of all the degeneracy solutions for a given true solution. Due to the one-to-one mapping structure the degeneracy solutions are shown to form a network. We extend our analysis into the parameter degeneracy in T- and CPT-conjugate measurement as well as to the setup with the golden and the silver channels, P( ν e → ν μ ) and P( ν e → ν τ ). Some characteristic features of the degeneracy solutions in CP-conjugate measurement, in particular their energy dependences, are illuminated by utilizing the explicit analytic solutions.

  8. Sparse and Specific Coding during Information Transmission between Co-cultured Dentate Gyrus and CA3 Hippocampal Networks.

    PubMed

    Poli, Daniele; Thiagarajan, Srikanth; DeMarse, Thomas B; Wheeler, Bruce C; Brewer, Gregory J

    2017-01-01

    To better understand encoding and decoding of stimulus information in two specific hippocampal sub-regions, we isolated and co-cultured rat primary dentate gyrus (DG) and CA3 neurons within a two-chamber device with axonal connectivity via micro-tunnels. We tested the hypothesis that, in these engineered networks, decoding performance of stimulus site information would be more accurate when stimuli and information flow occur in anatomically correct feed-forward DG to CA3 vs. CA3 back to DG. In particular, we characterized the neural code of these sub-regions by measuring sparseness and uniqueness of the responses evoked by specific paired-pulse stimuli. We used the evoked responses in CA3 to decode the stimulation sites in DG (and vice-versa) by means of learning algorithms for classification (support vector machine, SVM). The device was placed over an 8 × 8 grid of extracellular electrodes (micro-electrode array, MEA) in order to provide a platform for monitoring development, self-organization, and improved access to stimulation and recording at multiple sites. The micro-tunnels were designed with dimensions 3 × 10 × 400 μm allowing axonal growth but not migration of cell bodies and long enough to exclude traversal by dendrites. Paired-pulse stimulation (inter-pulse interval 50 ms) was applied at 22 different sites and repeated 25 times in each chamber for each sub-region to evoke time-locked activity. DG-DG and CA3-CA3 networks were used as controls. Stimulation in DG drove signals through the axons in the tunnels to activate a relatively small set of specific electrodes in CA3 (sparse code). CA3-CA3 and DG-DG controls were less sparse in coding than CA3 in DG-CA3 networks. Using all target electrodes with the three highest spike rates (14%), the evoked responses in CA3 specified each stimulation site in DG with optimum uniqueness of 64%. Finally, by SVM learning, these evoked responses in CA3 correctly decoded the stimulation sites in DG for 43% of the

  9. Sparse and Specific Coding during Information Transmission between Co-cultured Dentate Gyrus and CA3 Hippocampal Networks

    PubMed Central

    Poli, Daniele; Thiagarajan, Srikanth; DeMarse, Thomas B.; Wheeler, Bruce C.; Brewer, Gregory J.

    2017-01-01

    To better understand encoding and decoding of stimulus information in two specific hippocampal sub-regions, we isolated and co-cultured rat primary dentate gyrus (DG) and CA3 neurons within a two-chamber device with axonal connectivity via micro-tunnels. We tested the hypothesis that, in these engineered networks, decoding performance of stimulus site information would be more accurate when stimuli and information flow occur in anatomically correct feed-forward DG to CA3 vs. CA3 back to DG. In particular, we characterized the neural code of these sub-regions by measuring sparseness and uniqueness of the responses evoked by specific paired-pulse stimuli. We used the evoked responses in CA3 to decode the stimulation sites in DG (and vice-versa) by means of learning algorithms for classification (support vector machine, SVM). The device was placed over an 8 × 8 grid of extracellular electrodes (micro-electrode array, MEA) in order to provide a platform for monitoring development, self-organization, and improved access to stimulation and recording at multiple sites. The micro-tunnels were designed with dimensions 3 × 10 × 400 μm allowing axonal growth but not migration of cell bodies and long enough to exclude traversal by dendrites. Paired-pulse stimulation (inter-pulse interval 50 ms) was applied at 22 different sites and repeated 25 times in each chamber for each sub-region to evoke time-locked activity. DG-DG and CA3-CA3 networks were used as controls. Stimulation in DG drove signals through the axons in the tunnels to activate a relatively small set of specific electrodes in CA3 (sparse code). CA3-CA3 and DG-DG controls were less sparse in coding than CA3 in DG-CA3 networks. Using all target electrodes with the three highest spike rates (14%), the evoked responses in CA3 specified each stimulation site in DG with optimum uniqueness of 64%. Finally, by SVM learning, these evoked responses in CA3 correctly decoded the stimulation sites in DG for 43% of the

  10. Interplay of Intrinsic and Synaptic Conductances in the Generation of High-Frequency Oscillations in Interneuronal Networks with Irregular Spiking

    PubMed Central

    Baroni, Fabiano; Burkitt, Anthony N.; Grayden, David B.

    2014-01-01

    High-frequency oscillations (above 30 Hz) have been observed in sensory and higher-order brain areas, and are believed to constitute a general hallmark of functional neuronal activation. Fast inhibition in interneuronal networks has been suggested as a general mechanism for the generation of high-frequency oscillations. Certain classes of interneurons exhibit subthreshold oscillations, but the effect of this intrinsic neuronal property on the population rhythm is not completely understood. We study the influence of intrinsic damped subthreshold oscillations in the emergence of collective high-frequency oscillations, and elucidate the dynamical mechanisms that underlie this phenomenon. We simulate neuronal networks composed of either Integrate-and-Fire (IF) or Generalized Integrate-and-Fire (GIF) neurons. The IF model displays purely passive subthreshold dynamics, while the GIF model exhibits subthreshold damped oscillations. Individual neurons receive inhibitory synaptic currents mediated by spiking activity in their neighbors as well as noisy synaptic bombardment, and fire irregularly at a lower rate than population frequency. We identify three factors that affect the influence of single-neuron properties on synchronization mediated by inhibition: i) the firing rate response to the noisy background input, ii) the membrane potential distribution, and iii) the shape of Inhibitory Post-Synaptic Potentials (IPSPs). For hyperpolarizing inhibition, the GIF IPSP profile (factor iii)) exhibits post-inhibitory rebound, which induces a coherent spike-mediated depolarization across cells that greatly facilitates synchronous oscillations. This effect dominates the network dynamics, hence GIF networks display stronger oscillations than IF networks. However, the restorative current in the GIF neuron lowers firing rates and narrows the membrane potential distribution (factors i) and ii), respectively), which tend to decrease synchrony. If inhibition is shunting instead of

  11. Requiring collaboration: Hippocampal-prefrontal networks needed in spatial working memory and ageing. A multivariate analysis approach.

    PubMed

    Zancada-Menendez, C; Alvarez-Suarez, P; Sampedro-Piquero, P; Cuesta, M; Begega, A

    2017-04-01

    Ageing is characterized by a decline in the processes of retention and storage of spatial information. We have examined the behavioural performance of adult rats (3months old) and aged rats (18months old) in a spatial complex task (delayed match to sample). The spatial task was performed in the Morris water maze and consisted of three sessions per day over a period of three consecutive days. Each session consisted of two trials (one sample and retention) and inter-session intervals of 5min. Behavioural results showed that the spatial task was difficult for middle aged group. This worse execution could be associated with impairments of processing speed and spatial information retention. We examined the changes in the neuronal metabolic activity of different brain regions through cytochrome C oxidase histochemistry. Then, we performed MANOVA and Discriminant Function Analyses to determine the functional profile of the brain networks that are involved in the spatial learning of the adult and middle-aged groups. This multivariate analysis showed two principal functional networks that necessarily participate in this spatial learning. The first network was composed of the supramammillary nucleus, medial mammillary nucleus, CA3, and CA1. The second one included the anterior cingulate, prelimbic, and infralimbic areas of the prefrontal cortex, dentate gyrus, and amygdala complex (basolateral l and central subregions). There was a reduction in the hippocampal-supramammilar network in both learning groups, whilst there was an overactivation in the executive network, especially in the aged group. This response could be due to a higher requirement of the executive control in a complex spatial memory task in older animals. Copyright © 2017 Elsevier Inc. All rights reserved.

  12. Two distinct actin networks mediate traction oscillations to confer mechanosensitivity of focal adhesions

    NASA Astrophysics Data System (ADS)

    Wu, Zhanghan; Plotnikov, Sergey; Waterman, Clare; Liu, Jian

    Cells sense the mechanical stiffness of their extracellular matrix (ECM) by exerting traction force through focal adhesions (FAs), which are integrin-based protein assemblies. Strikingly, FA-mediated traction forces oscillate in time and space and govern durotaxis - the tendency of most cell types to migrate toward stiffer ECM. The underlying mechanism of this intriguing oscillation of FA traction force is unknown. Combing theory and experiment, we develop a model of FA growth, which integrates coordinated contributions of a branched actin network and stress fibers in the process. We show that retrograde flux of branched actin network contributes to a traction peak near the FA distal tip and that stress fiber-mediated actomyosin Contractility generates a second traction peak near the FA center. Formin-mediated stress fiber elongation negatively feeds back with actomyosin Contractility, resulting in the central traction peak oscillation. This underpins observed spatio-temporal patterns of the FA traction, and broadens the ECM stiffness range, over which FAs could accurately adapt with traction force generation. Our findings shed light on the fundamental mechanism of FA mechanosensing and hence durotaxis.

  13. Partial synchronization in networks of non-linearly coupled oscillators: The Deserter Hubs Model

    SciTech Connect

    Freitas, Celso Macau, Elbert; Pikovsky, Arkady

    2015-04-15

    We study the Deserter Hubs Model: a Kuramoto-like model of coupled identical phase oscillators on a network, where attractive and repulsive couplings are balanced dynamically due to no