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Sample records for hippocampal network oscillations

  1. KCNQ5 K(+) channels control hippocampal synaptic inhibition and fast network oscillations.

    PubMed

    Fidzinski, Pawel; Korotkova, Tatiana; Heidenreich, Matthias; Maier, Nikolaus; Schuetze, Sebastian; Kobler, Oliver; Zuschratter, Werner; Schmitz, Dietmar; Ponomarenko, Alexey; Jentsch, Thomas J

    2015-02-04

    KCNQ2 (Kv7.2) and KCNQ3 (Kv7.3) K(+) channels dampen neuronal excitability and their functional impairment may lead to epilepsy. Less is known about KCNQ5 (Kv7.5), which also displays wide expression in the brain. Here we show an unexpected role of KCNQ5 in dampening synaptic inhibition and shaping network synchronization in the hippocampus. KCNQ5 localizes to the postsynaptic site of inhibitory synapses on pyramidal cells and in interneurons. Kcnq5(dn/dn) mice lacking functional KCNQ5 channels display increased excitability of different classes of interneurons, enhanced phasic and tonic inhibition, and decreased electrical shunting of inhibitory postsynaptic currents. In vivo, loss of KCNQ5 function leads to reduced fast (gamma and ripple) hippocampal oscillations, altered gamma-rhythmic discharge of pyramidal cells and impaired spatial representations. Our work demonstrates that KCNQ5 controls excitability and function of hippocampal networks through modulation of synaptic inhibition.

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

    PubMed

    Miyawaki, Hiroyuki; Diba, Kamran

    2016-04-01

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

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

    PubMed

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

    2005-01-01

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

  4. 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

  5. Sharp wave/ripple network oscillations and learning-associated hippocampal maps.

    PubMed

    Csicsvari, Jozsef; Dupret, David

    2014-02-01

    Sharp wave/ripple (SWR, 150-250 Hz) hippocampal events have long been postulated to be involved in memory consolidation. However, more recent work has investigated SWRs that occur during active waking behaviour: findings that suggest that SWRs may also play a role in cell assembly strengthening or spatial working memory. Do such theories of SWR function apply to animal learning? This review discusses how general theories linking SWRs to memory-related function may explain circuit mechanisms related to rodent spatial learning and to the associated stabilization of new cognitive maps.

  6. Cholinergic Plasticity of Oscillating Neuronal Assemblies in Mouse Hippocampal Slices

    PubMed Central

    Zylla, Maura M.; Zhang, Xiaomin; Reichinnek, Susanne; Draguhn, Andreas; Both, Martin

    2013-01-01

    The mammalian hippocampus expresses several types of network oscillations which entrain neurons into transiently stable assemblies. These groups of co-active neurons are believed to support the formation, consolidation and recall of context-dependent memories. Formation of new assemblies occurs during theta- and gamma-oscillations under conditions of high cholinergic activity. Memory consolidation is linked to sharp wave-ripple oscillations (SPW-R) during decreased cholinergic tone. We hypothesized that increased cholinergic tone supports plastic changes of assemblies while low cholinergic tone favors their stability. Coherent spatiotemporal network patterns were measured during SPW-R activity in mouse hippocampal slices. We compared neuronal activity within the oscillating assemblies before and after a transient phase of carbachol-induced gamma oscillations. Single units maintained their coupling to SPW-R throughout the experiment and could be re-identified after the transient phase of gamma oscillations. However, the frequency of SPW-R-related unit firing was enhanced after muscarinic stimulation. At the network level, these changes resulted in altered patterns of extracellularly recorded SPW-R waveforms. In contrast, recording of ongoing SPW-R activity without intermittent cholinergic stimulation revealed remarkably stable repetitive activation of assemblies. These results show that activation of cholinergic receptors induces plasticity at the level of oscillating hippocampal assemblies, in line with the different role of gamma- and SPW-R network activity for memory formation and –consolidation, respectively. PMID:24260462

  7. 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

  8. Rhythms of the hippocampal network.

    PubMed

    Colgin, Laura Lee

    2016-04-01

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

  9. 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

  10. 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.

  11. Pyramidal cell-interneuron interactions underlie hippocampal ripple oscillations.

    PubMed

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

    2014-07-16

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

  12. Entrainment of neocortical neurons and gamma oscillations by the hippocampal theta rhythm

    PubMed Central

    Sirota, Anton; Montgomery, Sean; Fujisawa, Shigeyoshi; Isomura, Yoshikazu; Zugaro, Michael; Buzsáki, György

    2008-01-01

    SUMMARY Although it has been tacitly assumed that the hippocampus exerts an influence on neocortical networks, the mechanisms of this process are not well understood. We examined whether and how hippocampal theta oscillations affect neocortical assembly patterns by recording populations of single cells and transient gamma oscillations in multiple cortical regions, including the somatosensory area and prefrontal cortex in behaving rats and mice. Laminar analysis of neocortical gamma bursts revealed multiple gamma oscillators of varying frequency and location, which were spatially confined and synchronized local groups of neurons. A significant fraction of putative pyramidal cells and interneurons as well as localized gamma oscillations in all recorded neocortical areas were phase-biased by the hippocampal theta rhythm. We hypothesize that temporal coordination of neocortical gamma oscillators by hippocampal theta is a mechanism by which information contained in spatially widespread neocortical assemblies can be synchronously transferred to the associative networks of the hippocampus. PMID:19038224

  13. 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.

  14. Network synchronization in hippocampal neurons.

    PubMed

    Penn, Yaron; Segal, Menahem; Moses, Elisha

    2016-03-22

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

  15. 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

  16. Ketamine Protects Gamma Oscillations by Inhibiting Hippocampal LTD.

    PubMed

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

    2016-01-01

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

  17. 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

  18. On the synchronizing mechanisms of tetanically induced hippocampal oscillations.

    PubMed

    Bracci, E; Vreugdenhil, M; Hack, S P; Jefferys, J G

    1999-09-15

    gamma (30-100 Hz) and beta (10-30 Hz) oscillations follow tetanic stimulation in the CA1 region of the rat hippocampal slice. Pyramidal neurons undergo a slow depolarization after the tetanus and generate synchronous action potentials. The slow depolarization was previously attributed to metabotropic glutamate receptor (mGluR) activation. However, we found that this event was mediated by GABA(A) receptors, being blocked by bicuculline (50 microM) and accompanied by a dramatic drop in input resistance. Experiments with NMDA and non-NMDA glutamate receptor antagonists revealed that fast synaptic excitation was not necessary for oscillations. IPSPs were strongly depressed during the oscillations. Instead, synchronization was caused by field effects, as shown by: (1) Action potentials of pyramidal neurons proximal (<200 micrometer) to the stimulation site were often preceded by negative deflections of the intracellular potential that masked a net transmembrane depolarization caused by the population spike. (2) Pyramidal neurons located on the surface of the slice, where field effects are weak, fired repetitively but were not synchronized to the network activity. (3) A moderate decrease (50 mOsm) in artificial CSF (ACSF) osmolality did not affect the slow depolarization but increased oscillation amplitude and duration and recruited previously silent neurons into oscillations. (4) 50 mOsm increase in ACSF osmolality dramatically reduced, or abolished, post-tetanic oscillations. Phasic IPSPs, not detectable in proximal neurons, were present, late in the oscillation, in cells located 200-400 micrometer from the stimulation site and possibly contributed to slowing the rhythm during the gamma to beta transition.

  19. Multiple GABAA receptor subtypes regulate hippocampal ripple oscillations.

    PubMed

    Ponomarenko, A A; Korotkova, T M; Sergeeva, O A; Haas, H L

    2004-10-01

    High-frequency oscillations (140-200 Hz) were recorded in behaving rats from the CA1 area of the hippocampus. As generation of these synchronous patterns is assumed to depend on coordinated interneuronal inhibition, we studied the interference of benzodiazepines with the fine structure and occurrence of ripple oscillations. The nonselective GABAA receptor alpha-subunit agonist, diazepam, lowered the frequency of ripple oscillations and reduced their occurrence, amplitude and duration. Zolpidem, an alpha1-subunit selective benzodiazepine elevated ripple duration but acted similar to diazepam in other respects. The nonselective alpha-subunit benzodiazepine antagonist, flumazenil, reduced ripple numbers, amplitude and duration. Wavelet based analysis of the dynamics of intraripple frequency revealed a dramatic decay within a ripple. Only diazepam (1 mg/kg) accelerated this intraripple frequency accommodation. The effects were not due to increased behavioural activity and alertness as evident from vigilance state control. The results suggest a differential role of GABAA receptor subtype specific inhibitory mechanisms in the mediation and fine-tuning of the network synchronization during approximately 200 Hz hippocampal oscillations.

  20. Theta-Burst Stimulation of Hippocampal Slices Induces Network-Level Calcium Oscillations and Activates Analogous Gene Transcription to Spatial Learning

    PubMed Central

    O'Connor, John J.; Murphy, Keith J.

    2014-01-01

    Over four decades ago, it was discovered that high-frequency stimulation of the dentate gyrus induces long-term potentiation (LTP) of synaptic transmission. LTP is believed to underlie how we process and code external stimuli before converting it to salient information that we store as 'memories'. It has been shown that rats performing spatial learning tasks display theta-frequency (3–12 Hz) hippocampal neural activity. Moreover, administering theta-burst stimulation (TBS) to hippocampal slices can induce LTP. TBS triggers a sustained rise in intracellular calcium [Ca2+]i in neurons leading to new protein synthesis important for LTP maintenance. In this study, we measured TBS-induced [Ca2+]i oscillations in thousands of cells at increasing distances from the source of stimulation. Following TBS, a calcium wave propagates radially with an average speed of 5.2 µm/s and triggers multiple and regular [Ca2+]i oscillations in the hippocampus. Interestingly, the number and frequency of [Ca2+]i fluctuations post-TBS increased with respect to distance from the electrode. During the post-tetanic phase, 18% of cells exhibited 3 peaks in [Ca2+]i with a frequency of 17 mHz, whereas 2.3% of cells distributed further from the electrode displayed 8 [Ca2+]i oscillations at 33 mHz. We suggest that these observed [Ca2+]i oscillations could lead to activation of transcription factors involved in synaptic plasticity. In particular, the transcription factor, NF-κB, has been implicated in memory formation and is up-regulated after LTP induction. We measured increased activation of NF-κB 30 min post-TBS in CA1 pyramidal cells and also observed similar temporal up-regulation of NF-κB levels in CA1 neurons following water maze training in rats. Therefore, TBS of hippocampal slice cultures in vitro can mimic the cell type-specific up-regulations in activated NF-κB following spatial learning in vivo. This indicates that TBS may induce similar transcriptional changes to spatial learning

  1. Running speed alters the frequency of hippocampal gamma oscillations

    PubMed Central

    Ahmed, Omar J.; Mehta, Mayank R.

    2012-01-01

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

  2. Increase in hippocampal theta oscillations during spatial decision making

    PubMed Central

    Belchior, Hindiael; Lopes-dos-Santos, Vítor; Tort, Adriano BL; Ribeiro, Sidarta

    2014-01-01

    The processing of spatial and mnemonic information is believed to depend on hippocampal theta oscillations (5–12 Hz). However, in rats both the power and the frequency of the theta rhythm are modulated by locomotor activity, which is a major confounding factor when estimating its cognitive correlates. Previous studies have suggested that hippocampal theta oscillations support decision-making processes. In this study, we investigated to what extent spatial decision making modulates hippocampal theta oscillations when controlling for variations in locomotion speed. We recorded local field potentials from the CA1 region of rats while animals had to choose one arm to enter for reward (goal) in a four-arm radial maze. We observed prominent theta oscillations during the decision-making period of the task, which occurred in the center of the maze before animals deliberately ran through an arm toward goal location. In speed-controlled analyses, theta power and frequency were higher during the decision period when compared to either an intertrial delay period (also at the maze center), or to the period of running toward goal location. In addition, theta activity was higher during decision periods preceding correct choices than during decision periods preceding incorrect choices. Altogether, our data support a cognitive function for the hippocampal theta rhythm in spatial decision making. PMID:24520011

  3. Amyloid Beta Peptide Slows Down Sensory-Induced Hippocampal Oscillations

    PubMed Central

    Peña-Ortega, Fernando; Bernal-Pedraza, Ramón

    2012-01-01

    Alzheimer's disease (AD) progresses with a deterioration of hippocampal function that is likely induced by amyloid beta (Aβ) oligomers. Hippocampal function is strongly dependent on theta rhythm, and disruptions in this rhythm have been related to the reduction of cognitive performance in AD. Accordingly, both AD patients and AD-transgenic mice show an increase in theta rhythm at rest but a reduction in cognitive-induced theta rhythm. We have previously found that monomers of the short sequence of Aβ (peptide 25–35) reduce sensory-induced theta oscillations. However, considering on the one hand that different Aβ sequences differentially affect hippocampal oscillations and on the other hand that Aβ oligomers seem to be responsible for the cognitive decline observed in AD, here we aimed to explore the effect of Aβ oligomers on sensory-induced theta rhythm. Our results show that intracisternal injection of Aβ1–42 oligomers, which has no significant effect on spontaneous hippocampal activity, disrupts the induction of theta rhythm upon sensory stimulation. Instead of increasing the power in the theta band, the hippocampus of Aβ-treated animals responds to sensory stimulation (tail pinch) with an increase in lower frequencies. These findings demonstrate that Aβ alters induced theta rhythm, providing an in vivo model to test for therapeutic approaches to overcome Aβ-induced hippocampal and cognitive dysfunctions. PMID:22611415

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

    PubMed

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

    2005-01-01

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

  5. Hippocampal place cell assemblies are speed-controlled oscillators.

    PubMed

    Geisler, Caroline; Robbe, David; Zugaro, Michaël; Sirota, Anton; Buzsáki, György

    2007-05-01

    The phase of spikes of hippocampal pyramidal cells relative to the local field theta oscillation shifts forward ("phase precession") over a full theta cycle as the animal crosses the cell's receptive field ("place field"). The linear relationship between the phase of the spikes and the travel distance within the place field is independent of the animal's running speed. This invariance of the phase-distance relationship is likely to be important for coordinated activity of hippocampal cells and space coding, yet the mechanism responsible for it is not known. Here we show that at faster running speeds place cells are active for fewer theta cycles but oscillate at a higher frequency and emit more spikes per cycle. As a result, the phase shift of spikes from cycle to cycle (i.e., temporal precession slope) is faster, yet spatial-phase precession stays unchanged. Interneurons can also show transient-phase precession and contribute to the formation of coherently precessing assemblies. We hypothesize that the speed-correlated acceleration of place cell assembly oscillation is responsible for the phase-distance invariance of hippocampal place cells.

  6. Adverse Stress, Hippocampal Networks, and Alzheimer's Disease

    PubMed Central

    Rothman, Sarah M.; Mattson, Mark P.

    2009-01-01

    Recent clinical data have implicated chronic adverse stress as a potential risk factor in the development of Alzheimer's disease (AD) and data also suggest that normal, physiological stress responses may be impaired in AD. It is possible that pathology associated with AD causes aberrant responses to chronic stress, due to potential alterations in the hypothalamic-pituitary-adrenal (HPA) axis. Recent work in rodent models of AD suggests that chronic adverse stress exacerbates the cognitive deficits and hippocampal pathology that are present in the AD brain. This review summarizes recent findings obtained in experimental AD models regarding the influence of chronic adverse stress on the underlying cellular and molecular disease processes including the potential role of glucocorticoids. Emerging findings suggest that both AD and chronic adverse stress affect hippocampal neural networks in a similar fashion. We describe alterations in hippocampal plasticity that occur in both chronic stress and AD including dendritic remodeling, neurogenesis and long-term potentiation. Finally, we outline potential roles for oxidative stress and neurotrophic factor signaling as key determinants of the impact of chronic stress on the plasticity of neural networks and AD pathogenesis. PMID:19943124

  7. Histamine H3 receptor activation decreases kainate-induced hippocampal gamma oscillations in vitro by action potential desynchronization in pyramidal neurons

    PubMed Central

    Andersson, Richard; Lindskog, Maria; Fisahn, André

    2010-01-01

    The study of rhythmic electrical activity in slice preparations has generated important insights into neural network function. While the synaptic mechanisms involved in the generation of in vitro network oscillations have been studied widely, little is known about the modulatory influence exerted on rhythmic activity in neuronal networks by neuropeptides and biogenic amines. Gamma oscillations play an important role in cognitive processes and are altered or disrupted in disorders such as Alzheimer's disease (AD) and schizophrenia. Given the importance of gamma oscillations for learning, memory and cognition processes as well as the recent interest in histamine H3 receptors in the development of pro-cognitive drugs to treat disorders such as AD and schizophrenia, it is relevant to study the impact of histaminergic mechanisms on network gamma oscillations. Here we show for the first time a modulation of gamma oscillation by histaminergic mechanisms. Selective activation of the H3 receptor by R-α-methylhistamine significantly reduces the power of kainate-induced gamma oscillations, but not carbachol-induced gamma oscillations, in the rat hippocampal slice preparation without affecting oscillation frequency. This effect is neither caused by a decrease in excitatory or inhibitory postsynaptic currents, nor a decrease in cellular excitability. Instead, we find that the decrease in oscillation power following H3 receptor activation results from a desynchronization of pyramidal neuron action potential firing with regard to the local field potential oscillation cycle. Our data provide a possible mechanism of action for histamine in regulating gamma oscillations in the hippocampal network. PMID:20156850

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

    PubMed

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

    2016-01-01

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

  9. 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

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

    NASA Astrophysics Data System (ADS)

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

    2010-10-01

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

  11. 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

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

    PubMed

    Hartwich, Katja; Pollak, Thomas; Klausberger, Thomas

    2009-07-29

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

  13. Input-Output Features of Anatomically Identified CA3 Neurons during Hippocampal Sharp Wave/Ripple Oscillation In Vitro

    PubMed Central

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

    2013-01-01

    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. PMID:23843535

  14. 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.

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

    PubMed

    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.

  16. 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.

  17. 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.

  18. 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

  19. Fast effects of glucocorticoids on memory-related network oscillations in the mouse hippocampus.

    PubMed

    Weiss, E K; Krupka, N; Bähner, F; Both, M; Draguhn, A

    2008-05-01

    Transient or lasting increases in glucocorticoids accompany deficits in hippocampus-dependent memory formation. Recent data indicate that the formation and consolidation of declarative and spatial memory are mechanistically related to different patterns of hippocampal network oscillations. These include gamma oscillations during memory acquisition and the faster ripple oscillations (approximately 200 Hz) during subsequent memory consolidation. We therefore analysed the effects of acutely applied glucocorticoids on network activity in mouse hippocampal slices. Evoked field population spikes and paired-pulse responses were largely unaltered by corticosterone or cortisol, respectively, despite a slight increase in maximal population spike amplitude by 10 microm corticosterone. Several characteristics of sharp waves and superimposed ripple oscillations were affected by glucocorticoids, most prominently the frequency of spontaneously occurring sharp waves. At 0.1 microm, corticosterone increased this frequency, whereas maximal (10 microm) concentrations led to a reduction. In addition, gamma oscillations became slightly faster and less regular in the presence of high doses of corticosteroids. The present study describes acute effects of glucocorticoids on sharp wave-ripple complexes and gamma oscillations in mouse hippocampal slices, revealing a potential background for memory deficits in the presence of elevated levels of these hormones.

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

    PubMed

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

    2016-09-01

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

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

    PubMed Central

    Stella, Federico; Treves, Alessandro

    2011-01-01

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

  2. Neuronal Network Oscillations in Neurodegenerative Diseases.

    PubMed

    Nimmrich, Volker; Draguhn, Andreas; Axmacher, Nikolai

    2015-09-01

    Cognitive and behavioral acts go along with highly coordinated spatiotemporal activity patterns in neuronal networks. Most of these patterns are synchronized by coherent membrane potential oscillations within and between local networks. By entraining multiple neurons into a common time regime, such network oscillations form a critical interface between cellular activity and large-scale systemic functions. Synaptic integrity is altered in neurodegenerative diseases, and it is likely that this goes along with characteristic changes of coordinated network activity. This notion is supported by EEG recordings from human patients and from different animal models of such disorders. However, our knowledge about the pathophysiology of network oscillations in neurodegenerative diseases is surprisingly incomplete, and increased research efforts are urgently needed. One complicating factor is the pronounced diversity of network oscillations between different brain regions and functional states. Pathological changes must, therefore, be analyzed separately in each condition and affected area. However, cumulative evidence from different diseases may result, in the future, in more unifying "oscillopathy" concepts of neurodegenerative diseases. In this review, we report present evidence for pathological changes of network oscillations in Alzheimer's disease (AD), one of the most prominent and challenging neurodegenerative disorders. The heterogeneous findings from AD are contrasted to Parkinson's disease, where motor-related changes in specific frequency bands do already fulfill criteria of a valid biomarker. PMID:25920466

  3. 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.

  4. Intrinsic Ca2+-dependent theta oscillations in apical dendrites of hippocampal CA1 pyramidal cells in vitro.

    PubMed

    Hansen, Allan Kjeldsen; Nedergaard, Steen; Andreasen, Mogens

    2014-08-01

    Behavior-associated theta-frequency oscillation in the hippocampal network involves a patterned activation of place cells in the CA1, which can be accounted for by a somatic-dendritic interference model predicting the existence of an intrinsic dendritic oscillator. Here we describe an intrinsic oscillatory mechanism in apical dendrites of in vitro CA1 pyramidal cells, which is induced by suprathreshold depolarization and consists of rhythmic firing of slow spikes in the theta-frequency band. The incidence of slow spiking (29%) increased to 78% and 100% in the presence of the β-adrenergic agonist isoproterenol (2 μM) or 4-aminopyridine (2 mM), respectively. Prior depolarization facilitated the induction of slow spiking. Applied electrical field polarization revealed a distal dendritic origin of slow spikes. The oscillations were largely insensitive to tetrodotoxin, but blocked by nimodipine (10 μM), indicating that they depend on activation of L-type Ca2+ channels. Antagonists of T-, R-, N-, and P/Q-type Ca2+ channels had no detectable effect. The slow spike dimension and frequency was sensitive to 4-aminopyridine (0.1-2 mM) and TEA (10 mM), suggesting the contribution from voltage-dependent K+ channels to the oscillation mechanism. α-Dendrotoxin (10 μM), stromatoxin (2 μM), iberiotoxin (0.2 μM), apamin (0.5 μM), linorpidine (30 μM), and ZD7288 (20 μM) were without effect. Oscillations induced by sine-wave current injection or theta-burst synaptic stimulation were voltage-dependently attenuated by nimodipine, indicating an amplifying function of L-type Ca2+ channels on imposed signals. These results show that the apical dendrites have intrinsic oscillatory properties capable of generating rhythmic voltage fluctuations in the theta-frequency band. PMID:25252335

  5. 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

  6. Persistent Hyperdopaminergia Decreases the Peak Frequency of Hippocampal Theta Oscillations during Quiet Waking and REM Sleep

    PubMed Central

    Dzirasa, Kafui; Santos, Lucas M.; Ribeiro, Sidarta; Stapleton, Jennifer; Gainetdinov, Raul R.; Caron, Marc G.; Nicolelis, Miguel A. L.

    2009-01-01

    Long-term changes in dopaminergic signaling are thought to underlie the pathophysiology of a number of psychiatric disorders. Several conditions are associated with cognitive deficits such as disturbances in attention processes and learning and memory, suggesting that persistent changes in dopaminergic signaling may alter neural mechanisms underlying these processes. Dopamine transporter knockout (DAT-KO) mice exhibit a persistent five-fold increase in extracellular dopamine levels. Here, we demonstrate that DAT-KO mice display lower hippocampal theta oscillation frequencies during baseline periods of waking and rapid-eye movement sleep. These altered theta oscillations are not reversed via treatment with the antidopaminergic agent haloperidol. Thus, we propose that persistent hyperdopaminergia, together with secondary alterations in other neuromodulatory systems, results in lower frequency activity in neural systems responsible for various cognitive processes. PMID:19381303

  7. A neural network approach to hippocampal function in classical conditioning.

    PubMed

    Schmajuk, N A; DiCarlo, J J

    1991-02-01

    Hippocampal participation in classical conditioning in terms of Grossberg's (1975) attentional theory is described. According to the present rendition of this theory, pairing of a conditioned stimulus (CS) with an unconditioned stimulus (US) causes both an association of the sensory representation of the CS with the US (conditioned reinforcement learning) and an association of the sensory representation of the CS with the drive representation of the US (incentive motivation learning). Sensory representations compete among themselves for a limited-capacity short-term memory (STM) that is reflected in a long-term memory storage. The STM regulation hypothesis, which proposes that the hippocampus controls incentive motivation, self-excitation, and competition among sensory representations thereby regulating the contents of a limited capacity STM, is introduced. Under the STM regulation hypothesis, nodes and connections in Grossberg's neural network are mapped onto regional hippocampal-cerebellar circuits. The resulting neural model provides (a) a framework for understanding the dynamics of information processing and storage in the hippocampus and cerebellum during classical conditioning of the rabbit's nictitating membrane, (b) principles for understanding the effect of different hippocampal manipulations on classical conditioning, and (c) numerous novel and testable predictions.

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

    PubMed

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

    2015-10-01

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

  9. 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

  10. Driven synchronization in random networks of oscillators.

    PubMed

    Hindes, Jason; Myers, Christopher R

    2015-07-01

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

  11. 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.

  12. 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

  13. 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.

  14. 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.

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

    PubMed

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

    2016-03-16

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

  16. 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.

  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. Cortical EEG oscillations and network connectivity as efficacy indices for assessing drugs with cognition enhancing potential.

    PubMed

    Ahnaou, A; Huysmans, H; Jacobs, T; Drinkenburg, W H I M

    2014-11-01

    Synchronization of electroencephalographic (EEG) oscillations represents a core mechanism for cortical and subcortical networks, and disturbance in neural synchrony underlies cognitive processing deficits in neurological and neuropsychiatric disorders. Here, we investigated the effects of cognition enhancers (donepezil, rivastigmine, tacrine, galantamine and memantine), which are approved for symptomatic treatment of dementia, on EEG oscillations and network connectivity in conscious rats chronically instrumented with epidural electrodes in different cortical areas. Next, EEG network indices of cognitive impairments with the muscarinic receptor antagonist scopolamine were modeled. Lastly, we examined the efficacy of cognition enhancers to normalize those aberrant oscillations. Cognition enhancers elicited systematic ("fingerprint") enhancement of cortical slow theta (4.5-6 Hz) and gamma (30.5-50 Hz) oscillations correlated with lower activity levels. Principal component analysis (PCA) revealed a compact cluster that corresponds to shared underlying mechanisms as compared to different drug classes. Functional network connectivity revealed consistent elevated coherent slow theta activity in parieto-occipital and between interhemispheric cortical areas. In rats instrumented with depth hippocampal CA1-CA3 electrodes, donepezil elicited similar oscillatory and coherent activities in cortico-hippocampal networks. When combined with scopolamine, the cognition enhancers attenuated the leftward shift in coherent slow delta activity. Such a consistent shift in EEG coherence into slow oscillations associated with altered slow theta and gamma oscillations may underlie cognitive deficits in scopolamine-treated animals, whereas enhanced coherent slow theta and gamma activity may be a relevant mechanism by which cognition enhancers exert their beneficial effect on plasticity and cognitive processes. The findings underscore that PCA and network connectivity are valuable tools to

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

    PubMed Central

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

    2016-01-01

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

  20. 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

  1. 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

  2. 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

  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. Input-to-output transformation in a model of the rat hippocampal CA1 network.

    PubMed

    Olypher, Andrey V; Lytton, William W; Prinz, Astrid A

    2012-01-01

    Here we use computational modeling to gain new insights into the transformation of inputs in hippocampal field CA1. We considered input-output transformation in CA1 principal cells of the rat hippocampus, with activity synchronized by population gamma oscillations. Prior experiments have shown that such synchronization is especially strong for cells within one millimeter of each other. We therefore simulated a one-millimeter ıt patch of CA1 with 23,500 principal cells. We used morphologically and biophysically detailed neuronal models, each with more than 1000 compartments and thousands of synaptic inputs. Inputs came from binary patterns of spiking neurons from field CA3 and entorhinal cortex (EC). On average, each presynaptic pattern initiated action potentials in the same number of CA1 principal cells in the patch. We considered pairs of similar and pairs of distinct patterns. In all the cases CA1 strongly separated input patterns. However, CA1 cells were considerably more sensitive to small alterations in EC patterns compared to CA3 patterns. Our results can be used for comparison of input-to-output transformations in normal and pathological hippocampal networks.

  5. 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.

  6. Amyloid-β-induced action potential desynchronization and degradation of hippocampal gamma oscillations is prevented by interference with peptide conformation change and aggregation.

    PubMed

    Kurudenkandy, Firoz Roshan; Zilberter, Misha; Biverstål, Henrik; Presto, Jenny; Honcharenko, Dmytro; Strömberg, Roger; Johansson, Jan; Winblad, Bengt; Fisahn, André

    2014-08-20

    The amyloid-β hypothesis of Alzheimer's Disease (AD) focuses on accumulation of amyloid-β peptide (Aβ) as the main culprit for the myriad physiological changes seen during development and progression of AD including desynchronization of neuronal action potentials, consequent development of aberrant brain rhythms relevant for cognition, and final emergence of cognitive deficits. The aim of this study was to elucidate the cellular and synaptic mechanisms underlying the Aβ-induced degradation of gamma oscillations in AD, to identify aggregation state(s) of Aβ that mediate the peptides neurotoxicity, and to test ways to prevent the neurotoxic Aβ effect. We show that Aβ(1-42) in physiological concentrations acutely degrades mouse hippocampal gamma oscillations in a concentration- and time-dependent manner. The underlying cause is an Aβ-induced desynchronization of action potential generation in pyramidal cells and a shift of the excitatory/inhibitory equilibrium in the hippocampal network. Using purified preparations containing different aggregation states of Aβ, as well as a designed ligand and a BRICHOS chaperone domain, we provide evidence that the severity of Aβ neurotoxicity increases with increasing concentration of fibrillar over monomeric Aβ forms, and that Aβ-induced degradation of gamma oscillations and excitatory/inhibitory equilibrium is prevented by compounds that interfere with Aβ aggregation. Our study provides correlative evidence for a link between Aβ-induced effects on synaptic currents and AD-relevant neuronal network oscillations, identifies the responsible aggregation state of Aβ and proofs that strategies preventing peptide aggregation are able to prevent the deleterious action of Aβ on the excitatory/inhibitory equilibrium and on the gamma rhythm. PMID:25143621

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

    PubMed

    Jacobs, Joshua

    2014-02-01

    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.

  8. Quantifying phase-amplitude coupling in neuronal network oscillations.

    PubMed

    Onslow, Angela C E; Bogacz, Rafal; Jones, Matthew W

    2011-03-01

    Neuroscience time series data from a range of techniques and species reveal complex, non-linear interactions between different frequencies of neuronal network oscillations within and across brain regions. Here, we briefly review the evidence that these nested, cross-frequency interactions act in concert with linearly covariant (within-frequency) activity to dynamically coordinate functionally related neuronal ensembles during behaviour. Such studies depend upon reliable quantification of cross-frequency coordination, and we compare the properties of three techniques used to measure phase-amplitude coupling (PAC)--Envelope-to-Signal Correlation (ESC), the Modulation Index (MI) and Cross-Frequency Coherence (CFC)--by standardizing their filtering algorithms and systematically assessing their robustness to noise and signal amplitude using artificial signals. Importantly, we also introduce a freely-downloadable method for estimating statistical significance of PAC, a step overlooked in the majority of published studies. We find that varying data length and noise levels leads to the three measures differentially detecting false positives or correctly identifying frequency bands of interaction; these conditions should therefore be taken into careful consideration when selecting PAC analyses. Finally, we demonstrate the utility of the three measures in quantifying PAC in local field potential data simultaneously recorded from rat hippocampus and prefrontal cortex, revealing a novel finding of prefrontal cortical theta phase modulating hippocampal gamma power. Future adaptations that allow detection of time-variant PAC should prove essential in deciphering the roles of cross-frequency coupling in mediating or reflecting nervous system function.

  9. 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.

  10. Optimization of noise-induced synchronization of oscillator networks

    NASA Astrophysics Data System (ADS)

    Kawamura, Yoji; Nakao, Hiroya

    2016-09-01

    We investigate common-noise-induced synchronization between two identical networks of coupled phase oscillators exhibiting fully locked collective oscillations. Using the collective phase description method for fully locked oscillators, we demonstrate that two noninteracting networks of coupled phase oscillators can exhibit in-phase synchronization between the networks when driven by weak common noise. We derive the Lyapunov exponent characterizing the relaxation time for synchronization and develop a method of obtaining the optimal input pattern of common noise to achieve fast synchronization. We illustrate the theory using three representative networks with heterogeneous, global, and local coupling. The theoretical results are validated by direct numerical simulations.

  11. Winding Numbers and Average Frequencies in Phase Oscillator Networks

    NASA Astrophysics Data System (ADS)

    Golubitsky, M.; Josic, K.; Shea-Brown, E.

    2006-06-01

    We study networks of coupled phase oscillators and show that network architecture can force relations between average frequencies of the oscillators. The main tool of our analysis is the coupled cell theory developed by Stewart, Golubitsky, Pivato, and Torok, which provides precise relations between network architecture and the corresponding class of ODEs in RM and gives conditions for the flow-invariance of certain polydiagonal subspaces for all coupled systems with a given network architecture. The theory generalizes the notion of fixed-point subspaces for subgroups of network symmetries and directly extends to networks of coupled phase oscillators. For systems of coupled phase oscillators (but not generally for ODEs in RM, where M ≥ 2), invariant polydiagonal subsets of codimension one arise naturally and strongly restrict the network dynamics. We say that two oscillators i and j coevolve if the polydiagonal θi = θj is flow-invariant, and show that the average frequencies of these oscillators must be equal. Given a network architecture, it is shown that coupled cell theory provides a direct way of testing how coevolving oscillators form collections with closely related dynamics. We give a generalization of these results to synchronous clusters of phase oscillators using quotient networks, and discuss implications for networks of spiking cells and those connected through buffers that implement coupling dynamics.

  12. Effective Connectivity of Hippocampal Neural Network and Its Alteration in Mg2+-Free Epilepsy Model

    PubMed Central

    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. PMID:24658094

  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. Emergent Oscillations in Networks of Stochastic Spiking Neurons

    PubMed Central

    van Drongelen, Wim; Cowan, Jack D.

    2011-01-01

    Networks of neurons produce diverse patterns of oscillations, arising from the network's global properties, the propensity of individual neurons to oscillate, or a mixture of the two. Here we describe noisy limit cycles and quasi-cycles, two related mechanisms underlying emergent oscillations in neuronal networks whose individual components, stochastic spiking neurons, do not themselves oscillate. Both mechanisms are shown to produce gamma band oscillations at the population level while individual neurons fire at a rate much lower than the population frequency. Spike trains in a network undergoing noisy limit cycles display a preferred period which is not found in the case of quasi-cycles, due to the even faster decay of phase information in quasi-cycles. These oscillations persist in sparsely connected networks, and variation of the network's connectivity results in variation of the oscillation frequency. A network of such neurons behaves as a stochastic perturbation of the deterministic Wilson-Cowan equations, and the network undergoes noisy limit cycles or quasi-cycles depending on whether these have limit cycles or a weakly stable focus. These mechanisms provide a new perspective on the emergence of rhythmic firing in neural networks, showing the coexistence of population-level oscillations with very irregular individual spike trains in a simple and general framework. PMID:21573105

  15. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2016-06-01

    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.

  17. 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.

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

    PubMed

    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.

  19. Weak chimeras in minimal networks of coupled phase oscillators.

    PubMed

    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.

  20. 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.

  1. 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.

  2. Symmetry-broken states on networks of coupled oscillators.

    PubMed

    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.

  3. 5-Hydroxytryptamine1A receptor-activation hyperpolarizes pyramidal cells and suppresses hippocampal gamma oscillations via Kir3 channel activation

    PubMed Central

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

    2014-01-01

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

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

    PubMed

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

    2015-01-22

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

  5. Differential effects of blockade of ERG channels on gamma oscillations and excitability in rat hippocampal slices.

    PubMed

    Fano, Silvia; Çalışkan, Gürsel; Heinemann, Uwe

    2012-12-01

    Agents such as sertindole and astemizole affect heart action by inducing long-QT syndrome, suggesting that apart from their neuronal actions through histamine receptors, 5-HT2 serotonin receptors and D2 dopamine receptors they also affect ether-a-go-go channels and particularly ether-a-go-go-related (ERG) potassium (K(+)) channels, comprising the K(v) 11.1, K(v) 11.2 and K(v) 11.3 voltage-gated potassium currents. Changes in ERG K(+) channel expression and activity have been reported and may be linked to schizophrenia [Huffaker, S.J., Chen, J., Nicodemus, K.K., Sambataro, F., Yang, F., Mattay, V., Lipska, B.K., Hyde, T.M., Song, J., Rujescu, D., Giegling, I., Mayilyan, K., Proust, M.J., Soghoyan, A., Caforio, G., Callicott, J.H., Bertolino, A., Meyer-Lindenberg, A., Chang, J., Ji, Y., Egan, M.F., Goldberg, T.E., Kleinman, J.E., Lu, B. & Weinberger DR. (2009). Nat. Med., 15, 509-518; Shepard, P.D., Canavier, C.C. & Levitan, E.S. (2007). Schizophr Bull., 33, 1263-1269]. We have previously shown that histamine H1 blockers augment gamma oscillations (γ) which are thought to be involved in cognition and storage of information. These effects were particularly pronounced for γ induced by acetylcholine. Here we have compared neuronal effects of three agents which interfere with ERG K(+) channels. We found that astemizole and sertindole, but not the K(v) 11 channel blocker E4031, augmented γ induced by acetylcholine in hippocampal slices. Kainate-induced γ were only affected by astemizole. Evoked responses induced by stratum radiatum stimulation in area CA1 revealed that only E4031 augmented stimulus-induced synaptic potentials and neuronal excitability. Our findings suggest that K(v) 11 channels are involved in neuronal excitability without clear effects on γ and that the effect of astemizole is related to actions on H1 receptors. PMID:23050739

  6. Hypoxia-Ischemia Disrupts Directed Interactions within Neonatal Prefrontal-Hippocampal Networks

    PubMed Central

    Brockmann, Marco D.; Kukovic, Maja; Schönfeld, Michael; Sedlacik, Jan; Hanganu-Opatz, Ileana L.

    2013-01-01

    Due to improved survival rates and outcome of human infants experiencing a hypoxic-ischemic episode, cognitive dysfunctions have become prominent. They might result from abnormal communication within prefrontal-hippocampal networks, as synchrony and directed interactions between the prefrontal cortex and hippocampus account for mnemonic and executive performance. Here, we elucidate the structural and functional impact of hypoxic-ischemic events on developing prefrontal-hippocampal networks in an immature rat model of injury. The magnitude of infarction, cell loss and astrogliosis revealed that an early hypoxic-ischemic episode had either a severe or a mild/moderate outcome. Without affecting the gross morphology, hypoxia-ischemia with mild/moderate outcome diminished prefrontal neuronal firing and gamma network entrainment. This dysfunction resulted from decreased coupling synchrony within prefrontal-hippocampal networks and disruption of hippocampal theta drive. Thus, early hypoxia-ischemia may alter the functional maturation of neuronal networks involved in cognitive processing by disturbing the communication between the neonatal prefrontal cortex and hippocampus. PMID:24376636

  7. 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.

  8. 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.

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

    PubMed

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

    2016-06-01

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

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

    PubMed

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

    2016-06-01

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

  11. 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

  12. Networks of dissipative quantum harmonic oscillators: A general treatment

    SciTech Connect

    Ponte, M. A. de; Mizrahi, S. S.; Moussa, M. H. Y.

    2007-09-15

    We present a general treatment of a bosonic dissipative network: a chain of coupled dissipative harmonic oscillators whatever its topology--i.e., whichever the way the oscillators are coupled together, the strength of their couplings, and their natural frequencies. Starting with a general more realistic scenario where each oscillator is coupled to its own reservoir, we also discuss the case where all the network oscillators are coupled to a common reservoir. We obtain the master equation governing the dynamic of the network states and the associated evolution equation of the Glauber-Sudarshan P function. With these instruments we briefly show how to analyze the decoherence and the evolution of the linear entropy of general states of the network. We also show how to obtain the master equation for the case of distinct reservoirs from that of a common one.

  13. Chimeras in random non-complete networks of phase oscillators.

    PubMed

    Laing, Carlo R; Rajendran, Karthikeyan; Kevrekidis, Ioannis G

    2012-03-01

    We consider the simplest network of coupled non-identical phase oscillators capable of displaying a "chimera" state (namely, two subnetworks with strong coupling within the subnetworks and weaker coupling between them) and systematically investigate the effects of gradually removing connections within the network, in a random but systematically specified way. We average over ensembles of networks with the same random connectivity but different intrinsic oscillator frequencies and derive ordinary differential equations (ODEs), whose fixed points describe a typical chimera state in a representative network of phase oscillators. Following these fixed points as parameters are varied we find that chimera states are quite sensitive to such random removals of connections, and that oscillations of chimera states can be either created or suppressed in apparent bifurcation points, depending on exactly how the connections are gradually removed.

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

    PubMed

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

    2016-09-01

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

  15. Synchronization in complex oscillator networks and smart grids.

    PubMed

    Dörfler, Florian; Chertkov, Michael; Bullo, Francesco

    2013-02-01

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

  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

    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.

  18. 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…

  19. 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.

  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. PMID:26601231

  1. 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

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

    PubMed

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

    2014-12-10

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

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

    PubMed

    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. PMID:27627306

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

    PubMed

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

    2015-01-01

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

  6. 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.

  7. Phthalates and neurotoxic effects on hippocampal network plasticity.

    PubMed

    Holahan, Matthew R; Smith, Catherine A

    2015-05-01

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

  8. Phthalates and neurotoxic effects on hippocampal network plasticity.

    PubMed

    Holahan, Matthew R; Smith, Catherine A

    2015-05-01

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

  9. Phase clustering in complex networks of delay-coupled oscillators

    NASA Astrophysics Data System (ADS)

    Pérez, Toni; Eguíluz, Víctor M.; Arenas, Alex

    2011-06-01

    We study the clusterization of phase oscillators coupled with delay in complex networks. For the case of diffusive oscillators, we formulate the equations relating the topology of the network and the phases and frequencies of the oscillators (functional response). We solve them exactly in directed networks for the case of perfect synchronization. We also compare the reliability of the solution of the linear system for non-linear couplings. Taking advantage of the form of the solution, we propose a frequency adaptation rule to achieve perfect synchronization. We also propose a mean-field theory for uncorrelated random networks that proves to be pretty accurate to predict phase synchronization in real topologies, as for example, the Caenorhabditis elegans or the autonomous systems connectivity.

  10. 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.

  11. Amplitude death in networks of delay-coupled delay oscillators.

    PubMed

    Höfener, Johannes M; Sethia, Gautam C; Gross, Thilo

    2013-09-28

    Amplitude death is a dynamical phenomenon in which a network of oscillators settles to a stable state as a result of coupling. Here, we study amplitude death in a generalized model of delay-coupled delay oscillators. We derive analytical results for degree homogeneous networks which show that amplitude death is governed by certain eigenvalues of the network's adjacency matrix. In particular, these results demonstrate that in delay-coupled delay oscillators amplitude death can occur for arbitrarily large coupling strength k. In this limit, we find a region of amplitude death which already occurs at small coupling delays that scale with 1/k. We show numerically that these results remain valid in random networks with heterogeneous degree distribution.

  12. Age-related changes to oscillatory dynamics in hippocampal and neocortical networks.

    PubMed

    Rondina, Renante; Olsen, Rosanna K; McQuiggan, Douglas A; Fatima, Zainab; Li, Lingqian; Oziel, Esther; Meltzer, Jed A; Ryan, Jennifer D

    2016-10-01

    Recent models of hippocampal function have emphasized its role in relational binding - the ability to form lasting representations regarding the relations among distinct elements or items which can support memory performance, even over brief delays (e.g., several seconds). The present study examined the extent to which aging is associated with changes in the recruitment of oscillatory activity within hippocampal and neocortical regions to support relational binding performance on a short delay visuospatial memory task. Structural magnetic resonance imaging and MEG were used to characterize potential age-related changes in hippocampal volume, oscillatory activity, and subsequent memory performance, and the relationships among them. Participants were required to bind the relative visuospatial positions of objects that were presented singly across time. Subsequently, the objects were re-presented simultaneously, and participants were required to indicate whether the relative spatial positions among the objects had been maintained. Older and younger adults demonstrated similar task accuracy, and older adults had preserved hippocampal volumes relative to younger adults. Age-group differences were found in pre-stimulus theta (∼5Hz) and beta (∼20Hz) oscillations, and this pre-stimulus activity was related to hippocampal volumes in younger adults. Age-group differences were also found in the recruitment of oscillatory activity from the pre-stimulus period to the task. Only younger adults showed a task-related change in theta power that was predictive of memory performance. In contrast, older adults demonstrated task-related alpha (∼10Hz) oscillatory power changes that were not observed in younger adults. These findings provide novel evidence for the role of the hippocampus and functionally connected regions in relational binding that is disrupted in aging. The present findings are discussed in the context of current models regarding the cognitive neuroscience of

  13. Age-related changes to oscillatory dynamics in hippocampal and neocortical networks.

    PubMed

    Rondina, Renante; Olsen, Rosanna K; McQuiggan, Douglas A; Fatima, Zainab; Li, Lingqian; Oziel, Esther; Meltzer, Jed A; Ryan, Jennifer D

    2016-10-01

    Recent models of hippocampal function have emphasized its role in relational binding - the ability to form lasting representations regarding the relations among distinct elements or items which can support memory performance, even over brief delays (e.g., several seconds). The present study examined the extent to which aging is associated with changes in the recruitment of oscillatory activity within hippocampal and neocortical regions to support relational binding performance on a short delay visuospatial memory task. Structural magnetic resonance imaging and MEG were used to characterize potential age-related changes in hippocampal volume, oscillatory activity, and subsequent memory performance, and the relationships among them. Participants were required to bind the relative visuospatial positions of objects that were presented singly across time. Subsequently, the objects were re-presented simultaneously, and participants were required to indicate whether the relative spatial positions among the objects had been maintained. Older and younger adults demonstrated similar task accuracy, and older adults had preserved hippocampal volumes relative to younger adults. Age-group differences were found in pre-stimulus theta (∼5Hz) and beta (∼20Hz) oscillations, and this pre-stimulus activity was related to hippocampal volumes in younger adults. Age-group differences were also found in the recruitment of oscillatory activity from the pre-stimulus period to the task. Only younger adults showed a task-related change in theta power that was predictive of memory performance. In contrast, older adults demonstrated task-related alpha (∼10Hz) oscillatory power changes that were not observed in younger adults. These findings provide novel evidence for the role of the hippocampus and functionally connected regions in relational binding that is disrupted in aging. The present findings are discussed in the context of current models regarding the cognitive neuroscience of

  14. Control analysis for autonomously oscillating biochemical networks.

    PubMed

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

    2002-01-01

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

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

    PubMed Central

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

    2016-01-01

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

  16. 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.

  17. 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.

  18. Oscillations in the bistable regime of neuronal networks.

    PubMed

    Roxin, Alex; Compte, Albert

    2016-07-01

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

  19. 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.

  20. Oscillations and Filtering Networks Support Flexible Routing of Information

    PubMed Central

    Akam, Thomas; Kullmann, Dimitri M.

    2010-01-01

    Summary The mammalian brain exhibits profuse interregional connectivity. How information flow is rapidly and flexibly switched among connected areas remains poorly understood. Task-dependent changes in the power and interregion coherence of network oscillations suggest that such oscillations play a role in signal routing. We show that switching one of several convergent pathways from an asynchronous to an oscillatory state allows accurate selective transmission of population-coded information, which can be extracted even when other convergent pathways fire asynchronously at comparable rates. We further show that the band-pass filtering required to perform this information extraction can be implemented in a simple spiking network model with a single feed-forward interneuron layer. This constitutes a mechanism for flexible signal routing in neural circuits, which exploits sparsely synchronized network oscillations and temporal filtering by feed-forward inhibition. Video Abstract PMID:20670837

  1. 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.

  2. Flat and tubular membrane systems for the reconstruction of hippocampal neuronal network.

    PubMed

    Morelli, Sabrina; Piscioneri, Antonella; Salerno, Simona; Rende, Maria; Campana, Carla; Tasselli, Franco; di Vito, Anna; Giusi, Giuseppina; Canonaco, Marcello; Drioli, Enrico; De Bartolo, Loredana

    2012-04-01

    The selection of appropriate biomaterials that promote cellular adhesion and growth is particularly important for the in vitro reconstruction of neuronal network. This study focused on the development of new polymeric membranes in flat and tubular (hollow-fibre) configurations as novel biomaterials for neuronal outgrowth. Two membrane systems constituted by modified polyetheretherketone (PEEK-WC) and polyacrylonitrile (PAN) membranes were developed and used for the culture of hamster hippocampal neurons. We demonstrated that all investigated membranes supported the adhesion and growth of hippocampal neurons enhancing neuronal differentiation and neurite alignment. The differences in cell behaviours between cells cultured on flat and hollow-fibre (HF) membranes were highlighted by the quantitative analysis of neuronal marker fluorescence intensity, morphometric analysis, RT-PCR analysis and also by metabolic activity measurements. In particular, the PAN HF membranes showed ideal growth culture conditions, guaranteeing adequate levels of metabolic features. Primary hippocampal cells cultured on PAN HF membranes were able to recreate in vitro a 3D neural tissue-like structure that, mimicking the hippocampal tissue, could be used as a tool for the study of natural and pathological neurobiological events.

  3. 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.

  4. Ultra-slow oscillations in cortical networks in vitro.

    PubMed

    Mok, S Y; Nadasdy, Z; Lim, Y M; Goh, S Y

    2012-03-29

    An ultra-slow oscillation (<0.01 Hz) in the network-wide activity of dissociated cortical networks is described in this article. This slow rhythm is characterized by the recurrence of clusters of large synchronized bursts of activity lasting approximately 1-3 min, separated by an almost equivalent interval of relatively smaller bursts. Such rhythmic activity was detected in cultures starting from the fourth week in vitro. Our analysis revealed that the propagation motifs of constituent bursts were strongly conserved across multiple oscillation cycles, and these motifs were more consistent at the electrode level compared with the neuronal level.

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

    PubMed

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

    2014-12-01

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

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

    PubMed

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

    2014-12-01

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

  7. 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.

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

    PubMed

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

    2016-05-18

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

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

    PubMed

    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. PMID:26651770

  10. 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.

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

    PubMed

    Rolls, Edmund T

    2013-01-01

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

  12. 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

  13. Mnemonic networks in the hippocampal formation: from spatial maps to temporal and conceptual codes.

    PubMed

    Milivojevic, Branka; Doeller, Christian F

    2013-11-01

    The hippocampal formation has been associated with a wide variety of functions including spatial navigation and planning, memory encoding and retrieval, relational processing, novelty detection, and imagination. These functions are dissimilar in terms of their behavioral consequences and modality of representation. Consequently, theoretical standpoints have focused on explaining the role of the hippocampal formation in terms of either its spatial or nonspatial functions. Contrary to this dichotomy, we propose that it is essential to look beyond these traditional boundaries between mnemonic and spatial functions and focus instead on the processes that these functions have in common. In this framework, we use electrophysiology data from the spatial domain to predict effects on the systems level, both in spatial and nonspatial domains. We initially outline the results of studies that have used findings from spatial navigation in rodents to predict the patterns of brain activity observable in people who are exploring virtual environments. We discuss how certain properties of space-defining neurons enable space to be represented as a mental map of interconnected locations, which are expressed at multiple spatial scales in separate modules in the hippocampal formation. We then suggest that memories are also organized in networks, characterized by mnemonic and temporal hierarchies. We finish by discussing how virtual-reality techniques can be used to create novel lifelike episodes allowing us to look at episodic memory processes while multivariate analysis tools can be used to explore the organizational structure of mnemonic networks.

  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. A Bayesian approach for structure learning in oscillating regulatory networks

    PubMed Central

    Trejo Banos, Daniel; Millar, Andrew J.; Sanguinetti, Guido

    2015-01-01

    Motivation: Oscillations lie at the core of many biological processes, from the cell cycle, to circadian oscillations and developmental processes. Time-keeping mechanisms are essential to enable organisms to adapt to varying conditions in environmental cycles, from day/night to seasonal. Transcriptional regulatory networks are one of the mechanisms behind these biological oscillations. However, while identifying cyclically expressed genes from time series measurements is relatively easy, determining the structure of the interaction network underpinning the oscillation is a far more challenging problem. Results: Here, we explicitly leverage the oscillatory nature of the transcriptional signals and present a method for reconstructing network interactions tailored to this special but important class of genetic circuits. Our method is based on projecting the signal onto a set of oscillatory basis functions using a Discrete Fourier Transform. We build a Bayesian Hierarchical model within a frequency domain linear model in order to enforce sparsity and incorporate prior knowledge about the network structure. Experiments on real and simulated data show that the method can lead to substantial improvements over competing approaches if the oscillatory assumption is met, and remains competitive also in cases it is not. Availability: DSS, experiment scripts and data are available at http://homepages.inf.ed.ac.uk/gsanguin/DSS.zip. Contact: d.trejo-banos@sms.ed.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online. PMID:26177966

  16. Graph partitions and cluster synchronization in networks of oscillators

    NASA Astrophysics Data System (ADS)

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

    2016-09-01

    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.

  17. A Lognormal Recurrent Network Model for Burst Generation during Hippocampal Sharp Waves.

    PubMed

    Omura, Yoshiyuki; Carvalho, Milena M; Inokuchi, Kaoru; Fukai, Tomoki

    2015-10-28

    The strength of cortical synapses distributes lognormally, with a long tail of strong synapses. Various properties of neuronal activity, such as the average firing rates of neurons, the rate and magnitude of spike bursts, the magnitude of population synchrony, and the correlations between presynaptic and postsynaptic spikes, also obey lognormal-like distributions reported in the rodent hippocampal CA1 and CA3 areas. Theoretical models have demonstrated how such a firing rate distribution emerges from neural network dynamics. However, how the other properties also display lognormal patterns remain unknown. Because these features are likely to originate from neural dynamics in CA3, we model a recurrent neural network with the weights of recurrent excitatory connections distributed lognormally to explore the underlying mechanisms and their functional implications. Using multi-timescale adaptive threshold neurons, we construct a low-frequency spontaneous firing state of bursty neurons. This state well replicates the observed statistical properties of population synchrony in hippocampal pyramidal cells. Our results show that the lognormal distribution of synaptic weights consistently accounts for the observed long-tailed features of hippocampal activity. Furthermore, our model demonstrates that bursts spread over the lognormal network much more effectively than single spikes, implying an advantage of spike bursts in information transfer. This efficiency in burst propagation is not found in neural network models with Gaussian-weighted recurrent excitatory synapses. Our model proposes a potential network mechanism to generate sharp waves in CA3 and associated ripples in CA1 because bursts occur in CA3 pyramidal neurons most frequently during sharp waves.

  18. 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.

  19. 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).

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

    PubMed

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

    2011-06-01

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

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

    PubMed

    Agerskov, Claus

    2016-04-01

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

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

    PubMed

    Agerskov, Claus

    2016-04-01

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

  3. 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.

  4. 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.

  5. 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.

  6. Erosion of synchronization in networks of coupled oscillators.

    PubMed

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

    2015-01-01

    We report erosion of synchronization in networks of coupled phase oscillators, a phenomenon where perfect phase synchronization is unattainable in steady state, even in the limit of infinite coupling. An analysis reveals that the total erosion is separable into the product of terms characterizing coupling frustration and structural heterogeneity, both of which amplify erosion. The latter, however, can differ significantly from degree heterogeneity. Finally, we show that erosion is marked by the reorganization of oscillators according to their node degrees rather than their natural frequencies.

  7. 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.

  8. 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

  9. 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

  10. 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. PMID:26341391

  11. 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

  12. Rapid hippocampal network adaptation to recurring synchronous activity – a role for calcineurin

    PubMed Central

    Casanova, Jose R.; Nishimura, M.; Le, J.; Lam, T. T.; Swann, J. W.

    2013-01-01

    Neuronal networks are thought to gradually adapt to altered neuronal activity over many hours and days. For instance, when activity is increased by suppressing synaptic inhibition, excitatory synaptic transmission is reduced. The underlying compensatory cellular and molecular mechanisms are thought to contribute in important ways to maintaining normal network operations. Seizures, due to their massive and highly synchronized discharging, probably challenge the adaptive properties of neurons, especially when seizures are frequent and intense – a condition common in early childhood. In the experiments reported here, we used hippocampal slice cultures to explore the effects that recurring seizure-like activity had on the developing hippocampus. We found that developing networks adapted rapidly to recurring synchronized activity in that the duration of seizure-like events was reduced by 42% after 4 h of activity. At the same time, the frequency of spontaneous excitatory postsynaptic currents in pyramidal cells, the expression of biochemical biomarkers for glutamatergic synapses and the branching of pyramidal cell dendrites were all dramatically reduced. Experiments also showed that the reduction in N-methyl-D-aspartate receptor subunits and postsynaptic density protein 95 expression were N-methyl-D-aspartate receptor-dependent. To explore calcium signaling mechanisms in network adaptation, we tested inhibitors of calcineurin, a protein phosphatase known to play roles in synaptic plasticity and activity-dependent dendrite remodeling. We found that FK506 was able to prevent all of the electrophysiological, biochemical, and anatomical changes produced by synchronized network activity. Our results showed that hippocampal pyramidal cells and their networks adapted rapidly to intense synchronized activity and that calcineurin played an important role in the underlying processes. PMID:23879713

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

    PubMed Central

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

    2011-01-01

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

  14. 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

  15. Theta and gamma coordination of hippocampal networks during waking and rapid eye movement sleep.

    PubMed

    Montgomery, Sean M; Sirota, Anton; Buzsáki, György

    2008-06-25

    Rapid eye movement (REM) sleep has been considered a paradoxical state because, despite the high behavioral threshold to arousing perturbations, gross physiological patterns in the forebrain resemble those of waking states. To understand how intrahippocampal networks interact during REM sleep, we used 96 site silicon probes to record from different hippocampal subregions and compared the patterns of activity during waking exploration and REM sleep. Dentate/CA3 theta and gamma synchrony was significantly higher during REM sleep compared with active waking. In contrast, gamma power in CA1 and CA3-CA1 gamma coherence showed significant decreases in REM sleep. Changes in unit firing rhythmicity and unit-field coherence specified the local generation of these patterns. Although these patterns of hippocampal network coordination characterized the more common tonic periods of REM sleep (approximately 95% of total REM), we also detected large phasic bursts of local field potential power in the dentate molecular layer that were accompanied by transient increases in the firing of dentate and CA1 neurons. In contrast to tonic REM periods, phasic REM epochs were characterized by higher theta and gamma synchrony among the dentate, CA3, and CA1 regions. These data suggest enhanced dentate processing, but limited CA3-CA1 coordination during tonic REM sleep. In contrast, phasic bursts of activity during REM sleep may provide windows of opportunity to synchronize the hippocampal trisynaptic loop and increase output to cortical targets. We hypothesize that tonic REM sleep may support off-line mnemonic processing, whereas phasic bursts of activity during REM may promote memory consolidation.

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

    NASA Astrophysics Data System (ADS)

    Davison, Elizabeth; Dey, Biswadip; Leonard, Naomi

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

  17. 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.

  18. 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.

  19. 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

  20. 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.

  1. Analysis of torsional oscillations using an artificial neural network

    SciTech Connect

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

    1992-12-01

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

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

    PubMed

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

    2016-06-01

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

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

    PubMed

    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.

  4. 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.

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

    PubMed

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

    2014-03-01

    Network activation triggers a significant energy metabolism increase in both neurons and astrocytes. Questions of the primary neuronal energy substrate (e.g., glucose vs. lactate) as well as the relative contributions of glycolysis and oxidative phosphorylation and their cellular origin (neurons vs. astrocytes) are still a matter of debates. Using simultaneous measurements of electrophysiological and metabolic parameters during synaptic stimulation in hippocampal slices from mature mice, we show that neurons and astrocytes use both glycolysis and oxidative phosphorylation to meet their energy demands. Supplementation or replacement of glucose in artificial cerebrospinal fluid (ACSF) with pyruvate or lactate strongly modifies parameters related to network activity-triggered energy metabolism. These effects are not induced by changes in ATP content, pH(i), [Ca(2+)](i) or accumulation of reactive oxygen species. Our results suggest that during network activation, a significant fraction of NAD(P)H response (its overshoot phase) corresponds to glycolysis and the changes in cytosolic NAD(P)H and mitochondrial FAD are coupled. Our data do not support the hypothesis of a preferential utilization of astrocyte-released lactate by neurons during network activation in slices--instead, we show that during such activity glucose is an effective energy substrate for both neurons and astrocytes.

  6. 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

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

    PubMed Central

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

    2014-01-01

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

  8. 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.

  9. Visual confrontation naming and hippocampal function: A neural network study using quantitative (1)H magnetic resonance spectroscopy.

    PubMed

    Sawrie, S M; Martin, R C; Gilliam, F G; Faught, R E; Maton, B; Hugg, J W; Bush, N; Sinclair, K; Kuzniecky, R I

    2000-04-01

    Prior research on the relationship between visual confrontation naming and hippocampal function has been inconclusive. The present study examined this relationship using quantitative (1)H magnetic resonance spectroscopy ((1)H-MRS) to operationalize the function of the left and right hippocampi. The 60-item Boston Naming Test (BNT) was used to measure naming. Our sample included 46 patients with medically intractable, focal mesial temporal lobe epilepsy who had been screened for all pathology other than mesial temporal sclerosis. Statistics included Pearson correlations and neural network analysis (multilayer perceptron and radial basis function). Baseline BNT performance correlated significantly with left (1)H-MRS hippocampal ratios. Thirty-six per cent of the variance in baseline BNT performance was explained by a neural network model using left and right (1)H-MRS ratios(creatine/N-acetylaspartate) as input. This was elevated to 49% when input from the right hippocampus was lesioned mathematically. In a second model, left (1)H-MRS hippocampal ratios were modelled using measures of semantic and episodic memory as input (including the BNT). Explained variance in left (1)H-MRS hippocampal ratios fell from 60.8 to 3.6% when input from BNT and another semantic memory measure was degraded mathematically. These results provide evidence that the speech-dominant hippocampus is a significant component of the overall neuroanatomical network of visual confrontation naming. Clinical and theoretical implications are explored.

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

    PubMed

    Dabaghian, Y

    2016-06-01

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

  11. Accuracy of hippocampal network activity is disrupted by neuroinflammation: rescue by memantine

    PubMed Central

    Ramirez-Amaya, V.; Vazdarjanova, A.; Esparza, E. E.; Larkin, P. B.; Fike, J. R.; Wenk, G. L.; Barnes, C. A.

    2009-01-01

    Understanding how the hippocampus processes episodic memory information during neuropathological conditions is important for treatment and prevention applications. Previous data have shown that during chronic neuroinflammation the expression of the plasticity related behaviourally-induced immediate early gene Arc is altered within the CA3 and the dentate gyrus; both of these hippocampal regions show a pronounced increase in activated microglia. Low doses of memantine, a low to moderate affinity open channel uncompetitive N-Methyl-d-aspartate receptor antagonist, reduce neuroinflammation, return Arc expression to control levels and attenuate cognitive deficits induced by lipopolysaccharide. Here we investigate whether neuroinflammation affects the accuracy of information processing in the CA3 and CA1 hippocampal regions and if this is modified by memantine treatment. Using the immediate early gene-based brain-imaging method called cellular analysis of temporal activity by fluorescence in situ hybridization, it is possible to detect primary transcripts at the genomic alleles; this provides exceptional temporal and cellular resolution and facilitates the mapping of neuronal activity. Here, we use this method to compare the neuronal populations activated by two separate experiences in CA1 and CA3 and evaluate the accuracy of information processing during chronic neuroinflammation. Our results show that the CA3 pyramidal neuron activity is not stable between two exposures to the same environment context or two different contexts. CA1 networks, however, do not differ from control conditions. These data suggest that during chronic neuroinflammation, the CA3 networks show a disrupted ability to encode spatial information, and that CA1 neurons can work independently of CA3. Importantly, memantine treatment is able to partially normalize information processing in the hippocampus, suggesting that when given early during the development of the pathology memantine confers

  12. Undamped Oscillations Generated by Hopf Bifurcations in Fractional-Order Recurrent Neural Networks With Caputo Derivative.

    PubMed

    Xiao, Min; Zheng, Wei Xing; Jiang, Guoping; Cao, Jinde

    2015-12-01

    In this paper, a fractional-order recurrent neural network is proposed and several topics related to the dynamics of such a network are investigated, such as the stability, Hopf bifurcations, and undamped oscillations. The stability domain of the trivial steady state is completely characterized with respect to network parameters and orders of the commensurate-order neural network. Based on the stability analysis, the critical values of the fractional order are identified, where Hopf bifurcations occur and a family of oscillations bifurcate from the trivial steady state. Then, the parametric range of undamped oscillations is also estimated and the frequency and amplitude of oscillations are determined analytically and numerically for such commensurate-order networks. Meanwhile, it is shown that the incommensurate-order neural network can also exhibit a Hopf bifurcation as the network parameter passes through a critical value which can be determined exactly. The frequency and amplitude of bifurcated oscillations are determined.

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

    PubMed

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

    2015-10-25

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

  14. 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

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

    PubMed Central

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

    2015-01-01

    Neuronal circuits' ability to maintain the delicate balance between stability and flexibility in changing environments is critical for normal neuronal functioning. However, to what extent individual neurons and neuronal populations maintain internal firing properties remains largely unknown. In this study, we show that distributions of spontaneous population firing rates and synchrony are subject to accurate homeostatic control following increase of synaptic inhibition in cultured hippocampal networks. Reduction in firing rate triggered synaptic and intrinsic adaptive responses operating as global homeostatic mechanisms to maintain firing macro-stability, without achieving local homeostasis at the single-neuron level. Adaptive mechanisms, while stabilizing population firing properties, reduced short-term facilitation essential for synaptic discrimination of input patterns. Thus, invariant ongoing population dynamics emerge from intrinsically unstable activity patterns of individual neurons and synapses. The observed differences in the precision of homeostatic control at different spatial scales challenge cell-autonomous theory of network homeostasis and suggest the existence of network-wide regulation rules. DOI: http://dx.doi.org/10.7554/eLife.04378.001 PMID:25556699

  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

    2015-01-01

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

  17. Theta phase segregation of input-specific gamma patterns in entorhinal-hippocampal networks

    PubMed Central

    Schomburg, Erik W.; Fernández-Ruiz, Antonio; Mizuseki, Kenji; Berényi, Antal; Anastassiou, Costas A.; Koch, Christof; Buzsáki, György

    2014-01-01

    SUMMARY Precisely how rhythms support neuronal communication remains obscure. We investigated interregional coordination of gamma oscillations using high-density electrophysiological recordings in the rat hippocampus and entorhinal cortex. We found that 30–80 Hz gamma dominated CA1 local field potentials (LFP) on the descending phase of CA1 theta waves during navigation, with 60–120 Hz gamma at the theta peak. These signals corresponded to CA3 and entorhinal input, respectively. Above 50 Hz, interregional phase-synchronization of principal cell spikes occurred mostly for LFPs in the axonal target domain. CA1 pyramidal cells were phase-locked mainly to fast gamma (>100 Hz) LFP patterns restricted to CA1, which were strongest at the theta trough. While theta-phase coordination of spiking across entorhinal-hippocampal regions depended on memory demands, LFP gamma patterns below 100 Hz in the hippocampus were consistently layer-specific and largely reflected afferent activity. Gamma synchronization as a mechanism for interregional communication thus rapidly loses efficacy at higher frequencies. PMID:25263753

  18. 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. PMID:27497065

  19. 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.

  20. 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.

  1. 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

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

    PubMed

    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.

  3. 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.

  4. 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.

  5. Decoherence in a system of strongly coupled quantum oscillators. I. Symmetric network

    SciTech Connect

    Ponte, M.A. de; Oliveira, M.C. de; Moussa, M.H.Y.

    2004-08-01

    In this work we analyze the coherence dynamics and estimate decoherence times of quantum states in a network composed of N coupled dissipative quantum oscillators. We assume a symmetric network where all oscillators are coupled to each other with the same coupling strength. Master equations are derived for regimes of both weak and strong coupling between the oscillators. The strong coupling regime is characterized by the coupling strength between the oscillators or by the number of oscillators in the network. The decoherence times of particular states of the network are computed and the results are clarified by analyzing the processes of state swap and recurrence of reduced states of the network together with the linear entropies of the joint and reduced systems.

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

    PubMed

    Nishimura, Motoshi; Nakatsuka, Hiroki; Natsume, Kiyohisa

    2012-01-01

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

  7. 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.

  8. 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.

  9. 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.

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

    PubMed

    Heerebout, Bram T; Phaf, R Hans

    2010-05-01

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

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

    PubMed

    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 2N 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.

  12. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2011-04-01

    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.

  14. 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

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

    PubMed

    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.

  16. 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.

  17. Spatial memory extinction differentially affects dorsal and ventral hippocampal metabolic activity and associated functional brain networks.

    PubMed

    Méndez-Couz, Marta; González-Pardo, Héctor; Vallejo, Guillermo; Arias, Jorge L; Conejo, Nélida M

    2016-10-01

    Previous studies showed the involvement of brain regions associated with both spatial learning and associative learning in spatial memory extinction, although the specific role of the dorsal and ventral hippocampus and the extended hippocampal system including the mammillary body in the process is still controversial. The present study aimed to identify the involvement of the dorsal and ventral hippocampus, together with cortical regions, the amygdaloid nuclei, and the mammillary bodies in the extinction of a spatial memory task. To address these issues, quantitative cytochrome c oxidase histochemistry was applied as a metabolic brain mapping method. Rats were trained in a reference memory task using the Morris water maze, followed by an extinction procedure of the previously acquired memory task. Results show that rats learned successfully the spatial memory task as shown by the progressive decrease in measured latencies to reach the escape platform and the results obtained in the probe test. Spatial memory was subsequently extinguished as shown by the descending preference for the previously reinforced location. A control naïve group was added to ensure that brain metabolic changes were specifically related with performance in the spatial memory extinction task. Extinction of the original spatial learning task significantly modified the metabolic activity in the dorsal and ventral hippocampus, the amygdala and the mammillary bodies. Moreover, the ventral hippocampus, the lateral mammillary body and the retrosplenial cortex were differentially recruited in the spatial memory extinction task, as shown by group differences in brain metabolic networks. These findings provide new insights on the brain regions and functional brain networks underlying spatial memory, and specifically spatial memory extinction. © 2016 Wiley Periodicals, Inc.

  18. Spatial memory extinction differentially affects dorsal and ventral hippocampal metabolic activity and associated functional brain networks.

    PubMed

    Méndez-Couz, Marta; González-Pardo, Héctor; Vallejo, Guillermo; Arias, Jorge L; Conejo, Nélida M

    2016-10-01

    Previous studies showed the involvement of brain regions associated with both spatial learning and associative learning in spatial memory extinction, although the specific role of the dorsal and ventral hippocampus and the extended hippocampal system including the mammillary body in the process is still controversial. The present study aimed to identify the involvement of the dorsal and ventral hippocampus, together with cortical regions, the amygdaloid nuclei, and the mammillary bodies in the extinction of a spatial memory task. To address these issues, quantitative cytochrome c oxidase histochemistry was applied as a metabolic brain mapping method. Rats were trained in a reference memory task using the Morris water maze, followed by an extinction procedure of the previously acquired memory task. Results show that rats learned successfully the spatial memory task as shown by the progressive decrease in measured latencies to reach the escape platform and the results obtained in the probe test. Spatial memory was subsequently extinguished as shown by the descending preference for the previously reinforced location. A control naïve group was added to ensure that brain metabolic changes were specifically related with performance in the spatial memory extinction task. Extinction of the original spatial learning task significantly modified the metabolic activity in the dorsal and ventral hippocampus, the amygdala and the mammillary bodies. Moreover, the ventral hippocampus, the lateral mammillary body and the retrosplenial cortex were differentially recruited in the spatial memory extinction task, as shown by group differences in brain metabolic networks. These findings provide new insights on the brain regions and functional brain networks underlying spatial memory, and specifically spatial memory extinction. © 2016 Wiley Periodicals, Inc. PMID:27102086

  19. 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

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

    PubMed

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

    2016-01-01

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

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

    PubMed

    Hasan; Kalkofen; van Ballegooijen AA

    2000-05-20

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

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

    NASA Astrophysics Data System (ADS)

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

    2007-06-01

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

  3. 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

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

    PubMed

    Hoseini, Mahmood S; Wessel, Ralf

    2016-01-01

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

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

    PubMed

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

    2016-10-01

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

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

    PubMed Central

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

    2015-01-01

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

  7. Genetic oscillation deduced from Hopf bifurcation in a genetic regulatory network with delays.

    PubMed

    Xiao, Min; Cao, Jinde

    2008-09-01

    To understand how a gene regulatory network functioning as an oscillator is built, a genetic regulatory network with two transcriptional delays is investigated. We show by mathematical analysis and simulation that autorepression of mRNA and protein can provide a mechanism for the intracellular oscillator. Based on the linear stability approach and bifurcation theory, sufficient conditions for the oscillation of the genetic networks are derived, and critical values of Hopf bifurcation are assessed. In particular, the genetic network can exhibit Hopf bifurcation(oscillation appears) as the sum of delays or transcriptional rate passes through some critical values. Moreover, the robustness of amplitudes against change in delay can also be obtained from the delayed genetic network; period of oscillation increases with the total time delay in an almost linear way. While it is exactly opposite for transcriptional rate, the amplitude of oscillations always increases as the transcriptional rate increases; the robustness of period against change in the transcriptional rate occurs. Some simple genetic regulatory networks are used to study the impact of delays and transcriptional rate on the system dynamics where there are delays.

  8. Phase resetting for a network of oscillators via phase response curve approach.

    PubMed

    Efimov, D

    2015-02-01

    The problem of phase regulation for a population of oscillating systems is considered. The proposed control strategy is based on a phase response curve (PRC) model of an oscillator (the first-order reduced model obtained for linearized system and inputs with infinitesimal amplitude). It is proven that the control provides phase resetting for the original nonlinear system. Next, the problem of phase resetting for a network of oscillators is considered when applying a common control input. Performance of the obtained solutions is demonstrated via computer simulation for three different models of circadian/neural oscillators. PMID:25246107

  9. The role of axonal delay in the synchronization of networks of coupled cortical oscillators.

    PubMed

    Crook, S M; Ermentrout, G B; Vanier, M C; Bower, J M

    1997-04-01

    Coupled oscillator models use a single phase variable to approximate the voltage oscillation of each neuron during repetitive firing where the behavior of the model depends on the connectivity and the interaction function chosen to describe the coupling. We introduce a network model consisting of a continuum of these oscillators that includes the effects of spatially decaying coupling and axonal delay. We derive equations for determining the stability of solutions and analyze the network behavior for two different interaction functions. The first is a sine function, and the second is derived from a compartmental model of a pyramidal cell. In both cases, the system of coupled neural oscillators can undergo a bifurcation from synchronous oscillations to waves. The change in qualitative behavior is due to the axonal delay, which causes distant connections to encourage a phase shift between cells. We suggest that this mechanism could contribute to the behavior observed in several neurobiological systems.

  10. Disorder-induced dynamics in a pair of coupled heterogeneous phase oscillator networks.

    PubMed

    Laing, Carlo R

    2012-12-01

    We consider a pair of coupled heterogeneous phase oscillator networks and investigate their dynamics in the continuum limit as the intrinsic frequencies of the oscillators are made more and more disparate. The Ott/Antonsen Ansatz is used to reduce the system to three ordinary differential equations. We find that most of the interesting dynamics, such as chaotic behaviour, can be understood by analysing a gluing bifurcation of periodic orbits; these orbits can be thought of as "breathing chimeras" in the limit of identical oscillators. We also add Gaussian white noise to the oscillators' dynamics and derive a pair of coupled Fokker-Planck equations describing the dynamics in this case. Comparison with simulations of finite networks of oscillators is used to confirm many of the results.

  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. Rapid Throughput Analysis Demonstrates that Chemicals with Distinct Seizurogenic Mechanisms Differentially Alter Ca2+ Dynamics in Networks Formed by Hippocampal Neurons in Culture

    PubMed Central

    Cao, Zhengyu; Zou, Xiaohan; Cui, Yanjun; Hulsizer, Susan; Lein, Pamela J.; Wulff, Heike

    2015-01-01

    Primary cultured hippocampal neurons (HN) form functional networks displaying synchronous Ca2+ oscillations (SCOs) whose patterns influence plasticity. Whether chemicals with distinct seizurogenic mechanisms differentially alter SCO patterns was investigated using mouse HN loaded with the Ca2+ indicator fluo-4-AM. Intracellular Ca2+ dynamics were recorded from 96 wells simultaneously in real-time using fluorescent imaging plate reader. Although quiescent at 4 days in vitro (DIV), HN acquired distinctive SCO patterns as they matured to form extensive dendritic networks by 16 DIV. Challenge with kainate, a kainate receptor (KAR) agonist, 4-aminopyridine (4-AP), a K+ channel blocker, or pilocarpine, a muscarinic acetylcholine receptor agonist, caused distinct changes in SCO dynamics. Kainate at <1 µM produced a rapid rise in baseline Ca2+ (Phase I response) associated with high-frequency and low-amplitude SCOs (Phase II response), whereas SCOs were completely repressed with >1 µM kainate. KAR competitive antagonist CNQX [6-cyano-7-nitroquinoxaline-2,3-dione] (1-10 µM) normalized Ca2+ dynamics to the prekainate pattern. Pilocarpine lacked Phase I activity but caused a sevenfold prolongation of Phase II SCOs without altering either their frequency or amplitude, an effect normalized by atropine (0.3–1 µM). 4-AP (1–30 µM) elicited a delayed Phase I response associated with persistent high-frequency, low-amplitude SCOs, and these disturbances were mitigated by pretreatment with the KCa activator SKA-31 [naphtho[1,2-d]thiazol-2-ylamine]. Consistent with its antiepileptic and neuroprotective activities, nonselective voltage-gated Na+ and Ca2+ channel blocker lamotrigine partially resolved kainate- and pilocarpine-induced Ca2+ dysregulation. This rapid throughput approach can discriminate among distinct seizurogenic mechanisms that alter Ca2+ dynamics in neuronal networks and may be useful in screening antiepileptic drug candidates. PMID:25583085

  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. 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

  15. 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

  16. 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

  17. 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.

  18. 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.

  19. 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

  20. 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. PMID:22463016

  1. 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

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

    PubMed

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

    2015-01-01

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

  3. 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.

  4. A transient-chaotic autoassociative network (TCAN) based on Lee oscillators.

    PubMed

    Lee, R T

    2004-09-01

    In the past few decades, neural networks have been extensively adopted in various applications ranging from simple synaptic memory coding to sophisticated pattern recognition problems such as scene analysis. Moreover, current studies on neuroscience and physiology have reported that in a typical scene segmentation problem our major senses of perception (e.g., vision, olfaction, etc.) are highly involved in temporal (or what we call "transient") nonlinear neural dynamics and oscillations. This paper is an extension of the author's previous work on the dynamic neural model (EGDLM) of memory processing and on composite neural oscillators for scene segmentation. Moreover, it is inspired by the work of Aihara et al. and Wang on chaotic neural oscillators in pattern association. In this paper, the author proposes a new transient chaotic neural oscillator, namely the "Lee oscillator," to provide temporal neural coding and an information processing scheme. To illustrate its capability for memory association, a chaotic autoassociative network, namely the Transient-Chaotic Auto-associative Network (TCAN) was constructed based on the Lee oscillator. Different from classical autoassociators such as the celebrated Hopfield network, which provides a "time-independent" pattern association, the TCAN provides a remarkable progressive memory association scheme [what we call "progressive memory recalling" (PMR)] during the transient chaotic memory association. This is exactly consistent with the latest research in psychiatry and perception psychology on dynamic memory recalling schemes.

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

    NASA Astrophysics Data System (ADS)

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

    2015-03-01

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

  6. Neural oscillations: beta band activity across motor networks.

    PubMed

    Khanna, Preeya; Carmena, Jose M

    2015-06-01

    Local field potential (LFP) activity in motor cortical and basal ganglia regions exhibits prominent beta (15-40Hz) oscillations during reaching and grasping, muscular contraction, and attention tasks. While in vitro and computational work has revealed specific mechanisms that may give rise to the frequency and duration of this oscillation, there is still controversy about what behavioral processes ultimately drive it. Here, simultaneous behavioral and large-scale neural recording experiments from non-human primate and human subjects are reviewed in the context of specific hypotheses about how beta band activity is generated. Finally, a new experimental paradigm utilizing operant conditioning combined with motor tasks is proposed as a way to further investigate this oscillation. PMID:25528615

  7. 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

  8. 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.

  9. 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

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

    PubMed

    Suffczynski, Piotr; Crone, Nathan E; Franaszczuk, Piotr J

    2014-12-01

    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

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

    PubMed

    Goto, Hayato

    2016-01-01

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

  12. 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

  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. 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.

  15. 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.

  16. 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.

  17. The network method for solutions of oscillating reaction-diffusion systems

    SciTech Connect

    Horno, J.; Hayas, A.; Gonzalez-Fernandez, C.F.

    1995-05-01

    The network approach is a method whereby physicochemical systems are replaced by electrical networks, which are simulated by using a digital computer program such as PSPICE. The network method solves problems of great mathematical complexity in a versatile and efficient way. This method has been applied to a system involving coupled chemical reactions and diffusion (Brusselator system) as a prototype of an oscillating reaction system. 10 refs., 7 figs., 1 tab.

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

    PubMed

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

    2006-12-01

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

  19. Coexistence of regular and irregular dynamics in complex networks of pulse-coupled oscillators.

    PubMed

    Timme, Marc; Wolf, Fred; Geisel, Theo

    2002-12-16

    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.

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

    PubMed

    Werner, Sebastian; Lehnertz, Klaus

    2015-07-01

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

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

    SciTech Connect

    He, Zhiwei; Sun, Yong; Zhan, Meng

    2013-12-15

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

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

    PubMed

    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.

  3. 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.

  4. 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.

  5. 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.

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

    PubMed

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

    2016-10-01

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

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

    NASA Astrophysics Data System (ADS)

    Clarke, Bruce L.

    1992-08-01

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

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

    PubMed Central

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

    2014-01-01

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

  9. 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.

  10. Amplitude distribution of stochastic oscillations in biochemical networks due to intrinsic noise

    PubMed Central

    2009-01-01

    Intrinsic noise is a common phenomenon in biochemical reaction networks and may affect the occurence and amplitude of sustained oscillations in the states of the network. To evaluate properties of such oscillations in the time domain, it is usually required to conduct long-term stochastic simulations, using for example the Gillespie algorithm. In this paper, we present a new method to compute the amplitude distribution of the oscillations without the need for long-term stochastic simulations. By the derivation of the method, we also gain insight into the structural features underlying the stochastic oscillations. The method is applicable to a wide class of non-linear stochastic differential equations that exhibit stochastic oscillations. The application is exemplified for the MAPK cascade, a fundamental element of several biochemical signalling pathways. This example shows that the proposed method can accurately predict the amplitude distribution for the stochastic oscillations even when using further computational approximations. PACS Codes: 87.10.Mn, 87.18.Tt, 87.18.Vf MSC Codes: 92B05, 60G10, 65C30 PMID:19919689

  11. 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.

  12. Adaptive oscillator networks with conserved overall coupling: Sequential firing and near-synchronized states

    NASA Astrophysics Data System (ADS)

    Picallo, Clara B.; Riecke, Hermann

    2011-03-01

    Motivated by recent observations in neuronal systems we investigate all-to-all networks of nonidentical oscillators with adaptive coupling. The adaptation models spike-timing-dependent plasticity in which the sum of the weights of all incoming links is conserved. We find multiple phase-locked states that fall into two classes: near-synchronized states and splay states. Among the near-synchronized states are states that oscillate with a frequency that depends only very weakly on the coupling strength and is essentially given by the frequency of one of the oscillators, which is, however, neither the fastest nor the slowest oscillator. In sufficiently large networks the adaptive coupling is found to develop effective network topologies dominated by one or two loops. This results in a multitude of stable splay states, which differ in their firing sequences. With increasing coupling strength their frequency increases linearly and the oscillators become less synchronized. The essential features of the two classes of states are captured analytically in perturbation analyses of the extended Kuramoto model used in the simulations.

  13. 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

  14. 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.

  15. 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.

  16. 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.

  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. Adaptive synchronization in delay-coupled networks of Stuart-Landau oscillators.

    PubMed

    Selivanov, Anton A; Lehnert, Judith; Dahms, Thomas; Hövel, Philipp; Fradkov, Alexander L; Schöll, Eckehard

    2012-01-01

    We consider networks of delay-coupled Stuart-Landau oscillators. In these systems, the coupling phase has been found to be a crucial control parameter. By proper choice of this parameter one can switch between different synchronous oscillatory states of the network. Applying the speed-gradient method, we derive an adaptive algorithm for an automatic adjustment of the coupling phase such that a desired state can be selected from an otherwise multistable regime. We propose goal functions based on both the difference of the oscillators and a generalized order parameter and demonstrate that the speed-gradient method allows one to find appropriate coupling phases with which different states of synchronization, e.g., in-phase oscillation, splay, or various cluster states, can be selected.

  19. Mobility and density induced amplitude death in metapopulation networks of coupled oscillators.

    PubMed

    Shen, Chuansheng; Chen, Hanshuang; Hou, Zhonghuai

    2014-12-01

    We investigate the effects of mobility and density on the amplitude death of coupled Landau-Stuart oscillators and Brusselators in metapopulation networks, wherein each node represents a subpopulation occupied any number of mobile individuals. By numerical simulations in scale-free topology, we find that the systems undergo phase transitions from incoherent state to amplitude death, and then to frequency synchronization with increasing the mobility rate or density of oscillators. Especially, there exists an extent of intermediate mobility rate and density that can lead to global oscillator death. Furthermore, we show that such nontrivial phenomena are robust to diverse network topologies. Our findings may invoke further efforts and attentions to explore the underlying mechanism of collective behaviors in coupled metapopulation systems.

  20. Back to the Future: Preserved Hippocampal Network Activity during Reverse Ambulation

    PubMed Central

    Maurer, Andrew P.; Lester, Adam W.; Burke, Sara N.; Ferng, Jonathan J.

    2014-01-01

    During movement, there is a transition of activity across the population, such that place-field centers ahead of the rat are sequentially activated in the order that they will be encountered. Although the mechanisms responsible for this sequence updating are unknown, two classes of models can be considered. The first class involves head-direction information for activating neurons in the order that their place fields will be traversed. An alternative model contends that motion and turn-related information from the posterior parietal cortex shift the subset of active hippocampal cells across the population. To explicitly test these two models, rodents were trained to run backward on a linear track, placing movement in opposition with head orientation. Although head-direction did not change between running conditions, place-field activity remapped and there was an increase in place-field size during backward running compared with forward. The population activity, however, could still be used to reconstruct the location of the rat accurately. Moreover, theta phase precession was maintained in both running conditions, indicating preservation of place-field sequences on short-time scales. The observation that sequence encoding persists even when the animal is orientated away from the direction of movement favors the concept that posterior parietal cortical mechanisms may be partially responsible for updating hippocampal activity patterns. PMID:25378167

  1. 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.

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

    NASA Astrophysics Data System (ADS)

    José, Jorge V.; Tiesinga, Paul

    2003-05-01

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

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

    PubMed

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

    2016-09-01

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

  4. 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

  5. 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.

  6. 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

  7. 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

  8. 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.

  9. 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.

  10. 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.

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

    NASA Astrophysics Data System (ADS)

    Bressloff, P. C.; Coombes, S.

    1998-09-01

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

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

    PubMed

    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. PMID:27627319

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

    PubMed

    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.

  14. 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.

  15. Generalized synchronization in mutually coupled oscillators and complex networks.

    PubMed

    Moskalenko, Olga I; Koronovskii, Alexey A; Hramov, Alexander E; Boccaletti, Stefano

    2012-09-01

    We introduce a concept of generalized synchronization, able to encompass the setting of collective synchronized behavior for mutually coupled systems and networking systems featuring complex topologies in their connections. The onset of the synchronous regime is confirmed by the dependence of the system's Lyapunov exponents on the coupling parameter. The presence of a generalized synchronization regime is verified by means of the nearest neighbor method.

  16. 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.

  17. 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. PMID:25165437

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

    PubMed Central

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

    2014-01-01

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

  19. 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

  20. 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

  1. Inhibition of spontaneous network activity in neonatal hippocampal slices by energy substrates is not correlated with intracellular acidification.

    PubMed

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

    2011-01-01

    Several energy substrates complementary to glucose, including lactate, pyruvate and β-hydroxybutyrate, serve as a fuel for neurons. It was reported recently that these substrates can substantially modulate cortical excitability in neonatal slices. However, complementary energy substrates (CES) can also induce an intracellular acidification when added exogenously. Therefore, action of CES on the neuronal properties governing excitability in neonatal brain slices may be underlain by a change in the cell energy status or by intracellular acidification, or both. Here, we attempt to elucidate these possibilities in neonatal hippocampus by recording neuronal population activity and monitoring intracellular pH. We show that a spontaneous network activity pattern, giant depolarizing potentials (GDPs), characteristic for the neonatal hippocampal slices exposed to artificial cerebrospinal fluid, is strongly inhibited by CES and this effect is unlikely to be caused by a subtle intracellular acidification induced by these compounds. Indeed, a much stronger intracellular acidification in the HCO(3) -free solution inhibited neither the GDP frequency nor the GDP amplitude. Therefore, modulation of neuronal energy homeostasis is the most likely factor underlying the effect of lactate, pyruvate and β-hydroxybutyrate on network excitability in neonatal brain slices.

  2. Neuroprotective effect of piperine on primarily cultured hippocampal neurons.

    PubMed

    Fu, Min; Sun, Zhao-Hui; Zuo, Huan-Cong

    2010-01-01

    It was previously reported that piperine (PIP) significantly blocks convulsions induced by intracerebroventricular injection of threshold doses of kainate, but had no or only slight effects on convulsions induced by L-glutamate, N-methyl-D-aspartate and guanidinosuccinate. In traditional Chinese medicine, black pepper has been used for epileptic treatment; however, the exact mechanism is still unclear. We reported here in that appropriate concentration of PIP effectively inhibites the synchronized oscillation of intracellular calcium in rat hippocampal neuronal networks and represses spontaneous synaptic activities in terms of spontaneous synaptic currents (SSC) and spontaneous excitatory postsynaptic currents (sEPSC). Moreover, pretreatment with PIP expects protective effect on glutamate-induced decrease of cell viability and apoptosis of hippocampal neurons. These data suggest that the neuroprotective effects of PIP might be associated with suppression of synchronization of neuronal networks, presynaptic glutamic acid release, and Ca(2+) overloading.

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

    PubMed Central

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

    2013-01-01

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

  4. 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

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

    PubMed

    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

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

    PubMed

    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.

  7. Empathy in hippocampal amnesia.

    PubMed

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

    2013-01-01

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

  8. Empathy in Hippocampal Amnesia

    PubMed Central

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

    2013-01-01

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

  9. 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. PMID:27348738

  10. 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.

  11. 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

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

    NASA Astrophysics Data System (ADS)

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

    2010-07-01

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

  13. Neural networks with dynamical synapses: From mixed-mode oscillations and spindles to chaos

    NASA Astrophysics Data System (ADS)

    Lee, K.; Goltsev, A. V.; Lopes, M. A.; Mendes, J. F. F.

    2013-01-01

    Understanding of short-term synaptic depression (STSD) and other forms of synaptic plasticity is a topical problem in neuroscience. Here we study the role of STSD in the formation of complex patterns of brain rhythms. We use a cortical circuit model of neural networks composed of irregular spiking excitatory and inhibitory neurons having type 1 and 2 excitability and stochastic dynamics. In the model, neurons form a sparsely connected network and their spontaneous activity is driven by random spikes representing synaptic noise. Using simulations and analytical calculations, we found that if the STSD is absent, the neural network shows either asynchronous behavior or regular network oscillations depending on the noise level. In networks with STSD, changing parameters of synaptic plasticity and the noise level, we observed transitions to complex patters of collective activity: mixed-mode and spindle oscillations, bursts of collective activity, and chaotic behavior. Interestingly, these patterns are stable in a certain range of the parameters and separated by critical boundaries. Thus, the parameters of synaptic plasticity can play a role of control parameters or switchers between different network states. However, changes of the parameters caused by a disease may lead to dramatic impairment of ongoing neural activity. We analyze the chaotic neural activity by use of the 0-1 test for chaos (Gottwald, G. & Melbourne, I., 2004) and show that it has a collective nature.

  14. 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

  15. Fast oscillations in cortical-striatal networks switch frequency following rewarding events and stimulant drugs

    PubMed Central

    Berke, J.D.

    2009-01-01

    Oscillations may organize communication between components of large-scale brain networks. Although gamma-band oscillations have been repeatedly observed in cortical-basal ganglia circuits, their functional roles are not yet clear. Here I show that, in behaving animals, distinct frequencies of ventral striatal local field potential oscillations show coherence with different cortical inputs. ~50Hz gamma oscillations that normally predominate in awake ventral striatum are coherent with piriform cortex, while ~80-100Hz high-gamma oscillations are consistently coherent with frontal cortex. Within striatum, entrainment to gamma rhythms is selective to fast-spiking interneurons (FSIs), with distinct FSI populations entrained to different gamma frequencies. Administration of the psychomotor stimulant amphetamine or the dopamine agonist apomorphine causes a prolonged decrease in ~50Hz power and increase in ~80-100Hz power. The same frequency switch is observed for shorter epochs spontaneously in awake, undrugged animals, and is consistently provoked for <1s following reward receipt. Individual striatal neurons can participate in these brief high-gamma bursts with, or without, substantial changes in firing rate. Switching between discrete oscillatory states may allow different modes of information processing during decision-making and reinforcement-based learning, and may also be an important systems-level process by which stimulant drugs affect cognition and behavior. PMID:19659455

  16. 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.

  17. Biological oscillations for learning walking coordination: dynamic recurrent neural network functionally models physiological central pattern generator.

    PubMed

    Hoellinger, Thomas; Petieau, Mathieu; Duvinage, Matthieu; Castermans, Thierry; Seetharaman, Karthik; Cebolla, Ana-Maria; Bengoetxea, Ana; Ivanenko, Yuri; Dan, Bernard; Cheron, Guy

    2013-01-01

    The existence of dedicated neuronal modules such as those organized in the cerebral cortex, thalamus, basal ganglia, cerebellum, or spinal cord raises the question of how these functional modules are coordinated for appropriate motor behavior. Study of human locomotion offers an interesting field for addressing this central question. The coordination of the elevation of the 3 leg segments under a planar covariation rule (Borghese et al., 1996) was recently modeled (Barliya et al., 2009) by phase-adjusted simple oscillators shedding new light on the understanding of the central pattern generator (CPG) processing relevant oscillation signals. We describe the use of a dynamic recurrent neural network (DRNN) mimicking the natural oscillatory behavior of human locomotion for reproducing the planar covariation rule in both legs at different walking speeds. Neural network learning was based on sinusoid signals integrating frequency and amplitude features of the first three harmonics of the sagittal elevation angles of the thigh, shank, and foot of each lower limb. We verified the biological plausibility of the neural networks. Best results were obtained with oscillations extracted from the first three harmonics in comparison to oscillations outside the harmonic frequency peaks. Physiological replication steadily increased with the number of neuronal units from 1 to 80, where similarity index reached 0.99. Analysis of synaptic weighting showed that the proportion of inhibitory connections consistently increased with the number of neuronal units in the DRNN. This emerging property in the artificial neural networks resonates with recent advances in neurophysiology of inhibitory neurons that are involved in central nervous system oscillatory activities. The main message of this study is that this type of DRNN may offer a useful model of physiological central pattern generator for gaining insights in basic research and developing clinical applications.

  18. Detection of 5-hydroxytryptamine (5-HT) in vitro using a hippocampal neuronal network-based biosensor with extracellular potential analysis of neurons.

    PubMed

    Hu, Liang; Wang, Qin; Qin, Zhen; Su, Kaiqi; Huang, Liquan; Hu, Ning; Wang, Ping

    2015-04-15

    5-hydroxytryptamine (5-HT) is an important neurotransmitter in regulating emotions and related behaviors in mammals. To detect and monitor the 5-HT, effective and convenient methods are demanded in investigation of neuronal network. In this study, hippocampal neuronal networks (HNNs) endogenously expressing 5-HT receptors were employed as sensing elements to build an in vitro neuronal network-based biosensor. The electrophysiological characteristics were analyzed in both neuron and network levels. The firing rates and amplitudes were derived from signal to determine the biosensor response characteristics. The experimental results demonstrate a dose-dependent inhibitory effect of 5-HT on hippocampal neuron activities, indicating the effectiveness of this hybrid biosensor in detecting 5-HT with a response range from 0.01μmol/L to 10μmol/L. In addition, the cross-correlation analysis of HNNs activities suggests 5-HT could weaken HNN connectivity reversibly, providing more specificity of this biosensor in detecting 5-HT. Moreover, 5-HT induced spatiotemporal firing pattern alterations could be monitored in neuron and network levels simultaneously by this hybrid biosensor in a convenient and direct way. With those merits, this neuronal network-based biosensor will be promising to be a valuable and utility platform for the study of neurotransmitter in vitro.

  19. Intrinsic mechanisms stabilize encoding and retrieval circuits differentially in a hippocampal network model.

    PubMed

    Hummos, Ali; Franklin, Charles C; Nair, Satish S

    2014-12-01

    Acetylcholine regulates memory encoding and retrieval by inducing the hippocampus to switch between pattern separation and pattern completion modes. However, both processes can introduce significant variations in the level of network activity and potentially cause a seizure-like spread of excitation. Thus, mechanisms that keep network excitation within certain bounds are necessary to prevent such instability. We developed a biologically realistic computational model of the hippocampus to investigate potential intrinsic mechanisms that might stabilize the network dynamics during encoding and retrieval. The model was developed by matching experimental data, including neuronal behavior, synaptic current dynamics, network spatial connectivity patterns, and short-term synaptic plasticity. Furthermore, it was constrained to perform pattern completion and separation under the effects of acetylcholine. The model was then used to investigate the role of short-term synaptic depression at the recurrent synapses in CA3, and inhibition by basket cell (BC) interneurons and oriens lacunosum-moleculare (OLM) interneurons in stabilizing these processes. Results showed that when CA3 was considered in isolation, inhibition solely by BCs was not sufficient to control instability. However, both inhibition by OLM cells and short-term depression at the recurrent CA3 connections stabilized the network activity. In the larger network including the dentate gyrus, the model suggested that OLM inhibition could control the network during high cholinergic levels while depressing synapses at the recurrent CA3 connections were important during low cholinergic states. Our results demonstrate that short-term plasticity is a critical property of the network that enhances its robustness. Furthermore, simulations suggested that the low and high cholinergic states can each produce runaway excitation through unique mechanisms and different pathologies. Future studies aimed at elucidating the circuit

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

    NASA Technical Reports Server (NTRS)

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

    2003-01-01

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

  1. Oscillation, Conduction Delays, and Learning Cooperate to Establish Neural Competition in Recurrent Networks.

    PubMed

    Kato, Hideyuki; Ikeguchi, Tohru

    2016-01-01

    Specific memory might be stored in a subnetwork consisting of a small population of neurons. To select neurons involved in memory formation, neural competition might be essential. In this paper, we show that excitable neurons are competitive and organize into two assemblies in a recurrent network with spike timing-dependent synaptic plasticity (STDP) and axonal conduction delays. Neural competition is established by the cooperation of spontaneously induced neural oscillation, axonal conduction delays, and STDP. We also suggest that the competition mechanism in this paper is one of the basic functions required to organize memory-storing subnetworks into fine-scale cortical networks.

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

    PubMed

    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.

  3. Setting Up the Speech Production Network: How Oscillations Contribute to Lateralized Information Routing

    PubMed Central

    Gehrig, Johannes; Wibral, Michael; Arnold, Christiane; Kell, Christian A.

    2012-01-01

    Speech production involves widely distributed brain regions. This MEG study focuses on the spectro-temporal dynamics that contribute to the setup of this network. In 21 participants performing a cue-target reading paradigm, we analyzed local oscillations during preparation for overt and covert reading in the time-frequency domain and localized sources using beamforming. Network dynamics were studied by comparing different dynamic causal models of beta phase coupling in and between hemispheres. While a broadband low frequency effect was found for any task preparation in bilateral prefrontal cortices, preparation for overt speech production was specifically associated with left-lateralized alpha and beta suppression in temporal cortices and beta suppression in motor-related brain regions. Beta phase coupling in the entire speech production network was modulated by anticipation of overt reading. We propose that the processes underlying the setup of the speech production network connect relevant brain regions by means of beta synchronization and prepare the network for left-lateralized information routing by suppression of inhibitory alpha and beta oscillations. PMID:22685442

  4. Selectivity of stimulus induced responses in cultured hippocampal networks on microelectrode arrays.

    PubMed

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

    2016-08-01

    Sensory information can be encoded using the average firing rate and spike occurrence times in neuronal network responses to external stimuli. Decoding or retrieving stimulus characteristics from the response pattern generally implies that the corresponding neural network has a selective response to various input signals. The role of various spiking activity characteristics (e.g., spike rate and precise spike timing) for basic information processing was widely investigated on the level of neural populations but gave inconsistent evidence for particular mechanisms. Multisite electrophysiology of cultured neural networks grown on microelectrode arrays is a recently developed tool and currently an active research area. In this study, we analyzed the stimulus responses represented by network-wide bursts evoked from various spatial locations (electrodes). We found that the response characteristics, such as the burst initiation time and the spike rate, can be used to retrieve information about the stimulus location. The best selectivity in the response spiking pattern could be found for a small subpopulation of neurones (electrodes) at relatively short post-stimulus intervals. Such intervals were unique for each culture due to the non-uniform organization of the functional connectivity in the network during spontaneous development. PMID:27468317

  5. Selectivity of stimulus induced responses in cultured hippocampal networks on microelectrode arrays.

    PubMed

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

    2016-08-01

    Sensory information can be encoded using the average firing rate and spike occurrence times in neuronal network responses to external stimuli. Decoding or retrieving stimulus characteristics from the response pattern generally implies that the corresponding neural network has a selective response to various input signals. The role of various spiking activity characteristics (e.g., spike rate and precise spike timing) for basic information processing was widely investigated on the level of neural populations but gave inconsistent evidence for particular mechanisms. Multisite electrophysiology of cultured neural networks grown on microelectrode arrays is a recently developed tool and currently an active research area. In this study, we analyzed the stimulus responses represented by network-wide bursts evoked from various spatial locations (electrodes). We found that the response characteristics, such as the burst initiation time and the spike rate, can be used to retrieve information about the stimulus location. The best selectivity in the response spiking pattern could be found for a small subpopulation of neurones (electrodes) at relatively short post-stimulus intervals. Such intervals were unique for each culture due to the non-uniform organization of the functional connectivity in the network during spontaneous development.

  6. Effects of μ-opioid receptor modulation on the hippocampal network activity of sharp wave and ripples

    PubMed Central

    Giannopoulos, Panagiotis; Papatheodoropoulos, Costas

    2013-01-01

    Background and Purpose Hippocampus-dependent memory involves the activity of sharp wave ripples (SWRs), which are thought to participate in the process of memory consolidation. The hippocampus contains high levels of endogenous opioids and of μ-opioid receptors (MORs). Here, we have assessed the role of MOR agonists in the modulation of SWRs. Experimental Approach Using recordings of extracellular potentials from the CA1 field of rat hippocampal slices, we examined the pharmacological actions of morphine, DAMGO and fentanyl on SWRs and on network excitability and paired-pulse inhibition. Key Results All three MOR agonists (1 nM–10 μM) significantly increased the amplitude of sharp waves and the occurrence of SWR sequences, but reduced the initiation of episodes of SWRs. Fentanyl was most potent in producing these effects and morphine the least. Interestingly, although SWRs were reduced by relatively high concentrations (≥100 nM) of all agonists, they were significantly enhanced by very low concentrations of morphine (5–10 nM). Morphine and DAMGO at moderate-to-high concentrations increased network excitability and reduced inhibition. Furthermore, DAMGO suppressed inhibition more readily than it increased excitation, whereas morphine suppressed inhibition only at high concentrations. These drug effects were reversed by the MOR antagonists naloxone and CTOP. Conclusions and Implications We found that the SWRs were significantly modulated by three MOR agonists and that the SWRs were very sensitive to subtle changes in the excitation/inhibition balance induced by MOR agonists. Such modulation might underlie the effects of these agonists on hippocampus-dependent memory. PMID:23043226

  7. 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

  8. How synaptic weights determine stability of synchrony in networks of pulse-coupled excitatory and inhibitory oscillators.

    PubMed

    Kriener, Birgit

    2012-09-01

    Under which conditions can a network of pulse-coupled oscillators sustain stable collective activity states? Previously, it was shown that stability of the simplest pattern conceivable, i.e., global synchrony, in networks of symmetrically pulse-coupled oscillators can be decided in a rigorous mathematical fashion, if interactions either all advance or all retard oscillation phases ("mono-interaction network"). Yet, many real-world networks-for example neuronal circuits-are asymmetric and moreover crucially feature both types of interactions. Here, we study complex networks of excitatory (phase-advancing) and inhibitory (phase-retarding) leaky integrate-and-fire (LIF) oscillators. We show that for small coupling strength, previous results for mono-interaction networks also apply here: pulse time perturbations eventually decay if they are smaller than a transmission delay and if all eigenvalues of the linear stability operator have absolute value smaller or equal to one. In this case, the level of inhibition must typically be significantly stronger than that of excitation to ensure local stability of synchrony. For stronger coupling, however, network synchrony eventually becomes unstable to any finite perturbation, even if inhibition is strong and all eigenvalues of the stability operator are at most unity. This new type of instability occurs when any oscillator, inspite of receiving inhibitory input from the network on average, can by chance receive sufficient excitatory input to fire a pulse before all other pulses in the system are delivered, thus breaking the near-synchronous perturbation pattern.

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

    PubMed Central

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

    2015-01-01

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

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

    PubMed

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

    2016-07-01

    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 oscillations during

  11. Mathematical modeling of an oscillating gene circuit to unravel the circadian clock network of Arabidopsis thaliana

    PubMed Central

    Bujdoso, Nora; Davis, Seth J.

    2013-01-01

    The Arabidopsis thaliana circadian clock is an interconnected network highly tractable to systems approaches. Most elements in the transcriptional–translational oscillator were identified by genetic means and the expression of clock genes in various mutants led to the founding hypothesis of a positive–negative feedback loop being the core clock. The identification of additional clock genes beyond those defined in the core led to the use of systems approaches to decipher this angiosperm oscillator circuit. Kinetic modeling was first used to explain periodicity effects of various circadian mutants. This conformed in a flexible way to experimental details. Such observations allowed a recursive use of hypothesis generating from modeling, followed by experimental corroboration. More recently, the biochemical finding of new description of a DNA-binding activity for one class of clock components directed improvements in feature generation, one of which revealed that the core of the oscillator is a negative–negative feedback loop. The recursive use of modeling and experimental validation has thus revealed many essential transcriptional components that drive negative arms in the circadian oscillator. What awaits is to more fully describe the positive arms and an understanding of how additional pathways converge on the clock. PMID:23355842

  12. 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.

  13. 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

  14. Aminergic control of high-frequency (approximately 200 Hz) network oscillations in the hippocampus of the behaving rat.

    PubMed

    Ponomarenko, Alexei A; Knoche, Anja; Korotkova, Tatiana M; Haas, Helmut L

    2003-09-11

    Hippocampal high-frequency (200 Hz, 'ripple') oscillations were recorded in the CA1 area of behaving rats. The histamine H1-receptor antagonist pyrilamine facilitated while the H2-antagonist zolantidine (5 mg/kg i.p) transiently decreased ripple occurrence. Thioperamide, an H3 antagonist, had no effect. The 5-HT1A-receptor antagonist WAY100635 (50 microg i.c.v.) reduced the occurrence and the intrinsic frequency of ripples. The 5-HT3-receptor antagonist Y-25130 (i.c.v.) increased the number but reduced the amplitude of ripples. All the treatments affected sharp-waves and ripple oscillations to the same extent. Changes of ripple occurrence were not secondary to alterations of behavior. In the light of these divergent actions via different receptor subtypes the net effect of aminergic innervations will be determined by their state-dependent activities and mutual interactions as well as receptor localizations. PMID:12902028

  15. Chimeralike states in a network of oscillators under attractive and repulsive global coupling.

    PubMed

    Mishra, Arindam; Hens, Chittaranjan; Bose, Mridul; Roy, Prodyot K; Dana, Syamal K

    2015-12-01

    We report chimeralike states in an ensemble of oscillators using a type of global coupling consisting of two components: attractive and repulsive mean-field feedback. We identify the existence of two types of chimeralike states in a bistable Liénard system; in one type, both the coherent and the incoherent populations are in chaotic states (which we refer to as chaos-chaos chimeralike states) and, in another type, the incoherent population is in periodic state while the coherent population has irregular small oscillation. We find a metastable state in a parameter regime of the Liénard system where the coherent and noncoherent states migrate in time from one to another subpopulation. The relative size of the incoherent subpopulation, in the chimeralike states, remains almost stable with increasing size of the network. The generality of the coupling configuration in the origin of the chimeralike states is tested, using a second example of bistable system, the van der Pol-Duffing oscillator where the chimeralike states emerge as weakly chaotic in the coherent subpopulation and chaotic in the incoherent subpopulation. Furthermore, we apply the coupling, in a simplified form, to form a network of the chaotic Rössler system where both the noncoherent and the coherent subpopulations show chaotic dynamics. PMID:26764787

  16. Chimeralike states in a network of oscillators under attractive and repulsive global coupling

    NASA Astrophysics Data System (ADS)

    Mishra, Arindam; Hens, Chittaranjan; Bose, Mridul; Roy, Prodyot K.; Dana, Syamal K.

    2015-12-01

    We report chimeralike states in an ensemble of oscillators using a type of global coupling consisting of two components: attractive and repulsive mean-field feedback. We identify the existence of two types of chimeralike states in a bistable Liénard system; in one type, both the coherent and the incoherent populations are in chaotic states (which we refer to as chaos-chaos chimeralike states) and, in another type, the incoherent population is in periodic state while the coherent population has irregular small oscillation. We find a metastable state in a parameter regime of the Liénard system where the coherent and noncoherent states migrate in time from one to another subpopulation. The relative size of the incoherent subpopulation, in the chimeralike states, remains almost stable with increasing size of the network. The generality of the coupling configuration in the origin of the chimeralike states is tested, using a second example of bistable system, the van der Pol-Duffing oscillator where the chimeralike states emerge as weakly chaotic in the coherent subpopulation and chaotic in the incoherent subpopulation. Furthermore, we apply the coupling, in a simplified form, to form a network of the chaotic Rössler system where both the noncoherent and the coherent subpopulations show chaotic dynamics.

  17. Partial synchronization in networks of non-linearly coupled oscillators: The Deserter Hubs Model.

    PubMed

    Freitas, Celso; Macau, Elbert; Pikovsky, Arkady

    2015-04-01

    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 nonlinearity of interactions. Under weak force, an oscillator tends to follow the phase of its neighbors, but if an oscillator is compelled to follow its peers by a sufficient large number of cohesive neighbors, then it actually starts to act in the opposite manner, i.e., in anti-phase with the majority. Analytic results yield that if the repulsion parameter is small enough in comparison with the degree of the maximum hub, then the full synchronization state is locally stable. Numerical experiments are performed to explore the model beyond this threshold, where the overall cohesion is lost. We report in detail partially synchronous dynamical regimes, like stationary phase-locking, multistability, periodic and chaotic states. Via statistical analysis of different network organizations like tree, scale-free, and random ones, we found a measure allowing one to predict relative abundance of partially synchronous stationary states in comparison to time-dependent ones.

  18. 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 nonlinearity of interactions. Under weak force, an oscillator tends to follow the phase of its neighbors, but if an oscillator is compelled to follow its peers by a sufficient large number of cohesive neighbors, then it actually starts to act in the opposite manner, i.e., in anti-phase with the majority. Analytic results yield that if the repulsion parameter is small enough in comparison with the degree of the maximum hub, then the full synchronization state is locally stable. Numerical experiments are performed to explore the model beyond this threshold, where the overall cohesion is lost. We report in detail partially synchronous dynamical regimes, like stationary phase-locking, multistability, periodic and chaotic states. Via statistical analysis of different network organizations like tree, scale-free, and random ones, we found a measure allowing one to predict relative abundance of partially synchronous stationary states in comparison to time-dependent ones.

  19. Hippocampal brain-network coordination during volitional exploratory behavior enhances learning.

    PubMed

    Voss, Joel L; Gonsalves, Brian D; Federmeier, Kara D; Tranel, Daniel; Cohen, Neal J

    2011-01-01

    Exploratory behaviors during learning determine what is studied and when, helping to optimize subsequent memory performance. To elucidate the cognitive and neural determinants of exploratory behaviors, we manipulated the control that human subjects had over the position of a moving window through which they studied objects and their locations. Our behavioral, neuropsychological and neuroimaging data indicate that volitional control benefits memory performance and is linked to a brain network that is centered on the hippocampus. Increases in correlated activity between the hippocampus and other areas were associated with specific aspects of memory, which suggests that volitional control optimizes interactions among specialized neural systems through the hippocampus. Memory is therefore an active process that is intrinsically linked to behavior. Furthermore, brain structures that are typically seen as passive participants in memory encoding (for example, the hippocampus) are actually part of an active network that controls behavior dynamically as it unfolds. PMID:21102449

  20. Development of an artificial neuronal network with post-mitotic rat fetal hippocampal cells by polyethylenimine.

    PubMed

    Liu, Bingfang; Ma, Jun; Gao, Erjing; He, Yu; Cui, Fuzhai; Xu, Qunyuan

    2008-03-14

    The selection of appropriate surface materials that promote cellular adhesion and growth is an important consideration when designing a simplified neuronal network in vitro. In the past, extracellular matrix proteins such as laminin (LN) or positively charged substances such as poly-l-lysine (PLL) have been used. In this study, we examined the ability of another positively charged polymer, polyethyleneimine (PEI), to promote neuronal adhesion, growth and the formation of a functional neuronal network in vitro. PEI, PLL and LN were used to produce grid-shape patterns on glass coverslips by micro-contact printing. Post-mitotic neurons from the rat fetal hippocampus were cultured on the different polymers and the viability and morphology of these neurons under serum-free culture conditions were observed using fluorescent microscopy and atomic force microscopy (AFM). We show that neurons cultured on the PEI- and PLL-coated surfaces adhered to and extended neurites along the grid-shape patterns, whereas neurons cultured on the LN-coated coverslips clustered into clumps of cells. In addition, we found that the neurons on the PEI and PLL-coated grids survived for more than 2 weeks in serum-free conditions, whereas most neurons cultured on the LN-coated grids died after 1 week. Using AFM, we observed some neurosynapse-like structures near the neuronal soma on PEI-coated coverslips. These findings indicate that PEI is a suitable surface for establishing a functional neuronal network in vitro.

  1. Tonic GABAA conductance bidirectionally controls interneuron firing pattern and synchronization in the CA3 hippocampal network

    PubMed Central

    Pavlov, Ivan; Savtchenko, Leonid P.; Song, Inseon; Koo, Jaeyeon; Pimashkin, Alexey; Rusakov, Dmitri A.; Semyanov, Alexey

    2014-01-01

    The spiking output of interneurons is key for rhythm generation in the brain. However, what controls interneuronal firing remains incompletely understood. Here we combine dynamic clamp experiments with neural network simulations to understand how tonic GABAA conductance regulates the firing pattern of CA3 interneurons. In baseline conditions, tonic GABAA depolarizes these cells, thus exerting an excitatory action while also reducing the excitatory postsynaptic potential (EPSP) amplitude through shunting. As a result, the emergence of weak tonic GABAA conductance transforms the interneuron firing pattern driven by individual EPSPs into a more regular spiking mode determined by the cell intrinsic properties. The increased regularity of spiking parallels stronger synchronization of the local network. With further increases in tonic GABAA conductance the shunting inhibition starts to dominate over excitatory actions and thus moderates interneuronal firing. The remaining spikes tend to follow the timing of suprathreshold EPSPs and thus become less regular again. The latter parallels a weakening in network synchronization. Thus, our observations suggest that tonic GABAA conductance can bidirectionally control brain rhythms through changes in the excitability of interneurons and in the temporal structure of their firing patterns. PMID:24344272

  2. How synaptic weights determine stability of synchrony in networks of pulse-coupled excitatory and inhibitory oscillators

    NASA Astrophysics Data System (ADS)

    Kriener, Birgit

    2012-09-01

    Under which conditions can a network of pulse-coupled oscillators sustain stable collective activity states? Previously, it was shown that stability of the simplest pattern conceivable, i.e., global synchrony, in networks of symmetrically pulse-coupled oscillators can be decided in a rigorous mathematical fashion, if interactions either all advance or all retard oscillation phases ("mono-interaction network"). Yet, many real-world networks—for example neuronal circuits—are asymmetric and moreover crucially feature both types of interactions. Here, we study complex networks of excitatory (phase-advancing) and inhibitory (phase-retarding) leaky integrate-and-fire (LIF) oscillators. We show that for small coupling strength, previous results for mono-interaction networks also apply here: pulse time perturbations eventually decay if they are smaller than a transmission delay and if all eigenvalues of the linear stability operator have absolute value smaller or equal to one. In this case, the level of inhibition must typically be significantly stronger than that of excitation to ensure local stability of synchrony. For stronger coupling, however, network synchrony eventually becomes unstable to any finite perturbation, even if inhibition is strong and all eigenvalues of the stability operator are at most unity. This new type of instability occurs when any oscillator, inspite of receiving inhibitory input from the network on average, can by chance receive sufficient excitatory input to fire a pulse before all other pulses in the system are delivered, thus breaking the near-synchronous perturbation pattern.

  3. Quantifying biomarkers of cognitive dysfunction and neuronal network hyperexcitability in mouse models of Alzheimer's disease: depletion of calcium-dependent proteins and inhibitory hippocampal remodeling.

    PubMed

    Palop, Jorge J; Mucke, Lennart; Roberson, Erik D

    2011-01-01

    High levels of Aβ impair neuronal function at least in part by disrupting normal synaptic transmission and causing dysfunction of neural networks. This network dysfunction includes abnormal synchronization of neuronal activity resulting in epileptiform activity. Over time, this aberrant network activity can lead to the depletion of calcium-dependent proteins, such as calbindin, Fos, and Arc, and compensatory inhibitory remodeling of hippocampal circuits, including GABAergic sprouting and ectopic expression of the inhibitory neuropeptide Y (NPY) in dentate granule cells. Here we present detailed protocols for detecting and quantifying these alterations in mouse models of Alzheimer's disease (AD) by immunohistochemistry. These methods are useful as surrogate measures for detecting chronic aberrant network activity in models of AD and epilepsy. In addition, since we have found that the severity of these changes relates to the degree of Aβ-dependent cognitive impairments, the protocols are useful for quantifying biomarkers of cognitive impairment in mouse models of AD.

  4. Phase synchrony facilitates binding and segmentation of natural images in a coupled neural oscillator network

    PubMed Central

    Finger, Holger; König, Peter

    2014-01-01

    Synchronization has been suggested as a mechanism of binding distributed feature representations facilitating segmentation of visual stimuli. Here we investigate this concept based on unsupervised learning using natural visual stimuli. We simulate dual-variable neural oscillators with separate activation and phase variables. The binding of a set of neurons is coded by synchronized phase variables. The network of tangential synchronizing connections learned from the induced activations exhibits small-world properties and allows binding even over larger distances. We evaluate the resulting dynamic phase maps using segmentation masks labeled by human experts. Our simulation results show a continuously increasing phase synchrony between neurons within the labeled segmentation masks. The evaluation of the network dynamics shows that the synchrony between network nodes establishes a relational coding of the natural image inputs. This demonstrates that the concept of binding by synchrony is applicable in the context of unsupervised learning using natural visual stimuli. PMID:24478685

  5. Stabilizing Motifs in Autonomous Boolean Networks and the Yeast Cell Cycle Oscillator

    NASA Astrophysics Data System (ADS)

    Sevim, Volkan; Gong, Xinwei; Socolar, Joshua

    2009-03-01

    Synchronously updated Boolean networks are widely used to model gene regulation. Some properties of these model networks are known to be artifacts of the clocking in the update scheme. Autonomous updating is a less artificial scheme that allows one to introduce small timing perturbations and study stability of the attractors. We argue that the stabilization of a limit cycle in an autonomous Boolean network requires a combination of motifs such as feed-forward loops and auto-repressive links that can correct small fluctuations in the timing of switching events. A recently published model of the transcriptional cell-cycle oscillator in yeast contains the motifs necessary for stability under autonomous updating [1]. [1] D. A. Orlando, et al. Nature (London), 4530 (7197):0 944--947, 2008.

  6. Network of time-multiplexed optical parametric oscillators as a coherent Ising machine

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

    Finding the ground states of the Ising Hamiltonian maps to various combinatorial optimization problems in biology, medicine, wireless communications, artificial intelligence and social network. So far, no efficient classical and quantum algorithm is known for these problems and intensive research is focused on creating physical systems—Ising machines—capable of finding the absolute or approximate ground states of the Ising Hamiltonian. Here, we report an Ising machine using a network of degenerate optical parametric oscillators (OPOs). Spins are represented with above-threshold binary phases of the OPOs and the Ising couplings are realized by mutual injections. The network is implemented in a single OPO ring cavity with multiple trains of femtosecond pulses and configurable mutual couplings, and operates at room temperature. We programmed a small non-deterministic polynomial time-hard problem on a 4-OPO Ising machine and in 1,000 runs no computational error was detected.

  7. Elevated serotonergic signaling amplifies synaptic noise and facilitates the emergence of epileptiform network oscillations

    PubMed Central

    Puzerey, Pavel A.; Decker, Michael J.

    2014-01-01

    Serotonin fibers densely innervate the cortical sheath to regulate neuronal excitability, but its role in shaping network dynamics remains undetermined. We show that serotonin provides an excitatory tone to cortical neurons in the form of spontaneous synaptic noise through 5-HT3 receptors, which is persistent and can be augmented using fluoxetine, a selective serotonin re-uptake inhibitor. Augmented serotonin signaling also increases cortical network activity by enhancing synaptic excitation through activation of 5-HT2 receptors. This in turn facilitates the emergence of epileptiform network oscillations (10–16 Hz) known as fast runs. A computational model of cortical dynamics demonstrates that these two combined mechanisms, increased background synaptic noise and enhanced synaptic excitation, are sufficient to replicate the emergence fast runs and their statistics. Consistent with these findings, we show that blocking 5-HT2 receptors in vivo significantly raises the threshold for convulsant-induced seizures. PMID:25122717

  8. Functional optical probing of the hippocampal trisynaptic circuit in vitro: network dynamics, filter properties, and polysynaptic induction of CA1 LTP.

    PubMed

    Stepan, Jens; Dine, Julien; Eder, Matthias

    2015-01-01

    Decades of brain research have identified various parallel loops linking the hippocampus with neocortical areas, enabling the acquisition of spatial and episodic memories. Especially the hippocampal trisynaptic circuit [entorhinal cortex layer II → dentate gyrus (DG) → cornu ammonis (CA)-3 → CA1] was studied in great detail because of its seemingly simple connectivity and characteristic structures that are experimentally well accessible. While numerous researchers focused on functional aspects, obtained from a limited number of cells in distinct hippocampal subregions, little is known about the neuronal network dynamics which drive information across multiple synapses for subsequent long-term storage. Fast voltage-sensitive dye imaging in vitro allows real-time recording of activity patterns in large/meso-scale neuronal networks with high spatial resolution. In this way, we recently found that entorhinal theta-frequency input to the DG most effectively passes filter mechanisms of the trisynaptic circuit network, generating activity waves which propagate across the entire DG-CA axis. These "trisynaptic circuit waves" involve high-frequency firing of CA3 pyramidal neurons, leading to a rapid induction of classical NMDA receptor-dependent long-term potentiation (LTP) at CA3-CA1 synapses (CA1 LTP). CA1 LTP has been substantially evidenced to be essential for some forms of explicit learning in mammals. Here, we review data with particular reference to whole network-level approaches, illustrating how activity propagation can take place within the trisynaptic circuit to drive formation of CA1 LTP.

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

    NASA Astrophysics Data System (ADS)

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

    2011-08-01

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

  10. When are new hippocampal neurons, born in the adult brain, integrated into the network that processes spatial information?

    PubMed

    Sandoval, C Jimena; Martínez-Claros, Marisela; Bello-Medina, Paola C; Pérez, Oswaldo; Ramírez-Amaya, Víctor

    2011-03-09

    Adult-born neurons in the dentate gyrus (DG) functionally integrate into the behaviorally relevant hippocampal networks, showing a specific Arc-expression response to spatial exploration when mature. However, it is not clear when, during the 4- to 6-week interval that is critical for survival and maturation of these neurons, this specific response develops. Therefore, we characterized Arc expression after spatial exploration or cage control conditions in adult-born neurons from rats that were injected with BrdU on one day and were sacrificed 1, 7, 15, 30, and 45 days post-BrdU injection (PBI). Triple immunostaining for NeuN, Arc, and BrdU was analyzed through the different DG layers. Arc protein expression in BrdU-positive cells was observed from day 1 to day 15 PBI but was not related to behavioral stimulation. The specific Arc-expression response to spatial exploration was observed from day 30 and 45 in about 5% of the BrdU-positive cell population. Most of the BrdU-positive neurons expressing Arc in response to spatial exploration (∼90%) were located in DG layer 1, and no Arc expression was observed in cells located in the subgranular zone (SGZ). Using the current data and that obtained previously, we propose a mathematical model suggesting that new neurons are unlikely to respond to exploration by expressing Arc after they are 301 days old, and also that in a 7-month-old rat the majority (60%) of the neurons that respond to exploration must have been born during adulthood; thus, suggesting that adult neurogenesis in the DG is highly relevant for spatial information processing.

  11. When are new hippocampal neurons, born in the adult brain, integrated into the network that processes spatial information?

    PubMed

    Sandoval, C Jimena; Martínez-Claros, Marisela; Bello-Medina, Paola C; Pérez, Oswaldo; Ramírez-Amaya, Víctor

    2011-01-01

    Adult-born neurons in the dentate gyrus (DG) functionally integrate into the behaviorally relevant hippocampal networks, showing a specific Arc-expression response to spatial exploration when mature. However, it is not clear when, during the 4- to 6-week interval that is critical for survival and maturation of these neurons, this specific response develops. Therefore, we characterized Arc expression after spatial exploration or cage control conditions in adult-born neurons from rats that were injected with BrdU on one day and were sacrificed 1, 7, 15, 30, and 45 days post-BrdU injection (PBI). Triple immunostaining for NeuN, Arc, and BrdU was analyzed through the different DG layers. Arc protein expression in BrdU-positive cells was observed from day 1 to day 15 PBI but was not related to behavioral stimulation. The specific Arc-expression response to spatial exploration was observed from day 30 and 45 in about 5% of the BrdU-positive cell population. Most of the BrdU-positive neurons expressing Arc in response to spatial exploration (∼90%) were located in DG layer 1, and no Arc expression was observed in cells located in the subgranular zone (SGZ). Using the current data and that obtained previously, we propose a mathematical model suggesting that new neurons are unlikely to respond to exploration by expressing Arc after they are 301 days old, and also that in a 7-month-old rat the majority (60%) of the neurons that respond to exploration must have been born during adulthood; thus, suggesting that adult neurogenesis in the DG is highly relevant for spatial information processing. PMID:21408012

  12. Speed of synchronization in complex networks of neural oscillators: analytic results based on Random Matrix Theory.

    PubMed

    Timme, Marc; Geisel, Theo; Wolf, Fred

    2006-03-01

    We analyze the dynamics of networks of spiking neural oscillators. First, we present an exact linear stability theory of the synchronous state for networks of arbitrary connectivity. For general neuron rise functions, stability is determined by multiple operators, for which standard analysis is not suitable. We describe a general nonstandard solution to the multioperator problem. Subsequently, we derive a class of neuronal rise functions for which all stability operators become degenerate and standard eigenvalue analysis becomes a suitable tool. Interestingly, this class is found to consist of networks of leaky integrate-and-fire neurons. For random networks of inhibitory integrate-and-fire neurons, we then develop an analytical approach, based on the theory of random matrices, to precisely determine the eigenvalue distributions of the stability operators. This yields the asymptotic relaxation time for perturbations to the synchronous state which provides the characteristic time scale on which neurons can coordinate their activity in such networks. For networks with finite in-degree, i.e., finite number of presynaptic inputs per neuron, we find a speed limit to coordinating spiking activity. Even with arbitrarily strong interaction strengths neurons cannot synchronize faster than at a certain maximal speed determined by the typical in-degree.

  13. Master stability islands for amplitude death in networks of delay-coupled oscillators.

    PubMed

    Huddy, Stanley R; Sun, Jie

    2016-05-01

    This paper presents a master stability function (MSF) approach for analyzing the stability of amplitude death (AD) in networks of delay-coupled oscillators. Unlike the familiar MSFs for instantaneously coupled networks, which typically have a single input encoding for the effects of the eigenvalues of the network Laplacian matrix, for delay-coupled networks we show that such MSFs generally require two additional inputs: the time delay and the coupling strength. To utilize the MSF for determining the stability of AD of general networks for a chosen nonlinear system (node dynamics) and coupling function, we introduce the concept of master stability islands (MSIs), which are two-dimensional stability islands of the delay-coupling parameter space together with a third dimension ("altitude") encoding for eigenvalues that result in stable AD. We numerically compute the MSFs and visualize the corresponding MSIs for several common chaotic systems including the Rössler, the Lorenz, and Chen's system and find that it is generally possible to achieve AD and that a nonzero time delay is necessary for the stabilization of the AD states.

  14. Master stability islands for amplitude death in networks of delay-coupled oscillators

    NASA Astrophysics Data System (ADS)

    Huddy, Stanley R.; Sun, Jie

    2016-05-01

    This paper presents a master stability function (MSF) approach for analyzing the stability of amplitude death (AD) in networks of delay-coupled oscillators. Unlike the familiar MSFs for instantaneously coupled networks, which typically have a single input encoding for the effects of the eigenvalues of the network Laplacian matrix, for delay-coupled networks we show that such MSFs generally require two additional inputs: the time delay and the coupling strength. To utilize the MSF for determining the stability of AD of general networks for a chosen nonlinear system (node dynamics) and coupling function, we introduce the concept of master stability islands (MSIs), which are two-dimensional stability islands of the delay-coupling parameter space together with a third dimension ("altitude") encoding for eigenvalues that result in stable AD. We numerically compute the MSFs and visualize the corresponding MSIs for several common chaotic systems including the Rössler, the Lorenz, and Chen's system and find that it is generally possible to achieve AD and that a nonzero time delay is necessary for the stabilization of the AD states.

  15. Long-lasting desynchronization in rat hippocampal slice induced by coordinated reset stimulation

    SciTech Connect

    Tass, P. A.; Barnikol, U. B.; Silchenko, A. N.; Hauptmann, C.; Speckmann, E.-J.

    2009-07-15

    In computational models it has been shown that appropriate stimulation protocols may reshape the connectivity pattern of neural or oscillator networks with synaptic plasticity in a way that the network learns or unlearns strong synchronization. The underlying mechanism is that a network is shifted from one attractor to another, so that long-lasting stimulation effects are caused which persist after the cessation of stimulation. Here we study long-lasting effects of multisite electrical stimulation in a rat hippocampal slice rendered epileptic by magnesium withdrawal. We show that desynchronizing coordinated reset stimulation causes a long-lasting desynchronization between hippocampal neuronal populations together with a widespread decrease in the amplitude of the epileptiform activity. In contrast, periodic stimulation induces a long-lasting increase in both synchronization and amplitude.

  16. Delay decomposition approach to [Formula: see text] filtering analysis of genetic oscillator networks with time-varying delays.

    PubMed

    Revathi, V M; Balasubramaniam, P

    2016-04-01

    In this paper, the [Formula: see text] filtering problem is treated for N coupled genetic oscillator networks with time-varying delays and extrinsic molecular noises. Each individual genetic oscillator is a complex dynamical network that represents the genetic oscillations in terms of complicated biological functions with inner or outer couplings denote the biochemical interactions of mRNAs, proteins and other small molecules. Throughout the paper, first, by constructing appropriate delay decomposition dependent Lyapunov-Krasovskii functional combined with reciprocal convex approach, improved delay-dependent sufficient conditions are obtained to ensure the asymptotic stability of the filtering error system with a prescribed [Formula: see text] performance. Second, based on the above analysis, the existence of the designed [Formula: see text] filters are established in terms of linear matrix inequalities with Kronecker product. Finally, numerical examples including a coupled Goodwin oscillator model are inferred to illustrate the effectiveness and less conservatism of the proposed techniques.

  17. Complex patterns arise through spontaneous symmetry breaking in dense homogeneous networks of neural oscillators

    PubMed Central

    Singh, Rajeev; Menon, Shakti N.; Sinha, Sitabhra

    2016-01-01

    There has been much interest in understanding collective dynamics in networks of brain regions due to their role in behavior and cognitive function. Here we show that a simple, homogeneous system of densely connected oscillators, representing the aggregate activity of local brain regions, can exhibit a rich variety of dynamical patterns emerging via spontaneous breaking of permutation or translational symmetries. Upon removing just a few connections, we observe a striking departure from the mean-field limit in terms of the collective dynamics, which implies that the sparsity of these networks may have very important consequences. Our results suggest that the origins of some of the complicated activity patterns seen in the brain may be understood even with simple connection topologies. PMID:26916700

  18. Discovery and dissection of metabolic oscillations in the microaerobic nitric oxide response network of Escherichia coli.

    PubMed

    Robinson, Jonathan L; Brynildsen, Mark P

    2016-03-22

    The virulence of many pathogens depends upon their ability to cope with immune-generated nitric oxide (NO·). In Escherichia coli, the major NO· detoxification systems are Hmp, an NO· dioxygenase (NOD), and NorV, an NO· reductase (NOR). It is well established that Hmp is the dominant system under aerobic conditions, whereas NorV dominates anaerobic conditions; however, the quantitative contributions of these systems under the physiologically relevant microaerobic regime remain ill defined. Here, we investigated NO· detoxification in environments ranging from 0 to 50 μM O2, and discovered a regime in which E. coli NO· defenses were severely compromised, as well as conditions that exhibited oscillations in the concentration of NO·. Using an integrated computational and experimental approach, E. coli NO· detoxification was found to be extremely impaired at low O2 due to a combination of its inhibitory effects on NorV, Hmp, and translational activities, whereas oscillations were found to result from a kinetic competition for O2 between Hmp and respiratory cytochromes. Because at least 777 different bacterial species contain the genetic requirements of this stress response oscillator, we hypothesize that such oscillatory behavior could be a widespread phenomenon. In support of this hypothesis,Pseudomonas aeruginosa, whose respiratory and NO· response networks differ considerably from those of E. coli, was found to exhibit analogous oscillations in low O2 environments. This work provides insight into how bacterial NO· defenses function under the low O2 conditions that are likely to be encountered within host environments.

  19. Discovery and dissection of metabolic oscillations in the microaerobic nitric oxide response network of Escherichia coli

    PubMed Central

    Robinson, Jonathan L.; Brynildsen, Mark P.

    2016-01-01

    The virulence of many pathogens depends upon their ability to cope with immune-generated nitric oxide (NO·). In Escherichia coli, the major NO· detoxification systems are Hmp, an NO· dioxygenase (NOD), and NorV, an NO· reductase (NOR). It is well established that Hmp is the dominant system under aerobic conditions, whereas NorV dominates anaerobic conditions; however, the quantitative contributions of these systems under the physiologically relevant microaerobic regime remain ill defined. Here, we investigated NO· detoxification in environments ranging from 0 to 50 μM O2, and discovered a regime in which E. coli NO· defenses were severely compromised, as well as conditions that exhibited oscillations in the concentration of NO·. Using an integrated computational and experimental approach, E. coli NO· detoxification was found to be extremely impaired at low O2 due to a combination of its inhibitory effects on NorV, Hmp, and translational activities, whereas oscillations were found to result from a kinetic competition for O2 between Hmp and respiratory cytochromes. Because at least 777 different bacterial species contain the genetic requirements of this stress response oscillator, we hypothesize that such oscillatory behavior could be a widespread phenomenon. In support of this hypothesis, Pseudomonas aeruginosa, whose respiratory and NO· response networks differ considerably from those of E. coli, was found to exhibit analogous oscillations in low O2 environments. This work provides insight into how bacterial NO· defenses function under the low O2 conditions that are likely to be encountered within host environments. PMID:26951670

  20. Matrix metalloprotease activity shapes the magnitude of EPSPs and spike plasticity within the hippocampal CA3 network.

    PubMed

    Wójtowicz, Tomasz; Mozrzymas, Jerzy W

    2014-02-01

    Matrix metalloproteases (MMP) play a pivotal role in long-term synaptic plasticity, learning, and memory. The roles of different MMP subtypes are emerging, but the proteolytic activity of certain MMPs was shown to support these processes through the structural and functional modification of hippocampal Schaeffer collateral and mossy fiber (MF) synapses. However, certain patterns of synaptic activity are additionally associated with non-synaptic changes, such as the scaling of neuronal excitability. However, the extent to which MMPs affect this process remains unknown. We determined whether MMP activity interferes with excitatory post-synaptic potential EPSP-to-spike (E-S) coupling under conditions of varying synaptic activity. We evoked short- and long-term synaptic plasticity at associational/commissural (A/C) synapses of CA3 pyramidal neurons and simultaneously recorded population spikes (PSs) and EPSPs in acute rat (P30-60) brain slices in the presence of various MMP inhibitors. We found that MMP inhibition significantly reduced E-S coupling and shortened the PS latency associated with 4× 100 Hz stimulation or paired burst activity of MF-CA3 and A/C synapses. Moreover, MMP inhibition interfered with the scaling of amplitude of measured signals during high-frequency trains, thus affecting the induction of long-term potentiation (LTP). The inhibition of L-type voltage-gated calcium channels with 20 µM nifedipine or GABA-A receptors with 1-30 µM picrotoxin did not occlude the effects of MMP inhibitors. However, MMP inhibition significantly reduced the LTP of NMDA receptor-mediated EPSPs. Finally, the analysis of LTP saturation with multiple single (1× 100 Hz) or packed (4× 100 Hz) trains indicated that MMPs support E-S coupling evoked by selected synaptic activity patterns and set the ceiling for tetanically evoked E-S LTP. In conclusion, the activity of MMPs, particularly MMP-3, regulated the magnitude of EPSPs and spike plasticity in the CA3 network and may

  1. Medial septum regulates the hippocampal spatial representation

    PubMed Central

    Mamad, Omar; McNamara, Harold M.; Reilly, Richard B.; Tsanov, Marian

    2015-01-01

    The hippocampal circuitry undergoes attentional modulation by the cholinergic medial septum. However, it is unclear how septal activation regulates the spatial properties of hippocampal neurons. We investigated here what is the functional effect of selective-cholinergic and non-selective septal stimulation on septo-hippocampal system. We show for the first time selective activation of cholinergic cells and their differential network effect in medial septum of freely-behaving transgenic rats. Our data show that depolarization of cholinergic septal neurons evokes frequency-dependent response from the non-cholinergic septal neurons and hippocampal interneurons. Our findings provide vital evidence that cholinergic effect on septo-hippocampal axis is behavior-dependent. During the active behavioral state the activation of septal cholinergic projections is insufficient to evoke significant change in the spiking of the hippocampal neurons. The efficiency of septo-hippocampal processing during active exploration relates to the firing patterns of the non-cholinergic theta-bursting cells. Non-selective septal theta-burst stimulation resets the spiking of hippocampal theta cells, increases theta synchronization, entrains the spiking of hippocampal place cells, and tunes the spatial properties in a timing-dependent manner. The spatial properties are augmented only when the stimulation is applied in the periphery of the place field or 400–650 ms before the animals approached the center of the field. In summary, our data show that selective cholinergic activation triggers a robust network effect in the septo-hippocampal system during inactive behavioral state, whereas the non-cholinergic septal activation regulates hippocampal functional properties during explorative behavior. Together, our findings uncover fast septal modulation on hippocampal network and reveal how septal inputs up-regulate and down-regulate the encoding of spatial representation. PMID:26175674

  2. Hippocampal CA1 Ripples as Inhibitory Transients

    PubMed Central

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

    2016-01-01

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

  3. Neurodynamic oscillators

    NASA Technical Reports Server (NTRS)

    Espinosa, Ismael; Gonzalez, Hortensia; Quiza, Jorge; Gonazalez, J. Jesus; Arroyo, Ruben; Lara, Ritaluz

    1995-01-01

    Oscillation of electrical activity has been found in many nervous systems, from invertebrates to vertebrates including man. There exists experimental evidence of very simple circuits with the capability of oscillation. Neurons with intrinsic oscillation have been found and also neural circuits where oscillation is a property of the network. These two types of oscillations coexist in many instances. It is nowadays hypothesized that behind synchronization and oscillation there is a system of coupled oscillators responsible for activities that range from locomotion and feature binding in vision to control of sleep and circadian rhythms. The huge knowledge that has been acquired on oscillators from the times of Lord Rayleigh has made the simulation of neural oscillators a very active endeavor. This has been enhanced with more recent physiological findings about small neural circuits by means of intracellular and extracellular recordings as well as imaging methods. The future of this interdisciplinary field looks very promising; some researchers are going into quantum mechanics with the idea of trying to provide a quantum description of the brain. In this work we describe some simulations using neuron models by means of which we form simple neural networks that have the capability of oscillation. We analyze the oscillatory activity with root locus method, cross-correlation histograms, and phase planes. In the more complicated neural network models there is the possibility of chaotic oscillatory activity and we study that by means of Lyapunov exponents. The companion paper shows an example of that kind.

  4. Functional optical probing of the hippocampal trisynaptic circuit in vitro: network dynamics, filter properties, and polysynaptic induction of CA1 LTP

    PubMed Central

    Stepan, Jens; Dine, Julien; Eder, Matthias

    2015-01-01

    Decades of brain research have identified various parallel loops linking the hippocampus with neocortical areas, enabling the acquisition of spatial and episodic memories. Especially the hippocampal trisynaptic circuit [entorhinal cortex layer II → dentate gyrus (DG) → cornu ammonis (CA)-3 → CA1] was studied in great detail because of its seemingly simple connectivity and characteristic structures that are experimentally well accessible. While numerous researchers focused on functional aspects, obtained from a limited number of cells in distinct hippocampal subregions, little is known about the neuronal network dynamics which drive information across multiple synapses for subsequent long-term storage. Fast voltage-sensitive dye imaging in vitro allows real-time recording of activity patterns in large/meso-scale neuronal networks with high spatial resolution. In this way, we recently found that entorhinal theta-frequency input to the DG most effectively passes filter mechanisms of the trisynaptic circuit network, generating activity waves which propagate across the entire DG-CA axis. These “trisynaptic circuit waves” involve high-frequency firing of CA3 pyramidal neurons, leading to a rapid induction of classical NMDA receptor-dependent long-term potentiation (LTP) at CA3-CA1 synapses (CA1 LTP). CA1 LTP has been substantially evidenced to be essential for some forms of explicit learning in mammals. Here, we review data with particular reference to whole network-level approaches, illustrating how activity propagation can take place within the trisynaptic circuit to drive formation of CA1 LTP. PMID:25999809

  5. Network of phase-locking oscillators and a possible model for neural synchronization

    NASA Astrophysics Data System (ADS)

    Piqueira, José Roberto C.

    2011-09-01

    In order to model the synchronization of brain signals, a three-node fully-connected network is presented. The nodes are considered to be voltage control oscillator neurons (VCON) allowing to conjecture about how the whole process depends on synaptic gains, free-running frequencies and delays. The VCON, represented by phase-locked loops (PLL), are fully-connected and, as a consequence, an asymptotically stable synchronous state appears. Here, an expression for the synchronous state frequency is derived and the parameter dependence of its stability is discussed. Numerical simulations are performed providing conditions for the use of the derived formulae. Model differential equations are hard to be analytically treated, but some simplifying assumptions combined with simulations provide an alternative formulation for the long-term behavior of the fully-connected VCON network. Regarding this kind of network as models for brain frequency signal processing, with each PLL representing a neuron (VCON), conditions for their synchronization are proposed, considering the different bands of brain activity signals and relating them to synaptic gains, delays and free-running frequencies. For the delta waves, the synchronous state depends strongly on the delays. However, for alpha, beta and theta waves, the free-running individual frequencies determine the synchronous state.

  6. Arc Length Coding by Interference of Theta Frequency Oscillations May Underlie Context-Dependent Hippocampal Unit Data and Episodic Memory Function

    ERIC Educational Resources Information Center

    Hasselmo, Michael E.

    2007-01-01

    Many memory models focus on encoding of sequences by excitatory recurrent synapses in region CA3 of the hippocampus. However, data and modeling suggest an alternate mechanism for encoding of sequences in which interference between theta frequency oscillations encodes the position within a sequence based on spatial arc length or time. Arc length…

  7. Bifurcation analysis of oscillating network model of pattern recognition in the rabbit olfactory bulb

    NASA Astrophysics Data System (ADS)

    Baird, Bill

    1986-08-01

    A neural network model describing pattern recognition in the rabbit olfactory bulb is analysed to explain the changes in neural activity observed experimentally during classical Pavlovian conditioning. EEG activity recorded from an 8×8 arry of 64 electrodes directly on the surface on the bulb shows distinct spatial patterns of oscillation that correspond to the animal's recognition of different conditioned odors and change with conditioning to new odors. The model may be considered a variant of Hopfield's model of continuous analog neural dynamics. Excitatory and inhibitory cell types in the bulb and the anatomical architecture of their connection requires a nonsymmetric coupling matrix. As the mean input level rises during each breath of the animal, the system bifurcates from homogenous equilibrium to a spatially patterned oscillation. The theory of multiple Hopf bifurcations is employed to find coupled equations for the amplitudes of these unstable oscillatory modes independent of frequency. This allows a view of stored periodic attractors as fixed points of a gradient vector field and thereby recovers the more familiar dynamical systems picture of associative memory.

  8. Synchronization transition of identical phase oscillators in a directed small-world network

    NASA Astrophysics Data System (ADS)

    Tönjes, Ralf; Masuda, Naoki; Kori, Hiroshi

    2010-09-01

    We numerically study a directed small-world network consisting of attractively coupled, identical phase oscillators. While complete synchronization is always stable, it is not always reachable from random initial conditions. Depending on the shortcut density and on the asymmetry of the phase coupling function, there exists a regime of persistent chaotic dynamics. By increasing the density of shortcuts or decreasing the asymmetry of the phase coupling function, we observe a discontinuous transition in the ability of the system to synchronize. Using a control technique, we identify the bifurcation scenario of the order parameter. We also discuss the relation between dynamics and topology and remark on the similarity of the synchronization transition to directed percolation.

  9. A mechanism for ultra-slow oscillations in the cortical default network.

    PubMed

    Steyn-Ross, Moira L; Steyn-Ross, D A; Sleigh, J W; Wilson, M T

    2011-02-01

    When the brain is in its noncognitive "idling" state, functional MRI measurements reveal the activation of default cortical networks whose activity is suppressed during cognitive processing. This default or background mode is characterized by ultra-slow BOLD oscillations (∼0.05 Hz), signaling extremely slow cycling in cortical metabolic demand across distinct cortical regions. Here we describe a model of the cortex which predicts that slow cycling of cortical activity can arise naturally as a result of nonlinear interactions between temporal (Hopf) and spatial (Turing) instabilities. The Hopf instability is triggered by delays in the inhibitory postsynaptic response, while the Turing instability is precipitated by increases in the strength of the gap-junction coupling between interneurons. We comment on possible implications for slow dendritic computation and information processing. PMID:20821063

  10. Truncated Wigner theory of coherent Ising machines based on degenerate optical parametric oscillator network

    NASA Astrophysics Data System (ADS)

    Maruo, Daiki; Utsunomiya, Shoko; Yamamoto, Yoshihisa

    2016-08-01

    We present the quantum theory of coherent Ising machines based on networks of degenerate optical parametric oscillators (DOPOs). In a simple model consisting of two coupled DOPOs, both positive-P representation and truncated Wigner representation predict quantum correlation and inseparability between the two DOPOs in spite of the open-dissipative nature of the system. Here, we apply the truncated Wigner representation method to coherent Ising machines with thermal, vacuum, and squeezed reservoir fields. We find that the probability of finding the ground state of a one-dimensional Ising model increases substantially as a result of reducing excess thermal noise and squeezing the incident vacuum fluctuation on the out-coupling port.

  11. Forecasting the Indian summer monsoon intraseasonal oscillations using genetic algorithm and neural network

    NASA Astrophysics Data System (ADS)

    Dwivedi, Suneet; Pandey, Avinash C.

    2011-08-01

    The correct and timely forecast of the Indian summer monsoon Intraseasonal Oscillations (ISOs) is very important. It has great impact on the agriculture and economy of the Indian subcontinent region. The applicability of Genetic Algorithm (GA) is demonstrated for nonlinear curve fitting of the inherently chaotic and noisy Lorenz time series and the ISO data. A robust method is developed for the very long-range prediction of the ISO using a feed-forward time delay backpropagation Artificial Neural Network (ANN). Using an iterative one-step-ahead prediction strategy, five years (120 pentads) of advanced prediction is made for the ISO data with good forecast skill. It is shown that a hybrid GA-ANN model may be used as an early forecast model followed by ANN only model as a more reliable model.

  12. Collective Dynamics of Oscillator Networks: Why do we suffer from heavy jet lag?

    NASA Astrophysics Data System (ADS)

    Kori, Hiroshi

    The circadian rhythm of the entire body in mammals is orchestrated by a small tissue in the brain called the suprachiamatic nucleus (SCN). The SCN consists of a population of neurons, each of which exhibit circadian (i.e., approximately 24 h) gene expression. Neurons form a complex network and interact with each other using various types of neurotransmitters. The rhythmic gene expressions of individual cells in the SCN synchronize through such interaction. Jet-lag symptoms arise from temporal mismatch between the internal circadian clock orchestrated by the SCN and external solar time. It may take about one week or even longer to recover from jet lag after a long-distance trip. We recently found that recovery from jet lag is considerably accelerated in the knocked-out (KO) mice lacking the receptors of a certain neurotransmitter in the SCN. Importantly, all other properties of mice including sleep-awake rhythms and breeding seem to be intact. Only the response to the jet lag changes. It was also found that after a few days of jet lag, cells in the SCN desynchronize in the wild type (WT) mice, whereas they do not in KO mice. This desynchrony might be a main reason for heavy jet lag symptoms. To understand the mechanism underlying jet lag, we propose a simple model of the SCN, which is a network of phase oscillators. Despite its simplicity, this model can reproduce important dynamical properties of the SCN. For example, this model reproduces the desynchrony of oscillators after jet lag. Moreover, when intercellular interaction is weaker, this desynchrony is suppressed and the recover from jet lag is considerably accelerated. Our mathematical study provides a deeper understanding of jet lag and an idea how to circumvent heavy jet lag symptoms

  13. Entrainment and synchronization in networks of Rayleigh-van der Pol oscillators with diffusive and Haken-Kelso-Bunz couplings.

    PubMed

    Alderisio, Francesco; Bardy, Benoît G; di Bernardo, Mario

    2016-06-01

    We analyze a network of non-identical Rayleigh-van der Pol (RvdP) oscillators interconnected through either diffusive or nonlinear coupling functions. The work presented here extends existing results on the case of two nonlinearly coupled RvdP oscillators to the problem of considering a network of three or more of them. Specifically, we study synchronization and entrainment in networks of heterogeneous RvdP oscillators and contrast the effects of diffusive linear coupling strategies with the nonlinear Haken-Kelso-Bunz coupling, originally introduced to study human bimanual experiments. We show how convergence of the error among the nodes' trajectories toward a bounded region is possible with both linear and nonlinear coupling functions. Under the assumption that the network is connected, simple, and undirected, analytical results are obtained to prove boundedness of the error when the oscillators are coupled diffusively. All results are illustrated by way of numerical examples and compared with the experimental findings available in the literature on synchronization of people rocking chairs, confirming the effectiveness of the model we propose to capture some of the features of human group synchronization observed experimentally in the previous literature. PMID:27108135

  14. Inhibition recruitment in prefrontal cortex during sleep spindles and gating of hippocampal inputs

    PubMed Central

    Peyrache, Adrien; Battaglia, Francesco P.; Destexhe, Alain

    2011-01-01

    During light slow-wave sleep, the thalamo-cortical network oscillates in waxing-and-waning patterns at about 7 to 14 Hz and lasting for 500 ms to 3 s, called spindles, with the thalamus rhythmically sending strong excitatory volleys to the cortex. Concurrently, the hippocampal activity is characterized by transient and strong excitatory events, Sharp-Waves-Ripples (SPWRs), directly affecting neocortical activity—in particular the medial prefrontal cortex (mPFC)—which receives monosynaptic fibers from the ventral hippocampus and subiculum. Both spindles and SPWRs have been shown to be strongly involved in memory consolidation. However, the dynamics of the cortical network during natural sleep spindles and how prefrontal circuits simultaneously process hippocampal and thalamo-cortical activity remain largely undetermined. Using multisite neuronal recordings in rat mPFC, we show that during sleep spindles, oscillatory responses of cortical cells are different for different cell types and cortical layers. Superficial neurons are more phase-locked and tonically recruited during spindle episodes. Moreover, in a given layer, interneurons were always more modulated than pyramidal cells, both in firing rate and phase, suggesting that the dynamics are dominated by inhibition. In the deep layers, where most of the hippocampal fibers make contacts, pyramidal cells respond phasically to SPWRs, but not during spindles. Similar observations were obtained when analyzing γ-oscillation modulation in the mPFC. These results demonstrate that during sleep spindles, the cortex is functionnaly “deafferented” from its hippocampal inputs, based on processes of cortical origin, and presumably mediated by the strong recruitment of inhibitory interneurons. The interplay between hippocampal and thalamic inputs may underlie a global mechanism involved in the consolidation of recently formed memory traces. PMID:21949372

  15. Restoring oscillatory behavior from amplitude death with anti-phase synchronization patterns in networks of electrochemical oscillations

    NASA Astrophysics Data System (ADS)

    Nagao, Raphael; Zou, Wei; Kurths, Jürgen; Kiss, István Z.

    2016-09-01

    The dynamical behavior of delay-coupled networks of electrochemical reactions is investigated to explore the formation of amplitude death (AD) and the synchronization states in a parameter region around the amplitude death region. It is shown that difference coupling with odd and even numbered ring and random networks can produce the AD phenomenon. Furthermore, this AD can be restored by changing the coupling type from difference to direct coupling. The restored oscillations tend to create synchronization patterns in which neighboring elements are in nearly anti-phase configuration. The ring networks produce frozen and rotating phase waves, while the random network exhibits a complex synchronization pattern with interwoven frozen and propagating phase waves. The experimental results are interpreted with a coupled Stuart-Landau oscillator model. The experimental and theoretical results reveal that AD behavior is a robust feature of delayed coupled networks of chemical units; if an oscillatory behavior is required again, even a small amount of direct coupling could be sufficient to restore the oscillations. The restored nearly anti-phase oscillatory patterns, which, to a certain extent, reflect the symmetry of the network, represent an effective means to overcome the AD phenomenon.

  16. Sensorimotor Oscillations Prior to Speech Onset Reflect Altered Motor Networks in Adults Who Stutter

    PubMed Central

    Mersov, Anna-Maria; Jobst, Cecilia; Cheyne, Douglas O.; De Nil, Luc

    2016-01-01

    Adults who stutter (AWS) have demonstrated atypical coordination of motor and sensory regions during speech production. Yet little is known of the speech-motor network in AWS in the brief time window preceding audible speech onset. The purpose of the current study was to characterize neural oscillations in the speech-motor network during preparation for and execution of overt speech production in AWS using magnetoencephalography (MEG). Twelve AWS and 12 age-matched controls were presented with 220 words, each word embedded in a carrier phrase. Controls were presented with the same word list as their matched AWS participant. Neural oscillatory activity was localized using minimum-variance beamforming during two time periods of interest: speech preparation (prior to speech onset) and speech execution (following speech onset). Compared to controls, AWS showed stronger beta (15–25 Hz) suppression in the speech preparation stage, followed by stronger beta synchronization in the bilateral mouth motor cortex. AWS also recruited the right mouth motor cortex significantly earlier in the speech preparation stage compared to controls. Exaggerated motor preparation is discussed in the context of reduced coordination in the speech-motor network of AWS. It is further proposed that exaggerated beta synchronization may reflect a more strongly inhibited motor system that requires a stronger beta suppression to disengage prior to speech initiation. These novel findings highlight critical differences in the speech-motor network of AWS that occur prior to speech onset and emphasize the need to investigate further the speech-motor assembly in the stuttering population.

  17. Sensorimotor Oscillations Prior to Speech Onset Reflect Altered Motor Networks in Adults Who Stutter.

    PubMed

    Mersov, Anna-Maria; Jobst, Cecilia; Cheyne, Douglas O; De Nil, Luc

    2016-01-01

    Adults who stutter (AWS) have demonstrated atypical coordination of motor and sensory regions during speech production. Yet little is known of the speech-motor network in AWS in the brief time window preceding audible speech onset. The purpose of the current study was to characterize neural oscillations in the speech-motor network during preparation for and execution of overt speech production in AWS using magnetoencephalography (MEG). Twelve AWS and 12 age-matched controls were presented with 220 words, each word embedded in a carrier phrase. Controls were presented with the same word list as their matched AWS participant. Neural oscillatory activity was localized using minimum-variance beamforming during two time periods of interest: speech preparation (prior to speech onset) and speech execution (following speech onset). Compared to controls, AWS showed stronger beta (15-25 Hz) suppression in the speech preparation stage, followed by stronger beta synchronization in the bilateral mouth motor cortex. AWS also recruited the right mouth motor cortex significantly earlier in the speech preparation stage compared to controls. Exaggerated motor preparation is discussed in the context of reduced coordination in the speech-motor network of AWS. It is further proposed that exaggerated beta synchronization may reflect a more strongly inhibited motor system that requires a stronger beta suppression to disengage prior to speech initiation. These novel findings highlight critical differences in the speech-motor network of AWS that occur prior to speech onset and emphasize the need to investigate further the speech-motor assembly in the stuttering population. PMID:27642279

  18. Sensorimotor Oscillations Prior to Speech Onset Reflect Altered Motor Networks in Adults Who Stutter

    PubMed Central

    Mersov, Anna-Maria; Jobst, Cecilia; Cheyne, Douglas O.; De Nil, Luc

    2016-01-01

    Adults who stutter (AWS) have demonstrated atypical coordination of motor and sensory regions during speech production. Yet little is known of the speech-motor network in AWS in the brief time window preceding audible speech onset. The purpose of the current study was to characterize neural oscillations in the speech-motor network during preparation for and execution of overt speech production in AWS using magnetoencephalography (MEG). Twelve AWS and 12 age-matched controls were presented with 220 words, each word embedded in a carrier phrase. Controls were presented with the same word list as their matched AWS participant. Neural oscillatory activity was localized using minimum-variance beamforming during two time periods of interest: speech preparation (prior to speech onset) and speech execution (following speech onset). Compared to controls, AWS showed stronger beta (15–25 Hz) suppression in the speech preparation stage, followed by stronger beta synchronization in the bilateral mouth motor cortex. AWS also recruited the right mouth motor cortex significantly earlier in the speech preparation stage compared to controls. Exaggerated motor preparation is discussed in the context of reduced coordination in the speech-motor network of AWS. It is further proposed that exaggerated beta synchronization may reflect a more strongly inhibited motor system that requires a stronger beta suppression to disengage prior to speech initiation. These novel findings highlight critical differences in the speech-motor network of AWS that occur prior to speech onset and emphasize the need to investigate further the speech-motor assembly in the stuttering population. PMID:27642279

  19. Cross-frequency synchronization connects networks of fast and slow oscillations during visual working memory maintenance

    PubMed Central

    Siebenhühner, Felix; Wang, Sheng H; Palva, J Matias; Palva, Satu

    2016-01-01

    Neuronal activity in sensory and fronto-parietal (FP) areas underlies the representation and attentional control, respectively, of sensory information maintained in visual working memory (VWM). Within these regions, beta/gamma phase-synchronization supports the integration of sensory functions, while synchronization in theta/alpha bands supports the regulation of attentional functions. A key challenge is to understand which mechanisms integrate neuronal processing across these distinct frequencies and thereby the sensory and attentional functions. We investigated whether such integration could be achieved by cross-frequency phase synchrony (CFS). Using concurrent magneto- and electroencephalography, we found that CFS was load-dependently enhanced between theta and alpha–gamma and between alpha and beta-gamma oscillations during VWM maintenance among visual, FP, and dorsal attention (DA) systems. CFS also connected the hubs of within-frequency-synchronized networks and its strength predicted individual VWM capacity. We propose that CFS integrates processing among synchronized neuronal networks from theta to gamma frequencies to link sensory and attentional functions. DOI: http://dx.doi.org/10.7554/eLife.13451.001 PMID:27669146

  20. Large-scale Ising spin network based on degenerate optical parametric oscillators

    NASA Astrophysics Data System (ADS)

    Inagaki, Takahiro; Inaba, Kensuke; Hamerly, Ryan; Inoue, Kyo; Yamamoto, Yoshihisa; Takesue, Hiroki

    2016-06-01

    Solving combinatorial optimization problems is becoming increasingly important in modern society, where the analysis and optimization of unprecedentedly complex systems are required. Many such problems can be mapped onto the ground-state-search problem of the Ising Hamiltonian, and simulating the Ising spins with physical systems is now emerging as a promising approach for tackling such problems. Here, we report a large-scale network of artificial spins based on degenerate optical parametric oscillators (DOPOs), paving the way towards a photonic Ising machine capable of solving difficult combinatorial optimization problems. We generate >10,000 time-division-multiplexed DOPOs using dual-pump four-wave mixing in a highly nonlinear fibre placed in a cavity. Using those DOPOs, a one-dimensional Ising model is simulated by introducing nearest-neighbour optical coupling. We observe the formation of spin domains and find that the domain size diverges near the DOPO threshold, which suggests that the DOPO network can simulate the behaviour of low-temperature Ising spins.

  1. Wavelet Analysis of Spatiotemporal Network Oscillations Evoked in the Incilaria Brain

    NASA Astrophysics Data System (ADS)

    Schütt, A.; Rosso, O. A.; Makino, Y.; Fujie, T.; Yano, M.; Werner, M.; Figliola, A.; Hofmann, U. G.

    2007-05-01

    In the slugs and snails odor input signal, partly processed by the tentacle ganglion, propagates through the tentacle nerve (TN) to the cerebral ganglion, initially activating the meso-meta-region and finally the procerebral region (PC). The PC, equivalent to mammalian olfactory bulb, exerts slow spontaneous neuroelectrical oscillation, which changes its frequency and amplitude pattern responding to stimulus input. This has been related to a mechanism of signal processing for odor encoding. Three neuronal substructures, the cell mass (CM), the terminal mass (TM) and internal mass (IM) form the PC. Records from IM and CM have extensively been studied, but those from TM have scarcely been investigated. In the present study we aimed to clarify network dynamics among these cell ensembles with particular interest in the property of TM. Methods: We isolated the cerebral ganglia from the slug Incilaria together with TNs. We applied to TN electrical stimulation of weak to strong intensities (0.1 - 1.0 μA) and recorded activities at the three loci of PC by glass suction electrodes at a sampling rate of 200 Hz. The data were stored on hard drive and later off-line analysed by wavelet tools. Results: Wavelet analysis revealed that the major power of the spontaneous oscillations laid below 1.6 Hz. Namely, in the Incilaria PC, mainly the frequency components < 1.6 Hz take part in the dynamical signal processing. The frequency components, that are time-dependently, interacting with each other, contribute together to altering total entropy of a cell mass at a given time. Notably, the 0.1 - 0.2 Hz component contributing most strongly to total energy attributes most to dropping entropy ("ordering of neuronal state"). Response to the weakest stimulus is most sensitively elicited as "desynchronization" in TM-IM, but that to the stronger stimuli, as "synchronization or frequency ordering" in TM-CM, and finally "synchronization" in TM-IM-CM (the whole PC). The fact that the entropy of

  2. Power oscillator

    DOEpatents

    Gitsevich, Aleksandr

    2001-01-01

    An oscillator includes an amplifier having an input and an output, and an impedance transformation network connected between the input of the amplifier and the output of the amplifier, wherein the impedance transformation network is configured to provide suitable positive feedback from the output of the amplifier to the input of the amplifier to initiate and sustain an oscillating condition, and wherein the impedance transformation network is configured to protect the input of the amplifier from a destructive feedback signal. One example of the oscillator is a single active element device capable of providing over 70 watts of power at over 70% efficiency. Various control circuits may be employed to match the driving frequency of the oscillator to a plurality of tuning states of the lamp.

  3. Critical-state dynamics of avalanches and oscillations jointly emerge from balanced excitation/inhibition in neuronal networks.

    PubMed

    Poil, Simon-Shlomo; Hardstone, Richard; Mansvelder, Huibert D; Linkenkaer-Hansen, Klaus

    2012-07-18

    Criticality has gained widespread interest in neuroscience as an attractive framework for understanding the character and functional implications of variability in brain activity. The metastability of critical systems maximizes their dynamic range, storage capacity, and computational power. Power-law scaling-a hallmark of criticality-has been observed on different levels, e.g., in the distribution of neuronal avalanches in vitro and in vivo, but also in the decay of temporal correlations in behavioral performance and ongoing oscillations in humans. An unresolved issue is whether power-law scaling on different organizational levels in the brain-and possibly in other hierarchically organized systems-can be related. Here, we show that critical-state dynamics of avalanches and oscillations jointly emerge in a neuronal network model when excitation and inhibition is balanced. The oscillatory activity of the model was qualitatively similar to what is typically observed in recordings of human resting-state MEG. We propose that homeostatic plasticity mechanisms tune this balance in healthy brain networks, and that it is essential for critical behavior on multiple levels of neuronal organization with ensuing functional benefits. Based on our network model, we introduce a concept of multi-level criticality in which power-law scaling can emerge on multiple time scales in oscillating networks.

  4. Phase Matters: Responding to and Learning about Peripheral Stimuli Depends on Hippocampal ? Phase at Stimulus Onset

    ERIC Educational Resources Information Center

    Nokia, Miriam S.; Waselius, Tomi; Mikkonen, Jarno E.; Wikgren, Jan; Penttonen, Markku

    2015-01-01

    Hippocampal ? (3-12 Hz) oscillations are implicated in learning and memory, but their functional role remains unclear. We studied the effect of the phase of local ? oscillation on hippocampal responses to a neutral conditioned stimulus (CS) and subsequent learning of classical trace eyeblink conditioning in adult rabbits. High-amplitude, regular…

  5. Memory retrieval time and memory capacity of the CA3 network: role of gamma frequency oscillations.

    PubMed

    de Almeida, Licurgo; Idiart, Marco; Lisman, John E

    2007-11-01

    The existence of recurrent synaptic connections in CA3 led to the hypothesis that CA3 is an autoassociative network similar to the Hopfield networks studied by theorists. CA3 undergoes gamma frequency periodic inhibition that prevents a persistent attractor state. This argues against the analogy to Hopfield nets, in which an attractor state can be used for working memory. However, we show that such periodic inhibition allows one cycle of recurrent excitatory activity and that this is sufficient for memory retrieval (within milliseconds). Thus, gamma oscillations are compatible with a long-term autoassociative memory function for CA3. A second goal of our work was to evaluate previous methods for estimating the memory capacity (P) of CA3. We confirm the equation, P = c/a(2), where c is the probability that any two cells are recurrently connected and a is the fraction of cells representing a memory item. In applying this to CA3, we focus on CA3a, the subregion where recurrent connections are most numerous (c = 0.2) and approximate randomness. We estimate that a memory item is represented by approximately 225 of the 70,000 neurons in CA3a (a = 0.003) and that approximately 20,000 memory items can be stored. Our general conclusion is that the physiological and anatomical findings of CA3a are consistent with an autoassociative function. The nature of the information that is associated in CA3a is discussed. We also discuss how the autoassociative properties of CA3 and the heteroassociative properties of dentate synapses (linking sequential memories) form an integrated system for the storage and recall of item sequences. The recall process generates the phase precession in dentate, CA3, and entorhinal cortex.

  6. Memory retrieval time and memory capacity of the CA3 network: Role of gamma frequency oscillations

    PubMed Central

    de Almeida, Licurgo; Idiart, Marco; Lisman, John E.

    2007-01-01

    The existence of recurrent synaptic connections in CA3 led to the hypothesis that CA3 is an autoassociative network similar to the Hopfield networks studied by theorists. CA3 undergoes gamma frequency periodic inhibition that prevents a persistent attractor state. This argues against the analogy to Hopfield nets, in which an attractor state can be used for working memory. However, we show that such periodic inhibition allows one cycle of recurrent excitatory activity and that this is sufficient for memory retrieval (within milliseconds). Thus, gamma oscillations are compatible with a long-term autoassociative memory function for CA3. A second goal of our work was to evaluate previous methods for estimating the memory capacity (P) of CA3. We confirm the equation, P = c/a2, where c is the probability that any two cells are recurrently connected and a is the fraction of cells representing a memory item. In applying this to CA3, we focus on CA3a, the subregion where recurrent connections are most numerous (c = 0.2) and approximate randomness. We estimate that a memory item is represented by ∼225 of the 70,000 neurons in CA3a (a = 0.003) and that ∼20,000 memory items can be stored. Our general conclusion is that the physiological and anatomical findings of CA3a are consistent with an autoassociative function. The nature of the information that is associated in CA3a is discussed. We also discuss how the autoassociative properties of CA3 and the heteroassociative properties of dentate synapses (linking sequential memories) form an integrated system for the storage and recall of item sequences. The recall process generates the phase precession in dentate, CA3, and entorhinal cortex. PMID:18007022

  7. Oscillating central motor networks in pathological tremors and voluntary movements. What makes the difference?

    PubMed

    Muthuraman, M; Heute, U; Arning, K; Anwar, A R; Elble, R; Deuschl, G; Raethjen, J

    2012-04-01

    Parkinsonian tremor (PD), essential tremor (ET) and voluntarily mimicked tremor represent fundamentally different motor phenomena, yet, magnetoencephalographic and imaging data suggest their origin in the same motor centers of the brain. Using EEG-EMG coherence and coherent source analysis we found a different pattern of corticomuscular delays, time courses and central representations for the basic and double tremor frequencies typical for PD suggesting a wider range defective oscillatory activity. For the basic tremor frequency similar central representations in primary sensorimotor, prefrontal/premotor and diencephalic (e.g. thalamic) areas were reproduced for all three tremors. But renormalized partial directed coherence of the spatially filtered (source) signals revealed a mainly unidirectional flow of information from the diencephalon to cortex in voluntary tremor, e.g. a thalamocortical relay, as opposed to a bidirectional subcortico-cortical flow in PD and ET promoting uncontrollable, e.g. thalamocortical, loop oscillations. Our results help to understand why pathological tremors although originating from the physiological motor network are not under voluntary control and they may contribute to the solution of the puzzle why high frequency thalamic stimulation has a selective effect on pathological tremor leaving voluntary movement performance almost unaltered. PMID:22293134

  8. New molecules for hippocampal development.

    PubMed

    Skutella, T; Nitsch, R

    2001-02-01

    Pathfinding by developing axons towards their proper targets is an essential step in establishing appropriate neuronal connections. Recent work involving cell culture assays and molecular biology strategies, including knockout animals, strongly indicates that a complex network of guidance signals regulates the formation of hippocampal connections during development. Outgrowing axons are routed towards the hippocampal formation by specific expression of long-range cues, which include secreted class 3 semaphorins, netrin 1 and Slit proteins. Local membrane- or substrate-anchored molecules, such as ligands of the ephrin A subclass, provide layer-specific positional information. Understanding the molecular mechanisms that underlie axonal guidance during hippocampal development might be of importance in making therapeutic use of sprouting fibers, which are produced following the loss of afferents in CNS lesion. PMID:11164941

  9. The Role of Oscillations and Synchrony in Cortical Networks and Their Putative Relevance for the Pathophysiology of Schizophrenia

    PubMed Central

    Uhlhaas, Peter J.; Haenschel, Corinna; Nikolić, Danko; Singer, Wolf

    2008-01-01

    Neural oscillations and their synchronization may represent a versatile signal to realize flexible communication within and between cortical areas. By now, there is extensive evidence to suggest that cognitive functions depending on coordination of distributed neural responses, such as perceptual grouping, attention-dependent stimulus selection, subsystem integration, working memory, and consciousness, are associated with synchronized oscillatory activity in the theta-, alpha-, beta-, and gamma-band, suggesting a functional mechanism of neural oscillations in cortical networks. In addition to their role in normal brain functioning, there is increasing evidence that altered oscillatory activity may be associated with certain neuropsychiatric disorders, such as schizophrenia, that involve dysfunctional cognition and behavior. In the following article, we aim to summarize the evidence on the role of neural oscillations during normal brain functioning and their relationship to cognitive processes. In the second part, we review research that has examined oscillatory activity during cognitive and behavioral tasks in schizophrenia. These studies suggest that schizophrenia involves abnormal oscillations and synchrony that are related to cognitive dysfunctions and some of the symptoms of the disorder. Perspectives for future research will be discussed in relationship to methodological issues, the utility of neural oscillations as a biomarker, and the neurodevelopmental hypothesis of schizophrenia. PMID:18562344

  10. The canonical Notch pathway effector RBP-J regulates neuronal plasticity and expression of GABA transporters in hippocampal networks.

    PubMed

    Liu, Shuxi; Wang, Yue; Worley, Paul F; Mattson, Mark P; Gaiano, Nicholas

    2015-05-01

    Activation of the Notch pathway in neurons is essential for learning and memory in various species from invertebrates to mammals. However, it remains unclear how Notch signaling regulates neuronal plasticity, and whether the transcriptional regulator and canonical pathway effector RBP-J plays a role. Here, we report that conditional disruption of RBP-J in the postnatal hippocampus leads to defects in long-term potentiation, long-term depression, and in learning and memory. Using gene expression profiling and chromatin immunoprecipitation, we identified two GABA transporters, GAT2 and BGT1, as putative Notch/RBP-J pathway targets, which may function downstream of RBP-J to limit the accumulation of GABA in the Schaffer collateral pathway. Our results reveal an essential role for canonical Notch/RBP-J signaling in hippocampal synaptic plasticity and suggest that role, at least in part, is mediated by the regulation of GABAergic signaling. PMID:25515406

  11. The canonical Notch pathway effector RBP-J regulates neuronal plasticity and expression of GABA transporters in hippocampal networks

    PubMed Central

    Liu, Shuxi; Wang, Yue; Worley, Paul F.; Mattson, Mark P.; Gaiano, Nicholas

    2014-01-01

    Activation of the Notch pathway in neurons is essential for learning and memory in various species from invertebrates to mammals. However, it remains unclear how Notch signaling regulates neuronal plasticity, and whether the transcriptional regulator and canonical pathway effector RBP-J plays a role. Here we report that conditional disruption of RBP-J in the postnatal hippocampus leads to defects in long-term potentiation (LTP), long-term depression (LTD), and in learning and memory. Using gene expression profiling and chromatin immunoprecipitation, we identified two GABA transporters, GAT2 and BGT1, as putative Notch/RBP-J pathway targets, which may function downstream of RBP-J to limit the accumulation of GABA in the Schaffer collateral pathway. Our results reveal an essential role for canonical Notch/RBP-J signaling in hippocampal synaptic plasticity and suggest that role, at least in part, is mediated by the regulation of GABAergic signaling. PMID:25515406

  12. The canonical Notch pathway effector RBP-J regulates neuronal plasticity and expression of GABA transporters in hippocampal networks.

    PubMed

    Liu, Shuxi; Wang, Yue; Worley, Paul F; Mattson, Mark P; Gaiano, Nicholas

    2015-05-01

    Activation of the Notch pathway in neurons is essential for learning and memory in various species from invertebrates to mammals. However, it remains unclear how Notch signaling regulates neuronal plasticity, and whether the transcriptional regulator and canonical pathway effector RBP-J plays a role. Here, we report that conditional disruption of RBP-J in the postnatal hippocampus leads to defects in long-term potentiation, long-term depression, and in learning and memory. Using gene expression profiling and chromatin immunoprecipitation, we identified two GABA transporters, GAT2 and BGT1, as putative Notch/RBP-J pathway targets, which may function downstream of RBP-J to limit the accumulation of GABA in the Schaffer collateral pathway. Our results reveal an essential role for canonical Notch/RBP-J signaling in hippocampal synaptic plasticity and suggest that role, at least in part, is mediated by the regulation of GABAergic signaling.

  13. Macroscopic self-oscillations and aging transition in a network of synaptically coupled quadratic integrate-and-fire neurons

    NASA Astrophysics Data System (ADS)

    Ratas, Irmantas; Pyragas, Kestutis

    2016-09-01

    We analyze the dynamics of a large network of coupled quadratic integrate-and-fire neurons, which represent the canonical model for class I neurons near the spiking threshold. The network is heterogeneous in that it includes both inherently spiking and excitable neurons. The coupling is global via synapses that take into account the finite width of synaptic pulses. Using a recently developed reduction method based on the Lorentzian ansatz, we derive a closed system of equations for the neuron's firing rate and the mean membrane potential, which are exact in the infinite-size limit. The bifurcation analysis of the reduced equations reveals a rich scenario of asymptotic behavior, the most interesting of which is the macroscopic limit-cycle oscillations. It is shown that the finite width of synaptic pulses is a necessary condition for the existence of such oscillations. The robustness of the oscillations against aging damage, which transforms spiking neurons into nonspiking neurons, is analyzed. The validity of the reduced equations is confirmed by comparing their solutions with the solutions of microscopic equations for the finite-size networks.

  14. [Hippocampal stroke].

    PubMed

    Rollnik, J D; Traitel, B; Dietrich, B; Lenz, O

    2015-02-01

    Unilateral cerebral ischemia of the hippocampus is very rare. This paper reviews the literature and presents the case of a 59-year-old woman with an amnestic syndrome due to a left hippocampal stroke. The patient suffered from retrograde amnesia which was most severe over the 2 days prior to presenting and a slight anterograde amnesia. In addition, a verbal memory disorder was confirmed 1 week after admission by neurological tests. As risk factors, arterial hypertension and a relative hyper-beta lipoproteinemia were found. This case shows that unilateral amnestic stroke, e.g. in the hippocampus region, may be the cause of an amnestic syndrome and should be included in the differential diagnostics.

  15. Behavior-dependent specialization of identified hippocampal interneurons

    PubMed Central

    Lapray, Damien; Lasztoczi, Balint; Lagler, Michael; Viney, Tim James; Katona, Linda; Valenti, Ornella; Hartwich, Katja; Borhegyi, Zsolt; Somogyi, Peter; Klausberger, Thomas

    2012-01-01

    A large variety of GABAergic interneurons control information processing in hippocampal circuits governing the formation of neuronal representations. Whether distinct hippocampal interneuron types contribute differentially to information-processing during behavior is not known. We employed a novel technique for recording and labeling interneurons and pyramidal cells in drug-free, freely-moving rats. Recorded parvalbumin-expressing basket interneurons innervate somata and proximal pyramidal cell dendrites, whereas nitric-oxide-synthase- and neuropeptide-Y-expressing ivy cells provide synaptic and extrasynaptic dendritic modulation. Basket and ivy cells showed distinct spike timing dynamics, firing at different rates and times during theta and ripple oscillations. Basket but not ivy cells changed their firing rates during movement, sleep and quiet wakefulness, suggesting that basket cells coordinate cell assemblies in a behavioral state-contingent manner, whereas persistently-firing ivy cells might control network excitability and homeostasis. Different interneuron types provide GABA to specific subcellular domains at defined times and rates, thus differentially controlling network activity during behavior. PMID:22864613

  16. Hippocampal State-Dependent Behavioral Reflex to an Identical Sensory Input in Rats

    PubMed Central

    Tokuda, Keita; Nishikawa, Michimasa; Kawahara, Shigenori

    2014-01-01

    We examined the local field potential of the hippocampus to monitor brain states during a conditional discrimination task, in order to elucidate the relationship between ongoing brain states and a conditioned motor reflex. Five 10-week-old Wistar/ST male rats underwent a serial feature positive conditional discrimination task in eyeblink conditioning using a preceding light stimulus as a conditional cue for reinforced trials. In this task, a 2-s light stimulus signaled that the following 350-ms tone (conditioned stimulus) was reinforced with a co-terminating 100-ms periorbital electrical shock. The interval between the end of conditional cue and the onset of the conditioned stimulus was 4±1 s. The conditioned stimulus was not reinforced when the light was not presented. Animals successfully utilized the light stimulus as a conditional cue to drive differential responses to the identical conditioned stimulus. We found that presentation of the conditional cue elicited hippocampal theta oscillations, which persisted during the interval of conditional cue and the conditioned stimulus. Moreover, expression of the conditioned response to the tone (conditioned stimulus) was correlated with the appearance of theta oscillations immediately before the conditioned stimulus. These data support hippocampal involvement in the network underlying a conditional discrimination task in eyeblink conditioning. They also suggest that the preceding hippocampal activity can determine information processing of the tone stimulus in the cerebellum and its associated circuits. PMID:25397873

  17. Hippocampal state-dependent behavioral reflex to an identical sensory input in rats.

    PubMed

    Tokuda, Keita; Nishikawa, Michimasa; Kawahara, Shigenori

    2014-01-01

    We examined the local field potential of the hippocampus to monitor brain states during a conditional discrimination task, in order to elucidate the relationship between ongoing brain states and a conditioned motor reflex. Five 10-week-old Wistar/ST male rats underwent a serial feature positive conditional discrimination task in eyeblink conditioning using a preceding light stimulus as a conditional cue for reinforced trials. In this task, a 2-s light stimulus signaled that the following 350-ms tone (conditioned stimulus) was reinforced with a co-terminating 100-ms periorbital electrical shock. The interval between the end of conditional cue and the onset of the conditioned stimulus was 4±1 s. The conditioned stimulus was not reinforced when the light was not presented. Animals successfully utilized the light stimulus as a conditional cue to drive differential responses to the identical conditioned stimulus. We found that presentation of the conditional cue elicited hippocampal theta oscillations, which persisted during the interval of conditional cue and the conditioned stimulus. Moreover, expression of the conditioned response to the tone (conditioned stimulus) was correlated with the appearance of theta oscillations immediately before the conditioned stimulus. These data support hippocampal involvement in the network underlying a conditional discrimination task in eyeblink conditioning. They also suggest that the preceding hippocampal activity can determine information processing of the tone stimulus in the cerebellum and its associated circuits. PMID:25397873

  18. Movement Enhances the Nonlinearity of Hippocampal Theta

    PubMed Central

    Sheremet, Alex; Burke, Sara N.

    2016-01-01

    The nonlinear, metastable dynamics of the brain are essential for large-scale integration of smaller components and for the rapid organization of neurons in support of behavior. Therefore, understanding the nonlinearity of the brain is paramount for understanding the relationship between brain dynamics and behavior. Explicit quantitative descriptions of the properties and consequences of nonlinear neural networks, however, are rare. Because the local field potential (LFP) reflects the total activity across a population of neurons, nonlinearites of the nervous system should be quantifiable by examining oscillatory structure. We used high-order spectral analysis of LFP recorded from the dorsal and intermediate regions of the rat hippocampus to show that the nonlinear character of the hippocampal theta rhythm is directly related to movement speed of the animal. In the time domain, nonlinearity is expressed as the development of skewness and asymmetry in the theta shape. In the spectral domain, nonlinear dynamics manifest as the development of a chain of harmonics statistically phase coupled to the theta oscillation. This evolution was modulated across hippocampal regions, being stronger in the dorsal CA1 relative to more intermediate areas. The intensity and timing of the spiking activity of pyramidal cells and interneurons was strongly correlated to theta nonlinearity. Because theta is known to propagate from dorsal to ventral regions of the hippocampus, these data suggest that the nonlinear character of theta decreases as it travels and supports a hypothesis that activity dissipates along the longitudinal axis of the hippocampus. SIGNIFICANCE STATEMENT We describe the first explicit quantification regarding how behavior enhances the nonlinearity of the nervous system. Our findings demonstrate uniquely how theta changes with increasing speed due to the altered underlying neuronal dynamics and open new directions of research on the relationship between single

  19. Phase patterns in finite oscillator networks with insights from the piecewise linear approximation

    NASA Astrophysics Data System (ADS)

    Goldstein, Daniel

    2015-03-01

    Recent experiments on spatially extend arrays of droplets containing Belousov-Zhabotinsky reactants have shown a rich variety of spatio-temporal patterns. Motivated by this experimental set up, we study a simple model of chemical oscillators in the highly nonlinear excitable regime in order to gain insight into the mechanism giving rise to the observed multistable attractors. When coupled, these two attractors have different preferred phase synchronizations, leading to complex behavior. We study rings of coupled oscillators and observe a rich array of oscillating patterns. We combine Turing analysis and a piecewise linear approximation to better understand the observed patterns.

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

    NASA Astrophysics Data System (ADS)

    Mikkelsen, Kaare; Imparato, Alberto; Torcini, Alessandro

    2013-05-01

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

  1. Theta oscillations regulate the speed of locomotion via a hippocampus to lateral septum pathway.

    PubMed

    Bender, Franziska; Gorbati, Maria; Cadavieco, Marta Carus; Denisova, Natalia; Gao, Xiaojie; Holman, Constance; Korotkova, Tatiana; Ponomarenko, Alexey

    2015-10-12

    Hippocampal theta oscillations support encoding of an animal's position during spatial navigation, yet longstanding questions about their impact on locomotion remain unanswered. Combining optogenetic control of hippocampal theta oscillations with electrophysiological recordings in mice, we show that hippocampal theta oscillations regulate locomotion. In particular, we demonstrate that their regularity underlies more stable and slower running speeds during exploration. More regular theta oscillations are accompanied by more regular theta-rhythmic spiking output of pyramidal cells. Theta oscillations are coordinated between the hippocampus and its main subcortical output, the lateral septum (LS). Chemo- or optogenetic inhibition of this pathway reveals its necessity for the hippocampal regulation of running speed. Moreover, theta-rhythmic stimulation of LS projections to the lateral hypothalamus replicates the reduction of running speed induced by more regular hippocampal theta oscillations. These results suggest that changes in hippocampal theta synchronization are translated into rapid adjustment of running speed via the LS.

  2. Theta oscillations regulate the speed of locomotion via a hippocampus to lateral septum pathway

    PubMed Central

    Bender, Franziska; Gorbati, Maria; Cadavieco, Marta Carus; Denisova, Natalia; Gao, Xiaojie; Holman, Constance; Korotkova, Tatiana; Ponomarenko, Alexey

    2015-01-01

    Hippocampal theta oscillations support encoding of an animal's position during spatial navigation, yet longstanding questions about their impact on locomotion remain unanswered. Combining optogenetic control of hippocampal theta oscillations with electrophysiological recordings in mice, we show that hippocampal theta oscillations regulate locomotion. In particular, we demonstrate that their regularity underlies more stable and slower running speeds during exploration. More regular theta oscillations are accompanied by more regular theta-rhythmic spiking output of pyramidal cells. Theta oscillations are coordinated between the hippocampus and its main subcortical output, the lateral septum (LS). Chemo- or optogenetic inhibition of this pathway reveals its necessity for the hippocampal regulation of running speed. Moreover, theta-rhythmic stimulation of LS projections to the lateral hypothalamus replicates the reduction of running speed induced by more regular hippocampal theta oscillations. These results suggest that changes in hippocampal theta synchronization are translated into rapid adjustment of running speed via the LS. PMID:26455912

  3. Theta oscillations regulate the speed of locomotion via a hippocampus to lateral septum pathway.

    PubMed

    Bender, Franziska; Gorbati, Maria; Cadavieco, Marta Carus; Denisova, Natalia; Gao, Xiaojie; Holman, Constance; Korotkova, Tatiana; Ponomarenko, Alexey

    2015-01-01

    Hippocampal theta oscillations support encoding of an animal's position during spatial navigation, yet longstanding questions about their impact on locomotion remain unanswered. Combining optogenetic control of hippocampal theta oscillations with electrophysiological recordings in mice, we show that hippocampal theta oscillations regulate locomotion. In particular, we demonstrate that their regularity underlies more stable and slower running speeds during exploration. More regular theta oscillations are accompanied by more regular theta-rhythmic spiking output of pyramidal cells. Theta oscillations are coordinated between the hippocampus and its main subcortical output, the lateral septum (LS). Chemo- or optogenetic inhibition of this pathway reveals its necessity for the hippocampal regulation of running speed. Moreover, theta-rhythmic stimulation of LS projections to the lateral hypothalamus replicates the reduction of running speed induced by more regular hippocampal theta oscillations. These results suggest that changes in hippocampal theta synchronization are translated into rapid adjustment of running speed via the LS. PMID:26455912

  4. The Regulation of Cytokine Networks in Hippocampal CA1 Differentiates Extinction from Those Required for the Maintenance of Contextual Fear Memory after Recall

    PubMed Central

    Scholz, Birger; Doidge, Amie N.; Barnes, Philip; Hall, Jeremy; Wilkinson, Lawrence S.; Thomas, Kerrie L.

    2016-01-01

    We investigated the distinctiveness of gene regulatory networks in CA1 associated with the extinction of contextual fear memory (CFM) after recall using Affymetrix GeneChip Rat Genome 230 2.0 Arrays. These data were compared to previously published retrieval and reconsolidation-attributed, and consolidation datasets. A stringent dual normalization and pareto-scaled orthogonal partial least-square discriminant multivariate analysis together with a jack-knifing-based cross-validation approach was used on all datasets to reduce false positives. Consolidation, retrieval and extinction were correlated with distinct patterns of gene expression 2 hours later. Extinction-related gene expression was most distinct from the profile accompanying consolidation. A highly specific feature was the discrete regulation of neuroimmunological gene expression associated with retrieval and extinction. Immunity–associated genes of the tyrosine kinase receptor TGFβ and PDGF, and TNF families’ characterized extinction. Cytokines and proinflammatory interleukins of the IL-1 and IL-6 families were enriched with the no-extinction retrieval condition. We used comparative genomics to predict transcription factor binding sites in proximal promoter regions of the retrieval-regulated genes. Retrieval that does not lead to extinction was associated with NF-κB-mediated gene expression. We confirmed differential NF-κBp65 expression, and activity in all of a representative sample of our candidate genes in the no-extinction condition. The differential regulation of cytokine networks after the acquisition and retrieval of CFM identifies the important contribution that neuroimmune signalling plays in normal hippocampal function. Further, targeting cytokine signalling upon retrieval offers a therapeutic strategy to promote extinction mechanisms in human disorders characterised by dysregulation of associative memory. PMID:27224427

  5. Patterns of Cortical Oscillations Organize Neural Activity into Whole-Brain Functional Networks Evident in the fMRI BOLD Signal

    PubMed Central

    Whitman, Jennifer C.; Ward, Lawrence M.; Woodward, Todd S.

    2013-01-01

    Recent findings from electrophysiology and multimodal neuroimaging have elucidated the relationship between patterns of cortical oscillations evident in EEG/MEG and the functional brain networks evident in the BOLD signal. Much of the existing literature emphasized how high-frequency cortical oscillations are thought to coordinate neural activity locally, while low-frequency oscillations play a role in coordinating activity between more distant brain regions. However, the assignment of different frequencies to different spatial scales is an oversimplification. A more informative approach is to explore the arrangements by which these low- and high-frequency oscillations work in concert, coordinating neural activity into whole-brain functional networks. When relating such networks to the BOLD signal, we must consider how the patterns of cortical oscillations change at the same speed as cognitive states, which often last less than a second. Consequently, the slower BOLD signal may often reflect the summed neural activity of several transient network configurations. This temporal mismatch can be circumvented if we use spatial maps to assess correspondence between oscillatory networks and BOLD networks. PMID:23504590

  6. Hippocampal Sclerosis: Causes and Prevention.

    PubMed

    Walker, Matthew Charles

    2015-06-01

    Hippocampal sclerosis is the commonest cause of drug-resistant epilepsy in adults, and is associated with alterations to structures and networks beyond the hippocampus.In addition to being a cause of epilepsy, the hippocampus is vulnerable to damage from seizure activity. In particular, prolonged seizures (status epilepticus) can result in hippocampal sclerosis. The hippocampus is also vulnerable to other insults including traumatic brain injury, and inflammation. Hippocampal sclerosis can occur in association with other brain lesions; the prevailing view is that it is probably a secondary consequence. In such instances, successful surgical treatment usually involves the resection of both the lesion and the involved hippocampus. Experimental data have pointed to numerous neuroprotective strategies to prevent hippocampal sclerosis. Initial neuroprotective strategies aimed at glutamate receptors may be effective, but later, metabolic pathways, apoptosis, reactive oxygen species, and inflammation are involved, perhaps necessitating the use of interventions aimed at multiple targets. Some of the therapies that we use to treat status epilepticus may neuroprotect. However, prevention of neuronal death does not necessarily prevent the later development of epilepsy or cognitive deficits. Perhaps, the most important intervention is the early, aggressive treatment of seizure activity, and the prevention of prolonged seizures. PMID:26060898

  7. A new regime for highly robust gamma oscillation with co-exist of accurate and weak synchronization in excitatory-inhibitory networks.

    PubMed

    Wang, Zhijie; Fan, Hong; Han, Fang

    2014-08-01

    A great number of biological experiments show that gamma oscillation occurs in many brain areas after the presentation of stimulus. The neural systems in these brain areas are highly heterogeneous. Specifically, the neurons and synapses in these neural systems are diversified; the external inputs and parameters of these neurons and synapses are heterogeneous. How the gamma oscillation generated in such highly heterogeneous networks remains a challenging problem. Aiming at this problem, a highly heterogeneous complex network model that takes account of many aspects of real neural circuits was constructed. The network model consists of excitatory neurons and fast spiking interneurons, has three types of synapses (GABAA, AMPA, and NMDA), and has highly heterogeneous external drive currents. We found a new regime for robust gamma oscillation, i.e. the oscillation in inhibitory neurons is rather accurate but the oscillation in excitatory neurons is weak, in such highly heterogeneous neural networks. We also found that the mechanism of the oscillation is a mixture of interneuron gamma (ING) and pyramidal-interneuron gamma (PING). We explained the mixture ING and PING mechanism in a consistent-way by a compound post-synaptic current, which has a slowly rising-excitatory stage and a sharp decreasing-inhibitory stage.

  8. Uniting functional network topology and oscillations in the fronto-parietal single unit network of behaving primates.

    PubMed

    Dann, Benjamin; Michaels, Jonathan A; Schaffelhofer, Stefan; Scherberger, Hansjörg

    2016-08-15

    The functional communication of neurons in cortical networks underlies higher cognitive processes. Yet, little is known about the organization of the single neuron network or its relationship to the synchronization processes that are essential for its formation. Here, we show that the functional single neuron network of three fronto-parietal areas during active behavior of macaque monkeys is highly complex. The network was closely connected (small-world) and consisted of functional modules spanning these areas. Surprisingly, the importance of different neurons to the network was highly heterogeneous with a small number of neurons contributing strongly to the network function (hubs), which were in turn strongly inter-connected (rich-club). Examination of the network synchronization revealed that the identified rich-club consisted of neurons that were synchronized in the beta or low frequency range, whereas other neurons were mostly non-oscillatory synchronized. Therefore, oscillatory synchrony may be a central communication mechanism for highly organized functional spiking networks.

  9. Millisecond Timescale Synchrony among Hippocampal Neurons

    PubMed Central

    Amarasingham, Asohan; Mizuseki, Kenji; Buzsáki, György

    2014-01-01

    Inhibitory neurons in cortical circuits play critical roles in composing spike timing and oscillatory patterns in neuronal activity. These roles in turn require coherent activation of interneurons at different timescales. To investigate how the local circuitry provides for these activities, we applied resampled cross-correlation analyses to large-scale recordings of neuronal populations in the cornu ammonis 1 (CA1) and CA3 regions of the hippocampus of freely moving rats. Significant counts in the cross-correlation of cell pairs, relative to jittered surrogate spike-trains, allowed us to identify the effective couplings between neurons in CA1 and CA3 hippocampal regions on the timescale of milliseconds. In addition to putative excitatory and inhibitory monosynaptic connections, we uncovered prominent millisecond timescale synchrony between cell pairs, observed as peaks in the central 0 ms bin of cross-correlograms. This millisecond timescale synchrony appeared to be independent of network state, excitatory input, and γ oscillations. Moreover, it was frequently observed between cells of differing putative interneuronal type, arguing against gap junctions as the sole underlying source. Our observations corroborate recent in vitro findings suggesting that inhibition alone is sufficient to synchronize interneurons at such fast timescales. Moreover, we show that this synchronous spiking may cause stronger inhibition and rebound spiking in target neurons, pointing toward a potential function for millisecond synchrony of interneurons in shaping and affecting timing in pyramidal populations within and downstream from the circuit. PMID:25378164

  10. Molecular Titration Promotes Oscillations and Bistability in Minimal Network Models with Monomeric Regulators.

    PubMed

    Cuba Samaniego, Christian; Giordano, Giulia; Kim, Jongmin; Blanchini, Franco; Franco, Elisa

    2016-04-15

    Molecular titration is emerging as an important biochemical interaction mechanism within synthetic devices built with nucleic acids and the CRISPR/Cas system. We show that molecular titration in the context of feedback circuits is a suitable mechanism to enhance the emergence of oscillations and bistable behaviors. We consider biomolecular modules that can be inhibited or activated by input monomeric regulators; the regulators compete with constitutive titrating species to determine the activity of their target. By tuning the titration rate and the concentration of titrating species, it is possible to modulate the delay and convergence speed of the transient response, and the steepness and dead zone of the stationary response of the modules. These phenomena favor the occurrence of oscillations when modules are interconnected to create a negative feedback loop; bistability is favored in a positive feedback interconnection. Numerical simulations are supported by mathematical analysis showing that the capacity of the closed loop systems to exhibit oscillations or bistability is structural.

  11. Correlations, fluctuations, and stability of a finite-size network of coupled oscillators.

    PubMed

    Buice, Michael A; Chow, Carson C

    2007-09-01

    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 nonequilibrium 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.

  12. Correlations, fluctuations, and stability of a finite-size network of coupled oscillators

    SciTech Connect

    Buice, Michael A.; Chow, Carson C.

    2007-09-15

    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 nonequilibrium 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{yields}{infinity} limit of this theory is what is traditionally called mean field theory for the Kuramoto model.

  13. Topological defect formation in 1D and 2D spin chains realized by network of optical parametric oscillators

    NASA Astrophysics Data System (ADS)

    Hamerly, Ryan; Inaba, Kensuke; Inagaki, Takahiro; Takesue, Hiroki; Yamamoto, Yoshihisa; Mabuchi, Hideo

    2016-09-01

    A network of optical parametric oscillators (OPOs) is used to simulate classical Ising and XY spin chains. The collective nonlinear dynamics of this network, driven by quantum noise rather than thermal fluctuations, seeks out the Ising/XY ground state as the system transitions from below to above the lasing threshold. We study the behavior of this “Ising machine” for three canonical problems: a 1D ferromagnetic spin chain, a 2D square lattice and problems where next-nearest-neighbor couplings give rise to frustration. If the pump turn-on time is finite, topological defects form (domain walls for the Ising model, winding number and vortices for XY) and their density can be predicted from a numerical model involving a linear “growth stage” and a nonlinear “saturation stage”. These predictions are compared against recent data for a 10,000-spin 1D Ising machine.

  14. Synaptic Mechanisms of Memory Consolidation during Sleep Slow Oscillations

    PubMed Central

    Wei, Yina; Krishnan, Giri P.

    2016-01-01

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

  15. Oscillation and coding in a formal neural network considered as a guide for plausible simulations of the insect olfactory system.

    PubMed

    Horcholle-Bossavit, Ginette; Quenet, Brigitte; Foucart, Olivier

    2007-01-01

    For the analysis of coding mechanisms in the insect olfactory system, a fully connected network of synchronously updated McCulloch and Pitts neurons (MC-P type) was developed [Quenet, B., Horn, D., 2003. The dynamic neural filter: a binary model of spatio-temporal coding. Neural Comput. 15 (2), 309-329]. Considering the update time as an intrinsic clock, this "Dynamic Neural Filter" (DNF), which maps regions of input space into spatio-temporal sequences of neuronal activity, is able to produce exact binary codes extracted from the synchronized activities recorded at the level of projection neurons (PN) in the locust antennal lobe (AL) in response to different odors [Wehr, M., Laurent, G., 1996. Odor encoding by temporal sequences of firing in oscillating neural assemblies. Nature 384, 162-166]. Here, in a first step, we separate the populations of PN and local inhibitory neurons (LN) and use the DNF as a guide for simulations based on biological plausible neurons (Hodgkin-Huxley: H-H type). We show that a parsimonious network of 10 H-H neurons generates action potentials whose timing represents the required codes. In a second step, we construct a new type of DNF in order to study the population dynamics when different delays are taken into account. We find synaptic matrices which lead to both the emergence of robust oscillations and spatio-temporal patterns, using a formal criterion, based on a Normalized Euclidian Distance (NED), in order to measure the use of the temporal dimension as a coding dimension by the DNF. Similarly to biological PN, the activity of excitatory neurons in the model can be both phase-locked to different cycles of oscillations which remind local field potential (LFP), and nevertheless exhibit dynamic behavior complex enough to be the basis of spatio-temporal codes.

  16. Cerebellum shapes hippocampal spatial code.

    PubMed

    Rochefort, Christelle; Arabo, Arnaud; André, Marion; Poucet, Bruno; Save, Etienne; Rondi-Reig, Laure

    2011-10-21

    Spatial representation is an active process that requires complex multimodal integration from a large interacting network of cortical and subcortical structures. We sought to determine the role of cerebellar protein kinase C (PKC)-dependent plasticity in spatial navigation by recording the activity of hippocampal place cells in transgenic L7PKCI mice with selective disruption of PKC-dependent plasticity at parallel fiber-Purkinje cell synapses. Place cell properties were exclusively impaired when L7PKCI mice had to rely on self-motion cues. The behavioral consequence of such a deficit is evidenced here by selectively impaired navigation capabilities during a path integration task. Together, these results suggest that cerebellar PKC-dependent mechanisms are involved in processing self-motion signals essential to the shaping of hippocampal spatial representation.

  17. Uniting functional network topology and oscillations in the fronto-parietal single unit network of behaving primates

    PubMed Central

    Dann, Benjamin; Michaels, Jonathan A; Schaffelhofer, Stefan; Scherberger, Hansjörg

    2016-01-01

    The functional communication of neurons in cortical networks underlies higher cognitive processes. Yet, little is known about the organization of the single neuron network or its relationship to the synchronization processes that are essential for its formation. Here, we show that the functional single neuron network of three fronto-parietal areas during active behavior of macaque monkeys is highly complex. The network was closely connected (small-world) and consisted of functional modules spanning these areas. Surprisingly, the importance of different neurons to the network was highly heterogeneous with a small number of neurons contributing strongly to the network function (hubs), which were in turn strongly inter-connected (rich-club). Examination of the network synchronization revealed that the identified rich-club consisted of neurons that were synchronized in the beta or low frequency range, whereas other neurons were mostly non-oscillatory synchronized. Therefore, oscillatory synchrony may be a central communication mechanism for highly organized functional spiking networks. DOI: http://dx.doi.org/10.7554/eLife.15719.001 PMID:27525488

  18. The relationship between node degree and dissipation rate in networks of diffusively coupled oscillators and its significance for pancreatic beta cells.

    PubMed

    Gosak, Marko; Stožer, Andraž; Markovič, Rene; Dolenšek, Jurij; Marhl, Marko; Rupnik, Marjan Slak; Perc, Matjaž

    2015-07-01

    Self-sustained oscillatory dynamics is a motion along a stable limit cycle in the phase space, and it arises in a wide variety of mechanical, electrical, and biological systems. Typically, oscillations are due to a balance between energy dissipation and generation. Their stability depends on the properties of the attractor, in particular, its dissipative characteristics, which in turn determine the flexibility of a given dynamical system. In a network of oscillators, the coupling additionally contributes to the dissipation, and hence affects the robustness of the oscillatory solution. Here, we therefore investigate how a heterogeneous network structure affects the dissipation rate of individual oscillators. First, we show that in a network of diffusively coupled oscillators, the dissipation is a linearly decreasing function of the node degree, and we demonstrate this numerically by calculating the average divergence of coupled Hopf oscillators. Subsequently, we use recordings of intracellular calcium dynamics in pancreatic beta cells in mouse acute tissue slices and the corresponding functional connectivity networks for an experimental verification of the presented theory. We use methods of nonlinear time series analysis to reconstruct the phase space and calculate the sum of Lyapunov exponents. Our analysis reveals a clear tendency of cells with a higher degree, that is, more interconnected cells, having more negative values of divergence, thus confirming our theoretical predictions. We discuss these findings in the context of energetic aspects of signaling in beta cells and potential risks for pathological changes in the tissue. PMID:26232966

  19. The relationship between node degree and dissipation rate in networks of diffusively coupled oscillators and its significance for pancreatic beta cells.

    PubMed

    Gosak, Marko; Stožer, Andraž; Markovič, Rene; Dolenšek, Jurij; Marhl, Marko; Rupnik, Marjan Slak; Perc, Matjaž

    2015-07-01

    Self-sustained oscillatory dynamics is a motion along a stable limit cycle in the phase space, and it arises in a wide variety of mechanical, electrical, and biological systems. Typically, oscillations are due to a balance between energy dissipation and generation. Their stability depends on the properties of the attractor, in particular, its dissipative characteristics, which in turn determine the flexibility of a given dynamical system. In a network of oscillators, the coupling additionally contributes to the dissipation, and hence affects the robustness of the oscillatory solution. Here, we therefore investigate how a heterogeneous network structure affects the dissipation rate of individual oscillators. First, we show that in a network of diffusively coupled oscillators, the dissipation is a linearly decreasing function of the node degree, and we demonstrate this numerically by calculating the average divergence of coupled Hopf oscillators. Subsequently, we use recordings of intracellular calcium dynamics in pancreatic beta cells in mouse acute tissue slices and the corresponding functional connectivity networks for an experimental verification of the presented theory. We use methods of nonlinear time series analysis to reconstruct the phase space and calculate the sum of Lyapunov exponents. Our analysis reveals a clear tendency of cells with a higher degree, that is, more interconnected cells, having more negative values of divergence, thus confirming our theoretical predictions. We discuss these findings in the context of energetic aspects of signaling in beta cells and potential risks for pathological changes in the tissue.

  20. Memory Retrieval Time and Memory Capacity of the CA3 Network: Role of Gamma Frequency Oscillations

    ERIC Educational Resources Information Center

    de Almeida, Licurgo; Idiart, Marco; Lisman, John E.

    2007-01-01

    The existence of recurrent synaptic connections in CA3 led to the hypothesis that CA3 is an autoassociative network similar to the Hopfield networks studied by theorists. CA3 undergoes gamma frequency periodic inhibition that prevents a persistent attractor state. This argues against the analogy to Hopfield nets, in which an attractor state can be…

  1. Terminal Field and Firing Selectivity of Cholecystokinin-Expressing Interneurons in the Hippocampal CA3 Area

    PubMed Central

    Lasztóczi, Bálint; Tukker, John J.; Somogyi, Peter; Klausberger, Thomas

    2015-01-01

    Hippocampal oscillations reflect coordinated neuronal activity on many timescales. Distinct types of GABAergic interneuron participate in the coordination of pyramidal cells over different oscillatory cycle phases. In the CA3 area, which generates sharp waves and gamma oscillations, the contribution of identified GABAergic neurons remains to be defined. We have examined the firing of a family of cholecystokinin-expressing interneurons during network oscillations in urethane-anesthetized rats and compared them with firing of CA3 pyramidal cells. The position of the terminals of individual visualized interneurons was highly diverse, selective, and often spatially coaligned with either the entorhinal or the associational inputs to area CA3. The spike timing in relation to theta and gamma oscillations and sharp waves was correlated with the innervated pyramidal cell domain. Basket and dendritic-layer-innervating interneurons receive entorhinal and associational inputs and preferentially fire on the ascending theta phase, when pyramidal cell assemblies emerge. Perforant-path-associated cells, driven by recurrent collaterals of pyramidal cells fire on theta troughs, when established pyramidal cell assemblies are most active. In the CA3 area, slow and fast gamma oscillations occurred on opposite theta oscillation phases. Perforant-path-associated and some COUP-TFII-positive interneurons are strongly coupled to both fast and slow gamma oscillations, but basket and dendritic-layer-innervating cells are weakly coupled to fast gamma oscillations only. During sharp waves, different interneuron types are activated, inhibited, or remain unaffected. We suggest that specialization in pyramidal cell domain and glutamatergic input-specific operations, reflected in the position of GABAergic terminals, is the evolutionary drive underlying the diversity of cholecystokinin-expressing interneurons. PMID:22159120

  2. Oscillation-Driven Spike-Timing Dependent Plasticity Allows Multiple Overlapping Pattern Recognition in Inhibitory Interneuron Networks.

    PubMed

    Garrido, Jesús A; Luque, Niceto R; Tolu, Silvia; D'Angelo, Egidio

    2016-08-01

    The majority of operations carried out by the brain require learning complex signal patterns for future recognition, retrieval and reuse. Although learning is thought to depend on multiple forms of long-term synaptic plasticity, the way this latter contributes to pattern recognition is still poorly understood. Here, we have used a simple model of afferent excitatory neurons and interneurons with lateral inhibition, reproducing a network topology found in many brain areas from the cerebellum to cortical columns. When endowed with spike-timing dependent plasticity (STDP) at the excitatory input synapses and at the inhibitory interneuron-interneuron synapses, the interneurons rapidly learned complex input patterns. Interestingly, induction of plasticity required that the network be entrained into theta-frequency band oscillations, setting the internal phase-reference required to drive STDP. Inhibitory plasticity effectively distributed multiple patterns among available interneurons, thus allowing the simultaneous detection of multiple overlapping patterns. The addition of plasticity in intrinsic excitability made the system more robust allowing self-adjustment and rescaling in response to a broad range of input patterns. The combination of plasticity in lateral inhibitory connections and homeostatic mechanisms in the inhibitory interneurons optimized mutual information (MI) transfer. The storage of multiple complex patterns in plastic interneuron networks could be critical for the generation of sparse representations of information in excitatory neuron populations falling under their control. PMID:27079422

  3. Multistable Attractors in a Network of Phase Oscillators with Three-Body Interactions

    NASA Astrophysics Data System (ADS)

    Tanaka, Takuma; Aoyagi, Toshio

    2011-06-01

    Three-body interactions have been found in physics, biology, and sociology. To investigate their effect on dynamical systems, as a first step, we study numerically and theoretically a system of phase oscillators with a three-body interaction. As a result, an infinite number of multistable synchronized states appear above a critical coupling strength, while a stable incoherent state always exists for any coupling strength. Owing to the infinite multistability, the degree of synchrony in an asymptotic state can vary continuously within some range depending on the initial phase pattern.

  4. Stimulus Configuration, Classical Conditioning, and Hippocampal Function.

    ERIC Educational Resources Information Center

    Schmajuk, Nestor A.; DiCarlo, James J.

    1991-01-01

    The participation of the hippocampus in classical conditioning is described in terms of a multilayer network portraying stimulus configuration. A model of hippocampal function is presented, and computer simulations are used to study neural activity in the various brain areas mapped according to the model. (SLD)

  5. Hippocampal Theta Modulation of Neocortical Spike Times and Gamma Rhythm: A Biophysical Model Study

    PubMed Central

    Spaak, Eelke; Zeitler, Magteld; Gielen, Stan

    2012-01-01

    The hippocampal theta and neocortical gamma rhythms are two prominent examples of oscillatory neuronal activity. The hippocampus has often been hypothesized to influence neocortical networks by its theta rhythm, and, recently, evidence for such a direct influence has been found. We examined a possible mechanism for this influence by means of a biophysical model study using conductance-based model neurons. We found, in agreement with previous studies, that networks of fast-spiking GABA -ergic interneurons, coupled with shunting inhibition, synchronize their spike activity at a gamma frequency and are able to impose this rhythm on a network of pyramidal cells to which they are coupled. When our model was supplied with hippocampal theta-modulated input fibres, the theta rhythm biased the spike timings of both the fast-spiking and pyramidal cells. Furthermore, both the amplitude and frequency of local field potential gamma oscillations were influenced by the phase of the theta rhythm. We show that the fast-spiking cells, not pyramidal cells, are essential for this latter phenomenon, thus highlighting their crucial role in the interplay between hippocampus and neocortex. PMID:23056213

  6. Phase-resetting curves determine synchronization, phase locking, and clustering in networks of neural oscillators.

    PubMed

    Achuthan, Srisairam; Canavier, Carmen C

    2009-04-22

    Networks of model neurons were constructed and their activity was predicted using an iterated map based solely on the phase-resetting curves (PRCs). The predictions were quite accurate provided that the resetting to simultaneous inputs was calculated using the sum of the simultaneously active conductances, obviating the need for weak coupling assumptions. Fully synchronous activity was observed only when the slope of the PRC at a phase of zero, corresponding to spike initiation, was positive. A novel stability criterion was developed and tested for all-to-all networks of identical, identically connected neurons. When the PRC generated using N-1 simultaneously active inputs becomes too steep, the fully synchronous mode loses stability in a network of N model neurons. Therefore, the stability of synchrony can be lost by increasing the slope of this PRC either by increasing the network size or the strength of the individual synapses. Existence and stability criteria were also developed and tested for the splay mode in which neurons fire sequentially. Finally, N/M synchronous subclusters of M neurons were predicted using the intersection of parameters that supported both between-cluster splay and within-cluster synchrony. Surprisingly, the splay mode between clusters could enforce synchrony on subclusters that were incapable of synchronizing themselves. These results can be used to gain insights into the activity of networks of biological neurons whose PRCs can be measured.

  7. Molecular stripping, targets and decoys as modulators of oscillations in the NF-κB/IκBα/DNA genetic network

    PubMed Central

    Wang, Zhipeng; Wolynes, Peter G.

    2016-01-01

    Eukaryotic transcription factors in the NF-κB family are central components of an extensive genetic network that activates cellular responses to inflammation and to a host of other external stressors. This network consists of feedback loops that involve the inhibitor IκBα, numerous downstream functional targets, and still more numerous binding sites that do not appear to be directly functional. Under steady stimulation, the regulatory network of NF-κB becomes oscillatory, and temporal patterns of NF-κB pulses appear to govern the patterns of downstream gene expression needed for immune response. Understanding how the information from external stress passes to oscillatory signals and is then ultimately relayed to gene expression is a general issue in systems biology. Recently, in vitro kinetic experiments as well as molecular simulations suggest that active stripping of NF-κB by IκBα from its binding sites can modify the traditional systems biology view of NF-κB/IκBα gene circuits. In this work, we revise the commonly adopted minimal model of the NF-κB regulatory network to account for the presence of the large number of binding sites for NF-κB along with dissociation from these sites that may proceed either by passive unbinding or by active molecular stripping. We identify regimes where the kinetics of target and decoy unbinding and molecular stripping enter a dynamic tug of war that may either compensate each other or amplify nuclear NF-κB activity, leading to distinct oscillatory patterns. Our finding that decoys and stripping play a key role in shaping the NF-κB oscillations suggests strategies to control NF-κB responses by introducing artificial decoys therapeutically. PMID:27683001

  8. Interictal epileptiform discharges induce hippocampal-cortical coupling in temporal lobe epilepsy

    PubMed Central

    Gelinas, Jennifer N.; Khodagholy, Dion; Thesen, Thomas; Devinsky, Orrin; Buzsáki, György

    2016-01-01

    Interactions between the hippocampus and cortex are critical for memory. Interictal epileptiform discharges (IEDs) identify epileptic brain regions and can impair memory, but how they interact with physiological patterns of network activity is mostly undefined. We show in a rat model of temporal lobe epilepsy that spontaneous hippocampal IEDs correlate with impaired memory consolidation and are precisely coordinated with spindle oscillations in the prefrontal cortex during NREM sleep. This coordination surpasses the normal physiological ripple-spindle coupling and is accompanied by decreased ripple occurrence. IEDs also induce spindles during REM sleep and wakefulness, behavioral states that do not naturally express these oscillations, by generating a cortical ‘DOWN’ state. We confirm a similar correlation of temporofrontal IEDs with spindles over anatomically restricted cortical regions in a pilot clinical examination of four subjects with focal epilepsy. These findings imply that IEDs may impair memory via misappropriation of physiological mechanisms for hippocampal-cortical coupling, suggesting a target to treat memory impairment in epilepsy. PMID:27111281

  9. Effects of neonatal stress on gamma oscillations in hippocampus

    PubMed Central

    Dricks, Sally

    2016-01-01

    Chronic early life stress increases adult risk for depression, bipolar disorder and schizophrenia, illnesses characterized by aberrant functions of cognition and memory. We asked whether chronic early life stress disrupts maturation of gamma oscillations, on which these functions depend. Lifelong impairment of the stress response results from separation of rat pups from the dam for three hours per day during a critical period of hippocampal development (PNDs 2–14). Parvalbumin-expressing interneurons, including the basket cell network which is fundamental to gamma oscillations, are reduced in number in post mortem studies of bipolar disorder and schizophrenia, and in chronically-stressed adult rats. To determine effects of chronic early life stress on gamma oscillations, we separated pups from dams once each day on PNDs 2–14 and recorded in vitro at PNDs 15–21. In control pups, separated for 15 minutes per day, gamma power had highly significant correlations with both age (p = 0.0022) and weight (p = 0.0024); gamma in pups separated for 180 minutes per day was not correlated with either factor. ANCOVA indicated significant differences between the groups in both measures. These findings indicate that chronic early life stress can disrupt maturation of the gamma oscillation network. PMID:27363787

  10. Sleep-Stage Correlates of Hippocampal Electroencephalogram in Primates

    PubMed Central

    Eifuku, Satoshi; Fushiki, Hiroaki; Watanabe, Yukio; Uchiyama, Kumiko

    2013-01-01

    It has been demonstrated in the rodent hippocampus that rhythmic slow activity (theta) predominantly occurs during rapid eye movement (REM) sleep, while sharp waves and associated ripples occur mainly during non-REM sleep. However, evidence is lacking for correlates of sleep stages with electroencephalogram (EEG) in the hippocampus of monkeys. In the present study, we recorded hippocampal EEG from the dentate gyrus in monkeys overnight under conditions of polysomnographical monitoring. As result, the hippocampal EEG changed in a manner similar to that of the surface EEG: during wakefulness, the hippocampal EEG showed fast, desynchronized waves, which were partly replaced with slower waves of intermediate amplitudes during the shallow stages of non-REM sleep. During the deep stages of non-REM sleep, continuous, slower oscillations (0.5–8 Hz) with high amplitudes were predominant. During REM sleep, the hippocampal EEG again showed fast, desynchronized waves similar to those found during wakefulness. These results indicate that in the monkey, hippocampal rhythmic slow activity rarely occurs during REM sleep, which is in clear contrast to that of rodents. In addition, the increase in the slower oscillations of hippocampal EEG during non-REM sleep, which resembled that of the surface EEG, may at least partly reflect cortical inputs to the dentate gyrus during this behavioral state. PMID:24386134

  11. Climbing fiber burst size and olivary sub-threshold oscillations in a network setting.

    PubMed

    De Gruijl, Jornt R; Bazzigaluppi, Paolo; de Jeu, Marcel T G; De Zeeuw, Chris I

    2012-01-01

    The inferior olivary nucleus provides one of the two main inputs to the cerebellum: the so-called climbing fibers. Activation of climbing fibers is generally believed to be related to timing of motor commands and/or motor learning. Climbing fiber spikes lead to large all-or-none action potentials in cerebellar Purkinje cells, overriding any other ongoing activity and silencing these cells for a brief period of time afterwards. Empirical evidence shows that the climbing fiber can transmit a short burst of spikes as a result of an olivary cell somatic spike, potentially increasing the information being transferred to the cerebellum per climbing fiber activation. Previously reported results from in vitro studies suggested that the information encoded in the climbing fiber burst is related to the occurrence of the spike relative to the ongoing sub-threshold membrane potential oscillation of the olivary cell, i.e. that the phase of the oscillation is reflected in the size of the climbing fiber burst. We used a detailed three-compartmental model of an inferior olivary cell to further investigate the possible factors determining the size of the climbing fiber burst. Our findings suggest that the phase-dependency of the burst size is present but limited and that charge flow between soma and dendrite is a major determinant of the climbing fiber burst. From our findings it follows that phenomena such as cell ensemble synchrony can have a big effect on the climbing fiber burst size through dendrodendritic gap-junctional coupling between olivary cells.

  12. Lamina-specific contribution of glutamatergic and GABAergic potentials to hippocampal sharp wave-ripple complexes.

    PubMed

    Schönberger, Jan; Draguhn, Andreas; Both, Martin

    2014-01-01

    The mammalian hippocampus expresses highly organized patterns of neuronal activity which form a neuronal correlate of spatial memories. These memory-encoding neuronal ensembles form on top of different network oscillations which entrain neurons in a state- and experience-dependent manner. The mechanisms underlying activation, timing and selection of participating neurons are incompletely understood. Here we studied the synaptic mechanisms underlying one prominent network pattern called sharp wave-ripple complexes (SPW-R) which are involved in memory consolidation during sleep. We recorded SPW-R with extracellular electrodes along the different layers of area CA1 in mouse hippocampal slices. Contribution of glutamatergic excitation and GABAergic inhibition, respectively, was probed by local application of receptor antagonists into s. radiatum, pyramidale and oriens. Laminar profiles of field potentials show that GABAergic potentials contribute substantially to sharp waves and superimposed ripple oscillations in s. pyramidale. Inhibitory inputs to s. pyramidale and s. oriens are crucial for action potential timing by ripple oscillations, as revealed by multiunit-recordings in the pyramidal cell layer. Glutamatergic afferents, on the other hand, contribute to sharp waves in s. radiatum where they also evoke a fast oscillation at ~200 Hz. Surprisingly, field ripples in s. radiatum are slightly slower than ripples in s. pyramidale, resulting in a systematic shift between dendritic and somatic oscillations. This complex interplay between dendritic excitation and perisomatic inhibition may be responsible for the precise timing of discharge probability during the time course of SPW-R. Together, our data illustrate a complementary role of spatially confined excitatory and inhibitory transmission during highly ordered network patterns in the hippocampus. PMID:25202239

  13. Between giant oscillations and uniform distribution of droplets: The role of varying lumen of channels in microfluidic networks.

    PubMed

    Cybulski, Olgierd; Jakiela, Slawomir; Garstecki, Piotr

    2015-12-01

    The simplest microfluidic network (a loop) comprises two parallel channels with a common inlet and a common outlet. Recent studies that assumed a constant cross section of the channels along their length have shown that the sequence of droplets entering the left (L) or right (R) arm of the loop can present either a uniform distribution of choices (e.g., RLRLRL...) or long sequences of repeated choices (RRR...LLL), with all the intermediate permutations being dynamically equivalent and virtually equally probable to be observed. We use experiments and computer simulations to show that even small variation of the cross section along channels completely shifts the dynamics either into the strong preference for highly grouped patterns (RRR...LLL) that generate system-size oscillations in flow or just the opposite-to patterns that distribute the droplets homogeneously between the arms of the loop. We also show the importance of noise in the process of self-organization of the spatiotemporal patterns of droplets. Our results provide guidelines for rational design of systems that reproducibly produce either grouped or homogeneous sequences of droplets flowing in microfluidic networks.

  14. Between giant oscillations and uniform distribution of droplets: The role of varying lumen of channels in microfluidic networks

    NASA Astrophysics Data System (ADS)

    Cybulski, Olgierd; Jakiela, Slawomir; Garstecki, Piotr

    2015-12-01

    The simplest microfluidic network (a loop) comprises two parallel channels with a common inlet and a common outlet. Recent studies that assumed a constant cross section of the channels along their length have shown that the sequence of droplets entering the left (L) or right (R) arm of the loop can present either a uniform distribution of choices (e.g., RLRLRL⋯) or long sequences of repeated choices (RRR⋯LLL), with all the intermediate permutations being dynamically equivalent and virtually equally probable to be observed. We use experiments and computer simulations to show that even small variation of the cross section along channels completely shifts the dynamics either into the strong preference for highly grouped patterns (RRR⋯LLL) that generate system-size oscillations in flow or just the opposite—to patterns that distribute the droplets homogeneously between the arms of the loop. We also show the importance of noise in the process of self-organization of the spatiotemporal patterns of droplets. Our results provide guidelines for rational design of systems that reproducibly produce either grouped or homogeneous sequences of droplets flowing in microfluidic networks.

  15. Apolipoprotein E ε4 Modulates Cognitive Profiles, Hippocampal Volume, and Resting-State Functional Connectivity in Alzheimer's Disease.

    PubMed

    Wang, Xiao; Wang, Jinhui; He, Yi; Li, Huiying; Yuan, Huishu; Evans, Alan; Yu, Xin; He, Yong; Wang, Huali

    2015-01-01

    The apolipoprotein E ε4 (APOE ε4) allele is a well-established genetic risk factor for Alzheimer's disease (AD). Numerous studies have suggested that the modulation of APOE ε4 affects cognition and brain structure and function in healthy populations, particularly in the hippocampus, a key area associated with AD pathology. However, the effect of APOE ε4 allele on cognitive performance, hippocampal structural morphology, and specifically on functional characteristics in patients with AD remains poorly understood. Here, we employed a neuropsychological battery test and multi-modal structural MRI and resting-state functional MRI dataset to systematically investigate cognitive performance, hippocampal structural volume, and functional properties (including local low-frequency oscillating amplitude, intra-regional functional synchrony, and inter-regional functional connectivity) in 16 APOE ε4-carriers and 26 non-carriers at early stages of AD. Compared to non-carriers, APOE ε4-carriers exhibited poorer performance on recognition performance, but performed better on the late item generation of the verbal fluency task (associated with executive function). Structural imaging analysis revealed that APOE ε4-carriers exhibited smaller left hippocampal volumes compared to non-carriers, and the result remains significant after correcting for effects of brain size. Functional imaging analysis revealed that APOE ε4-carriers exhibited decreased amplitude of low-frequency fluctuations in the left hippocampus, non-significant changes in intra-regional synchronization within the hippocampus and decreased hippocampal functional connectivity predominantly in components of the default-mode network including the medial frontal and parietal cortices and the lateral temporal cortical regions. Taken together, our results showed APOE genotypic effects on the cognitive profile and hippocampal structural and functional characteristics in patients at early stages of AD, thus providing

  16. A population-based model of the nonlinear dynamics of the thalamocortical feedback network displays intrinsic oscillations in the spindling (7-14 Hz) range.

    PubMed

    Yousif, Nada A B; Denham, Michael

    2005-12-01

    The thalamocortical network is modelled using the Wilson-Cowan equations for neuronal population activity. We show that this population model with biologically derived parameters possesses intrinsic nonlinear oscillatory dynamics, and that the frequency of oscillation lies within the spindle range. Spindle oscillations are an early sleep oscillation characterized by high-frequency bursts of action potentials followed by a period of quiescence, at a frequency of 7-14 Hz. Spindles are generally regarded as being generated by intrathalamic circuitry, as decorticated thalamic slices and the isolated thalamic reticular nucleus exhibit spindles. However, the role of cortical feedback has been shown to regulate and synchronize the oscillation. Previous modelling studies have mainly used conductance-based models and hence the mechanism relied upon the inclusion of ionic currents, particularly the T-type calcium current. Here we demonstrate that spindle-frequency oscillatory activity can also arise from the nonlinear dynamics of the thalamocortical circuit, and we use bifurcation analysis to examine the robustness of this oscillation in terms of the functional range of the parameters used in the model. The results suggest that the thalamocortical circuit has intrinsic nonlinear population dynamics which are capable of providing robust support for oscillatory activity within the frequency range of spindle oscillations.

  17. Hippocampal “Time Cells”: Time versus Path Integration

    PubMed Central

    Kraus, Benjamin J.; Robinson, Robert J.; White, John A.; Eichenbaum, Howard; Hasselmo, Michael E.

    2014-01-01

    SUMMARY Recent studies have reported the existence of hippocampal “time cells,” neurons that fire at particular moments during periods when behavior and location are relatively constant. However, an alternative explanation of apparent time coding is that hippocampal neurons “path integrate” to encode the distance an animal has traveled. Here, we examined hippocampal neuronal firing patterns as rats ran in place on a treadmill, thus “clamping” behavior and location, while we varied the treadmill speed to distinguish time elapsed from distance traveled. Hippocampal neurons were strongly influenced by time and distance, and less so by minor variations in location. Furthermore, the activity of different neurons reflected integration over time and distance to varying extents, with most neurons strongly influenced by both factors and some significantly influenced by only time or distance. Thus, hippocampal neuronal networks captured both the organization of time and distance in a situation where these dimensions dominated an ongoing experience. PMID:23707613

  18. Acute Ethanol Inhibition of γ Oscillations Is Mediated by Akt and GSK3β.

    PubMed

    Wang, JianGang; Zhao, JingXi; Liu, ZhiHua; Guo, FangLi; Wang, Yali; Wang, Xiaofang; Zhang, RuiLing; Vreugdenhil, Martin; Lu, Chengbiao

    2016-01-01

    Hippocampal network oscillations at gamma band frequency (γ, 30-80 Hz) are closely associated with higher brain functions such as learning and memory. Acute ethanol exposure at intoxicating concentrations (≥50 mM) impairs cognitive function. This study aimed to determine the effects and the mechanisms of acute ethanol exposure on γ oscillations in an in vitro model. Ethanol (25-100 mM) suppressed kainate-induced γ oscillations in CA3 area of the rat hippocampal slices, in a concentration-dependent, reversible manner. The ethanol-induced suppression was reduced by the D1R antagonist SCH23390 or the PKA inhibitor H89, was prevented by the Akt inhibitor triciribine or the GSk3β inhibitor SB415286, was enhanced by the NMDA receptor antagonist D-AP5, but was not affected by the MAPK inhibitor U0126 or PI3K inhibitor wortmanin. Our results indicate that the intracellular kinases Akt and GSk3β play a critical role in the ethanol-induced suppression of γ oscillations and reveal new cellular pathways involved in the ethanol-induced cognitive impairment. PMID:27582689

  19. Acute Ethanol Inhibition of γ Oscillations Is Mediated by Akt and GSK3β

    PubMed Central

    Wang, JianGang; Zhao, JingXi; Liu, ZhiHua; Guo, FangLi; Wang, Yali; Wang, Xiaofang; Zhang, RuiLing; Vreugdenhil, Martin; Lu, Chengbiao

    2016-01-01

    Hippocampal network oscillations at gamma band frequency (γ, 30–80 Hz) are closely associated with higher brain functions such as learning and memory. Acute ethanol exposure at intoxicating concentrations (≥50 mM) impairs cognitive function. This study aimed to determine the effects and the mechanisms of acute ethanol exposure on γ oscillations in an in vitro model. Ethanol (25–100 mM) suppressed kainate-induced γ oscillations in CA3 area of the rat hippocampal slices, in a concentration-dependent, reversible manner. The ethanol-induced suppression was reduced by the D1R antagonist SCH23390 or the PKA inhibitor H89, was prevented by the Akt inhibitor triciribine or the GSk3β inhibitor SB415286, was enhanced by the NMDA receptor antagonist D-AP5, but was not affected by the MAPK inhibitor U0126 or PI3K inhibitor wortmanin. Our results indicate that the intracellular kinases Akt and GSk3β play a critical role in the ethanol-induced suppression of γ oscillations and reveal new cellular pathways involved in the ethanol-induced cognitive impairment. PMID:27582689

  20. Vulnerability to paroxysmal oscillations in delayed neural networks: A basis for nocturnal frontal lobe epilepsy?

    NASA Astrophysics Data System (ADS)

    Quan, Austin; Osorio, Ivan; Ohira, Toru; Milton, John

    2011-12-01

    Resonance can occur in bistable dynamical systems due to the interplay between noise and delay (τ) in the absence of a periodic input. We investigate resonance in a two-neuron model with mutual time-delayed inhibitory feedback. For appropriate choices of the parameters and inputs three fixed-point attractors co-exist: two are stable and one is unstable. In the absence of noise, delay-induced transient oscillations (referred to herein as DITOs) arise whenever the initial function is tuned sufficiently close to the unstable fixed-point. In the presence of noisy perturbations, DITOs arise spontaneously. Since the correlation time for the stationary dynamics is ˜τ, we approximated a higher order Markov process by a three-state Markov chain model by rescaling time as t → 2sτ, identifying the states based on whether the sub-intervals were completely confined to one basin of attraction (the two stable attractors) or straddled the separatrix, and then determining the transition probability matrix empirically. The resultant Markov chain model captured the switching behaviors including the statistical properties of the DITOs. Our observations indicate that time-delayed and noisy bistable dynamical systems are prone to generate DITOs as switches between the two attractors occur. Bistable systems arise transiently in situations when one attractor is gradually replaced by another. This may explain, for example, why seizures in certain epileptic syndromes tend to occur as sleep stages change.

  1. Thalamic network oscillations synchronize ontogenetic columns in the newborn rat barrel cortex.

    PubMed

    Yang, Jenq-Wei; An, Shuming; Sun, Jyh-Jang; Reyes-Puerta, Vicente; Kindler, Jennifer; Berger, Thomas; Kilb, Werner; Luhmann, Heiko J

    2013-06-01

    Neocortical areas are organized in columns, which form the basic structural and functional modules of intracortical information processing. Using voltage-sensitive dye imaging and simultaneous multi-channel extracellular recordings in the barrel cortex of newborn rats in vivo, we found that spontaneously occurring and whisker stimulation-induced gamma bursts followed by longer lasting spindle bursts were topographically organized in functional cortical columns already at the day of birth. Gamma bursts synchronized a cortical network of 300-400 µm in diameter and were coherent with gamma activity recorded simultaneously in the thalamic ventral posterior medial (VPM) nucleus. Cortical gamma bursts could be elicited by focal electrical stimulation of the VPM. Whisker stimulation-induced spindle and gamma bursts and the majority of spontaneously occurring events were profoundly reduced by the local inactivation of the VPM, indicating that the thalamus is important to generate these activity patterns. Furthermore, inactivation of the barrel cortex with lidocaine reduced the gamma activity in the thalamus, suggesting that a cortico-thalamic feedback loop modulates this early thalamic network activity.

  2. Oscillations in large-scale cortical networks: map-based model.

    PubMed

    Rulkov, N F; Timofeev, I; Bazhenov, M

    2004-01-01

    We develop a new computationally efficient approach for the analysis of complex large-scale neurobiological networks. Its key element is the use of a new phenomenological model of a neuron capable of replicating important spike pattern characteristics and designed in the form of a system of difference equations (a map). We developed a set of map-based models that replicate spiking activity of cortical fast spiking, regular spiking and intrinsically bursting neurons. Interconnected with synaptic currents these model neurons demonstrated responses very similar to those found with Hodgkin-Huxley models and in experiments. We illustrate the efficacy of this approach in simulations of one- and two-dimensional cortical network models consisting of regular spiking neurons and fast spiking interneurons to model sleep and activated states of the thalamocortical system. Our study suggests that map-based models can be widely used for large-scale simulations and that such models are especially useful for tasks where the modeling of specific firing patterns of different cell classes is important. PMID:15306740

  3. Hippocampal theta sequences reflect current goals.

    PubMed

    Wikenheiser, Andrew M; Redish, A David

    2015-02-01

    Hippocampal information processing is discretized by oscillations, and the ensemble activity of place cells is organized into temporal sequences bounded by theta cycles. Theta sequences represent time-compressed trajectories through space. Their forward-directed nature makes them an intuitive candidate mechanism for planning future trajectories, but their connection to goal-directed behavior remains unclear. As rats performed a value-guided decision-making task, the extent to which theta sequences projected ahead of the animal's current location varied on a moment-by-moment basis depending on the rat's goals. Look-ahead extended farther on journeys to distant goals than on journeys to more proximal goals and was predictive of the animal's destination. On arrival at goals, however, look-ahead was similar regardless of where the animal began its journey from. Together, these results provide evidence that hippocampal theta sequences contain information related to goals or intentions, pointing toward a potential spatial basis for planning.

  4. STABILIZED OSCILLATOR

    DOEpatents

    Jessen, P.L.; Price, H.J.

    1958-03-18

    This patent relates to sine-wave generators and in particular describes a generator with a novel feedback circuit resulting in improved frequency stability. The generator comprises two triodes having a common cathode circuit connected to oscillate at a frequency and amplitude at which the loop galn of the circutt ls unity, and another pair of triodes having a common cathode circuit arranged as a conventional amplifier. A signal is conducted from the osciliator through a frequency selective network to the amplifier and fed back to the osciliator. The unique feature of the feedback circuit is the amplifier operates in the nonlinear portion of its tube characteristics thereby providing a relatively constant feedback voltage to the oscillator irrespective of the amplitude of its input signal.

  5. Thermodynamics based on the principle of least abbreviated action: Entropy production in a network of coupled oscillators

    SciTech Connect

    Garcia-Morales, Vladimir Pellicer, Julio; Manzanares, Jose A.

    2008-08-15

    We present some novel thermodynamic ideas based on the Maupertuis principle. By considering Hamiltonians written in terms of appropriate action-angle variables we show that thermal states can be characterized by the action variables and by their evolution in time when the system is nonintegrable. We propose dynamical definitions for the equilibrium temperature and entropy as well as an expression for the nonequilibrium entropy valid for isolated systems with many degrees of freedom. This entropy is shown to increase in the relaxation to equilibrium of macroscopic systems with short-range interactions, which constitutes a dynamical justification of the Second Law of Thermodynamics. Several examples are worked out to show that this formalism yields the right microcanonical (equilibrium) quantities. The relevance of this approach to nonequilibrium situations is illustrated with an application to a network of coupled oscillators (Kuramoto model). We provide an expression for the entropy production in this system finding that its positive value is directly related to dissipation at the steady state in attaining order through synchronization.

  6. On-off intermittency of thalamo-cortical neuronal network oscillations in the electroencephalogram of rodents with genetic predisposition to absence epilepsy

    NASA Astrophysics Data System (ADS)

    Hramov, Alexander E.; Grubov, Vadim V.; Pavlov, Alexey N.; Sitnikova, Evgenija Yu.; Koronovskii, Alexey A.; Runnova, Anastasija E.; Shurugina, Sveltlana A.; Ivanov, Alexey V.

    2013-02-01

    Spike-wave discharges are electroencephalographic hallmarks of absence epilepsy. Spike-wave discharges are known to originate from thalamo-cortical neuronal network that normally produces sleep spindle oscillations. Although both sleep spindles and spike-wave discharges are considered as thalamo-cortical oscillations, functional relationship between them is still uncertain. The present study describes temporal dynamics of spike-wave discharges and sleep spindles as determined in long-time electroencephalograms (EEG) recorded in WAG/Rij rat model of absence epilepsy. We have proposed the wavelet-based method for the automatic detection of spike-wave discharges, sleep spindles (10-15Hz) and 5-9Hz oscillations in EEG. It was found that non-linear dynamics of spike-wave discharges and sleep spindles fits well to the law of 'on-off intermittency'. Intermittency in sleep spindles and spike-wave discharges implies that (1) temporal dynamics of these oscillations are deterministic in nature, and (2) it might be controlled by a system-level mechanism responsible for circadian modulation of neuronal network activity.

  7. Effects of memantine on hippocampal long-term potentiation, gamma activity, and sensorimotor gating in freely moving rats.

    PubMed

    Ma, Jingyi; Mufti, Asfandyar; Stan Leung, L

    2015-09-01

    Memantine, an uncompetitive N-methyl-D-aspartate receptor antagonist, is used for treatment of patients with Alzheimer's disease. The mechanisms of memantine in relieving cognitive and behavioral symptoms are unclear, and this study attempts to elucidate its action on network and synaptic functions of the hippocampus. The effects of memantine on electrographic activity and hippocampal long-term potentiation (LTP) were investigated in freely moving rats. Basal dendritic excitation on hippocampal CA1 pyramidal cells showed a robust LTP after theta-frequency primed bursts, and the LTP was higher after 5-10 mg/kg intraperitoneal (ip) memantine pretreatment, as compared with saline pretreatment. Injection of scopolamine (5 mg/kg ip) before memantine failed to block the LTP-enhancing effect of memantine. Memantine as compared with saline pretreatment did not affect the LTP after an afterdischarge induced by high-frequency (200-Hz) train stimulation. Memantine (5 or 10 mg/kg ip) significantly enhanced gamma oscillations in the hippocampal local field potentials of 40-100 Hz during walking and awake immobility. Memantine at 10 mg/kg ip, but not at 5 mg/kg ip, increased prepulse inhibition of the acoustic startle response, while both 5 and 10 mg/kg ip memantine enhanced the acoustic startle response as compared with saline-injected rats. These electrophysiological and behavioral effects of memantine are unique among N-methyl-D-aspartate receptor antagonists but are consistent with memantine's effects in improving cognitive and sensorimotor functions of Alzheimer's patients.

  8. Inhibitory control of hippocampal inhibitory neurons

    PubMed Central

    Chamberland, Simon; Topolnik, Lisa

    2012-01-01

    Information processing within neuronal networks is determined by a dynamic partnership between principal neurons and local circuit inhibitory interneurons. The population of GABAergic interneurons is extremely heterogeneous and comprises, in many brain regions, cells with divergent morphological and physiological properties, distinct molecular expression profiles, and highly specialized functions. GABAergic interneurons have been studied extensively during the past two decades, especially in the hippocampus, which is a relatively simple cortical structure. Different types of hippocampal inhibitory interneurons control spike initiation [e.g., axo-axonic and basket cells (BCs)] and synaptic integration (e.g., bistratified and oriens–lacunosum moleculare interneurons) within pyramidal neurons and synchronize local network activity, providing a means for functional segregation of neuronal ensembles and proper routing of hippocampal information. Thus, it is thought that, at least in the hippocampus, GABAergic inhibitory interneurons represent critical regulating elements at all stages of information processing, from synaptic integration and spike generation to large-scale network activity. However, this raises an important question: if inhibitory interneurons are fundamental for network computations, what are the mechanisms that control the activity of the interneurons themselves? Given the essential role of synaptic inhibition in the regulation of neuronal activity, it would be logical to expect that specific inhibitory mechanisms have evolved to control the operation of interneurons. Here, we review the mechanisms of synaptic inhibition of interneurons and discuss their role in the operation of hippocampal inhibitory circuits. PMID:23162426

  9. Optogenetic Activation of Septal Glutamatergic Neurons Drive Hippocampal Theta Rhythms.

    PubMed

    Robinson, Jennifer; Manseau, Frédéric; Ducharme, Guillaume; Amilhon, Bénédicte; Vigneault, Erika; El Mestikawy, Salah; Williams, Sylvain

    2016-03-01

    The medial septum and diagonal band of Broca (MS-DBB) has an essential role for theta rhythm generation in the hippocampus and is critical for learning and memory. The MS-DBB contains cholinergic, GABAergic, and recently described glutamatergic neurons, but their specific contribution to theta generation is poorly understood. Here, we examined the role of MS-DBB glutamatergic neurons in theta rhythm using optogenetic activation and electrophysiological recordings performed in in vitro preparations and in freely behaving mice. The experiments in slices suggest that MS-DBB glutamatergic neurons provide prominent excitatory inputs to a majority of local GABAergic and a minority of septal cholinergic neurons. In contrast, activation of MS-DBB glutamatergic fiber terminals in hippocampal slices elicited weak postsynaptic responses in hippocampal neurons. In the in vitro septo-hippocampal preparation, activation of MS-DBB glutamatergic neurons did increase the rhythmicity of hippocampal theta oscillations, whereas stimulation of septo-hippocampal glutamatergic fibers in the fornix did not have an effect. In freely behaving mice, activation of these neurons in the MS-DBB strongly synchronized hippocampal theta rhythms over a wide range of frequencies, whereas activation of their projections to the hippocampus through fornix stimulations had no effect on theta rhythms, suggesting that MS-DBB glutamatergic neurons played a role in theta generation through local modulation of septal neurons. Together, these results provide the first evidence that MS-DBB glutamatergic neurons modulate local septal circuits, which in turn contribute to theta rhythms in the hippocampus.

  10. Inhibitory microcircuit modules in hippocampal learning.

    PubMed

    Caroni, Pico

    2015-12-01

    It has recently become possible to investigate connectivities and roles of identified hippocampal GABAergic interneurons (INs) in behaving rodents. INs targeting distinct pyramidal neuron subcompartments are recruited dynamically at defined phases of behavior and learning. They include Parvalbumin Axo-axonic and perisomatic Basket cells, and Somatostatin radiatum-oriens and oriens-lacunosum moleculare cells. Each IN is in turn either activated or inhibited upon specific behavioral and network state requirements through specific inputs and neuromodulators. Subpopulations of these principal neurons and INs interconnect selectively, suggesting selective processing and routing of alternate information streams. First canonical functional modules have emerged, which will have to be further defined and linked to identified afferents and efferents towards a circuit understanding of how hippocampal networks support behavior.

  11. Buttressing a balanced brain: Target-derived FGF signaling regulates excitatory/inhibitory tone and adult neurogenesis within the maturating hippocampal network.

    PubMed

    Dabrowski, Ania; Umemori, Hisashi

    2016-01-01

    Brain development involves multiple levels of molecular coordination in forming a functional nervous system. The hippocampus is a brain area that is important for memory formation and spatial reasoning. During early postnatal development of the hippocampal circuit, Fibroblast growth factor 22 (FGF22) and FGF7 act to establish a balance of excitatory and inhibitory tone. Both FGFs are secreted from CA3 dendrites, acting on excitatory or inhibitory axon terminals formed onto CA3 dendrites, respectively. Mechanistically, FGF22 utilizes FGFR2b and FGFR1b to induce synaptic vesicle recruitment within axons of dentate granule cells (DGCs), and FGF7 utilizes FGFR2b to induce synaptic vesicle recruitment within interneuron axons. FGF signaling eventually induces gene expression in the presynaptic neurons; however, the effects of FGF22-induced gene expression within DGCs and FGF7-induced gene expression within interneurons in the context of a developing hippocampal circuit have yet to be explored. Here, we propose one hypothetical mechanism of FGF22-induced gene expression in controlling adult neurogenesis. PMID:27605441

  12. Oscillation death in diffusively coupled oscillators by local repulsive link.

    PubMed

    Hens, C R; Olusola, Olasunkanmi I; Pal, Pinaki; Dana, Syamal K

    2013-09-01

    A death of oscillation is reported in a network of coupled synchronized oscillators in the presence of additional repulsive coupling. The repulsive link evolves as an averaging effect of mutual interaction between two neighboring oscillators due to a local fault and the number of repulsive links grows in time when the death scenario emerges. Analytical condition for oscillation death is derived for two coupled Landau-Stuart systems. Numerical results also confirm oscillation death in chaotic systems such as a Sprott system and the Rössler oscillator. We explore the effect in large networks of globally coupled oscillators and find that the number of repulsive links is always fewer than the size of the network.

  13. Validation of solar-cycle changes in low-degree helioseismic parameters from the Birmingham Solar-Oscillations Network

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

    We present a new and up-to-date analysis of the solar low-degree p-mode parameter shifts from the Birmingham Solar-Oscillations Network over the past 22 years, up to the end of 2014. We aim to demonstrate that they are not dominated by changes in the asymmetry of the resonant peak profiles of the modes and that the previously published results on the solar-cycle variations of mode parameters are reliable. We compare the results obtained using a conventional maximum-likelihood estimation algorithm and a new one based on the Markov Chain Monte Carlo (MCMC) technique, both taking into account mode asymmetry. We assess the reliability of the solar-cycle trends seen in the data by applying the same analysis to artificially generated spectra. We find that the two methods are in good agreement. Both methods accurately reproduce the input frequency shifts in the artificial data and underestimate the amplitude and width changes by a small amount, around 10 per cent. We confirm earlier findings that the frequency and line width are positively correlated, and the mode amplitude anticorrelated, with the level of solar activity, with the energy supplied to the modes remaining essentially unchanged. For the mode asymmetry the correlation with activity is marginal, but the MCMC algorithm gives more robust results than the MLE (Maximum-Likelihood Estimate). The magnitude of the parameter shifts is consistent with earlier work. There is no evidence that the frequency changes we see arise from changes in the asymmetry, which would need to be much larger than those observed in order to give the observed frequency shift.

  14. Neuropeptides and hippocampal neurogenesis.

    PubMed

    Zaben, M J; Gray, W P

    2013-12-01

    Hippocampal neurogenesis is important for modulating the behavioural responses to stress and for certain forms of learning and memory. The mechanisms underlying the necessary coupling of neuronal activity to neural stem/progenitor cell (NSPC) function remain poorly understood. Within the dentate subgranular stem cell niche, local interneurons appear to play an important part in this excitation-neurogenesis coupling via GABAergic transmission, which promotes neuronal differentiation and integration. Neuropeptides such as neuropeptide Y (NPY), vasoactive intestinal peptide (VIP) and galanin have emerged as important mediators for signalling local and extrinsic interneuronal activity to subgranular zone precursors. Here we review the distribution of these neuropeptides and their receptors in the neurogenic area of the hippocampus and their precise effects on hippocampal neurogenesis. We also discuss neuropeptides' potential involvement in functional aspects of hippocampal neurogenesis particularly their involvement in the modulation of learning and memory and behavior responses.

  15. Spatial Noise in Coupling Strength and Natural Frequency within a Pacemaker Network; Consequences for Development of Intestinal Motor Patterns According to a Weakly Coupled Phase Oscillator Model.

    PubMed

    Parsons, Sean P; Huizinga, Jan D

    2016-01-01

    Pacemaker activities generated by networks of interstitial cells of Cajal (ICC), in conjunction with the enteric nervous system, orchestrate most motor patterns in the gastrointestinal tract. It was our objective to understand the role of network features of ICC associated with the myenteric plexus (ICC-MP) in the shaping of motor patterns of the small intestine. To that end, a model of weakly coupled oscillators (oscillators influence each other's phase but not amplitude) was created with most parameters derived from experimental data. The ICC network is a uniform two dimensional network coupled by gap junctions. All ICC generate pacemaker (slow wave) activity with a frequency gradient in mice from 50/min at the proximal end of the intestine to 40/min at the distal end. Key features of motor patterns, directly related to the underlying pacemaker activity, are frequency steps and dislocations. These were accurately mimicked by reduction of coupling strength at a point in the chain of oscillators. When coupling strength was expressed as a product of gap junction density and conductance, and gap junction density was varied randomly along the chain (i.e., spatial noise) with a long-tailed distribution, plateau steps occurred at pointsof low density. As gap junction conductance was decreased, the number of plateaus increased, mimicking the effect of the gap junction inhibitor carbenoxolone. When spatial noise was added to the natural interval gradient, as gap junction conductance decreased, the number of plateaus increased as before but in addition the phase waves frequently changed direction of apparent propagation, again mimicking the effect of carbenoxolone. In summary, key features of the motor patterns that are governed by pacemaker activity may be a direct consequence of biological noise, specifically spatial noise in gap junction coupling and pacemaker frequency. PMID:26869875

  16. Spatial Noise in Coupling Strength and Natural Frequency within a Pacemaker Network; Consequences for Development of Intestinal Motor Patterns According to a Weakly Coupled Phase Oscillator Model

    PubMed Central

    Parsons, Sean P.; Huizinga, Jan D.

    2016-01-01

    Pacemaker activities generated by networks of interstitial cells of Cajal (ICC), in conjunction with the enteric nervous system, orchestrate most motor patterns in the gastrointestinal tract. It was our objective to understand the role of network features of ICC associated with the myenteric plexus (ICC-MP) in the shaping of motor patterns of the small intestine. To that end, a model of weakly coupled oscillators (oscillators influence each other's phase but not amplitude) was created with most parameters derived from experimental data. The ICC network is a uniform two dimensional network coupled by gap junctions. All ICC generate pacemaker (slow wave) activity with a frequency gradient in mice from 50/min at the proximal end of the intestine to 40/min at the distal end. Key features of motor patterns, directly related to the underlying pacemaker activity, are frequency steps and dislocations. These were accurately mimicked by reduction of coupling strength at a point in the chain of oscillators. When coupling strength was expressed as a product of gap junction density and conductance, and gap junction density was varied randomly along the chain (i.e., spatial noise) with a long-tailed distribution, plateau steps occurred at pointsof low density. As gap junction conductance was decreased, the number of plateaus increased, mimicking the effect of the gap junction inhibitor carbenoxolone. When spatial noise was added to the natural interval gradient, as gap junction conductance decreased, the number of plateaus increased as before but in addition the phase waves frequently changed direction of apparent propagation, again mimicking the effect of carbenoxolone. In summary, key features of the motor patterns that are governed by pacemaker activity may be a direct consequence of biological noise, specifically spatial noise in gap junction coupling and pacemaker frequency. PMID:26869875

  17. Stiff substrates enhance cultured neuronal network activity

    PubMed Central

    Zhang, Quan-You; Zhang, Yan-Yan; Xie, Jing; Li, Chen-Xu; Chen, Wei-Yi; Liu, Bai-Lin; Wu, Xiao-an; Li, Shu-Na; Huo, Bo; Jiang, Lin-Hua; Zhao, Hu-Cheng

    2014-01-01

    The mechanical property of extracellular matrix and cell-supporting substrates is known to modulate neuronal growth, differentiation, extension and branching. Here we show that substrate stiffness is an important microenvironmental cue, to which mouse hippocampal neurons respond and integrate into synapse formation and transmission in cultured neuronal network. Hippocampal neurons were cultured on polydimethylsiloxane substrates fabricated to have similar surface properties but a 10-fold difference in Young's modulus. Voltage-gated Ca2+ channel currents determined by patch-clamp recording were greater in neurons on stiff substrates than on soft substrates. Ca2+ oscillations in cultured neuronal network monitored using time-lapse single cell imaging increased in both amplitude and frequency among neurons on stiff substrates. Consistently, synaptic connectivity recorded by paired recording was enhanced between neurons on stiff substrates. Furthermore, spontaneous excitatory postsynaptic activity became greater and more frequent in neurons on stiff substrates. Evoked excitatory transmitter release and excitatory postsynaptic currents also were heightened at synapses between neurons on stiff substrates. Taken together, our results provide compelling evidence to show that substrate stiffness is an important biophysical factor modulating synapse connectivity and transmission in cultured hippocampal neuronal network. Such information is useful in designing instructive scaffolds or supporting substrates for neural tissue engineering. PMID:25163607

  18. Decoupling of Sleep-Dependent Cortical and Hippocampal Interactions in a Neurodevelopmental Model of Schizophrenia

    PubMed Central

    Phillips, Keith G.; Bartsch, Ullrich; McCarthy, Andrew P.; Edgar, Dale M.; Tricklebank, Mark D.; Wafford, Keith A.; Jones, Matt W.

    2012-01-01

    Summary Rhythmic neural network activity patterns are defining features of sleep, but interdependencies between limbic and cortical oscillations at different frequencies and their functional roles have not been fully resolved. This is particularly important given evidence linking abnormal sleep architecture and memory consolidation in psychiatric diseases. Using EEG, local field potential (LFP), and unit recordings in rats, we show that anteroposterior propagation of neocortical slow-waves coordinates timing of hippocampal ripples and prefrontal cortical spindles during NREM sleep. This coordination is selectively disrupted in a rat neurodevelopmental model of schizophrenia: fragmented NREM sleep and impaired slow-wave propagation in the model culminate in deficient ripple-spindle coordination and disrupted spike timing, potentially as a consequence of interneuronal abnormalities reflected by reduced parvalbumin expression. These data further define the interrelationships among slow-wave, spindle, and ripple events, indicating that sleep disturbances may be associated with state-dependent decoupling of hippocampal and cortical circuits in psychiatric diseases. PMID:23141065

  19. Long-lasting increase of corticosterone after fear memory reactivation: anxiolytic effects and network activity modulation in the ventral hippocampus.

    PubMed

    Albrecht, Anne; Çalışkan, Gürsel; Oitzl, Melly S; Heinemann, Uwe; Stork, Oliver

    2013-02-01

    Pathological fear and anxiety can be studied, in rodents, with fear conditioning and exposure to reminder cues. These paradigms are thought to critically involve the ventral hippocampus, which also serves as key site of glucocorticoid action in the brain. Here, we demonstrate a long-lasting reduction of kainate-induced gamma oscillations in slice preparations of the ventral hippocampal area CA3, 30 days after a single fear conditioning training. Reduction of gamma power was sensitive to corticosterone application and associated with a decrease in glucocorticoid and mineralocorticoid receptor mRNA expression across strata of the ventral hippocampal CA3. A fear reactivation session 24 h after the initial conditioning normalized receptor expression levels and attenuated the corticosterone-mediated recovery of gamma oscillations. It moreover increased both baseline and stimulus-induced corticosterone plasma levels and evoked a generalization of fear memory to the background context. Reduced ventral hippocampal gamma oscillation in both fear reactivated and non-reactivated mice were associated with a decrease of anxiety-like behavior in an elevated plus maze. Taking advantage of the circadian fluctuation in corticosterone, we demonstrated the association of high endogenous basal corticosterone plasma concentrations during morning hours with reduced anxiety-like behavior in fear reactivated mice. The anxiolytic effect of the hormone was verified with local applications to the ventral hippocampus. Our data suggest that corticosterone acting on ventral hippocampal network activity has anxiolytic-like effects following fear exposure, highlighting its potential therapeutic value for anxiety disorders.

  20. Coupling between Theta Oscillations and Cognitive Control Network during Cross-Modal Visual and Auditory Attention: Supramodal vs Modality-Specific Mechanisms

    PubMed Central

    Wang, Wuyi; Viswanathan, Shivakumar; Lee, Taraz; Grafton, Scott T.

    2016-01-01

    Cortical theta band oscillations (4–8 Hz) in EEG signals have been shown to be important for a variety of different cognitive control operations in visual attention paradigms. However the synchronization source of these signals as defined by fMRI BOLD activity and the extent to which theta oscillations play a role in multimodal attention remains unknown. Here we investigated the extent to which cross-modal visual and auditory attention impacts theta oscillations. Using a simultaneous EEG-fMRI paradigm, healthy human participants performed an attentional vigilance task with six cross-modal conditions using naturalistic stimuli. To assess supramodal mechanisms, modulation of theta oscillation amplitude for attention to either visual or auditory stimuli was correlated with BOLD activity by conjunction analysis. Negative correlation was localized to cortical regions associated with the default mode network and positively with ventral premotor areas. Modality-associated attention to visual stimuli was marked by a positive correlation of theta and BOLD activity in fronto-parietal area that was not observed in the auditory condition. A positive correlation of theta and BOLD activity was observed in auditory cortex, while a negative correlation of theta and BOLD activity was observed in visual cortex during auditory attention. The data support a supramodal interaction of theta activity with of DMN function, and modality-associated processes within fronto-parietal networks related to top-down theta related cognitive control in cross-modal visual attention. On the other hand, in sensory cortices there are opposing effects of theta activity during cross-modal auditory attention. PMID:27391013

  1. The thalamic low-threshold Ca²⁺ potential: a key determinant of the local and global dynamics of the slow (<1 Hz) sleep oscillation in thalamocortical networks.

    PubMed

    Crunelli, Vincenzo; Errington, Adam C; Hughes, Stuart W; Tóth, Tibor I

    2011-10-13

    During non-rapid eye movement sleep and certain types of anaesthesia, neurons in the neocortex and thalamus exhibit a distinctive slow (<1 Hz) oscillation that consists of alternating UP and DOWN membrane potential states and which correlates with a pronounced slow (<1 Hz) rhythm in the electroencephalogram. While several studies have claimed that the slow oscillation is generated exclusively in neocortical networks and then transmitted to other brain areas, substantial evidence exists to suggest that the full expression of the slow oscillation in an intact thalamocortical (TC) network requires the balanced interaction of oscillator systems in both the neocortex and thalamus. Within such a scenario, we have previously argued that the powerful low-threshold Ca(2+) potential (LTCP)-mediated burst of action potentials that initiates the UP states in individual TC neurons may be a vital signal for instigating UP states in related cortical areas. To investigate these issues we constructed a computational model of the TC network which encompasses the important known aspects of the slow oscillation that have been garnered from earlier in vivo and in vitro experiments. Using this model we confirm that the overall expression of the slow oscillation is intricately reliant on intact connections between the thalamus and the cortex. In particular, we demonstrate that UP state-related LTCP-mediated bursts in TC neurons are proficient in triggering synchronous UP states in cortical networks, thereby bringing about a synchronous slow oscillation in the whole network. The importance of LTCP-mediated action potential bursts in the slow oscillation is also underlined by the observation that their associated dendritic Ca(2+) signals are the only ones that inform corticothalamic synapses of the TC neuron output, since they, but not those elicited by tonic action potential firing, reach the distal dendritic sites where these synapses are located.

  2. Braided oscillators

    NASA Astrophysics Data System (ADS)

    Yildiz, A.

    2002-03-01

    A generalized oscillator algebra is proposed and the braided Hopf algebra structure for this generalized oscillator is investigated. Using the solutions for the braided Hopf algebra structure, two types of braided Fibonacci oscillators are introduced. This leads to two types of braided Biedenharn-Macfarlane oscillators as special cases of the Fibonacci oscillators. We also find the braided Hopf algebra solutions for the three dimensional braided space. One of these, as a special case, gives the Hopf algebra given in the literature.

  3. Dynamical robustness of coupled heterogeneous oscillators.

    PubMed

    Tanaka, Gouhei; Morino, Kai; Daido, Hiroaki; Aihara, Kazuyuki

    2014-05-01

    We study tolerance of dynamic behavior in networks of coupled heterogeneous oscillators to deterioration of the individual oscillator components. As the deterioration proceeds with reduction in dynamic behavior of the oscillators, an order parameter evaluating the level of global oscillation decreases and then vanishes at a certain critical point. We present a method to analytically derive a general formula for this critical point and an approximate formula for the order parameter in the vicinity of the critical point in networks of coupled Stuart-Landau oscillators. Using the critical point as a measure for dynamical robustness of oscillator networks, we show that the more heterogeneous the oscillator components are, the more robust the oscillatory behavior of the network is to the component deterioration. This property is confirmed also in networks of Morris-Lecar neuron models coupled through electrical synapses. Our approach could provide a useful framework for theoretically understanding the role of population heterogeneity in robustness of biological networks.

  4. Constructing, Perceiving, and Maintaining Scenes: Hippocampal Activity and Connectivity

    PubMed Central

    Zeidman, Peter; Mullally, Sinéad L.; Maguire, Eleanor A.

    2015-01-01

    In recent years, evidence has accumulated to suggest the hippocampus plays a role beyond memory. A strong hippocampal response to scenes has been noted, and patients with bilateral hippocampal damage cannot vividly recall scenes from their past or construct scenes in their imagination. There is debate about whether the hippocampus is involved in the online processing of scenes independent of memory. Here, we investigated the hippocampal response to visually perceiving scenes, constructing scenes in the imagination, and maintaining scenes in working memory. We found extensive hippocampal activation for perceiving scenes, and a circumscribed area of anterior medial hippocampus common to perception and construction. There was significantly less hippocampal activity for maintaining scenes in working memory. We also explored the functional connectivity of the anterior medial hippocampus and found significantly stronger connectivity with a distributed set of brain areas during scene construction compared with scene perception. These results increase our knowledge of the hippocampus by identifying a subregion commonly engaged by scenes, whether perceived or constructed, by separating scene construction from working memory, and by revealing the functional network underlying scene construction, offering new insights into why patients with hippocampal lesions cannot construct scenes. PMID:25405941

  5. Spatiotemporal patterns of electrocorticographic very fast oscillations (>80 Hz) consistent with a network model based on electrical coupling between principal neurons

    PubMed Central

    Traub, Roger D.; Duncan, Roderick; Russell, Aline J.C.; Baldeweg, Torsten; Tu, Yuhai; Cunningham, Mark O.; Whittington, Miles A.

    2010-01-01

    SUMMARY Purpose We sought to characterize spatial and temporal patterns of electrocorticography (ECoG) very fast oscillations (> ~80 Hz, VFOs) prior to seizures in human frontotemporal neocortex, and to develop a testable network model of these patterns. Methods ECoG data were recorded with subdural grids from two preoperative patients with seizures of frontal lobe onset in an epilepsy monitoring unit. VFOs were recorded from rat neocortical slices. A “cellular automaton” model of network oscillations was developed, extending ideas of Traub et al. (Neuroscience, 92, 1999, 407) and Lewis & Rinzel (Network: Comput Neural Syst, 11, 12000, 299); this model is based on postulated electrical coupling between pyramidal cell axons. Results Layer 5 of rat neocortex, in vitro, can generate VFOs when chemical synapses are blocked. Human epileptic neocortex, in situ, produces preseizure VFOs characterized by the sudden appearance of “blobs” of activity that evolve into spreading wavefronts. When wavefronts meet, they coalesce and propagate perpendicularly but never pass through each other. This type of pattern has been described by Lewis & Rinzel in cellular automaton models with spatially localized connectivity, and is demonstrated here with 120,000- to 5,760,000-cell models. We provide a formula for estimating VFO period from structural parameters and estimate the spatial scale of the connectivity. Discussion These data provide further evidence, albeit indirect, that preseizure VFOs are generated by networks of pyramidal neurons coupled by gap junctions, each predominantly confined to pairs of neurons having somata separated by < ~1–2 mm. Plausible antiepileptic targets are tissue mechanisms, such as pH regulation, that influence gap-junction conductance. PMID:20002152

  6. Alterations in resting state oscillations and connectivity within sensory and motor networks in women with interstitial cystitis/painful bladder syndrome

    PubMed Central

    Kilpatrick, Lisa A.; Tillisch, Kirsten; Naliboff, Bruce; Labus, Jennifer; Jiang, Zhiguo; Farmer, Melissa; Apkarian, A. Vania; Mackey, Sean; Martucci, Katherine T.; Clauw, Dan; Harris, Richard E.; Deutsch, Georg; Ness, Timothy; Yang, Claire C.; Maravilla, Kenneth; Mullins, Chris; Mayer, Emeran A.

    2015-01-01

    Purpose The pathophysiology of interstitial cystitis/painful bladder syndrome (IC/PBS) remains incompletely understood, but is thought to involve a central disturbance in the processing of pain and viscerosensory signals. We aimed to identify differences in brain activity and connectivity between female IC/PBS patients and healthy controls in order to advance clinical phenotyping and treatment efforts for IC/PBS. Materials and Methods We examined oscillation dynamics of intrinsic brain activity in a large sample of well-phenotyped female IC/PBS patients and female healthy controls collected during a 10-minute resting fMRI scan as part of the Multidisciplinary Approach to the Study of Chronic Pelvic Pain (MAPP) Research Network* project. The BOLD signal was transformed to the frequency domain and relative power was computed for multiple frequency bands. Results The results demonstrated altered frequency distributions in a viscerosensory region (post Insula) and sensorimotor cortices (postcentral gyrus, paracentral lobule, supplementary motor area (SMA), including a region likely involved in control of pelvic floor muscles (PelMotor). Additionally, the SMA, paracentral lobule and PelMotor all demonstrated increased functional connectivity to the midbrain (red nucleus) and cerebellum. This increased functional connectivity was greatest in patients reporting pain during bladder filling. Conclusions These findings suggest that women with IC/PBS have a neuromotor component to their pathology involving an alteration in the intrinsic oscillations and connectivity within a cortico-cerebellar network previously associated with urinary bladder function. PMID:24681331

  7. Synchronization, non-linear dynamics and low-frequency fluctuations: Analogy between spontaneous brain activity and networked single-transistor chaotic oscillators

    SciTech Connect

    Minati, Ludovico E-mail: ludovico.minati@unitn.it

    2015-03-15

    In this paper, the topographical relationship between functional connectivity (intended as inter-regional synchronization), spectral and non-linear dynamical properties across cortical areas of the healthy human brain is considered. Based upon functional MRI acquisitions of spontaneous activity during wakeful idleness, node degree maps are determined by thresholding the temporal correlation coefficient among all voxel pairs. In addition, for individual voxel time-series, the relative amplitude of low-frequency fluctuations and the correlation dimension (D{sub 2}), determined with respect to Fourier amplitude and value distribution matched surrogate data, are measured. Across cortical areas, high node degree is associated with a shift towards lower frequency activity and, compared to surrogate data, clearer saturation to a lower correlation dimension, suggesting presence of non-linear structure. An attempt to recapitulate this relationship in a network of single-transistor oscillators is made, based on a diffusive ring (n = 90) with added long-distance links defining four extended hub regions. Similarly to the brain data, it is found that oscillators in the hub regions generate signals with larger low-frequency cycle amplitude fluctuations and clearer saturation to a lower correlation dimension compared to surrogates. The effect emerges more markedly close to criticality. The homology observed between the two systems despite profound differences in scale, coupling mechanism and dynamics appears noteworthy. These experimental results motivate further investigation into the heterogeneity of cortical non-linear dynamics in relation to connectivity and underline the ability for small networks of single-transistor oscillators to recreate collective phenomena arising in much more complex biological systems, potentially representing a future platform for modelling disease-related changes.

  8. Synchronization, non-linear dynamics and low-frequency fluctuations: analogy between spontaneous brain activity and networked single-transistor chaotic oscillators.

    PubMed

    Minati, Ludovico; Chiesa, Pietro; Tabarelli, Davide; D'Incerti, Ludovico; Jovicich, Jorge

    2015-03-01

    In this paper, the topographical relationship between functional connectivity (intended as inter-regional synchronization), spectral and non-linear dynamical properties across cortical areas of the healthy human brain is considered. Based upon functional MRI acquisitions of spontaneous activity during wakeful idleness, node degree maps are determined by thresholding the temporal correlation coefficient among all voxel pairs. In addition, for individual voxel time-series, the relative amplitude of low-frequency fluctuations and the correlation dimension (D2), determined with respect to Fourier amplitude and value distribution matched surrogate data, are measured. Across cortical areas, high node degree is associated with a shift towards lower frequency activity and, compared to surrogate data, clearer saturation to a lower correlation dimension, suggesting presence of non-linear structure. An attempt to recapitulate this relationship in a network of single-transistor oscillators is made, based on a diffusive ring (n = 90) with added long-distance links defining four extended hub regions. Similarly to the brain data, it is found that oscillators in the hub regions generate signals with larger low-frequency cycle amplitude fluctuations and clearer saturation to a lower correlation dimension compared to surrogates. The effect emerges more markedly close to criticality. The homology observed between the two systems despite profound differences in scale, coupling mechanism and dynamics appears noteworthy. These experimental results motivate further investigation into the heterogeneity of cortical non-linear dynamics in relation to connectivity and underline the ability for small networks of single-transistor oscillators to recreate collective phenomena arising in much more complex biological systems, potentially representing a future platform for modelling disease-related changes.

  9. Hippocampal MR volumetry

    NASA Astrophysics Data System (ADS)

    Haller, John W.; Botteron, K.; Brunsden, Barry S.; Sheline, Yvette I.; Walkup, Ronald K.; Black, Kevin J.; Gado, Mokhtar; Vannier, Michael W.

    1994-09-01

    Goal: To estimate hippocampal volumes from in vivo 3D magnetic resonance (MR) brain images and determine inter-rater and intra- rater repeatability. Objective: The precision and repeatability of hippocampal volume estimates using stereologic measurement methods is sought. Design: Five normal control and five schizophrenic subjects were MR scanned using a MPRAGE protocol. Fixed grid stereologic methods were used to estimate hippocampal volumes on a graphics workstation. The images were preprocessed using histogram analysis to standardize 3D MR image scaling from 16 to 8 bits and image volumes were interpolated to 0.5 mm3 isotropic voxels. The following variables were constant for the repeated stereologic measures: grid size, inter-slice distance (1.5 mm), voxel dimensions (0.5 mm3), number of hippocampi measured (10), total number of measurements per rater (40), and number of raters (5). Two grid sizes were tested to determine the coefficient of error associated with the number of sampled 'hits' (approximately 140 and 280) on the hippocampus. Starting slice and grid position were randomly varied to assure unbiased volume estimates. Raters were blind to subject identity, diagnosis, and side of the brain from which the image volumes were extracted and the order of subject presentation was randomized for each of the raters. Inter- and intra-rater intraclass correlation coefficients (ICC) were determined. Results: The data indicate excellent repeatability of fixed grid stereologic hippocampal volume measures when using an inter-slice distance of 1.5 mm and a 6.25 mm2 grid (inter-rater ICCs equals 0.86 - 0.97, intra- rater ICCs equals 0.85 - 0.97). One major advantage of the current study was the use of 3D MR data which significantly improved visualization of hippocampal boundaries by providing the ability to access simultaneous orthogonal views while counting stereological marks within the hippocampus. Conclusion: Stereological estimates of 3D volumes from 2D MR

  10. Acute intracerebral treatment with amyloid-beta (1–42) alters the profile of neuronal oscillations that accompany LTP induction and results in impaired LTP in freely behaving rats

    PubMed Central

    Kalweit, Alexander Nikolai; Yang, Honghong; Colitti-Klausnitzer, Jens; Fülöp, Livia; Bozsó, Zsolt; Penke, Botond; Manahan-Vaughan, Denise

    2015-01-01

    Accumulation of amyloid plaques comprises one of the major hallmarks of Alzheimer’s disease (AD). In rodents, acute treatment with amyloid-beta (Aβ; 1–42) elicits immediate debilitating effects on hippocampal long-term potentiation (LTP). Whereas LTP contributes to synaptic information storage, information is transferred across neurons by means of neuronal oscillations. Furthermore, changes in theta-gamma oscillations, that appear during high-frequency stimulation (HFS) to induce LTP, predict whether successful LTP will occur. Here, we explored if intra-cerebral treatment with Aβ(1–42), that prevents LTP, also results in alterations of hippocampal oscillations that occur during HFS of the perforant path-dentate gyrus synapse in 6-month-old behaving rats. HFS resulted in LTP that lasted for over 24 h. In Aβ-treated animals, LTP was significantly prevented. During HFS, spectral power for oscillations below 100 Hz (δ, θ, α, β and γ) was significantly higher in Aβ-treated animals compared to controls. In addition, the trough-to-peak amplitudes of theta and gamma cycles were higher during HFS in Aβ-treated animals. We also observed a lower amount of envelope-to-signal correlations during HFS in Aβ-treated animals. Overall, the characteristic profile of theta-gamma oscillations that accompany successful LTP induction was disrupted. These data indicate that alterations in network oscillations accompany Aβ-effects on hippocampal LTP. This may comprise an underlying mechanism through which disturbances in synaptic information storage and hippocampus-dependent memory occurs in AD. PMID:25999827

  11. Entorhinal-Hippocampal Neuronal Circuits Bridge Temporally Discontiguous Events

    ERIC Educational Resources Information Center

    Kitamura, Takashi; Macdonald, Christopher J.; Tonegawa, Susumu

    2015-01-01

    The entorhinal cortex (EC)-hippocampal (HPC) network plays an essential role for episodic memory, which preserves spatial and temporal information about the occurrence of past events. Although there has been significant progress toward understanding the neural circuits underlying the spatial dimension of episodic memory, the relevant circuits…

  12. Summation in the Hippocampal CA3-CA1 Network Remains Robustly Linear Following Inhibitory Modulation and Plasticity, but Undergoes Scaling and Offset Transformations.

    PubMed

    Parameshwaran, Dhanya; Bhalla, Upinder S

    2012-01-01

    Many theories of neural network function assume linear summation. This is in apparent conflict with several known forms of non-linearity in real neurons. Furthermore, key network properties depend on the summation parameters, which are themselves subject to modulation and plasticity in real neurons. We tested summation responses as measured by spiking activity in small groups of CA1 pyramidal neurons using permutations of inputs delivered on an electrode array. We used calcium dye recordings as a readout of the summed spiking response of cell assemblies in the network. Each group consisted of 2-10 cells, and the calcium signal from each cell correlated with individual action potentials. We find that the responses of these small cell groups sum linearly, despite previously reported dendritic non-linearities and the thresholded responses of individual cells. This linear summation persisted when input strengths were reduced. Blockage of inhibition shifted responses up toward saturation, but did not alter the slope of the linear region of summation. Long-term potentiation of synapses in the slice also preserved the linear fit, with an increase in absolute response. However, in this case the summation gain decreased, suggesting a homeostatic process for preserving overall network excitability. Overall, our results suggest that cell groups in the CA3-CA1 network robustly follow a consistent set of linear summation and gain-control rules, notwithstanding the intrinsic non-linearities of individual neurons. Cell-group responses remain linear, with well-defined transformations following inhibitory modulation and plasticity. Our measures of these transformations provide useful parameters to apply to neural network analyses involving modulation and plasticity.

  13. VOLTAGE-CONTROLLED TRANSISTOR OSCILLATOR

    DOEpatents

    Scheele, P.F.

    1958-09-16

    This patent relates to transistor oscillators and in particular to those transistor oscillators whose frequencies vary according to controlling voltages. A principal feature of the disclosed transistor oscillator circuit resides in the temperature compensation of the frequency modulating stage by the use of a resistorthermistor network. The resistor-thermistor network components are selected to have the network resistance, which is in series with the modulator transistor emitter circuit, vary with temperature to compensate for variation in the parameters of the transistor due to temperature change.

  14. Spontaneous EEG alpha oscillation interacts with positive and negative BOLD responses in the visual-auditory cortices and default-mode network.

    PubMed

    Mayhew, Stephen D; Ostwald, Dirk; Porcaro, Camillo; Bagshaw, Andrew P

    2013-08-01

    The human brain is continually, dynamically active and spontaneous fluctuations in this activity play a functional role in affecting both behavioural and neuronal responses. However, the mechanisms through which this occurs remain poorly understood. Simultaneous EEG-fMRI is a promising technique to study how spontaneous activity modulates the brain's response to stimulation, as temporal indices of ongoing cortical excitability can be integrated with spatially localised evoked responses. Here we demonstrate an interaction between the ongoing power of the electrophysiological alpha oscillation and the magnitude of both positive (PBR) and negative (NBR) fMRI responses to two contrasts of visual checkerboard reversal. Furthermore, the amplitude of pre-stimulus EEG alpha-power significantly modulated the amplitude and shape of subsequent PBR and NBR to the visual stimulus. A nonlinear reduction of visual PBR and an enhancement of auditory NBR and default-mode network NBR were observed in trials preceded by high alpha-power. These modulated areas formed a functionally connected network during a separate resting-state recording. Our findings suggest that the "baseline" state of the brain exhibits considerable trial-to-trial variability which arises from fluctuations in the balance of cortical inhibition/excitation that are represented by respective increases/decreases in the power of the EEG alpha oscillation. The consequence of this spontaneous electrophysiological variability is modulated amplitudes of both PBR and NBR to stimulation. Fluctuations in alpha-power may subserve a functional relationship in the visual-auditory network, acting as mediator for both short and long-range cortical inhibition, the strength of which is represented in part by NBR. PMID:23507378

  15. Critical self-organized self-sustained oscillations in large regulatory networks: towards understanding the gene expression initiation.

    PubMed

    Rosenfeld, Simon

    2011-03-22

    In this paper, a new model of self-organized criticality is introduced. This model, called the gene expression paradigm, is motivated by the problem of gene expression initiation in the newly-born daughter cells after mitosis. The model is fundamentally different in dynamics and properties from the well known sand-pile paradigm. Simulation experiments demonstrate that a critical total number of proteins exists below which transcription is impossible. Above this critical threshold, the system enters the regime of self-sustained oscillations with standard deviations and periods proportional to the genes' complexities with probability one. The borderline between these two regimes is very sharp. Importantly, such a self-organization emerges without any deterministic feedback loops or external supervision, and is a result of completely random redistribution of proteins between inactive genes. Given the size of the genome, the domain of self-organized oscillatory motion is also limited by the genes' maximal complexities. Below the critical complexity, all the regimes of self-organized oscillations are self-similar and largely independent of the genes' complexities. Above the level of critical complexity, the whole-genome transcription is impossible. Again, the borderline between the domains of oscillations and quiescence is very sharp. The gene expression paradigm is an example of cellular automata with the domain of application potentially far beyond its biological context. The model seems to be simple enough for staging an experiment for verification of its remarkable properties.

  16. Optogenetic Activation of Septal Glutamatergic Neurons Drive Hippocampal Theta Rhythms.

    PubMed

    Robinson, Jennifer; Manseau, Frédéric; Ducharme, Guillaume; Amilhon, Bénédicte; Vigneault, Erika; El Mestikawy, Salah; Williams, Sylvain

    2016-03-01

    The medial septum and diagonal band of Broca (MS-DBB) has an essential role for theta rhythm generation in the hippocampus and is critical for learning and memory. The MS-DBB contains cholinergic, GABAergic, and recently described glutamatergic neurons, but their specific contribution to theta generation is poorly understood. Here, we examined the role of MS-DBB glutamatergic neurons in theta rhythm using optogenetic activation and electrophysiological recordings performed in in vitro preparations and in freely behaving mice. The experiments in slices suggest that MS-DBB glutamatergic neurons provide prominent excitatory inputs to a majority of local GABAergic and a minority of septal cholinergic neurons. In contrast, activation of MS-DBB glutamatergic fiber terminals in hippocampal slices elicited weak postsynaptic responses in hippocampal neurons. In the in vitro septo-hippocampal preparation, activation of MS-DBB glutamatergic neurons did increase the rhythmicity of hippocampal theta oscillations, whereas stimulation of septo-hippocampal glutamatergic fibers in the fornix did not have an effect. In freely behaving mice, activation of these neurons in the MS-DBB strongly synchronized hippocampal theta rhythms over a wide range of frequencies, whereas activation of their projections to the hippocampus through fornix stimulations had no effect on theta rhythms, suggesting that MS-DBB glutamatergic neurons played a role in theta generation through local modulation of septal neurons. Together, these results provide the first evidence that MS-DBB glutamatergic neurons modulate local septal circuits, which in turn contribute to theta rhythms in the hippocampus. PMID:26961955

  17. Coordination of entorhinal-hippocampal ensemble activity during associative learning.

    PubMed

    Igarashi, Kei M; Lu, Li; Colgin, Laura L; Moser, May-Britt; Moser, Edvard I

    2014-06-01

    Accumulating evidence points to cortical oscillations as a mechanism for mediating interactions among functionally specialized neurons in distributed brain circuits. A brain function that may use such interactions is declarative memory--that is, memory that can be consciously recalled, such as episodes and facts. Declarative memory is enabled by circuits in the entorhinal cortex that interface the hippocampus with the neocortex. During encoding and retrieval of declarative memories, entorhinal and hippocampal circuits are thought to interact via theta and gamma oscillations, which in awake rodents predominate frequency spectra in both regions. In favour of this idea, theta-gamma coupling has been observed between entorhinal cortex and hippocampus under steady-state conditions in well-trained rats; however, the relationship between interregional coupling and memory formation remains poorly understood. Here we show, by multisite recording at successive stages of associative learning, that the coherence of firing patterns in directly connected entorhinal-hippocampus circuits evolves as rats learn to use an odour cue to guide navigational behaviour, and that such coherence is invariably linked to the development of ensemble representations for unique trial outcomes in each area. Entorhinal-hippocampal coupling was observed specifically in the 20-40-hertz frequency band and specifically between the distal part of hippocampal area CA1 and the lateral part of entorhinal cortex, the subfields that receive the predominant olfactory input to the hippocampal region. Collectively, the results identify 20-40-hertz oscillations as a mechanism for synchronizing evolving representations in dispersed neural circuits during encoding and retrieval of olfactory-spatial associative memory. PMID:24739966

  18. Chronic stimulation of cultured neuronal networks boosts low-frequency oscillatory activity at theta and gamma with spikes phase-locked to gamma frequencies

    NASA Astrophysics Data System (ADS)

    Leondopulos, Stathis S.; Boehler, Michael D.; Wheeler, Bruce C.; Brewer, Gregory J.

    2012-04-01

    Slow wave oscillations in the brain are essential for coordinated network activity but have not been shown to self-organize in vitro. Here, the development of dissociated hippocampal neurons into an active network with oscillations on multi-electrode arrays was evaluated in the absence and presence of chronic external stimulation. Significant changes in signal power were observed in the range of 1-400 Hz with an increase in amplitude during bursts. Stimulation increased oscillatory activity primarily in the theta (4-11 Hz) and slow gamma (30-55 Hz) bands. Spikes were most prominently phase-locked to the slow gamma waves. Notably, the dissociated network self-organized to exhibit sustained delta, theta, beta and gamma oscillations without input from cortex, thalamus or organized pyramidal cell layers.

  19. Hippocampal theta sequences reflect current goals

    PubMed Central

    Wikenheiser, Andrew M; Redish, A David

    2015-01-01

    Hippocampal information processing is discretized by oscillations, and the ensemble activity of place cells is organized into temporal sequences bounded by theta cycles. Theta sequences represent time-compressed trajectories through space. Their forward-directed nature makes them an intuitive candidate mechanism for planning future trajectories, but their connection to goal-directed behavior remains unclear. As rats performed a value-guided decision-making task, the extent to which theta sequences projected ahead of the animal’s current location varied on a moment-by-moment basis depending on the rat’s goals. Look-ahead extended farther on journeys to distant goals than on journeys to more proximal goals and was predictive of the animal’s destination. On arrival at goals, however, look-ahead was similar regardless of where the animal began its journey from. Together, these results provide evidence that hippocampal theta sequences contain information related to goals or intentions, pointing toward a potential spatial basis for planning. PMID:25559082

  20. Distinguishing between direct and indirect directional couplings in large oscillator networks: Partial or non-partial phase analyses?

    NASA Astrophysics Data System (ADS)

    Rings, Thorsten; Lehnertz, Klaus

    2016-09-01

    We investigate the relative merit of phase-based methods for inferring directional couplings in complex networks of weakly interacting dynamical systems from multivariate time-series data. We compare the evolution map approach and its partialized extension to each other with respect to their ability to correctly infer the network topology in the presence of indirect directional couplings for various simulated experimental situations using coupled model systems. In addition, we investigate whether the partialized approach allows for additional or complementary indications of directional interactions in evolving epileptic brain networks using intracranial electroencephalographic recordings from an epilepsy patient. For such networks, both direct and indirect directional couplings can be expected, given the brain's connection structure and effects that may arise from limitations inherent to the recording technique. Our findings indicate that particularly in larger networks (number of nodes ≫10 ), the partialized approach does not provide information about directional couplings extending the information gained with the evolution map approach.

  1. Repeating Spatial-Temporal Motifs of CA3 Activity Dependent on Engineered Inputs from Dentate Gyrus Neurons in Live Hippocampal Networks

    PubMed Central

    Bhattacharya, Aparajita; Desai, Harsh; DeMarse, Thomas B.; Wheeler, Bruce C.; Brewer, Gregory J.

    2016-01-01

    Anatomical and behavioral studies, and in vivo and slice electrophysiology of the hippocampus suggest specific functions of the dentate gyrus (DG) and the CA3 subregions, but the underlying activity dynamics and repeatability of information processing remains poorly understood. To approach this problem, we engineered separate living networks of the DG and CA3 neurons that develop connections through 51 tunnels for axonal communication. Growing these networks on top of an electrode array enabled us to determine whether the subregion dynamics were separable and repeatable. We found spontaneous development of polarized propagation of 80% of the activity in the native direction from DG to CA3 and different spike and burst dynamics for these subregions. Spatial-temporal differences emerged when the relationships of target CA3 activity were categorized with to the number and timing of inputs from the apposing network. Compared to times of CA3 activity when there was no recorded tunnel input, DG input led to CA3 activity bursts that were 7× more frequent, increased in amplitude and extended in temporal envelope. Logistic regression indicated that a high number of tunnel inputs predict CA3 activity with 90% sensitivity and 70% specificity. Compared to no tunnel input, patterns of >80% tunnel inputs from DG specified different patterns of first-to-fire neurons in the CA3 target well. Clustering dendrograms revealed repeating motifs of three or more patterns at up to 17 sites in CA3 that were importantly associated with specific spatial-temporal patterns of tunnel activity. The number of these motifs recorded in 3 min was significantly higher than shuffled spike activity and not seen above chance in control networks in which CA3 was apposed to CA3 or DG to DG. Together, these results demonstrate spontaneous input-dependent repeatable coding of distributed activity in CA3 networks driven by engineered inputs from DG networks. These functional configurations at measured times

  2. Repeating Spatial-Temporal Motifs of CA3 Activity Dependent on Engineered Inputs from Dentate Gyrus Neurons in Live Hippocampal Networks.

    PubMed

    Bhattacharya, Aparajita; Desai, Harsh; DeMarse, Thomas B; Wheeler, Bruce C; Brewer, Gregory J

    2016-01-01

    Anatomical and behavioral studies, and in vivo and slice electrophysiology of the hippocampus suggest specific functions of the dentate gyrus (DG) and the CA3 subregions, but the underlying activity dynamics and repeatability of information processing remains poorly understood. To approach this problem, we engineered separate living networks of the DG and CA3 neurons that develop connections through 51 tunnels for axonal communication. Growing these networks on top of an electrode array enabled us to determine whether the subregion dynamics were separable and repeatable. We found spontaneous development of polarized propagation of 80% of the activity in the native direction from DG to CA3 and different spike and burst dynamics for these subregions. Spatial-temporal differences emerged when the relationships of target CA3 activity were categorized with to the number and timing of inputs from the apposing network. Compared to times of CA3 activity when there was no recorded tunnel input, DG input led to CA3 activity bursts that were 7× more frequent, increased in amplitude and extended in temporal envelope. Logistic regression indicated that a high number of tunnel inputs predict CA3 activity with 90% sensitivity and 70% specificity. Compared to no tunnel input, patterns of >80% tunnel inputs from DG specified different patterns of first-to-fire neurons in the CA3 target well. Clustering dendrograms revealed repeating motifs of three or more patterns at up to 17 sites in CA3 that were importantly associated with specific spatial-temporal patterns of tunnel activity. The number of these motifs recorded in 3 min was significantly higher than shuffled spike activity and not seen above chance in control networks in which CA3 was apposed to CA3 or DG to DG. Together, these results demonstrate spontaneous input-dependent repeatable coding of distributed activity in CA3 networks driven by engineered inputs from DG networks. These functional configurations at measured times

  3. Associative reinstatement memory measures hippocampal function in Parkinson's Disease.

    PubMed

    Cohn, Melanie; Giannoylis, Irene; De Belder, Maya; Saint-Cyr, Jean A; McAndrews, Mary Pat

    2016-09-01

    In Parkinson's Disease (PD), hippocampal atrophy is associated with rapid cognitive decline. Hippocampal function is typically assessed using memory tests but current clinical tools (e.g., free recall) also rely on executive functions or use material that is not optimally engaging hippocampal memory networks. Because of the ubiquity of executive dysfunction in PD, our ability to detect true memory deficits is suboptimal. Our previous behavioural and neuroimaging work in other populations suggests that an experimental memory task - Associative Reinstatement Memory (ARM) - may prove useful in investigating hippocampal function in PD. In this study, we investigated whether ARM is compromised in PD and we assessed its convergent and divergent validity by comparing it to standardized measures of memory and of attention and executive functioning in PD, respectively. Using fMRI, we also investigated whether performance in PD relates to degree of hippocampal engagement. Fifteen participants with PD and 13 age-matched healthy controls completed neuropsychological testing as well as an ARM fMRI recognition paradigm in which they were instructed to identify word pairs comprised of two studied words (intact or rearranged pairs) and those containing at least one new word (new or half new pairs). ARM is measured by the differences in hit rates between intact and rearranged pairs. Behaviourally, ARM was poorer in PD relative to controls and was correlated with verbal memory measures, but not with attention or executive functioning in the PD group. Hippocampal activation associated with ARM was reduced in PD relative to controls and covaried with ARM scores in both groups. To conclude, ARM is a sensitive measure of hippocampal memory function that is unaffected by attention or executive dysfunction in PD. Our study highlights the benefit of integrating cognitive neuroscience frameworks and novel experimental tasks to improve the practice of clinical neuropsychology in PD. PMID

  4. Effects of Dopamine and Serotonin Systems on Modulating Neural Oscillations in Hippocampus-Prefrontal Cortex Pathway in Rats.

    PubMed

    Xu, Xiaxia; Zheng, Chenguang; An, Lei; Wang, Rubin; Zhang, Tao

    2016-07-01

    Theta and gamma oscillations are believed to play an important role in cognition and memory, and their phase coupling facilitates the information transmission in hippocampal-cortex network. In a rat model of chronic stress, the phase coupling of both theta and gamma oscillations between ventral hippocampal CA1 (vCA1) and medial prefrontal cortex (mPFC) was found to be disrupted, which was associated with the impaired synaptic plasticity in the pathway. However, little was known about the mechanisms underlying the process. In order to address this issue, both dopamine and serotonin as monoaminergic neurotransmitters were involved in this study, since they were crucial factors in pathological basis of depressive disorder. Local field potentials (LFPs) were recorded simultaneously at both vCA1 and mPFC regions under anesthesia, before and after the injection of dopamine D1 receptor antagonist and 5-HT1A receptor agonist, respectively. The results showed that the blockage of D1 receptor could lead to depression-like decrement on theta phase coupling. In addition, the activation of 5-HT1A receptor enhanced vCA1-mPFC coupling on gamma oscillations, and attenuated CA1 theta-fast gamma cross frequency coupling. These data suggest that the theta phase coupling between vCA1 and mPFC may be modulated by dopamine system that is an underlying mechanism of the cognitive dysfunction in depression. Besides, the serotonergic system is probably involved in the regulation of gamma oscillations coupling in vCA1-mPFC network. PMID:26969669

  5. VEGF is necessary for exercise-induced adult hippocampal neurogenesis.

    PubMed

    Fabel, Klaus; Fabel, Konstanze; Tam, Betty; Kaufer, Daniela; Baiker, Armin; Simmons, Natalie; Kuo, Calvin J; Palmer, Theo D

    2003-11-01

    Declining learning and memory function is associated with the attenuation of adult hippocampal neurogenesis. As in humans, chronic stress or depression in animals is accompanied by hippocampal dysfunction, and neurogenesis is correspondingly down regulated, in part, by the activity of the hypothalamic-pituitary-adrenal axis as well as glutamatergic and serotonergic networks. Antidepressants can reverse this effect over time but one of the most clinically effective moderators of stress or depression and robust stimulators of neurogenesis is simple voluntary physical exercise such as running. Curiously, running also elevates circulating stress hormone levels yet neurogenesis is doubled in running animals. In evaluating the signalling that running provides to the central nervous system in mice, we have found that peripheral vascular endothelial growth factor (VEGF) is necessary for the effects of running on adult hippocampal neurogenesis. Peripheral blockade of VEGF abolished running-induced neurogenesis but had no detectable effect on baseline neurogenesis in non-running animals. These data suggest that VEGF is an important element of a 'somatic regulator' of adult neurogenesis and that these somatic signalling networks can function independently of the central regulatory networks that are typically considered in the context of hippocampal neurogenesis.

  6. The Epileptic Thalamocortical Network is a Macroscopic Self-Sustained Oscillator: Evidence from Frequency-Locking Experiments in Rat Brains

    NASA Astrophysics Data System (ADS)

    Velazquez, J. L. Perez; Erra, R. Guevara; Rosenblum, M.

    2015-02-01

    The rhythmic activity observed in nervous systems, in particular in epilepsies and Parkinson's disease, has often been hypothesized to originate from a macroscopic self-sustained neural oscillator. However, this assumption has not been tested experimentally. Here we support this viewpoint with in vivo experiments in a rodent model of absence seizures, by demonstrating frequency locking to external periodic stimuli and finding the characteristic Arnold tongue. This result has important consequences for developing methods for the control of brain activity, such as seizure cancellation.

  7. The epileptic thalamocortical network is a macroscopic self-sustained oscillator: evidence from frequency-locking experiments in rat brains.

    PubMed

    Velazquez, J L Perez; Erra, R Guevara; Rosenblum, M

    2015-02-12

    The rhythmic activity observed in nervous systems, in particular in epilepsies and Parkinson's disease, has often been hypothesized to originate from a macroscopic self-sustained neural oscillator. However, this assumption has not been tested experimentally. Here we support this viewpoint with in vivo experiments in a rodent model of absence seizures, by demonstrating frequency locking to external periodic stimuli and finding the characteristic Arnold tongue. This result has important consequences for developing methods for the control of brain activity, such as seizure cancellation.

  8. Modeling the contributions of Ca2+ flows to spontaneous Ca2+ oscillations and cortical spreading depression-triggered Ca2+ waves in astrocyte networks.

    PubMed

    Li, Bing; Chen, Shangbin; Zeng, Shaoqun; Luo, Qingming; Li, Pengcheng

    2012-01-01

    Astrocytes participate in brain functions through Ca(2+) signals, including Ca(2+) waves and Ca(2+) oscillations. Currently the mechanisms of Ca(2+) signals in astrocytes are not fully clear. Here, we present a computational model to specify the relative contributions of different Ca(2+) flows between the extracellular space, the cytoplasm and the endoplasmic reticulum of astrocytes to the generation of spontaneous Ca(2+) oscillations (CASs) and cortical spreading depression (CSD)-triggered Ca(2+) waves (CSDCWs) in a one-dimensional astrocyte network. This model shows that CASs depend primarily on Ca(2+) released from internal stores of astrocytes, and CSDCWs depend mainly on voltage-gated Ca(2+) influx. It predicts that voltage-gated Ca(2+) influx is able to generate Ca(2+) waves during the process of CSD even after depleting internal Ca(2+) stores. Furthermore, the model investigates the interactions between CASs and CSDCWs and shows that the pass of CSDCWs suppresses CASs, whereas CASs do not prevent the generation of CSDCWs. This work quantitatively analyzes the generation of astrocytic Ca(2+) signals and indicates different mechanisms underlying CSDCWs and non-CSDCWs. Research on the different types of Ca(2+) signals might help to understand the ways by which astrocytes participate in information processing in brain functions.

  9. Adult Hippocampal Neurogenesis: Regulation, Functional Implications, And Contribution to Disease Pathology

    PubMed Central

    Balu, Darrick T.; Lucki, Irwin

    2009-01-01

    It is now well established that the mammalian brain has the capacity to produce new neurons into adulthood. One such region that provides the proper milieu to sustain progenitor cells and is permissive to neuronal fate determination is located in the dentate gyrus of the hippocampus. This review will discuss in detail the complex process of adult hippocampal neurogenesis, including proliferation, differentiation, survival, and incorporation into neuronal networks. The regulation of this phenomenon by a number of factors is described, including neurotransmitter systems, growth factors, paracrine signaling molecules, neuropeptides, transcription factors, endogenous psychotropic systems, sex hormones, stress, and others. This review also addresses the functional significance of adult born hippocampal granule cells with regard to hippocampal circuitry dynamics and behavior. Furthermore, the relevance of perturbations in adult hippocampal neurogenesis to the pathophysiology of various disease states, including depression, schizophrenia, epilepsy, and diabetes are examined. Finally, this review discusses the potential of using hippocampal neurogenesis as a therapeutic target for these disorders. PMID:18786562

  10. Asymmetry in cross-hippocampal connectivity in unilateral mesial temporal lobe epilepsy.

    PubMed

    Li, Hong; Fan, Wenliang; Yang, Jie; Song, Shuyan; Liu, Yuan; Lei, Ping; Shrestha, Lochan; Mella, Grace; Chen, Wei; Xu, Haibo

    2015-12-01

    Mesial temporal lobe epilepsy (mTLE) is mostly characterized by hippocampal sclerosis (HS) changes. Although considerable progress has been made in understanding the altered functional network of mTLE patients, whether one side of the abnormal hippocampal (HP) structure will affect the other healthy side of the hippocampal network is still unclear. Here, we used a seed-based method to explore the commonly alterative hippocampal network in mTLE patients by comparing the bilateral hippocampal network of unilateral mTLE patients with healthy control participants. We observed that both sides of the hippocampal network in unilateral mTLE patients were changed independent of the affected or "healthy" side, which may suggest a common plasticity network for both sides of hippocampal sclerosis mesial temporal lobe epilepsy patients. Furthermore, using the HP as the ROI, we found that the functional connectivity of the intra-HP in the left mTLE-HS group was moderately positively correlated with the duration of the disease, while a strong negative correlation between functional connectivity of the intra-HP and duration were detected in the right mTLE-HS group, which suggested that it was easier for the right HP than the left HP to communicate with the contralateral HP according to the progression of mTLE disease because the hippocampus plays different roles in the communication and compensatory mechanism associated with the contralateral side of the hemisphere. We hope that this potential relevance may help us to better characterize mTLE with hippocampal sclerosis and ultimately assist in providing a better diagnosis and more accurate invasive treatments of mTLE. PMID:26561924

  11. Dynamic modulation of excitation and inhibition during stimulation at gamma and beta frequencies in the CA1 hippocampal region.

    PubMed

    Bracci, E; Vreugdenhil, M; Hack, S P; Jefferys, J G

    2001-06-01

    transient disinhibition of the local network leads to a short-lasting facilitation of polysynaptic EPSPs. These results set constraints on the role that synchronous, rhythmic IPSPs may play in pacing oscillations at gamma frequency in the CA1 hippocampal region.

  12. Architecture of spatial circuits in the hippocampal region.

    PubMed

    Witter, Menno P; Canto, Cathrin B; Couey, Jonathan J; Koganezawa, Noriko; O'Reilly, Kally C

    2014-02-01

    The hippocampal region contains several principal neuron types, some of which show distinct spatial firing patterns. The region is also known for its diversity in neural circuits and many have attempted to causally relate network architecture within and between these unique circuits to functional outcome. Still, much is unknown about the mechanisms or network properties by which the functionally specific spatial firing profiles of neurons are generated, let alone how they are integrated into a coherently functioning meta-network. In this review, we explore the architecture of local networks and address how they may interact within the context of an overarching space circuit, aiming to provide directions for future successful explorations.

  13. Integrated Solar Disk Oscillation Measurements Using the Magneto-Optical Filter: Tests with a Two Station Network

    NASA Technical Reports Server (NTRS)

    Cacciani, Alessandro; Rosati, P.; Ricci, D.; Marquedant, R.; Smith, E.

    1988-01-01

    The magneto-optical filter (MOF) was used to get high and intermediate l-modes of solar oscillations. For very low l-modes the imaging capability of the MOF is still attractive since it allows a pixel by pixel intensity normalization. However, a crude attempt to get very low l power spectra from Dopplergrams obtained at Mt. Wilson gave noisy results. This means that a careful analysis of all the factors potentially affecting high resolution Dopplergrams should be accomplished. In order to better investigate this problem, a nonimaging channel using the lock-in amplifier technique was considered. Two systems are now operational, one at JPL and the other at University of Rome. Observations in progress are used to discuss the MOF stability, the noise level, and the possible application in asteroseismology.

  14. Distinguishing mechanisms of gamma frequency oscillations in human current source signals using a computational model of a laminar neocortical network

    PubMed Central

    Lee, Shane; Jones, Stephanie R.

    2013-01-01

    Gamma frequency rhythms have been implicated in numerous studies for their role in healthy and abnormal brain function. The frequency band has been described to encompass as broad a range as 30–150 Hz. Crucial to understanding the role of gamma in brain function is an identification of the underlying neural mechanisms, which is particularly difficult in the absence of invasive recordings in macroscopic human signals such as those from magnetoencephalography (MEG) and electroencephalography (EEG). Here, we studied features of current dipole (CD) signals from two distinct mechanisms of gamma generation, using a computational model of a laminar cortical circuit designed specifically to simulate CDs in a biophysically principled manner (Jones et al., 2007, 2009). We simulated spiking pyramidal interneuronal gamma (PING) whose period is regulated by the decay time constant of GABAA-mediated synaptic inhibition and also subthreshold gamma driven by gamma-periodic exogenous excitatory synaptic drive. Our model predicts distinguishable CD features created by spiking PING compared to subthreshold driven gamma that can help to disambiguate mechanisms of gamma oscillations in human signals. We found that gamma rhythms in neocortical layer 5 can obscure a simultaneous, independent gamma in layer 2/3. Further, we arrived at a novel interpretation of the origin of high gamma frequency rhythms (100–150 Hz), showing that they emerged from a specific temporal feature of CDs associated with single cycles of PING activity and did not reflect a separate rhythmic process. Last we show that the emergence of observable subthreshold gamma required highly coherent exogenous drive. Our results are the first to demonstrate features of gamma oscillations in human current source signals that distinguish cellular and circuit level mechanisms of these rhythms and may help to guide understanding of their functional role. PMID:24385958

  15. BLOCKING OSCILLATOR DOUBLE PULSE GENERATOR CIRCUIT

    DOEpatents

    Haase, J.A.

    1961-01-24

    A double-pulse generator, particuiarly a double-pulse generator comprising a blocking oscillator utilizing a feedback circuit to provide means for producing a second pulse within the recovery time of the blocking oscillator, is described. The invention utilized a passive network which permits adjustment of the spacing between the original pulses derived from the blocking oscillator and further utilizes the original pulses to trigger a circuit from which other pulses are initiated. These other pulses are delayed and then applied to the input of the blocking oscillator, with the result that the output from the oscillator circuit contains twice the number of pulses originally initiated by the blocking oscillator itself.

  16. Slow Noise in the Period of a Biological Oscillator Underlies Gradual Trends and Abrupt Transitions in Phasic Relationships in Hybrid Neural Networks

    PubMed Central

    Norman, Sharon E.; Butera, Robert J.; Canavier, Carmen C.

    2014-01-01

    In order to study the ability of coupled neural oscillators to synchronize in the presence of intrinsic as opposed to synaptic noise, we constructed hybrid circuits consisting of one biological and one computational model neuron with reciprocal synaptic inhibition using the dynamic clamp. Uncoupled, both neurons fired periodic trains of action potentials. Most coupled circuits exhibited qualitative changes between one-to-one phase-locking with fairly constant phasic relationships and phase slipping with a constant progression in the phasic relationships across cycles. The phase resetting curve (PRC) and intrinsic periods were measured for both neurons, and used to construct a map of the firing intervals for both the coupled and externally forced (PRC measurement) conditions. For the coupled network, a stable fixed point of the map predicted phase locking, and its absence produced phase slipping. Repetitive application of the map was used to calibrate different noise models to simultaneously fit the noise level in the measurement of the PRC and the dynamics of the hybrid circuit experiments. Only a noise model that added history-dependent variability to the intrinsic period could fit both data sets with the same parameter values, as well as capture bifurcations in the fixed points of the map that cause switching between slipping and locking. We conclude that the biological neurons in our study have slowly-fluctuating stochastic dynamics that confer history dependence on the period. Theoretical results to date on the behavior of ensembles of noisy biological oscillators may require re-evaluation to account for transitions induced by slow noise dynamics. PMID:24830924

  17. Evidence that NO/cGMP/PKG signalling cascade mediates endothelium dependent inhibition of IP3R mediated Ca2+