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

PubMed Central

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

2011-01-01

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

[The mechanism and function of hippocampal neural oscillation].

PubMed

Lu, Ning; Xing, Dan-Qin; Sheng, Tao; Lu, Wei

2017-10-25

Neural oscillation is rhythmic or repetitive neural activity in the central nervous system that is usually generated by oscillatory activity of neuronal ensembles, reflecting regular and synchronized activities within these cell populations. According to several oscillatory bands covering frequencies from approximately 0.5 Hz to >100 Hz, neural oscillations are usually classified as delta oscillation (0.5-3 Hz), theta oscillation (4-12 Hz), beta oscillation (12-30 Hz), gamma oscillation (30-100 Hz) and sharp-wave ripples (>100 Hz ripples superimposed on 0.01-3 Hz sharp waves). Neural oscillation in different frequencies can be detected in different brain regions of human and animal during perception, motion and sleep, and plays an essential role in cognition, learning and memory process. In this review, we summarize recent findings on neural oscillations in hippocampus, as well as the mechanism and function of hippocampal theta oscillation, gamma oscillation and sharp-wave ripples. This review may yield new insights into the functions of neural oscillation in general.

Midline thalamic neurons are differentially engaged during hippocampus network oscillations.

PubMed

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

2016-07-14

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

Dissociation between dorsal and ventral hippocampal theta oscillations during decision-making.

PubMed

Schmidt, Brandy; Hinman, James R; Jacobson, Tara K; Szkudlarek, Emily; Argraves, Melissa; Escabí, Monty A; Markus, Etan J

2013-04-03

Hippocampal theta oscillations are postulated to support mnemonic processes in humans and rodents. Theta oscillations facilitate encoding and spatial navigation, but to date, it has been difficult to dissociate the effects of volitional movement from the cognitive demands of a task. Therefore, we examined whether volitional movement or cognitive demands exerted a greater modulating factor over theta oscillations during decision-making. Given the anatomical, electrophysiological, and functional dissociations along the dorsal-ventral axis, theta oscillations were simultaneously recorded in the dorsal and ventral hippocampus in rats trained to switch between place and motor-response strategies. Stark differences in theta characteristics were found between the dorsal and ventral hippocampus in frequency, power, and coherence. Theta power increased in the dorsal, but decreased in the ventral hippocampus, during the decision-making epoch. Interestingly, the relationship between running speed and theta power was uncoupled during the decision-making epoch, a phenomenon limited to the dorsal hippocampus. Theta frequency increased in both the dorsal and ventral hippocampus during the decision epoch, although this effect was greater in the dorsal hippocampus. Despite these differences, ventral hippocampal theta was responsive to the navigation task; theta frequency, power, and coherence were all affected by cognitive demands. Theta coherence increased within the dorsal hippocampus during the decision-making epoch on all three tasks. However, coherence selectively increased throughout the hippocampus (dorsal to ventral) on the task with new hippocampal learning. Interestingly, most results were consistent across tasks, regardless of hippocampal-dependent learning. These data indicate increased integration and cooperation throughout the hippocampus during information processing.

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

PubMed

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

2013-05-15

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

Selective Reduction of AMPA Currents onto Hippocampal Interneurons Impairs Network Oscillatory Activity

PubMed Central

Le Magueresse, Corentin; Monyer, Hannah

2012-01-01

Reduction of excitatory currents onto GABAergic interneurons in the forebrain results in impaired spatial working memory and altered oscillatory network patterns in the hippocampus. Whether this phenotype is caused by an alteration in hippocampal interneurons is not known because most studies employed genetic manipulations affecting several brain regions. Here we performed viral injections in genetically modified mice to ablate the GluA4 subunit of the AMPA receptor in the hippocampus (GluA4HC−/− mice), thereby selectively reducing AMPA receptor-mediated currents onto a subgroup of hippocampal interneurons expressing GluA4. This regionally selective manipulation led to a strong spatial working memory deficit while leaving reference memory unaffected. Ripples (125–250 Hz) in the CA1 region of GluA4HC−/− mice had larger amplitude, slower frequency and reduced rate of occurrence. These changes were associated with an increased firing rate of pyramidal cells during ripples. The spatial selectivity of hippocampal pyramidal cells was comparable to that of controls in many respects when assessed during open field exploration and zigzag maze running. However, GluA4 ablation caused altered modulation of firing rate by theta oscillations in both interneurons and pyramidal cells. Moreover, the correlation between the theta firing phase of pyramidal cells and position was weaker in GluA4HC−/− mice. These results establish the involvement of AMPA receptor-mediated currents onto hippocampal interneurons for ripples and theta oscillations, and highlight potential cellular and network alterations that could account for the altered working memory performance. PMID:22675480

The Influence of Cold Temperature on Cellular Excitability of Hippocampal Networks

PubMed Central

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

2012-01-01

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

Role of GABAergic inhibition in hippocampal network oscillations.

PubMed

Mann, Edward O; Paulsen, Ole

2007-07-01

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

Phencyclidine Discoordinates Hippocampal Network Activity But Not Place Fields

PubMed Central

Kao, Hsin-Yi; Kenney, Jana; Kelemen, Eduard

2017-01-01

We used the psychotomimetic phencyclidine (PCP) to investigate the relationships among cognitive behavior, coordinated neural network function, and information processing within the hippocampus place cell system. We report in rats that PCP (5 mg/kg, i.p.) impairs a well learned, hippocampus-dependent place avoidance behavior in rats that requires cognitive control even when PCP is injected directly into dorsal hippocampus. PCP increases 60–100 Hz medium-freguency gamma oscillations in hippocampus CA1 and these increases correlate with the cognitive impairment caused by systemic PCP administration. PCP discoordinates theta-modulated medium-frequency and slow gamma oscillations in CA1 LFPs such that medium-frequency gamma oscillations become more theta-organized than slow gamma oscillations. CA1 place cell firing fields are preserved under PCP, but the drug discoordinates the subsecond temporal organization of discharge among place cells. This discoordination causes place cell ensemble representations of a familiar space to cease resembling pre-PCP representations despite preserved place fields. These findings point to the cognitive impairments caused by PCP arising from neural discoordination. PCP disrupts the timing of discharge with respect to the subsecond timescales of theta and gamma oscillations in the LFP. Because these oscillations arise from local inhibitory synaptic activity, these findings point to excitation–inhibition discoordination as the root of PCP-induced cognitive impairment. SIGNIFICANCE STATEMENT Hippocampal neural discharge is temporally coordinated on timescales of theta and gamma oscillations in the LFP and the discharge of a subset of pyramidal neurons called “place cells” is spatially organized such that discharge is restricted to locations called a cell's “place field.” Because this temporal coordination and spatial discharge organization is thought to represent spatial knowledge, we used the psychotomimetic phencyclidine (PCP

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

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

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

PubMed

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

2017-11-01

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

Extracellular calcium controls the expression of two different forms of ripple-like hippocampal oscillations.

PubMed

Aivar, Paloma; Valero, Manuel; Bellistri, Elisa; Menendez de la Prida, Liset

2014-02-19

Hippocampal high-frequency oscillations (HFOs) are prominent in physiological and pathological conditions. During physiological ripples (100-200 Hz), few pyramidal cells fire together coordinated by rhythmic inhibitory potentials. In the epileptic hippocampus, fast ripples (>200 Hz) reflect population spikes (PSs) from clusters of bursting cells, but HFOs in the ripple and the fast ripple range are vastly intermixed. What is the meaning of this frequency range? What determines the expression of different HFOs? Here, we used different concentrations of Ca(2+) in a physiological range (1-3 mM) to record local field potentials and single cells in hippocampal slices from normal rats. Surprisingly, we found that this sole manipulation results in the emergence of two forms of HFOs reminiscent of ripples and fast ripples recorded in vivo from normal and epileptic rats, respectively. We scrutinized the cellular correlates and mechanisms underlying the emergence of these two forms of HFOs by combining multisite, single-cell and paired-cell recordings in slices prepared from a rat reporter line that facilitates identification of GABAergic cells. We found a major effect of extracellular Ca(2+) in modulating intrinsic excitability and disynaptic inhibition, two critical factors shaping network dynamics. Moreover, locally modulating the extracellular Ca(2+) concentration in an in vivo environment had a similar effect on disynaptic inhibition, pyramidal cell excitability, and ripple dynamics. Therefore, the HFO frequency band reflects a range of firing dynamics of hippocampal networks.

Slow oscillations orchestrating fast oscillations and memory consolidation.

PubMed

Mölle, Matthias; Born, Jan

2011-01-01

Slow-wave sleep (SWS) facilitates the consolidation of hippocampus-dependent declarative memory. Based on the standard two-stage memory model, we propose that memory consolidation during SWS represents a process of system consolidation which is orchestrated by the neocortical <1Hz electroencephalogram (EEG) slow oscillation and involves the reactivation of newly encoded representations and their subsequent redistribution from temporary hippocampal to neocortical long-term storage sites. Indeed, experimental induction of slow oscillations during non-rapid eye movement (non-REM) sleep by slowly alternating transcranial current stimulation distinctly improves consolidation of declarative memory. The slow oscillations temporally group neuronal activity into up-states of strongly enhanced neuronal activity and down-states of neuronal silence. In a feed-forward efferent action, this grouping is induced not only in the neocortex but also in other structures relevant to consolidation, namely the thalamus generating 10-15Hz spindles, and the hippocampus generating sharp wave-ripples, with the latter well known to accompany a replay of newly encoded memories taking place in hippocampal circuitries. The feed-forward synchronizing effect of the slow oscillation enables the formation of spindle-ripple events where ripples and accompanying reactivated hippocampal memory information become nested into the single troughs of spindles. Spindle-ripple events thus enable reactivated memory-related hippocampal information to be fed back to neocortical networks in the excitable slow oscillation up-state where they can induce enduring plastic synaptic changes underlying the effective formation of long-term memories. Copyright © 2011 Elsevier B.V. All rights reserved.

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

PubMed

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

2013-07-10

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

Hippocampal Network Modularity Is Associated With Relational Memory Dysfunction in Schizophrenia.

PubMed

Avery, Suzanne N; Rogers, Baxter P; Heckers, Stephan

2018-05-01

Functional dysconnectivity has been proposed as a major pathophysiological mechanism for cognitive dysfunction in schizophrenia. The hippocampus is a focal point of dysconnectivity in schizophrenia, with decreased hippocampal functional connectivity contributing to the marked memory deficits observed in patients. Normal memory function relies on the interaction of complex corticohippocampal networks. However, only recent technological advances have enabled the large-scale exploration of functional networks with accuracy and precision. We investigated the modularity of hippocampal resting-state functional networks in a sample of 45 patients with schizophrenia spectrum disorders and 38 healthy control subjects. Modularity was calculated for two distinct functional networks: a core hippocampal-medial temporal lobe cortex network and an extended hippocampal-cortical network. As hippocampal function differs along its longitudinal axis, follow-up analyses examined anterior and posterior networks separately. To explore effects of resting network function on behavior, we tested associations between modularity and relational memory ability. Age, sex, handedness, and parental education were similar between groups. Network modularity was lower in schizophrenia patients, especially in the posterior hippocampal network. Schizophrenia patients also showed markedly lower relational memory ability compared with control subjects. We found a distinct brain-behavior relationship in schizophrenia that differed from control subjects by network and anterior/posterior division-while relational memory in control subjects was associated with anterior hippocampal-cortical modularity, schizophrenia patients showed an association with posterior hippocampal-medial temporal lobe cortex network modularity. Our findings support a model of abnormal resting-state corticohippocampal network coherence in schizophrenia, which may contribute to relational memory deficits. Copyright © 2018 Society of

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

PubMed

Cutsuridis, Vassilis; Hasselmo, Michael

2012-07-01

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

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

PubMed Central

Tukker, John J; Klausberger, Thomas; Somogyi, Peter

2015-01-01

Hippocampal sharp waves are population discharges initiated by an unknown mechanism in pyramidal cell networks of CA3. Axo-axonic cells (AACs) regulate action potential generation through GABAergic synapses on the axon initial segment. We found that CA3 AACs in anesthetized rats and AACs in freely moving rats stopped firing during sharp waves, when pyramidal cells fire most. AACs fired strongly and rhythmically around the peak of theta oscillations, when pyramidal cells fire at low probability. Distinguishing AACs from other parvalbumin-expressing interneurons by their lack of detectable SATB1 transcription factor immunoreactivity, we discovered a somatic GABAergic input originating from the medial septum that preferentially targets AACs. We recorded septo-hippocampal GABAergic cells that were activated during hippocampal sharp waves and projected to CA3. We hypothesize that inhibition of AACs, and the resulting subcellular redistribution of inhibition from the axon initial segment to other pyramidal cell domains, is a necessary condition for the emergence of sharp waves promoting memory consolidation. PMID:24141313

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.

Lateralized hippocampal oscillations underlie distinct aspects of human spatial memory and navigation.

PubMed

Miller, Jonathan; Watrous, Andrew J; Tsitsiklis, Melina; Lee, Sang Ah; Sheth, Sameer A; Schevon, Catherine A; Smith, Elliot H; Sperling, Michael R; Sharan, Ashwini; Asadi-Pooya, Ali Akbar; Worrell, Gregory A; Meisenhelter, Stephen; Inman, Cory S; Davis, Kathryn A; Lega, Bradley; Wanda, Paul A; Das, Sandhitsu R; Stein, Joel M; Gorniak, Richard; Jacobs, Joshua

2018-06-21

The hippocampus plays a vital role in various aspects of cognition including both memory and spatial navigation. To understand electrophysiologically how the hippocampus supports these processes, we recorded intracranial electroencephalographic activity from 46 neurosurgical patients as they performed a spatial memory task. We measure signals from multiple brain regions, including both left and right hippocampi, and we use spectral analysis to identify oscillatory patterns related to memory encoding and navigation. We show that in the left but not right hippocampus, the amplitude of oscillations in the 1-3-Hz "low theta" band increases when viewing subsequently remembered object-location pairs. In contrast, in the right but not left hippocampus, low-theta activity increases during periods of navigation. The frequencies of these hippocampal signals are slower than task-related signals in the neocortex. These results suggest that the human brain includes multiple lateralized oscillatory networks that support different aspects of cognition.

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.

Regulation of the Hippocampal Network by VGLUT3-Positive CCK- GABAergic Basket Cells

PubMed Central

Fasano, Caroline; Rocchetti, Jill; Pietrajtis, Katarzyna; Zander, Johannes-Friedrich; Manseau, Frédéric; Sakae, Diana Y.; Marcus-Sells, Maya; Ramet, Lauriane; Morel, Lydie J.; Carrel, Damien; Dumas, Sylvie; Bolte, Susanne; Bernard, Véronique; Vigneault, Erika; Goutagny, Romain; Ahnert-Hilger, Gudrun; Giros, Bruno; Daumas, Stéphanie; Williams, Sylvain; El Mestikawy, Salah

2017-01-01

Hippocampal interneurons release the inhibitory transmitter GABA to regulate excitation, rhythm generation and synaptic plasticity. A subpopulation of GABAergic basket cells co-expresses the GABA/glycine vesicular transporters (VIAAT) and the atypical type III vesicular glutamate transporter (VGLUT3); therefore, these cells have the ability to signal with both GABA and glutamate. GABAergic transmission by basket cells has been extensively characterized but nothing is known about the functional implications of VGLUT3-dependent glutamate released by these cells. Here, using VGLUT3-null mice we observed that the loss of VGLUT3 results in a metaplastic shift in synaptic plasticity at Shaeffer’s collaterals – CA1 synapses and an altered theta oscillation. These changes were paralleled by the loss of a VGLUT3-dependent inhibition of GABAergic current in CA1 pyramidal layer. Therefore presynaptic type III metabotropic could be activated by glutamate released from VGLUT3-positive interneurons. This putative presynaptic heterologous feedback mechanism inhibits local GABAergic tone and regulates the hippocampal neuronal network. PMID:28559797

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

PubMed Central

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

2014-01-01

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

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

Transient slow gamma synchrony underlies hippocampal memory replay

PubMed Central

Carr, Margaret F.; Karlsson, Mattias P.; Frank, Loren M.

2012-01-01

Summary The replay of previously stored memories during hippocampal sharp wave ripples (SWRs) is thought to support both memory retrieval and consolidation in distributed hippocampal-neocortical circuits. Replay events consist of precisely timed sequences of spikes from CA3 and CA1 neurons that are coordinated both within and across hemispheres. The mechanism of this coordination is not understood. Here we show that during SWRs in both awake and quiescent states there are transient increases in slow gamma (20-50Hz) power and synchrony across dorsal CA3 and CA1 networks of both hemispheres. These gamma oscillations entrain CA3 and CA1 spiking. Moreover, during awake SWRs, higher levels of slow gamma synchrony are predictive of higher quality replay of past experiences. Our results indicate that CA3–CA1 gamma synchronization is a central component of awake memory replay and suggest that transient gamma synchronization serves as a clocking mechanism to enable coordinated memory reactivation across the hippocampal network. PMID:22920260

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

Enhanced temporal stability of cholinergic hippocampal gamma oscillations following respiratory alkalosis in vitro.

PubMed

Stenkamp, K; Palva, J M; Uusisaari, M; Schuchmann, S; Schmitz, D; Heinemann, U; Kaila, K

2001-05-01

The decrease in brain CO(2) partial pressure (pCO(2)) that takes place both during voluntary and during pathological hyperventilation is known to induce gross alterations in cortical functions that lead to subjective sensations and altered states of consciousness. The mechanisms that mediate the effects of the decrease in pCO(2) at the neuronal network level are largely unexplored. In the present work, the modulation of gamma oscillations by hypocapnia was studied in rat hippocampal slices. Field potential oscillations were induced by the cholinergic agonist carbachol under an N-methyl-D-aspartate (NMDA)-receptor blockade and were recorded in the dendritic layer of the CA3 region with parallel measurements of changes in interstitial and intraneuronal pH (pH(o) and pH(i), respectively). Hypocapnia from 5 to 1% CO(2) led to a stable monophasic increase of 0.5 and 0.2 units in pH(o) and pH(i), respectively. The mean oscillation frequency increased slightly but significantly from 32 to 34 Hz and the mean gamma-band amplitude (20 to 80 Hz) decreased by 20%. Hypocapnia induced a dramatic enhancement of the temporal stability of the oscillations, as was indicated by a two-fold increase in the exponential decay time constant fitted to the autocorrelogram. A rise in pH(i) evoked by the weak base trimethylamine (TriMA) was associated with a slight increase in oscillation frequency (37 to 39 Hz) and a decrease in amplitude (30%). Temporal stability, on the other hand, was decreased by TriMA, which suggests that its enhancement in 1% CO(2) was related to the rise in pH(o). In 1% CO(2), the decay-time constant of the evoked monosynaptic pyramidal inhibitory postsynaptic current (IPSC) was unaltered but its amplitude was enhanced. This increase in IPSC amplitude seems to significantly contribute to the enhancement of temporal stability because the enhancement was almost fully reversed by a low concentration of bicuculline. These results suggest that changes in brain pCO(2) can

First and second generation antipsychotics influence hippocampal gamma oscillations by interactions with 5-HT3 and D3 receptors

PubMed Central

Schulz, Steffen B; Heidmann, Karin E; Mike, Arpad; Klaft, Zin-Juan; Heinemann, Uwe; Gerevich, Zoltan

2012-01-01

BACKGROUND AND PURPOSE Disturbed cortical gamma band oscillations (30–80 Hz) have been observed in schizophrenia: positive symptoms of the disease correlate with an increase in gamma oscillation power, whereas negative symptoms are associated with a decrease. EXPERIMENTAL APPROACH Here we investigated the effects of first and second generation antipsychotics (FGAs and SGAs, respectively) on gamma oscillations. The FGAs haloperidol, flupenthixol, chlorpromazine, chlorprothixene and the SGAs clozapine, risperidone, ziprasidone, amisulpride were applied on gamma oscillations induced by acetylcholine and physostigmine in the CA3 region of rat hippocampal slices. KEY RESULTS Antipsychotics inhibited the power of gamma oscillations and increased the bandwidth of the gamma band. Haloperidol and clozapine had the highest inhibitory effects. To determine which receptor is responsible for the alterations in gamma oscillations, the effects of the antipsychotics were plotted against their pKi values for 19 receptors and analysed for correlation. Our results indicated that 5-HT3 receptors have an enhancing effect on gamma oscillations whereas dopamine D3 receptors inhibit them. To test this prediction, m-chlorophenylbiguanide, PD 128907 and CP 809101, selective agonists at 5-HT3, D3 and 5-HT2C receptors were applied and revealed that 5-HT3 receptors indeed enhanced the gamma power whereas D3 receptors reduced it. As predicted, 5-HT2C receptors had no effects on gamma oscillations. CONCLUSION AND IMPLICATIONS Our data suggest that antipsychotics alter hippocampal gamma oscillations by interacting with 5-HT3 and dopamine D3 receptors. Moreover, a correlation of receptor affinities with the biological effects can be used to predict targets for the pharmacological effects of multi-target drugs. PMID:22817643

Network and intrinsic cellular mechanisms underlying theta phase precession of hippocampal neurons.

PubMed

Maurer, Andrew P; McNaughton, Bruce L

2007-07-01

Hippocampal 'place cells' systematically shift their phase of firing in relation to the theta rhythm as an animal traverses the 'place field'. These dynamics imply that the neural ensemble begins each theta cycle at a point in its state-space that might 'represent' the current location of the rat, but that the ensemble 'looks ahead' during the rest of the cycle. Phase precession could result from intrinsic cellular dynamics involving interference of two oscillators of different frequencies, or from network interactions, similar to Hebb's 'phase sequence' concept, involving asymmetric synaptic connections. Both models have difficulties accounting for all of the available experimental data, however. A hybrid model, in which the look-ahead phenomenon implied by phase precession originates in superficial entorhinal cortex by some form of interference mechanism and is enhanced in the hippocampus proper by asymmetric synaptic plasticity during sequence encoding, seems to be consistent with available data, but as yet there is no fully satisfactory theoretical account of this phenomenon. This review is part of the INMED/TINS special issue Physiogenic and pathogenic oscillations: the beauty and the beast, based on presentations at the annual INMED/TINS symposium (http://inmednet.com).

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

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

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

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 shiftmore » 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

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

PubMed

Csicsvari, Jozsef; Dupret, David

2014-02-05

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.

Choline-mediated modulation of hippocampal sharp wave-ripple complexes in vitro.

PubMed

Fischer, Viktoria; Both, Martin; Draguhn, Andreas; Egorov, Alexei V

2014-06-01

The cholinergic system is critically involved in the modulation of cognitive functions, including learning and memory. Acetylcholine acts through muscarinic (mAChRs) and nicotinic receptors (nAChRs), which are both abundantly expressed in the hippocampus. Previous evidence indicates that choline, the precursor and degradation product of Acetylcholine, can itself activate nAChRs and thereby affects intrinsic and synaptic neuronal functions. Here, we asked whether the cellular actions of choline directly affect hippocampal network activity. Using mouse hippocampal slices we found that choline efficiently suppresses spontaneously occurring sharp wave-ripple complexes (SPW-R) and can induce gamma oscillations. In addition, choline reduces synaptic transmission between hippocampal subfields CA3 and CA1. Surprisingly, these effects are mediated by activation of both mAChRs and α7-containing nAChRs. Most nicotinic effects became only apparent after local, fast application of choline, indicating rapid desensitization kinetics of nAChRs. Effects were still present following block of choline uptake and are, therefore, likely because of direct actions of choline at the respective receptors. Together, choline turns out to be a potent regulator of patterned network activity within the hippocampus. These actions may be of importance for understanding state transitions in normal and pathologically altered neuronal networks. In this study we asked whether choline, the precursor and degradation product of acetylcholine, directly affects hippocampal network activity. Using mouse hippocampal slices we found that choline efficiently suppresses spontaneously occurring sharp wave-ripple complexes (SPW-R). In addition, choline reduces synaptic transmission between hippocampal subfields. These effects are mediated by direct activation of muscarinic as well as nicotinic cholinergic pathways. Together, choline turns out to be a potent regulator of patterned activity within hippocampal

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.

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.

From network heterogeneities to familiarity detection and hippocampal memory management

PubMed Central

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

2009-01-01

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. PMID:18999453

Transition from amplitude to oscillation death in a network of oscillators

NASA Astrophysics Data System (ADS)

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.

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.

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

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

Tass, P. A.; Barnikol, U. B.; Department of Stereotaxic and Functional Neurosurgery, University of Cologne, D-50931 Cologne

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 amore » widespread decrease in the amplitude of the epileptiform activity. In contrast, periodic stimulation induces a long-lasting increase in both synchronization and amplitude.« less

Transition from amplitude to oscillation death in a network of oscillators

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

Nandan, Mauparna; Department of Mathematics, National Institute of Technology, Durgapur 713209; Hens, C. R.

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 determinemore » 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.« less

Insensitive dependence of delay-induced oscillation death on complex networks

NASA Astrophysics Data System (ADS)

Zou, Wei; Zheng, Xing; Zhan, Meng

2011-06-01

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

Hippocampal mechanisms for the context-dependent retrieval of episodes

PubMed Central

Hasselmo, Michael E.; Eichenbaum, Howard B.

2008-01-01

Behaviors ranging from delivering newspapers to waiting tables depend on remembering previous episodes to avoid incorrect repetition. Physiologically, this requires mechanisms for long-term storage and selective retrieval of episodes based on time of occurrence, despite variable intervals and similarity of events in a familiar environment. Here, this process has been modeled based on physiological properties of the hippocampal formation, including mechanisms for sustained activity in entorhinal cortex and theta rhythm oscillations in hippocampal subregions. The model simulates the context-sensitive firing properties of hippocampal neurons including trial specific firing during spatial alternation and trial by trial changes in theta phase precession on a linear track. This activity is used to guide behavior, and lesions of the hippocampal network impair memory-guided behavior. The model links data at the cellular level to behavior at the systems level, describing a physiologically plausible mechanism for the brain to recall a given episode which occurred at a specific place and time. PMID:16263240

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

PubMed Central

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

2016-01-01

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

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

Theta Oscillations During Active Sleep Synchronize The Developing Rubro-Hippocampal Sensorimotor Network

PubMed Central

Rio-Bermudez, Carlos Del; Kim, Jangjin; Sokoloff, Greta; Blumberg, Mark S.

2017-01-01

Summary Neuronal oscillations comprise a fundamental mechanism by which distant neural structures establish and express functional connectivity. Long-range functional connectivity between the hippocampus and other forebrain structures is enabled by theta oscillations. Here we show for the first time that the infant rat red nucleus (RN)—a brainstem sensorimotor structure— exhibits theta (4-7 Hz) oscillations restricted primarily to periods of active (REM) sleep. At postnatal day (P) 8, theta is expressed as brief bursts immediately following myoclonic twitches; by P12, theta oscillations are expressed continuously across bouts of active sleep. Simultaneous recordings from the hippocampus and RN at P12 show that theta oscillations in both structures are coherent, co-modulated, and mutually interactive during active sleep. Critically, at P12, inactivation of the medial septum eliminates theta in both structures. The developmental emergence of theta-dependent functional coupling between the hippocampus and RN parallels that between the hippocampus and prefrontal cortex. Accordingly, disruptions in the early expression of theta could underlie the cognitive and sensorimotor deficits associated with neurodevelopmental disorders such as autism and schizophrenia. PMID:28479324

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.

Creation and perturbation of planar networks of chemical oscillators

PubMed Central

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

2015-01-01

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

Synchronization in complex oscillator networks and smart grids.

PubMed

Dörfler, Florian; Chertkov, Michael; Bullo, Francesco

2013-02-05

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

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.

Auditory stimulation of sleep slow oscillations modulates subsequent memory encoding through altered hippocampal function

PubMed Central

Ong, Ju Lynn; Chee, Nicholas I Y N; Lee, Xuan Kai; Poh, Jia-Hou; Chee, Michael W L

2018-01-01

Abstract Study Objectives Slow oscillations (SO) during sleep contribute to the consolidation of learned material. How the encoding of declarative memories during subsequent wakefulness might benefit from their enhancement during sleep is less clear. In this study, we investigated the impact of acoustically enhanced SO during a nap on subsequent encoding of declarative material. Methods Thirty-seven healthy young adults were studied under two conditions: stimulation (STIM) and no stimulation (SHAM), in counter-balanced order following a night of sleep restriction (4 hr time-in-bed [TIB]). In the STIM condition, auditory tones were phase-locked to the SO up-state during a 90 min nap opportunity. In the SHAM condition, corresponding time points were marked but tones were not presented. Thirty minutes after awakening, participants encoded pictures while undergoing fMRI. Picture recognition was tested 60 min later. Results Acoustic stimulation augmented SO across the group, but there was no group level benefit on memory. However, the magnitude of SO enhancement correlated with greater recollection. SO enhancement was also positively correlated with hippocampal activation at encoding. Although spindle activity increased, this did not correlate with memory benefit or shift in hippocampal signal. Conclusions Acoustic stimulation during a nap can benefit encoding of declarative memories. Hippocampal activation positively correlated with SO augmentation. PMID:29425369

Auditory stimulation of sleep slow oscillations modulates subsequent memory encoding through altered hippocampal function.

PubMed

Ong, Ju Lynn; Patanaik, Amiya; Chee, Nicholas I Y N; Lee, Xuan Kai; Poh, Jia-Hou; Chee, Michael W L

2018-05-01

Slow oscillations (SO) during sleep contribute to the consolidation of learned material. How the encoding of declarative memories during subsequent wakefulness might benefit from their enhancement during sleep is less clear. In this study, we investigated the impact of acoustically enhanced SO during a nap on subsequent encoding of declarative material. Thirty-seven healthy young adults were studied under two conditions: stimulation (STIM) and no stimulation (SHAM), in counter-balanced order following a night of sleep restriction (4 hr time-in-bed [TIB]). In the STIM condition, auditory tones were phase-locked to the SO up-state during a 90 min nap opportunity. In the SHAM condition, corresponding time points were marked but tones were not presented. Thirty minutes after awakening, participants encoded pictures while undergoing fMRI. Picture recognition was tested 60 min later. Acoustic stimulation augmented SO across the group, but there was no group level benefit on memory. However, the magnitude of SO enhancement correlated with greater recollection. SO enhancement was also positively correlated with hippocampal activation at encoding. Although spindle activity increased, this did not correlate with memory benefit or shift in hippocampal signal. Acoustic stimulation during a nap can benefit encoding of declarative memories. Hippocampal activation positively correlated with SO augmentation.

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

Mesopontine median raphe regulates hippocampal ripple oscillation and memory consolidation.

PubMed

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

2015-05-01

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

Mesopontine median raphe regulates hippocampal ripple oscillation and memory consolidation

PubMed Central

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

2015-01-01

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

Robustness and fragility in coupled oscillator networks under targeted attacks.

PubMed

Yuan, Tianyu; Aihara, Kazuyuki; Tanaka, Gouhei

2017-01-01

The dynamical tolerance of coupled oscillator networks against local failures is studied. As the fraction of failed oscillator nodes gradually increases, the mean oscillation amplitude in the entire network decreases and then suddenly vanishes at a critical fraction as a phase transition. This critical fraction, widely used as a measure of the network robustness, was analytically derived for random failures but not for targeted attacks so far. Here we derive the general formula for the critical fraction, which can be applied to both random failures and targeted attacks. We consider the effects of targeting oscillator nodes based on their degrees. First we deal with coupled identical oscillators with homogeneous edge weights. Then our theory is applied to networks with heterogeneous edge weights and to those with nonidentical oscillators. The analytical results are validated by numerical experiments. Our results reveal the key factors governing the robustness and fragility of oscillator networks.

Global Oscillation Network Group

NASA Astrophysics Data System (ADS)

Murdin, P.

2000-11-01

The Global Oscillation Network Group (GONG) is an international, community-based project, operated by the NATIONAL SOLAR OBSERVATORY for the US National Science Foundation, to conduct a detailed study of the internal structure and dynamics of the Sun over an 11 year solar cycle using helioseismology. 10 242 velocity images are obtained by a six-station network located at Big Bear Solar Observato...

Checkpoints couple transcription network oscillator dynamics to cell-cycle progression.

PubMed

Bristow, Sara L; Leman, Adam R; Simmons Kovacs, Laura A; Deckard, Anastasia; Harer, John; Haase, Steven B

2014-09-05

The coupling of cyclin dependent kinases (CDKs) to an intrinsically oscillating network of transcription factors has been proposed to control progression through the cell cycle in budding yeast, Saccharomyces cerevisiae. The transcription network regulates the temporal expression of many genes, including cyclins, and drives cell-cycle progression, in part, by generating successive waves of distinct CDK activities that trigger the ordered program of cell-cycle events. Network oscillations continue autonomously in mutant cells arrested by depletion of CDK activities, suggesting the oscillator can be uncoupled from cell-cycle progression. It is not clear what mechanisms, if any, ensure that the network oscillator is restrained when progression in normal cells is delayed or arrested. A recent proposal suggests CDK acts as a master regulator of cell-cycle processes that have the potential for autonomous oscillatory behavior. Here we find that mitotic CDK is not sufficient for fully inhibiting transcript oscillations in arrested cells. We do find that activation of the DNA replication and spindle assembly checkpoints can fully arrest the network oscillator via overlapping but distinct mechanisms. Further, we demonstrate that the DNA replication checkpoint effector protein, Rad53, acts to arrest a portion of transcript oscillations in addition to its role in halting cell-cycle progression. Our findings indicate that checkpoint mechanisms, likely via phosphorylation of network transcription factors, maintain coupling of the network oscillator to progression during cell-cycle arrest.

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

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

PubMed

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

2017-04-01

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

Stellar Oscillations Network Group

NASA Astrophysics Data System (ADS)

Grundahl, F.; Kjeldsen, H.; Christensen-Dalsgaard, J.; Arentoft, T.; Frandsen, S.

2007-06-01

Stellar Oscillations Network Group (SONG) is an initiative aimed at designing and building a network of 1m-class telescopes dedicated to asteroseismology and planet hunting. SONG will have 8 identical telescope nodes each equipped with a high-resolution spectrograph and an iodine cell for obtaining precision radial velocities and a CCD camera for guiding and imaging purposes. The main asteroseismology targets for the network are the brightest (V < 6) stars. In order to improve performance and reduce maintenance costs the instrumentation will only have very few modes of operation. In this contribution we describe the motivations for establishing a network, the basic outline of SONG and the expected performance.

Clusters in nonsmooth oscillator networks

NASA Astrophysics Data System (ADS)

Nicks, Rachel; Chambon, Lucie; Coombes, Stephen

2018-03-01

For coupled oscillator networks with Laplacian coupling, the master stability function (MSF) has proven a particularly powerful tool for assessing the stability of the synchronous state. Using tools from group theory, this approach has recently been extended to treat more general cluster states. However, the MSF and its generalizations require the determination of a set of Floquet multipliers from variational equations obtained by linearization around a periodic orbit. Since closed form solutions for periodic orbits are invariably hard to come by, the framework is often explored using numerical techniques. Here, we show that further insight into network dynamics can be obtained by focusing on piecewise linear (PWL) oscillator models. Not only do these allow for the explicit construction of periodic orbits, their variational analysis can also be explicitly performed. The price for adopting such nonsmooth systems is that many of the notions from smooth dynamical systems, and in particular linear stability, need to be modified to take into account possible jumps in the components of Jacobians. This is naturally accommodated with the use of saltation matrices. By augmenting the variational approach for studying smooth dynamical systems with such matrices we show that, for a wide variety of networks that have been used as models of biological systems, cluster states can be explicitly investigated. By way of illustration, we analyze an integrate-and-fire network model with event-driven synaptic coupling as well as a diffusively coupled network built from planar PWL nodes, including a reduction of the popular Morris-Lecar neuron model. We use these examples to emphasize that the stability of network cluster states can depend as much on the choice of single node dynamics as it does on the form of network structural connectivity. Importantly, the procedure that we present here, for understanding cluster synchronization in networks, is valid for a wide variety of systems in

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

Transient synchronization of hippocampo-striato-thalamo-cortical networks during sleep spindle oscillations induces motor memory consolidation.

PubMed

Boutin, Arnaud; Pinsard, Basile; Boré, Arnaud; Carrier, Julie; Fogel, Stuart M; Doyon, Julien

2018-04-01

Sleep benefits motor memory consolidation. This mnemonic process is thought to be mediated by thalamo-cortical spindle activity during NREM-stage2 sleep episodes as well as changes in striatal and hippocampal activity. However, direct experimental evidence supporting the contribution of such sleep-dependent physiological mechanisms to motor memory consolidation in humans is lacking. In the present study, we combined EEG and fMRI sleep recordings following practice of a motor sequence learning (MSL) task to determine whether spindle oscillations support sleep-dependent motor memory consolidation by transiently synchronizing and coordinating specialized cortical and subcortical networks. To that end, we conducted EEG source reconstruction on spindle epochs in both cortical and subcortical regions using novel deep-source localization techniques. Coherence-based metrics were adopted to estimate functional connectivity between cortical and subcortical structures over specific frequency bands. Our findings not only confirm the critical and functional role of NREM-stage2 sleep spindles in motor skill consolidation, but provide first-time evidence that spindle oscillations [11-17 Hz] may be involved in sleep-dependent motor memory consolidation by locally reactivating and functionally binding specific task-relevant cortical and subcortical regions within networks including the hippocampus, putamen, thalamus and motor-related cortical regions. Copyright © 2018 Elsevier Inc. All rights reserved.

Hyperbolic geometry of Kuramoto oscillator networks

NASA Astrophysics Data System (ADS)

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

2017-09-01

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

Synchronization in oscillator networks with delayed coupling: a stability criterion.

PubMed

Earl, Matthew G; Strogatz, Steven H

2003-03-01

We derive a stability criterion for the synchronous state in networks of identical phase oscillators with delayed coupling. The criterion applies to any network (whether regular or random, low dimensional or high dimensional, directed or undirected) in which each oscillator receives delayed signals from k others, where k is uniform for all oscillators.

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

Local complexity predicts global synchronization of hierarchically networked oscillators

NASA Astrophysics Data System (ADS)

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

2017-07-01

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

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

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

PubMed Central

Catoni, Nicholas

2015-01-01

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

Slow oscillation amplitudes and up-state lengths relate to memory improvement.

PubMed

Heib, Dominik P J; Hoedlmoser, Kerstin; Anderer, Peter; Zeitlhofer, Josef; Gruber, Georg; Klimesch, Wolfgang; Schabus, Manuel

2013-01-01

There is growing evidence of the active involvement of sleep in memory consolidation. Besides hippocampal sharp wave-ripple complexes and sleep spindles, slow oscillations appear to play a key role in the process of sleep-associated memory consolidation. Furthermore, slow oscillation amplitude and spectral power increase during the night after learning declarative and procedural memory tasks. However, it is unresolved whether learning-induced changes specifically alter characteristics of individual slow oscillations, such as the slow oscillation up-state length and amplitude, which are believed to be important for neuronal replay. 24 subjects (12 men) aged between 20 and 30 years participated in a randomized, within-subject, multicenter study. Subjects slept on three occasions for a whole night in the sleep laboratory with full polysomnography. Whereas the first night only served for adaptation purposes, the two remaining nights were preceded by a declarative word-pair task or by a non-learning control task. Slow oscillations were detected in non-rapid eye movement sleep over electrode Fz. Results indicate positive correlations between the length of the up-state as well as the amplitude of both slow oscillation phases and changes in memory performance from pre to post sleep. We speculate that the prolonged slow oscillation up-state length might extend the timeframe for the transfer of initial hippocampal to long-term cortical memory representations, whereas the increase in slow oscillation amplitudes possibly reflects changes in the net synaptic strength of cortical networks.

Global competition and local cooperation in a network of neural oscillators

NASA Astrophysics Data System (ADS)

Terman, David; Wang, DeLiang

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

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.

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.

Dynamics of a network of phase oscillators with plastic couplings

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

Nekorkin, V. I.; Kasatkin, D. V.; Moscow Institute of Physics and Technology

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.

Modulation of hippocampal rhythms by subthreshold electric fields and network topology

PubMed Central

Berzhanskaya, Julia; Chernyy, Nick; Gluckman, Bruce J.; Schiff, Steven J.; Ascoli, Giorgio A.

2012-01-01

Theta (4–12 Hz) and gamma (30–80 Hz) rhythms are considered important for cortical and hippocampal function. Although several neuron types are implicated in rhythmogenesis, the exact cellular mechanisms remain unknown. Subthreshold electric fields provide a flexible, area-specific tool to modulate neural activity and directly test functional hypotheses. Here we present experimental and computational evidence of the interplay among hippocampal synaptic circuitry, neuronal morphology, external electric fields, and network activity. Electrophysiological data are used to constrain and validate an anatomically and biophysically realistic model of area CA1 containing pyramidal cells and two interneuron types: dendritic- and perisomatic-targeting. We report two lines of results: addressing the network structure capable of generating theta-modulated gamma rhythms, and demonstrating electric field effects on those rhythms. First, theta-modulated gamma rhythms require specific inhibitory connectivity. In one configuration, GABAergic axo-dendritic feedback on pyramidal cells is only effective in proximal but not distal layers. An alternative configuration requires two distinct perisomatic interneuron classes, one exclusively receiving excitatory contacts, the other additionally targeted by inhibition. These observations suggest novel roles for particular classes of oriens and basket cells. The second major finding is that subthreshold electric fields robustly alter the balance between different rhythms. Independent of network configuration, positive electric fields decrease, while negative fields increase the theta/gamma ratio. Moreover, electric fields differentially affect average theta frequency depending on specific synaptic connectivity. These results support the testable prediction that subthreshold electric fields can alter hippocampal rhythms, suggesting new approaches to explore their cognitive functions and underlying circuitry. PMID:23053863

Synchronization of mobile chaotic oscillator networks

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

Fujiwara, Naoya, E-mail: fujiwara@csis.u-tokyo.ac.jp; Kurths, Jürgen; Díaz-Guilera, Albert

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 themore » 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.« less

Synchronization of Lienard-Type Oscillators in Uniform Electrical Networks

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

Sinha, Mohit; Dorfler, Florian; Johnson, Brian B.

2016-08-01

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

Graph partitions and cluster synchronization in networks of oscillators

PubMed Central

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

2017-01-01

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

Synchronization and desynchronization in a network of locally coupled Wilson-Cowan oscillators.

PubMed

Campbell, S; Wang, D

1996-01-01

A network of Wilson-Cowan (WC) oscillators is constructed, and its emergent properties of synchronization and desynchronization are investigated by both computer simulation and formal analysis. The network is a 2D matrix, where each oscillator is coupled only to its neighbors. We show analytically that a chain of locally coupled oscillators (the piecewise linear approximation to the WC oscillator) synchronizes, and we present a technique to rapidly entrain finite numbers of oscillators. The coupling strengths change on a fast time scale based on a Hebbian rule. A global separator is introduced which receives input from and sends feedback to each oscillator in the matrix. The global separator is used to desynchronize different oscillator groups. Unlike many other models, the properties of this network emerge from local connections that preserve spatial relationships among components and are critical for encoding Gestalt principles of feature grouping. The ability to synchronize and desynchronize oscillator groups within this network offers a promising approach for pattern segmentation and figure/ground segregation based on oscillatory correlation.

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.

Spontaneous oscillations in microfluidic networks

NASA Astrophysics Data System (ADS)

Case, Daniel; Angilella, Jean-Regis; Motter, Adilson

2017-11-01

Precisely controlling flows within microfluidic systems is often difficult which typically results in systems being heavily reliant on numerous external pumps and computers. Here, I present a simple microfluidic network that exhibits flow rate switching, bistablity, and spontaneous oscillations controlled by a single pressure. That is, by solely changing the driving pressure, it is possible to switch between an oscillating and steady flow state. Such functionality does not rely on external hardware and may even serve as an on-chip memory or timing mechanism. I use an analytic model and rigorous fluid dynamics simulations to show these results.

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.

Control of coupled oscillator networks with application to microgrid technologies

NASA Astrophysics Data System (ADS)

Arenas, Alex

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 syn- chronized 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.

Direct brain recordings reveal hippocampal rhythm underpinnings of language processing.

PubMed

Piai, Vitória; Anderson, Kristopher L; Lin, Jack J; Dewar, Callum; Parvizi, Josef; Dronkers, Nina F; Knight, Robert T

2016-10-04

Language is classically thought to be supported by perisylvian cortical regions. Here we provide intracranial evidence linking the hippocampal complex to linguistic processing. We used direct recordings from the hippocampal structures to investigate whether theta oscillations, pivotal in memory function, track the amount of contextual linguistic information provided in sentences. Twelve participants heard sentences that were either constrained ("She locked the door with the") or unconstrained ("She walked in here with the") before presentation of the final word ("key"), shown as a picture that participants had to name. Hippocampal theta power increased for constrained relative to unconstrained contexts during sentence processing, preceding picture presentation. Our study implicates hippocampal theta oscillations in a language task using natural language associations that do not require memorization. These findings reveal that the hippocampal complex contributes to language in an active fashion, relating incoming words to stored semantic knowledge, a necessary process in the generation of sentence meaning.

Resumption of dynamism in damaged networks of coupled oscillators

NASA Astrophysics Data System (ADS)

Kundu, Srilena; Majhi, Soumen; Ghosh, Dibakar

2018-05-01

Deterioration in dynamical activities may come up naturally or due to environmental influences in a massive portion of biological and physical systems. Such dynamical degradation may have outright effect on the substantive network performance. This requires us to provide some proper prescriptions to overcome undesired circumstances. In this paper, we present a scheme based on external feedback that can efficiently revive dynamism in damaged networks of active and inactive oscillators and thus enhance the network survivability. Both numerical and analytical investigations are performed in order to verify our claim. We also provide a comparative study on the effectiveness of this mechanism for feedbacks to the inactive group or to the active group only. Most importantly, resurrection of dynamical activity is realized even in time-delayed damaged networks, which are considered to be less persistent against deterioration in the form of inactivity in the oscillators. Furthermore, prominence in our approach is substantiated by providing evidence of enhanced network persistence in complex network topologies taking small-world and scale-free architectures, which makes the proposed remedy quite general. Besides the study in the network of Stuart-Landau oscillators, affirmative influence of external feedback has been justified in the network of chaotic Rössler systems as well.

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

NASA Astrophysics Data System (ADS)

Wang, DeLiang; Terman, David

1995-01-01

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

Intermittent and sustained periodic windows in networked chaotic Rössler oscillators

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

He, Zhiwei; Sun, Yong; University of the Chinese Academy of Sciences, Beijing 100049

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 weakmore » 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.« less

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

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

Oscillator networks with tissue-specific circadian clocks in plants.

PubMed

Inoue, Keisuke; Araki, Takashi; Endo, Motomu

2017-09-08

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

Synchronization of networked chaotic oscillators under external periodic driving.

PubMed

Yang, Wenchao; Lin, Weijie; Wang, Xingang; Huang, Liang

2015-03-01

The dynamical responses of a complex system to external perturbations are of both fundamental interest and practical significance. Here, by the model of networked chaotic oscillators, we investigate how the synchronization behavior of a complex network is influenced by an externally added periodic driving. Interestingly, it is found that by a slight change of the properties of the external driving, e.g., the frequency or phase lag between its intrinsic oscillation and external driving, the network synchronizability could be significantly modified. We demonstrate this phenomenon by different network models and, based on the method of master stability function, give an analysis on the underlying mechanisms. Our studies highlight the importance of external perturbations on the collective behaviors of complex networks, and also provide an alternate approach for controlling network synchronization.

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

PubMed

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

2009-01-01

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

Regulating Cortical Oscillations in an Inhibition-Stabilized Network.

PubMed

Jadi, Monika P; Sejnowski, Terrence J

2014-04-21

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

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

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

PubMed

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

2014-01-01

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

Distinct hippocampal versus frontoparietal-network contributions to retrieval and memory-guided exploration

PubMed Central

Bridge, Donna J.; Cohen, Neal J.; Voss, Joel L.

2017-01-01

Memory can profoundly influence new learning, presumably because memory optimizes exploration of to-be-learned material. Although hippocampus and frontoparietal networks have been implicated in memory-guided exploration, their specific and interactive roles have not been identified. We examined eye movements during fMRI scanning to identify neural correlates of the influences of memory retrieval on exploration and learning. Following retrieval of one object in a multi-object array, viewing was strategically directed away from the retrieved object toward non-retrieved objects, such that exploration was directed towards to-be-learned content. Retrieved objects later served as optimal reminder cues, indicating that exploration caused memory to become structured around the retrieved content. Hippocampal activity was associated with memory retrieval whereas frontoparietal activity varied with strategic viewing patterns deployed following retrieval, thus providing spatiotemporal dissociation of memory retrieval from memory-guided learning strategies. Time-lagged fMRI connectivity analyses indicated that hippocampal activity predicted frontoparietal activity to a greater extent for a condition in which retrieval guided exploration than for a passive control condition in which exploration was not influenced by retrieval. This demonstrates network-level interaction effects specific to influences of memory on strategic exploration. These findings show how memory guides behavior during learning and demonstrate distinct yet interactive hippocampal-frontoparietal roles in implementing strategic exploration behaviors that determine the fate of evolving memory representations. PMID:28471729

Distinct Hippocampal versus Frontoparietal Network Contributions to Retrieval and Memory-guided Exploration.

PubMed

Bridge, Donna J; Cohen, Neal J; Voss, Joel L

2017-08-01

Memory can profoundly influence new learning, presumably because memory optimizes exploration of to-be-learned material. Although hippocampus and frontoparietal networks have been implicated in memory-guided exploration, their specific and interactive roles have not been identified. We examined eye movements during fMRI scanning to identify neural correlates of the influences of memory retrieval on exploration and learning. After retrieval of one object in a multiobject array, viewing was strategically directed away from the retrieved object toward nonretrieved objects, such that exploration was directed toward to-be-learned content. Retrieved objects later served as optimal reminder cues, indicating that exploration caused memory to become structured around the retrieved content. Hippocampal activity was associated with memory retrieval, whereas frontoparietal activity varied with strategic viewing patterns deployed after retrieval, thus providing spatiotemporal dissociation of memory retrieval from memory-guided learning strategies. Time-lagged fMRI connectivity analyses indicated that hippocampal activity predicted frontoparietal activity to a greater extent for a condition in which retrieval guided exploration occurred than for a passive control condition in which exploration was not influenced by retrieval. This demonstrates network-level interaction effects specific to influences of memory on strategic exploration. These findings show how memory guides behavior during learning and demonstrate distinct yet interactive hippocampal-frontoparietal roles in implementing strategic exploration behaviors that determine the fate of evolving memory representations.

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.

Interactions between neural networks: a mechanism for tuning chaos and oscillations

PubMed Central

2007-01-01

We show that chaos and oscillations in a higher-order binary neural network can be tuned effectively using interactions between neural networks. Our results suggest that network interactions may be useful as a means of adjusting the level of dynamic activities in systems that employ chaos and oscillations for information processing, or as a means of suppressing oscillatory behaviors in systems that require stability. PMID:19003511

Interactions between neural networks: a mechanism for tuning chaos and oscillations.

PubMed

Wang, Lipo

2007-06-01

We show that chaos and oscillations in a higher-order binary neural network can be tuned effectively using interactions between neural networks. Our results suggest that network interactions may be useful as a means of adjusting the level of dynamic activities in systems that employ chaos and oscillations for information processing, or as a means of suppressing oscillatory behaviors in systems that require stability.

Synchrony-optimized networks of Kuramoto oscillators with inertia

NASA Astrophysics Data System (ADS)

Pinto, Rafael S.; Saa, Alberto

2016-12-01

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

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

PubMed

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

2017-01-18

Sharp wave-ripple (SWR) oscillations play a key role in memory consolidation during non-rapid eye movement sleep, immobility, and consummatory behavior. However, whether temporally modulated synaptic excitation or inhibition underlies the ripples is controversial. To address this question, we performed simultaneous recordings of excitatory and inhibitory postsynaptic currents (EPSCs and IPSCs) and local field potentials (LFPs) in the CA1 region of awake mice in vivo. During SWRs, inhibition dominated over excitation, with a peak conductance ratio of 4.1 ± 0.5. Furthermore, the amplitude of SWR-associated IPSCs was positively correlated with SWR magnitude, whereas that of EPSCs was not. Finally, phase analysis indicated that IPSCs were phase-locked to individual ripple cycles, whereas EPSCs were uniformly distributed in phase space. Optogenetic inhibition indicated that PV + interneurons provided a major contribution to SWR-associated IPSCs. Thus, phasic inhibition, but not excitation, shapes SWR oscillations in the hippocampal CA1 region in vivo. Copyright © 2017 The Author(s). Published by Elsevier Inc. All rights reserved.

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

Thermodynamic characterization of synchronization-optimized oscillator networks

NASA Astrophysics Data System (ADS)

Yanagita, Tatsuo; Ichinomiya, Takashi

2014-12-01

We consider a canonical ensemble of synchronization-optimized networks of identical oscillators under external noise. By performing a Markov chain Monte Carlo simulation using the Kirchhoff index, i.e., the sum of the inverse eigenvalues of the Laplacian matrix (as a graph Hamiltonian of the network), we construct more than 1 000 different synchronization-optimized networks. We then show that the transition from star to core-periphery structure depends on the connectivity of the network, and is characterized by the node degree variance of the synchronization-optimized ensemble. We find that thermodynamic properties such as heat capacity show anomalies for sparse networks.

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…

PTEN Loss Increases the Connectivity of Fast Synaptic Motifs and Functional Connectivity in a Developing Hippocampal Network

PubMed Central

McCabe, Matthew P.; Chen, Hongmei; Swann, John W.

2017-01-01

Changes in synaptic strength and connectivity are thought to be a major mechanism through which many gene variants cause neurological disease. Hyperactivation of the PI3K-mTOR signaling network, via loss of function of repressors such as PTEN, causes epilepsy in humans and animal models, and altered mTOR signaling may contribute to a broad range of neurological diseases. Changes in synaptic transmission have been reported in animal models of PTEN loss; however, the full extent of these changes, and their effect on network function, is still unknown. To better understand the scope of these changes, we recorded from pairs of mouse hippocampal neurons cultured in a two-neuron microcircuit configuration that allowed us to characterize all four major connection types within the hippocampus. Loss of PTEN caused changes in excitatory and inhibitory connectivity, and these changes were postsynaptic, presynaptic, and transynaptic, suggesting that disruption of PTEN has the potential to affect most connection types in the hippocampal circuit. Given the complexity of the changes at the synaptic level, we measured changes in network behavior after deleting Pten from neurons in an organotypic hippocampal slice network. Slices containing Pten-deleted neurons showed increased recruitment of neurons into network bursts. Importantly, these changes were not confined to Pten-deleted neurons, but involved the entire network, suggesting that the extensive changes in synaptic connectivity rewire the entire network in such a way that promotes a widespread increase in functional connectivity. SIGNIFICANCE STATEMENT Homozygous deletion of the Pten gene in neuronal subpopulations in the mouse serves as a valuable model of epilepsy caused by mTOR hyperactivation. To better understand how gene deletions lead to altered neuronal activity, we investigated the synaptic and network effects that occur 1 week after Pten deletion. PTEN loss increased the connectivity of all four types of hippocampal

Hippocampal Sleep Features: Relations to Human Memory Function

PubMed Central

Ferrara, Michele; Moroni, Fabio; De Gennaro, Luigi; Nobili, Lino

2012-01-01

The recent spread of intracranial electroencephalographic (EEG) recording techniques for presurgical evaluation of drug-resistant epileptic patients is providing new information on the activity of different brain structures during both wakefulness and sleep. The interest has been mainly focused on the medial temporal lobe, and in particular the hippocampal formation, whose peculiar local sleep features have been recently described, providing support to the idea that sleep is not a spatially global phenomenon. The study of the hippocampal sleep electrophysiology is particularly interesting because of its central role in the declarative memory formation. Recent data indicate that sleep contributes to memory formation. Therefore, it is relevant to understand whether specific patterns of activity taking place during sleep are related to memory consolidation processes. Fascinating similarities between different states of consciousness (wakefulness, REM sleep, non-REM sleep) in some electrophysiological mechanisms underlying cognitive processes have been reported. For instance, large-scale synchrony in gamma activity is important for waking memory and perception processes, and its changes during sleep may be the neurophysiological substrate of sleep-related deficits of declarative memory. Hippocampal activity seems to specifically support memory consolidation during sleep, through specific coordinated neurophysiological events (slow waves, spindles, ripples) that would facilitate the integration of new information into the pre-existing cortical networks. A few studies indeed provided direct evidence that rhinal ripples as well as slow hippocampal oscillations are correlated with memory consolidation in humans. More detailed electrophysiological investigations assessing the specific relations between different types of memory consolidation and hippocampal EEG features are in order. These studies will add an important piece of knowledge to the elucidation of the ultimate

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

Indirect synchronization control in a starlike network of phase oscillators

NASA Astrophysics Data System (ADS)

Kuptsov, Pavel V.; Kuptsova, Anna V.

2018-04-01

A starlike network of non-identical phase oscillators is considered that contains the hub and tree rays each having a single node. In such network effect of indirect synchronization control is reported: changing the natural frequency and the coupling strength of one of the peripheral oscillators one can switch on an off the synchronization of the others. The controlling oscillator at that is not synchronized with them and has a frequency that is approximately four time higher then the frequency of the synchronization. The parameter planes showing a corresponding synchronization tongue are represented and time dependencies of phase differences are plotted for points within and outside of the tongue.

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.

Dependence of synchronization on frequency mismatch and network configuration in chemo-mechanical oscillators

NASA Astrophysics Data System (ADS)

Kumar, Pawan; Parmananda, P.

2018-04-01

In this paper, synchronization among the mercury beating heart (MBH) oscillators is studied. In the first set of experiments, two MBH oscillators were taken. Frequency of one oscillator is kept constant and that of the other is increased monotonically. These were then coupled using bidirectional and unidirectional coupling mechanisms separately. Dependence of synchronization on the frequency difference between the two oscillators is investigated. For the second set of experiments involving unidirectional coupling, an ensemble of fifteen oscillators was taken and different configurations of these oscillators were considered. These include an all-to-all network and fractionally distributed master slave configurations. The effect of both the extent of coupling and network configuration on synchronization among these oscillators was investigated.

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

PubMed Central

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

2014-01-01

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

Gap junction plasticity as a mechanism to regulate network-wide oscillations

PubMed Central

Nicola, Wilten; Clopath, Claudia

2018-01-01

Cortical oscillations are thought to be involved in many cognitive functions and processes. Several mechanisms have been proposed to regulate oscillations. One prominent but understudied mechanism is gap junction coupling. Gap junctions are ubiquitous in cortex between GABAergic interneurons. Moreover, recent experiments indicate their strength can be modified in an activity-dependent manner, similar to chemical synapses. We hypothesized that activity-dependent gap junction plasticity acts as a mechanism to regulate oscillations in the cortex. We developed a computational model of gap junction plasticity in a recurrent cortical network based on recent experimental findings. We showed that gap junction plasticity can serve as a homeostatic mechanism for oscillations by maintaining a tight balance between two network states: asynchronous irregular activity and synchronized oscillations. This homeostatic mechanism allows for robust communication between neuronal assemblies through two different mechanisms: transient oscillations and frequency modulation. This implies a direct functional role for gap junction plasticity in information transmission in cortex. PMID:29529034

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

PubMed Central

Zhang, Kechen

2016-01-01

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

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.

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

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

PubMed

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

2016-01-13

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. 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. Copyright © 2016 Booth, Witton et al.

Theta frequency decreases throughout the hippocampal formation in a focal epilepsy model.

PubMed

Kilias, Antje; Häussler, Ute; Heining, Katharina; Froriep, Ulrich P; Haas, Carola A; Egert, Ulrich

2018-06-01

Mesial temporal lobe epilepsy is characterized by focal, recurrent spontaneous seizures, sclerosis and granule cell dispersion (GCD) in the hippocampal formation. Changes in theta rhythm properties have been correlated with the severity of hippocampal restructuring and were suggested as a cause of memory deficits accompanying epilepsy. For severe sclerosis, it has even been questioned whether theta band oscillations persist. We asked how theta oscillations change with graded restructuring along the longitudinal hippocampal axis and whether these changes correlate with the overall severity of temporal lobe epilepsy. We recorded local field potentials in the medial entorhinal cortex and along the septo-temporal axis of the dentate gyrus at sites with different degrees of GCD in freely behaving epileptic mice. Theta frequency was decreased at all recording positions throughout the dentate gyrus and in the medial entorhinal cortex, irrespective of the extent of GCD or the rate of severe epileptic events. The frequency reduction by up to 1.7 Hz, corresponding to 1/3 octaves within the theta range, was present during rest, exploration and running. Despite the frequency reduction, theta oscillations remained coherent across the hippocampal formation and were modulated by running speed as in controls. The reduction in theta frequency thus is likely not a consequence of the local restructuring but rather a global phenomenon affecting the hippocampal formation as a whole. © 2018 Wiley Periodicals, Inc.

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

NASA Astrophysics Data System (ADS)

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

2016-02-01

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

Complex Dynamical Networks Constructed with Fully Controllable Nonlinear Nanomechanical Oscillators.

PubMed

Fon, Warren; Matheny, Matthew H; Li, Jarvis; Krayzman, Lev; Cross, Michael C; D'Souza, Raissa M; Crutchfield, James P; Roukes, Michael L

2017-10-11

Control of the global parameters of complex networks has been explored experimentally in a variety of contexts. Yet, the more difficult prospect of realizing arbitrary network architectures, especially analog physical networks that provide dynamical control of individual nodes and edges, has remained elusive. Given the vast hierarchy of time scales involved, it also proves challenging to measure a complex network's full internal dynamics. These span from the fastest nodal dynamics to very slow epochs over which emergent global phenomena, including network synchronization and the manifestation of exotic steady states, eventually emerge. Here, we demonstrate an experimental system that satisfies these requirements. It is based upon modular, fully controllable, nonlinear radio frequency nanomechanical oscillators, designed to form the nodes of complex dynamical networks with edges of arbitrary topology. The dynamics of these oscillators and their surrounding network are analog and continuous-valued and can be fully interrogated in real time. They comprise a piezoelectric nanomechanical membrane resonator, which serves as the frequency-determining element within an electrical feedback circuit. This embodiment permits network interconnections entirely within the electrical domain and provides unprecedented node and edge control over a vast region of parameter space. Continuous measurement of the instantaneous amplitudes and phases of every constituent oscillator node are enabled, yielding full and detailed network data without reliance upon statistical quantities. We demonstrate the operation of this platform through the real-time capture of the dynamics of a three-node ring network as it evolves from the uncoupled state to full synchronization.

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

PubMed

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

2017-02-01

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

Chimera states in two-dimensional networks of locally coupled oscillators

NASA Astrophysics Data System (ADS)

Kundu, Srilena; Majhi, Soumen; Bera, Bidesh K.; Ghosh, Dibakar; Lakshmanan, M.

2018-02-01

Chimera state is defined as a mixed type of collective state in which synchronized and desynchronized subpopulations of a network of coupled oscillators coexist and the appearance of such anomalous behavior has strong connection to diverse neuronal developments. Most of the previous studies on chimera states are not extensively done in two-dimensional ensembles of coupled oscillators by taking neuronal systems with nonlinear coupling function into account while such ensembles of oscillators are more realistic from a neurobiological point of view. In this paper, we report the emergence and existence of chimera states by considering locally coupled two-dimensional networks of identical oscillators where each node is interacting through nonlinear coupling function. This is in contrast with the existence of chimera states in two-dimensional nonlocally coupled oscillators with rectangular kernel in the coupling function. We find that the presence of nonlinearity in the coupling function plays a key role to produce chimera states in two-dimensional locally coupled oscillators. We analytically verify explicitly in the case of a network of coupled Stuart-Landau oscillators in two dimensions that the obtained results using Ott-Antonsen approach and our analytical finding very well matches with the numerical results. Next, we consider another type of important nonlinear coupling function which exists in neuronal systems, namely chemical synaptic function, through which the nearest-neighbor (locally coupled) neurons interact with each other. It is shown that such synaptic interacting function promotes the emergence of chimera states in two-dimensional lattices of locally coupled neuronal oscillators. In numerical simulations, we consider two paradigmatic neuronal oscillators, namely Hindmarsh-Rose neuron model and Rulkov map for each node which exhibit bursting dynamics. By associating various spatiotemporal behaviors and snapshots at particular times, we study the chimera

Chimera states in two-dimensional networks of locally coupled oscillators.

PubMed

Kundu, Srilena; Majhi, Soumen; Bera, Bidesh K; Ghosh, Dibakar; Lakshmanan, M

2018-02-01

Chimera state is defined as a mixed type of collective state in which synchronized and desynchronized subpopulations of a network of coupled oscillators coexist and the appearance of such anomalous behavior has strong connection to diverse neuronal developments. Most of the previous studies on chimera states are not extensively done in two-dimensional ensembles of coupled oscillators by taking neuronal systems with nonlinear coupling function into account while such ensembles of oscillators are more realistic from a neurobiological point of view. In this paper, we report the emergence and existence of chimera states by considering locally coupled two-dimensional networks of identical oscillators where each node is interacting through nonlinear coupling function. This is in contrast with the existence of chimera states in two-dimensional nonlocally coupled oscillators with rectangular kernel in the coupling function. We find that the presence of nonlinearity in the coupling function plays a key role to produce chimera states in two-dimensional locally coupled oscillators. We analytically verify explicitly in the case of a network of coupled Stuart-Landau oscillators in two dimensions that the obtained results using Ott-Antonsen approach and our analytical finding very well matches with the numerical results. Next, we consider another type of important nonlinear coupling function which exists in neuronal systems, namely chemical synaptic function, through which the nearest-neighbor (locally coupled) neurons interact with each other. It is shown that such synaptic interacting function promotes the emergence of chimera states in two-dimensional lattices of locally coupled neuronal oscillators. In numerical simulations, we consider two paradigmatic neuronal oscillators, namely Hindmarsh-Rose neuron model and Rulkov map for each node which exhibit bursting dynamics. By associating various spatiotemporal behaviors and snapshots at particular times, we study the chimera

Phase matters: responding to and learning about peripheral stimuli depends on hippocampal θ phase at stimulus onset

PubMed Central

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

2015-01-01

Hippocampal θ (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 θ oscillation on hippocampal responses to a neutral conditioned stimulus (CS) and subsequent learning of classical trace eyeblink conditioning in adult rabbits. High-amplitude, regular hippocampal θ-band responses (that predict good learning) were elicited by the CS when it was timed to commence at the fissure θ trough (Trough group). Regardless, learning in this group was not enhanced compared with a yoked control group, possibly due to a ceiling effect. However, when the CS was consistently presented to the peak of θ (Peak group), hippocampal θ-band responding was less organized and learning was retarded. In well-trained animals, the hippocampal θ phase at CS onset no longer affected performance of the learned response, suggesting a time-limited role for hippocampal processing in learning. To our knowledge, this is the first study to demonstrate that timing a peripheral stimulus to a specific phase of the hippocampal θ cycle produces robust effects on the synchronization of neural responses and affects learning at the behavioral level. Our results support the notion that the phase of spontaneous hippocampal θ oscillation is a means of regulating the processing of information in the brain to a behaviorally relevant degree. PMID:25979993

PTEN Loss Increases the Connectivity of Fast Synaptic Motifs and Functional Connectivity in a Developing Hippocampal Network.

PubMed

Barrows, Caitlynn M; McCabe, Matthew P; Chen, Hongmei; Swann, John W; Weston, Matthew C

2017-09-06

Changes in synaptic strength and connectivity are thought to be a major mechanism through which many gene variants cause neurological disease. Hyperactivation of the PI3K-mTOR signaling network, via loss of function of repressors such as PTEN, causes epilepsy in humans and animal models, and altered mTOR signaling may contribute to a broad range of neurological diseases. Changes in synaptic transmission have been reported in animal models of PTEN loss; however, the full extent of these changes, and their effect on network function, is still unknown. To better understand the scope of these changes, we recorded from pairs of mouse hippocampal neurons cultured in a two-neuron microcircuit configuration that allowed us to characterize all four major connection types within the hippocampus. Loss of PTEN caused changes in excitatory and inhibitory connectivity, and these changes were postsynaptic, presynaptic, and transynaptic, suggesting that disruption of PTEN has the potential to affect most connection types in the hippocampal circuit. Given the complexity of the changes at the synaptic level, we measured changes in network behavior after deleting Pten from neurons in an organotypic hippocampal slice network. Slices containing Pten -deleted neurons showed increased recruitment of neurons into network bursts. Importantly, these changes were not confined to Pten -deleted neurons, but involved the entire network, suggesting that the extensive changes in synaptic connectivity rewire the entire network in such a way that promotes a widespread increase in functional connectivity. SIGNIFICANCE STATEMENT Homozygous deletion of the Pten gene in neuronal subpopulations in the mouse serves as a valuable model of epilepsy caused by mTOR hyperactivation. To better understand how gene deletions lead to altered neuronal activity, we investigated the synaptic and network effects that occur 1 week after Pten deletion. PTEN loss increased the connectivity of all four types of

Synchronization in Random Pulse Oscillator Networks

NASA Astrophysics Data System (ADS)

Brown, Kevin; Hermundstad, Ann

Motivated by synchronization phenomena in neural systems, we study synchronization of random networks of coupled pulse oscillators. We begin by considering binomial random networks whose nodes have intrinsic linear dynamics. We quantify order in the network spiking dynamics using a new measure: the normalized Lev-Zimpel complexity (LZC) of the nodes' spike trains. Starting from a globally-synchronized state, we see two broad classes of behaviors. In one (''temporally random''), the LZC is high and nodes spike independently with no coherent pattern. In another (''temporally regular''), the network does not globally synchronize but instead forms coherent, repeating population firing patterns with low LZC. No topological feature of the network reliably predicts whether an individual network will show temporally random or regular behavior; however, we find evidence that degree heterogeneity in binomial networks has a strong effect on the resulting state. To confirm these findings, we generate random networks with independently-adjustable degree mean and variance. We find that the likelihood of temporally-random behavior increases as degree variance increases. Our results indicate the subtle and complex relationship between network structure and dynamics.

Hippocampal theta, gamma, and theta-gamma coupling: effects of aging, environmental change, and cholinergic activation

PubMed Central

Jacobson, Tara K.; Howe, Matthew D.; Schmidt, Brandy; Hinman, James R.; Escabí, Monty A.

2013-01-01

Hippocampal theta and gamma oscillations coordinate the timing of multiple inputs to hippocampal neurons and have been linked to information processing and the dynamics of encoding and retrieval. One major influence on hippocampal rhythmicity is from cholinergic afferents. In both humans and rodents, aging is linked to impairments in hippocampus-dependent function along with degradation of cholinergic function. Cholinomimetics can reverse some age-related memory impairments and modulate oscillations in the hippocampus. Therefore, one would expect corresponding changes in these oscillations and possible rescue with the cholinomimetic physostigmine. Hippocampal activity was recorded while animals explored a familiar or a novel maze configuration. Reexposure to a familiar situation resulted in minimal aging effects or changes in theta or gamma oscillations. In contrast, exploration of a novel maze configuration increased theta power; this was greater in adult than old animals, although the deficit was reversed with physostigmine. In contrast to the theta results, the effects of novelty, age, and/or physostigmine on gamma were relatively weak. Unrelated to the behavioral situation were an age-related decrease in the degree of theta-gamma coupling and the fact that physostigmine lowered the frequency of theta in both adult and old animals. The results indicate that age-related changes in gamma and theta modulation of gamma, while reflecting aging changes in hippocampal circuitry, seem less related to aging changes in information processing. In contrast, the data support a role for theta and the cholinergic system in encoding and that hippocampal aging is related to impaired encoding of new information. PMID:23303862

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.

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

NASA Astrophysics Data System (ADS)

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

2017-03-01

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

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

PubMed Central

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

2017-01-01

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

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

PubMed

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

2017-03-21

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

Gamma oscillations in a nonlinear regime: a minimal model approach using heterogeneous integrate-and-fire networks.

PubMed

Bathellier, Brice; Carleton, Alan; Gerstner, Wulfram

2008-12-01

Fast oscillations and in particular gamma-band oscillation (20-80 Hz) are commonly observed during brain function and are at the center of several neural processing theories. In many cases, mathematical analysis of fast oscillations in neural networks has been focused on the transition between irregular and oscillatory firing viewed as an instability of the asynchronous activity. But in fact, brain slice experiments as well as detailed simulations of biological neural networks have produced a large corpus of results concerning the properties of fully developed oscillations that are far from this transition point. We propose here a mathematical approach to deal with nonlinear oscillations in a network of heterogeneous or noisy integrate-and-fire neurons connected by strong inhibition. This approach involves limited mathematical complexity and gives a good sense of the oscillation mechanism, making it an interesting tool to understand fast rhythmic activity in simulated or biological neural networks. A surprising result of our approach is that under some conditions, a change of the strength of inhibition only weakly influences the period of the oscillation. This is in contrast to standard theoretical and experimental models of interneuron network gamma oscillations (ING), where frequency tightly depends on inhibition strength, but it is similar to observations made in some in vitro preparations in the hippocampus and the olfactory bulb and in some detailed network models. This result is explained by the phenomenon of suppression that is known to occur in strongly coupled oscillating inhibitory networks but had not yet been related to the behavior of oscillation frequency.

Distinct hippocampal functional networks revealed by tractography-based parcellation.

PubMed

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

2016-07-01

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

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.

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

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.

Chaos in generically coupled phase oscillator networks with nonpairwise interactions.

PubMed

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.

Chaos in generically coupled phase oscillator networks with nonpairwise interactions

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

Bick, Christian; Ashwin, Peter; Rodrigues, Ana

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 dynamicsmore » 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.« less

Glutamatergic drive along the septo-temporal axis of hippocampus boosts prelimbic oscillations in the neonatal mouse

PubMed Central

Ahlbeck, Joachim; Song, Lingzhen; Chini, Mattia; Bitzenhofer, Sebastian H

2018-01-01

The long-range coupling within prefrontal-hippocampal networks that account for cognitive performance emerges early in life. The discontinuous hippocampal theta bursts have been proposed to drive the generation of neonatal prefrontal oscillations, yet the cellular substrate of these early interactions is still unresolved. Here, we selectively target optogenetic manipulation of glutamatergic projection neurons in the CA1 area of either dorsal or intermediate/ventral hippocampus at neonatal age to elucidate their contribution to the emergence of prefrontal oscillatory entrainment. We show that despite stronger theta and ripples power in dorsal hippocampus, the prefrontal cortex is mainly coupled with intermediate/ventral hippocampus by phase-locking of neuronal firing via dense direct axonal projections. Theta band-confined activation by light of pyramidal neurons in intermediate/ventral but not dorsal CA1 that were transfected by in utero electroporation with high-efficiency channelrhodopsin boosts prefrontal oscillations. Our data causally elucidate the cellular origin of the long-range coupling in the developing brain. PMID:29631696

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

PubMed

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

2017-09-19

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

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.

Robust Weak Chimeras in Oscillator Networks with Delayed Linear and Quadratic Interactions

NASA Astrophysics Data System (ADS)

Bick, Christian; Sebek, Michael; Kiss, István Z.

2017-10-01

We present an approach to generate chimera dynamics (localized frequency synchrony) in oscillator networks with two populations of (at least) two elements using a general method based on a delayed interaction with linear and quadratic terms. The coupling design yields robust chimeras through a phase-model-based design of the delay and the ratio of linear and quadratic components of the interactions. We demonstrate the method in the Brusselator model and experiments with electrochemical oscillators. The technique opens the way to directly bridge chimera dynamics in phase models and real-world oscillator networks.

Reconfiguration of a Multi-oscillator Network by Light in the Drosophila Circadian Clock.

PubMed

Chatterjee, Abhishek; Lamaze, Angélique; De, Joydeep; Mena, Wilson; Chélot, Elisabeth; Martin, Béatrice; Hardin, Paul; Kadener, Sebastian; Emery, Patrick; Rouyer, François

2018-06-07

The brain clock that drives circadian rhythms of locomotor activity relies on a multi-oscillator neuronal network. In addition to synchronizing the clock with day-night cycles, light also reformats the clock-driven daily activity pattern. How changes in lighting conditions modify the contribution of the different oscillators to remodel the daily activity pattern remains largely unknown. Our data in Drosophila indicate that light readjusts the interactions between oscillators through two different modes. We show that a morning s-LNv > DN1p circuit works in series, whereas two parallel evening circuits are contributed by LNds and other DN1ps. Based on the photic context, the master pacemaker in the s-LNv neurons swaps its enslaved partner-oscillator-LNd in the presence of light or DN1p in the absence of light-to always link up with the most influential phase-determining oscillator. When exposure to light further increases, the light-activated LNd pacemaker becomes independent by decoupling from the s-LNvs. The calibration of coupling by light is layered on a clock-independent network interaction wherein light upregulates the expression of the PDF neuropeptide in the s-LNvs, which inhibits the behavioral output of the DN1p evening oscillator. Thus, light modifies inter-oscillator coupling and clock-independent output-gating to achieve flexibility in the network. It is likely that the light-induced changes in the Drosophila brain circadian network could reveal general principles of adapting to varying environmental cues in any neuronal multi-oscillator system. Copyright © 2018 Elsevier Ltd. All rights reserved.

Human Hippocampal Dynamics during Response Conflict.

PubMed

Oehrn, Carina R; Baumann, Conrad; Fell, Juergen; Lee, Hweeling; Kessler, Henrik; Habel, Ute; Hanslmayr, Simon; Axmacher, Nikolai

2015-08-31

Besides its relevance for declarative memory functions, hippocampal activation has been observed during disambiguation of uncertainty and conflict. Uncertainty and conflict may arise on various levels. On the perceptual level, the hippocampus has been associated with signaling of contextual deviance and disambiguation of similar items (i.e., pattern separation). Furthermore, conflicts can occur on the response level. Animal experiments showed a role of the hippocampus for inhibition of prevailing response tendencies and suppression of automatic stimulus-response mappings, potentially related to increased theta oscillations (3-8 Hz). In humans, a recent fMRI study demonstrated hippocampal involvement in approach-avoidance conflicts. However, the more general significance of hippocampal activity for dealing with response conflicts also on a cognitive level is still unknown. Here, we investigated the role of the hippocampus for response conflict in the Stroop task by combining intracranial electroencephalography (iEEG) recordings from the hippocampus of epilepsy patients with region of interest-based fMRI in healthy participants. Both methods revealed converging evidence that the hippocampus is recruited in a regionally specific manner during response conflict. Moreover, our iEEG data show that this activation depends on theta oscillations and is relevant for successful response conflict resolution. Copyright © 2015 Elsevier Ltd. All rights reserved.

Sleep, Plasticity and Memory from Molecules to Whole-Brain Networks

PubMed Central

Abel, Ted; Havekes, Robbert; Saletin, Jared M.; Walker, Matthew P.

2014-01-01

Despite the ubiquity of sleep across phylogeny, its function remains elusive. In this review, we consider one compelling candidate: brain plasticity associated with memory processing. Focusing largely on hippocampus-dependent memory in rodents and humans, we describe molecular, cellular, network, whole-brain and behavioral evidence establishing a role for sleep both in preparation for initial memory encoding, and in the subsequent offline consolidation ofmemory. Sleep and sleep deprivation bidirectionally alter molecular signaling pathways that regulate synaptic strength and control plasticity-related gene transcription and protein translation. At the cellular level, sleep deprivation impairs cellular excitability necessary for inducing synaptic potentiation and accelerates the decay of long-lasting forms of synaptic plasticity. In contrast, NREM and REM sleep enhance previously induced synaptic potentiation, although synaptic de-potentiation during sleep has also been observed. Beyond single cell dynamics, large-scale cell ensembles express coordinated replay of prior learning-related firing patterns during subsequent sleep. This occurs in the hippocampus, in the cortex, and between the hippocampus and cortex, commonly in association with specific NREM sleep oscillations. At the whole-brain level, somewhat analogous learning-associated hippocampal (re)activation during NREM sleep has been reported in humans. Moreover, the same cortical NREM oscillations associated with replay in rodents also promote human hippocampal memory consolidation, and this process can be manipulated using exogenous reactivation cues during sleep. Mirroring molecular findings in rodents, specific NREM sleep oscillations before encoding refresh human hippocampal learning capacity, while deprivation of sleep conversely impairs subsequent hippocampal activity and associated encoding. Together, these cross-descriptive level findings demonstrate that the unique neurobiology of sleep exert

Causal relationships between neurons of the nucleus incertus and the hippocampal theta activity in the rat.

PubMed

Martínez-Bellver, Sergio; Cervera-Ferri, Ana; Luque-García, Aina; Martínez-Ricós, Joana; Valverde-Navarro, Alfonso; Bataller, Manuel; Guerrero, Juan; Teruel-Marti, Vicent

2017-03-01

The nucleus incertus is a key node of the brainstem circuitry involved in hippocampal theta rhythmicity. Synchronisation exists between the nucleus incertus and hippocampal activities during theta periods. By the Granger causality analysis, we demonstrated a directional information flow between theta rhythmical neurons in the nucleus incertus and the hippocampus in theta-on states. The electrical stimulation of the nucleus incertus is also able to evoke a phase reset of the hippocampal theta wave. Our data suggest that the nucleus incertus is a key node of theta generation and the modulation network. In recent years, a body of evidence has shown that the nucleus incertus (NI), in the dorsal tegmental pons, is a key node of the brainstem circuitry involved in hippocampal theta rhythmicity. Ascending reticular brainstem system activation evokes hippocampal theta rhythm with coupled neuronal activity in the NI. In a recent paper, we showed three populations of neurons in the NI with differential firing during hippocampal theta activation. The objective of this work was to better evaluate the causal relationship between the activity of NI neurons and the hippocampus during theta activation in order to further understand the role of the NI in the theta network. A Granger causality analysis was run to determine whether hippocampal theta activity with sensory-evoked theta depends on the neuronal activity of the NI, or vice versa. The analysis showed causal interdependence between the NI and the hippocampus during theta activity, whose directional flow depended on the different neuronal assemblies of the NI. Whereas type I and II NI neurons mainly acted as receptors of hippocampal information, type III neuronal activity was the predominant source of flow between the NI and the hippocampus in theta states. We further determined that the electrical activation of the NI was able to reset hippocampal waves with enhanced theta-band power, depending on the septal area

Bidirectional control of spike timing by GABA(A) receptor-mediated inhibition during theta oscillation in CA1 pyramidal neurons.

PubMed

Kwag, Jeehyun; Paulsen, Ole

2009-08-26

Precisely controlled spike times relative to theta-frequency network oscillations play an important role in hippocampal memory processing. Here we study how inhibitory synaptic input during theta oscillation contributes to the control of spike timing. Using whole-cell patch-clamp recordings from CA1 pyramidal cells in vitro with dynamic clamp to simulate theta-frequency oscillation (5 Hz), we show that gamma-aminobutyric acid-A (GABA(A)) receptor-mediated inhibitory postsynaptic potentials (IPSPs) can not only delay but also advance the postsynaptic spike depending on the timing of the inhibition relative to the oscillation. Spike time advancement with IPSP was abolished by the h-channel blocker ZD7288 (10 microM), suggesting that IPSPs can interact with intrinsic membrane conductances to yield bidirectional control of spike timing.

Complementary theta resonance filtering by two spatially segregated mechanisms in CA1 hippocampal pyramidal neurons.

PubMed

Hu, Hua; Vervaeke, Koen; Graham, Lyle J; Storm, Johan F

2009-11-18

Synaptic input to a neuron may undergo various filtering steps, both locally and during transmission to the soma. Using simultaneous whole-cell recordings from soma and apical dendrites from rat CA1 hippocampal pyramidal cells, and biophysically detailed modeling, we found two complementary resonance (bandpass) filters of subthreshold voltage signals. Both filters favor signals in the theta (3-12 Hz) frequency range, but have opposite location, direction, and voltage dependencies: (1) dendritic H-resonance, caused by h/HCN-channels, filters signals propagating from soma to dendrite when the membrane potential is close to rest; and (2) somatic M-resonance, caused by M/Kv7/KCNQ and persistent Na(+) (NaP) channels, filters signals propagating from dendrite to soma when the membrane potential approaches spike threshold. Hippocampal pyramidal cells participate in theta network oscillations during behavior, and we suggest that that these dual, polarized theta resonance mechanisms may convey voltage-dependent tuning of theta-mediated neural coding in the entorhinal/hippocampal system during locomotion, spatial navigation, memory, and sleep.

Disrupting neural activity related to awake-state sharp wave-ripple complexes prevents hippocampal learning.

PubMed

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

2012-01-01

Oscillations in hippocampal local-field potentials (LFPs) reflect the crucial involvement of the hippocampus in memory trace formation: theta (4-8 Hz) oscillations and ripples (~200 Hz) occurring during sharp waves are thought to mediate encoding and consolidation, respectively. During sharp wave-ripple complexes (SPW-Rs), hippocampal cell firing closely follows the pattern that took place during the initial experience, most likely reflecting replay of that event. Disrupting hippocampal ripples using electrical stimulation either during training in awake animals or during sleep after training retards spatial learning. Here, adult rabbits were trained in trace eyeblink conditioning, a hippocampus-dependent associative learning task. A bright light was presented to the animals during the inter-trial interval (ITI), when awake, either during SPW-Rs or irrespective of their neural state. Learning was particularly poor when the light was presented following SPW-Rs. While the light did not disrupt the ripple itself, it elicited a theta-band oscillation, a state that does not usually coincide with SPW-Rs. Thus, it seems that consolidation depends on neuronal activity within and beyond the hippocampus taking place immediately after, but by no means limited to, hippocampal SPW-Rs.

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

NASA Astrophysics Data System (ADS)

Leiser, Randolph J.; Rotstein, Horacio G.

2017-08-01

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

Reviving oscillations in coupled nonlinear oscillators.

PubMed

Zou, Wei; Senthilkumar, D V; Zhan, Meng; Kurths, Jürgen

2013-07-05

By introducing a processing delay in the coupling, we find that it can effectively annihilate the quenching of oscillation, amplitude death (AD), in a network of coupled oscillators by switching the stability of AD. It revives the oscillation in the AD regime to retain sustained rhythmic functioning of the networks, which is in sharp contrast to the propagation delay with the tendency to induce AD. This processing delay-induced phenomenon occurs both with and without the propagation delay. Further this effect is rather general from two coupled to networks of oscillators in all known scenarios that can exhibit AD, and it has a wide range of applications where sustained oscillations should be retained for proper functioning of the systems.

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.

Hippocampal functional connectivity and episodic memory in early childhood

PubMed Central

Riggins, Tracy; Geng, Fengji; Blankenship, Sarah L.; Redcay, Elizabeth

2016-01-01

Episodic memory relies on a distributed network of brain regions, with the hippocampus playing a critical and irreplaceable role. Few studies have examined how changes in this network contribute to episodic memory development early in life. The present addressed this gap by examining relations between hippocampal functional connectivity and episodic memory in 4-and 6-year-old children (n=40). Results revealed similar hippocampal functional connectivity between age groups, which included lateral temporal regions, precuneus, and multiple parietal and prefrontal regions, and functional specialization along the longitudinal axis. Despite these similarities, developmental differences were also observed. Specifically, 3 (of 4) regions within the hippocampal memory network were positively associated with episodic memory in 6-year-old children, but negatively associated with episodic memory in 4-year-old children. In contrast, all 3 regions outside the hippocampal memory network were negatively associated with episodic memory in older children, but positively associated with episodic memory in younger children. These interactions are interpreted within an interactive specialization framework and suggest the hippocampus becomes functionally integrated with cortical regions that are part of the hippocampal memory network in adults and functionally segregated from regions unrelated to memory in adults, both of which are associated with age-related improvements in episodic memory ability. PMID:26900967

Synchronous high-frequency oscillations in inhibitory-dominant network motifs consisting of three dentate gyrus-CA3 systems

NASA Astrophysics Data System (ADS)

Zhang, Liyuan; Fan, Denggui; Wang, Qingyun

2018-06-01

Studies on the structural-functional connectomes of the human brain have demonstrated the existence of synchronous firings in a specific brain network motif. In particular, synchronization of high-frequency oscillations (HFOs) has been observed in the experimental data sets of temporal lobe epilepsy (TLE). In addition, both clinical and experimental evidences have accumulated to demonstrate the effect of electrical stimulation on TLE, which, however, remains largely unexplored. In this work, we first employ our previously proposed dentate gyrus (DG)-CA3 network model to investigate the influence of an external electrical stimulus on the HFO transitions. The results indicate that the reinforcing stimulus can induce the HFO transitions of the DG-CA3 system from the gamma band to the fast ripples band. Along with that, the consistent oscillations of neurons within DG-CA3 can also be enhanced with the increasing of stimulus. Then, we expand into a simple motif of three coupled DG-CA3 systems in both the feedforward inhibition and feedback inhibition connections, to investigate the synchronous evolutions of HFOs by regulating both the stimulation strength and inhibitory function. It is shown that the comprehensive effects, which lead to band transition, are independent of the motif configurations. The enhanced external electrical stimulus weakens the synchronism and correlation of connected motifs. In contrast, we demonstrate that the increased inhibitory coupling could facilitate correlation to some extent. Overall, our work highlights the possible origin of synchronous HFOs of hippocampal motifs governed by external inputs and inhibitory connection, which might contribute to a better understanding of the interplay between synchronization dynamics and epileptic structure in the human brain.

The Influence of Neuronal Density and Maturation on Network Activity of Hippocampal Cell Cultures: A Methodological Study

PubMed Central

Menegon, Andrea; Ferrigno, Giancarlo; Pedrocchi, Alessandra

2013-01-01

It is known that cell density influences the maturation process of in vitro neuronal networks. Neuronal cultures plated with different cell densities differ in number of synapses per neuron and thus in single neuron synaptic transmission, which results in a density-dependent neuronal network activity. Although many authors provided detailed information about the effects of cell density on neuronal culture activity, a dedicated report of density and age influence on neuronal hippocampal culture activity has not yet been reported. Therefore, this work aims at providing reference data to researchers that set up an experimental study on hippocampal neuronal cultures, helping in planning and decoding the experiments. In this work, we analysed the effects of both neuronal density and culture age on functional attributes of maturing hippocampal cultures. We characterized the electrophysiological activity of neuronal cultures seeded at three different cell densities, recording their spontaneous electrical activity over maturation by means of MicroElectrode Arrays (MEAs). We had gather data from 86 independent hippocampal cultures to achieve solid statistic results, considering the high culture-to-culture variability. Network activity was evaluated in terms of simple spiking, burst and network burst features. We observed that electrical descriptors were characterized by a functional peak during maturation, followed by a stable phase (for sparse and medium density cultures) or by a decrease phase (for high dense neuronal cultures). Moreover, 900 cells/mm2 cultures showed characteristics suitable for long lasting experiments (e.g. chronic effect of drug treatments) while 1800 cells/mm2 cultures should be preferred for experiments that require intense electrical activity (e.g. to evaluate the effect of inhibitory molecules). Finally, cell cultures at 3600 cells/mm2 are more appropriate for experiments in which time saving is relevant (e.g. drug screenings). These results are

The influence of neuronal density and maturation on network activity of hippocampal cell cultures: a methodological study.

PubMed

Biffi, Emilia; Regalia, Giulia; Menegon, Andrea; Ferrigno, Giancarlo; Pedrocchi, Alessandra

2013-01-01

It is known that cell density influences the maturation process of in vitro neuronal networks. Neuronal cultures plated with different cell densities differ in number of synapses per neuron and thus in single neuron synaptic transmission, which results in a density-dependent neuronal network activity. Although many authors provided detailed information about the effects of cell density on neuronal culture activity, a dedicated report of density and age influence on neuronal hippocampal culture activity has not yet been reported. Therefore, this work aims at providing reference data to researchers that set up an experimental study on hippocampal neuronal cultures, helping in planning and decoding the experiments. In this work, we analysed the effects of both neuronal density and culture age on functional attributes of maturing hippocampal cultures. We characterized the electrophysiological activity of neuronal cultures seeded at three different cell densities, recording their spontaneous electrical activity over maturation by means of MicroElectrode Arrays (MEAs). We had gather data from 86 independent hippocampal cultures to achieve solid statistic results, considering the high culture-to-culture variability. Network activity was evaluated in terms of simple spiking, burst and network burst features. We observed that electrical descriptors were characterized by a functional peak during maturation, followed by a stable phase (for sparse and medium density cultures) or by a decrease phase (for high dense neuronal cultures). Moreover, 900 cells/mm(2) cultures showed characteristics suitable for long lasting experiments (e.g. chronic effect of drug treatments) while 1800 cells/mm(2) cultures should be preferred for experiments that require intense electrical activity (e.g. to evaluate the effect of inhibitory molecules). Finally, cell cultures at 3600 cells/mm(2) are more appropriate for experiments in which time saving is relevant (e.g. drug screenings). These results

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

NASA Astrophysics Data System (ADS)

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

2017-07-01

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

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

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

PubMed

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

2011-07-01

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

Enhanced oscillatory activity in the hippocampal-prefrontal network is related to short-term memory function after early-life seizures

PubMed Central

Kleen, Jonathan K.; Wu, Edie X.; Holmes, Gregory L.; Scott, Rod C.; Lenck-Santini, Pierre-Pascal

2011-01-01

Neurological insults during development are associated with later impairments in learning and memory. Although remedial training can help restore cognitive function, the neural mechanisms of this recovery in memory systems are largely unknown. To examine this issue we measured electrophysiological oscillatory activity in the hippocampus (both CA3 and CA1) and prefrontal cortex of adult rats that had experienced repeated seizures in the first weeks of life, while they were remedially trained on a delayed-nonmatch-to-sample memory task. Seizure-exposed rats showed initial difficulties learning the task but performed similar to control rats after extra training. Whole-session analyses illustrated enhanced theta power in all three structures while seizure rats learned response tasks prior to the memory task. Whilst performing the memory task, dynamic oscillation patterns revealed that prefrontal cortex theta power was increased among seizure-exposed rats. This enhancement appeared after the first memory training steps using short delays and plateaued at the most difficult steps which included both short and long delays. Further, seizure rats showed enhanced CA1-prefrontal theta coherence in correct trials compared to incorrect trials when long delays were imposed, suggesting increased hippocampal-prefrontal synchrony for the task in this group when memory demand was high. Seizure-exposed rats also showed heightened gamma power and coherence among all three structures during the trials. Our results demonstrate the first evidence of hippocampal-prefrontal enhancements following seizures in early development. Dynamic compensatory changes in this network and interconnected circuits may underpin cognitive rehabilitation following other neurological insults to higher cognitive systems. PMID:22031886

Tuning the synchronization of a network of weakly coupled self-oscillating gels via capacitors.

PubMed

Fang, Yan; Yashin, Victor V; Dickerson, Samuel J; Balazs, Anna C

2018-05-01

We consider a network of coupled oscillating units, where each unit comprises a self-oscillating polymer gel undergoing the Belousov-Zhabotinsky (BZ) reaction and an overlaying piezoelectric (PZ) cantilever. Through chemo-mechano-electrical coupling, the oscillations of the networked BZ-PZ units achieve in-phase or anti-phase synchronization, enabling, for example, the storage of information within the system. Herein, we develop numerical and computational models to show that the introduction of capacitors into the BZ-PZ system enhances the dynamical behavior of the oscillating network by yielding additional stable synchronization modes. We specifically show that the capacitors lead to a redistribution of charge in the system and alteration of the force that the PZ cantilevers apply to the underlying gel. Hence, the capacitors modify the strength of the coupling between the oscillators in the network. We utilize a linear stability analysis to determine the phase behavior of BZ-PZ networks encompassing different capacitances, force polarities, and number of units and then verify our findings with numerical simulations. Thus, through analytical calculations and numerical simulations, we determine the impact of the capacitors on the existence of the synchronization modes, their stability, and the rate of synchronization within these complex dynamical systems. The findings from our study can be used to design robotic materials that harness the materials' intrinsic, responsive properties to perform such functions as sensing, actuation, and information storage.

Tuning the synchronization of a network of weakly coupled self-oscillating gels via capacitors

NASA Astrophysics Data System (ADS)

Fang, Yan; Yashin, Victor V.; Dickerson, Samuel J.; Balazs, Anna C.

2018-05-01

We consider a network of coupled oscillating units, where each unit comprises a self-oscillating polymer gel undergoing the Belousov-Zhabotinsky (BZ) reaction and an overlaying piezoelectric (PZ) cantilever. Through chemo-mechano-electrical coupling, the oscillations of the networked BZ-PZ units achieve in-phase or anti-phase synchronization, enabling, for example, the storage of information within the system. Herein, we develop numerical and computational models to show that the introduction of capacitors into the BZ-PZ system enhances the dynamical behavior of the oscillating network by yielding additional stable synchronization modes. We specifically show that the capacitors lead to a redistribution of charge in the system and alteration of the force that the PZ cantilevers apply to the underlying gel. Hence, the capacitors modify the strength of the coupling between the oscillators in the network. We utilize a linear stability analysis to determine the phase behavior of BZ-PZ networks encompassing different capacitances, force polarities, and number of units and then verify our findings with numerical simulations. Thus, through analytical calculations and numerical simulations, we determine the impact of the capacitors on the existence of the synchronization modes, their stability, and the rate of synchronization within these complex dynamical systems. The findings from our study can be used to design robotic materials that harness the materials' intrinsic, responsive properties to perform such functions as sensing, actuation, and information storage.

Regular theta-firing neurons in the nucleus incertus during sustained hippocampal activation.

PubMed

Martínez-Bellver, Sergio; Cervera-Ferri, Ana; Martínez-Ricós, Joana; Ruiz-Torner, Amparo; Luque-Garcia, Aina; Luque-Martinez, Aina; Blasco-Serra, Arantxa; Guerrero-Martínez, Juan; Bataller-Mompeán, Manuel; Teruel-Martí, Vicent

2015-04-01

This paper describes the existence of theta-coupled neuronal activity in the nucleus incertus (NI). Theta rhythm is relevant for cognitive processes such as spatial navigation and memory processing, and can be recorded in a number of structures related to the hippocampal activation including the NI. Strong evidence supports the role of this tegmental nucleus in neural circuits integrating behavioural activation with the hippocampal theta rhythm. Theta oscillations have been recorded in the local field potential of the NI, highly coupled to the hippocampal waves, although no rhythmical activity has been reported in neurons of this nucleus. The present work analyses the neuronal activity in the NI in conditions leading to sustained hippocampal theta in the urethane-anaesthetised rat, in order to test whether such activation elicits a differential firing pattern. Wavelet analysis has been used to better define the neuronal activity already described in the nucleus, i.e., non-rhythmical neurons firing at theta frequency (type I neurons) and fast-firing rhythmical neurons (type II). However, the most remarkable finding was that sustained stimulation activated regular-theta neurons (type III), which were almost silent in baseline conditions and have not previously been reported. Thus, we describe the electrophysiological properties of type III neurons, focusing on their coupling to the hippocampal theta. Their spike rate, regularity and phase locking to the oscillations increased at the beginning of the stimulation, suggesting a role in the activation or reset of the oscillation. Further research is needed to address the specific contribution of these neurons to the entire circuit. © 2015 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

Hippocampal functional connectivity and episodic memory in early childhood.

PubMed

Riggins, Tracy; Geng, Fengji; Blankenship, Sarah L; Redcay, Elizabeth

2016-06-01

Episodic memory relies on a distributed network of brain regions, with the hippocampus playing a critical and irreplaceable role. Few studies have examined how changes in this network contribute to episodic memory development early in life. The present addressed this gap by examining relations between hippocampal functional connectivity and episodic memory in 4- and 6-year-old children (n=40). Results revealed similar hippocampal functional connectivity between age groups, which included lateral temporal regions, precuneus, and multiple parietal and prefrontal regions, and functional specialization along the longitudinal axis. Despite these similarities, developmental differences were also observed. Specifically, 3 (of 4) regions within the hippocampal memory network were positively associated with episodic memory in 6-year-old children, but negatively associated with episodic memory in 4-year-old children. In contrast, all 3 regions outside the hippocampal memory network were negatively associated with episodic memory in older children, but positively associated with episodic memory in younger children. These interactions are interpreted within an interactive specialization framework and suggest the hippocampus becomes functionally integrated with cortical regions that are part of the hippocampal memory network in adults and functionally segregated from regions unrelated to memory in adults, both of which are associated with age-related improvements in episodic memory ability. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Explosive death of conjugate coupled Van der Pol oscillators on networks

NASA Astrophysics Data System (ADS)

Zhao, Nannan; Sun, Zhongkui; Yang, Xiaoli; Xu, Wei

2018-06-01

Explosive death phenomenon has been gradually gaining attention of researchers due to the research boom of explosive synchronization, and it has been observed recently for the identical or nonidentical coupled systems in all-to-all network. In this work, we investigate the emergence of explosive death in networked Van der Pol (VdP) oscillators with conjugate variables coupling. It is demonstrated that the network structures play a crucial role in identifying the types of explosive death behaviors. We also observe that the damping coefficient of the VdP system not only can determine whether the explosive death state is generated but also can adjust the forward transition point. We further show that the backward transition point is independent of the network topologies and the damping coefficient, which is well confirmed by theoretical analysis. Our results reveal the generality of explosive death phenomenon in different network topologies and are propitious to promote a better comprehension for the oscillation quenching behaviors.

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.

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

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

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

Entraining the topology and the dynamics of a network of phase oscillators

NASA Astrophysics Data System (ADS)

Sendiña-Nadal, I.; Leyva, I.; Buldú, J. M.; Almendral, J. A.; Boccaletti, S.

2009-04-01

We show that the topology and dynamics of a network of unsynchronized Kuramoto oscillators can be simultaneously controlled by means of a forcing mechanism which yields a phase locking of the oscillators to that of an external pacemaker in connection with the reshaping of the network’s degree distribution. The entrainment mechanism is based on the addition, at regular time intervals, of unidirectional links from oscillators that follow the dynamics of a pacemaker to oscillators in the pristine graph whose phases hold a prescribed phase relationship. Such a dynamically based rule in the attachment process leads to the emergence of a power-law shape in the final degree distribution of the graph whenever the network is entrained to the dynamics of the pacemaker. We show that the arousal of a scale-free distribution in connection with the success of the entrainment process is a robust feature, characterizing different networks’ initial configurations and parameters.

Non-invasive Investigation of Human Hippocampal Rhythms Using Magnetoencephalography: A Review.

PubMed

Pu, Yi; Cheyne, Douglas O; Cornwell, Brian R; Johnson, Blake W

2018-01-01

Hippocampal rhythms are believed to support crucial cognitive processes including memory, navigation, and language. Due to the location of the hippocampus deep in the brain, studying hippocampal rhythms using non-invasive magnetoencephalography (MEG) recordings has generally been assumed to be methodologically challenging. However, with the advent of whole-head MEG systems in the 1990s and development of advanced source localization techniques, simulation and empirical studies have provided evidence that human hippocampal signals can be sensed by MEG and reliably reconstructed by source localization algorithms. This paper systematically reviews simulation studies and empirical evidence of the current capacities and limitations of MEG "deep source imaging" of the human hippocampus. Overall, these studies confirm that MEG provides a unique avenue to investigate human hippocampal rhythms in cognition, and can bridge the gap between animal studies and human hippocampal research, as well as elucidate the functional role and the behavioral correlates of human hippocampal oscillations.

Non-invasive Investigation of Human Hippocampal Rhythms Using Magnetoencephalography: A Review

PubMed Central

Pu, Yi; Cheyne, Douglas O.; Cornwell, Brian R.; Johnson, Blake W.

2018-01-01

Hippocampal rhythms are believed to support crucial cognitive processes including memory, navigation, and language. Due to the location of the hippocampus deep in the brain, studying hippocampal rhythms using non-invasive magnetoencephalography (MEG) recordings has generally been assumed to be methodologically challenging. However, with the advent of whole-head MEG systems in the 1990s and development of advanced source localization techniques, simulation and empirical studies have provided evidence that human hippocampal signals can be sensed by MEG and reliably reconstructed by source localization algorithms. This paper systematically reviews simulation studies and empirical evidence of the current capacities and limitations of MEG “deep source imaging” of the human hippocampus. Overall, these studies confirm that MEG provides a unique avenue to investigate human hippocampal rhythms in cognition, and can bridge the gap between animal studies and human hippocampal research, as well as elucidate the functional role and the behavioral correlates of human hippocampal oscillations. PMID:29755314

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

Behavior-Dependent Activity and Synaptic Organization of Septo-hippocampal GABAergic Neurons Selectively Targeting the Hippocampal CA3 Area.

PubMed

Joshi, Abhilasha; Salib, Minas; Viney, Tim James; Dupret, David; Somogyi, Peter

2017-12-20

Rhythmic medial septal (MS) GABAergic input coordinates cortical theta oscillations. However, the rules of innervation of cortical cells and regions by diverse septal neurons are unknown. We report a specialized population of septal GABAergic neurons, the Teevra cells, selectively innervating the hippocampal CA3 area bypassing CA1, CA2, and the dentate gyrus. Parvalbumin-immunopositive Teevra cells show the highest rhythmicity among MS neurons and fire with short burst duration (median, 38 ms) preferentially at the trough of both CA1 theta and slow irregular oscillations, coincident with highest hippocampal excitability. Teevra cells synaptically target GABAergic axo-axonic and some CCK interneurons in restricted septo-temporal CA3 segments. The rhythmicity of their firing decreases from septal to temporal termination of individual axons. We hypothesize that Teevra neurons coordinate oscillatory activity across the septo-temporal axis, phasing the firing of specific CA3 interneurons, thereby contributing to the selection of pyramidal cell assemblies at the theta trough via disinhibition. VIDEO ABSTRACT. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Voluntary control of intracortical oscillations for reconfiguration of network activity

PubMed Central

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

2016-01-01

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

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.

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

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

PubMed Central

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

2010-01-01

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

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

PubMed Central

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

2016-01-01

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

Distinct Dendritic Arborization and In Vivo Firing Patterns of Parvalbumin-Expressing Basket Cells in the Hippocampal Area CA3

PubMed Central

Tukker, John J.; Lasztóczi, Bálint; Katona, Linda; Roberts, J. David B.; Pissadaki, Eleftheria K.; Dalezios, Yannis; Márton, László; Zhang, Limei; Klausberger, Thomas; Somogyi, Peter

2015-01-01

Hippocampal CA3 area generates temporally structured network activity such as sharp waves and gamma and theta oscillations. Parvalbumin-expressing basket cells, making GABAergic synapses onto cell bodies and proximal dendrites of pyramidal cells, control pyramidal cell activity and participate in network oscillations in slice preparations, but their roles in vivo remain to be tested. We have recorded the spike timing of parvalbumin-expressing basket cells in areas CA2/3 of anesthetized rats in relation to CA3 putative pyramidal cell firing and activity locally and in area CA1. During theta oscillations, CA2/3 basket cells fired on the same phase as putative pyramidal cells, but, surprisingly, significantly later than downstream CA1 basket cells. This indicates a distinct modulation of CA3 and CA1 pyramidal cells by basket cells, which receive different inputs. We observed unexpectedly large dendritic arborization of CA2/3 basket cells in stratum lacunosum moleculare (33% of length, 29% surface, and 24% synaptic input from a total of ~35,000), different from the dendritic arborizations of CA1 basket cells. Area CA2/3 basket cells fired phase locked to both CA2/3 and CA1 gamma oscillations, and increased firing during CA1 sharp waves, thus supporting the role of CA3 networks in the generation of gamma oscillations and sharp waves. However, during ripples associated with sharp waves, firing of CA2/3 basket cells was phase locked only to local but not CA1 ripples, suggesting the independent generation of fast oscillations by basket cells in CA1 and CA2/3. The distinct spike timing of basket cells during oscillations in CA1 and CA2/3 suggests differences in synaptic inputs paralleled by differences in dendritic arborizations. PMID:23595740

Human hippocampal theta power indicates movement onset and distance travelled

PubMed Central

Bird, Chris M.; Gollwitzer, Stephanie; Rodionov, Roman; Diehl, Beate; McEvoy, Andrew W.; Walker, Matthew C.; Burgess, Neil

2017-01-01

Theta frequency oscillations in the 6- to 10-Hz range dominate the rodent hippocampal local field potential during translational movement, suggesting that theta encodes self-motion. Increases in theta power have also been identified in the human hippocampus during both real and virtual movement but appear as transient bursts in distinct high- and low-frequency bands, and it is not yet clear how these bursts relate to the sustained oscillation observed in rodents. Here, we examine depth electrode recordings from the temporal lobe of 13 presurgical epilepsy patients performing a self-paced spatial memory task in a virtual environment. In contrast to previous studies, we focus on movement-onset periods that incorporate both initial acceleration and an immediately preceding stationary interval associated with prominent theta oscillations in the rodent hippocampal formation. We demonstrate that movement-onset periods are associated with a significant increase in both low (2–5 Hz)- and high (6–9 Hz)-frequency theta power in the human hippocampus. Similar increases in low- and high-frequency theta power are seen across lateral temporal lobe recording sites and persist throughout the remainder of movement in both regions. In addition, we show that movement-related theta power is greater both before and during longer paths, directly implicating human hippocampal theta in the encoding of translational movement. These findings strengthen the connection between studies of theta-band activity in rodents and humans and offer additional insight into the neural mechanisms of spatial navigation. PMID:29078334

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

PubMed

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

2016-12-24

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

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

A Larger Social Network Enhances Novel Object Location Memory and Reduces Hippocampal Microgliosis in Aged Mice.

PubMed

Smith, Bryon M; Yao, Xinyue; Chen, Kelly S; Kirby, Elizabeth D

2018-01-01

The mammalian hippocampus shows marked decline in function with aging across many species, including humans and laboratory rodent models. This decline frequently manifests in memory impairments that occur even in the absence of dementia pathology. In humans, a number of factors correlate with preserved hippocampal memory in aging, such as exercise, cognitive stimulation and number of social ties. While interventional studies and animal models clearly indicate that exercise and cognitive stimulation lead to hippocampal preservation, there is relatively little research on whether a decline in social ties leads to cognitive decline or vice versa. Even in animal studies of environmental enrichment in aging, the focus typically falls on physical enrichment such as a rotating cast of toys, rather than the role of social interactions. The present studies investigated the hypothesis that a greater number of social ties in aging mice would lead to improved hippocampal function. Aged, female C57/Bl6 mice were housed for 3 months in pairs or large groups (7 mice per cage). Group-housed mice showed greater novel object location memory and stronger preference for a spatial navigation strategy in the Barnes maze, though no difference in escape latency, compared to pair-housed mice. Group-housed mice did not differ from pair-housed mice in basal corticosterone levels or adult hippocampal neurogenesis. Group-housed mice did, however, show reduced numbers of Iba1/CD68+ microglia in the hippocampus. These findings suggest that group housing led to better memory function and reduced markers of neuroinflammation in aged mice. More broadly, they support a causative link between social ties and hippocampal function, suggesting that merely having a larger social network can positively influence the aging brain. Future research should address the molecular mechanisms by which a greater number of social ties alters hippocampal function.

A Larger Social Network Enhances Novel Object Location Memory and Reduces Hippocampal Microgliosis in Aged Mice

PubMed Central

Smith, Bryon M.; Yao, Xinyue; Chen, Kelly S.; Kirby, Elizabeth D.

2018-01-01

The mammalian hippocampus shows marked decline in function with aging across many species, including humans and laboratory rodent models. This decline frequently manifests in memory impairments that occur even in the absence of dementia pathology. In humans, a number of factors correlate with preserved hippocampal memory in aging, such as exercise, cognitive stimulation and number of social ties. While interventional studies and animal models clearly indicate that exercise and cognitive stimulation lead to hippocampal preservation, there is relatively little research on whether a decline in social ties leads to cognitive decline or vice versa. Even in animal studies of environmental enrichment in aging, the focus typically falls on physical enrichment such as a rotating cast of toys, rather than the role of social interactions. The present studies investigated the hypothesis that a greater number of social ties in aging mice would lead to improved hippocampal function. Aged, female C57/Bl6 mice were housed for 3 months in pairs or large groups (7 mice per cage). Group-housed mice showed greater novel object location memory and stronger preference for a spatial navigation strategy in the Barnes maze, though no difference in escape latency, compared to pair-housed mice. Group-housed mice did not differ from pair-housed mice in basal corticosterone levels or adult hippocampal neurogenesis. Group-housed mice did, however, show reduced numbers of Iba1/CD68+ microglia in the hippocampus. These findings suggest that group housing led to better memory function and reduced markers of neuroinflammation in aged mice. More broadly, they support a causative link between social ties and hippocampal function, suggesting that merely having a larger social network can positively influence the aging brain. Future research should address the molecular mechanisms by which a greater number of social ties alters hippocampal function. PMID:29904345

Oscillator Neural Network Retrieving Sparsely Coded Phase Patterns

NASA Astrophysics Data System (ADS)

Aoyagi, Toshio; Nomura, Masaki

1999-08-01

Little is known theoretically about the associative memory capabilities of neural networks in which information is encoded not only in the mean firing rate but also in the timing of firings. Particularly, in the case of sparsely coded patterns, it is biologically important to consider the timings of firings and to study how such consideration influences storage capacities and quality of recalled patterns. For this purpose, we propose a simple extended model of oscillator neural networks to allow for expression of a nonfiring state. Analyzing both equilibrium states and dynamical properties in recalling processes, we find that the system possesses good associative memory.

Multiplex Networks of Cortical and Hippocampal Neurons Revealed at Different Timescales

PubMed Central

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

2014-01-01

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

Hippocampal Atrophy Is Associated with Altered Hippocampus-Posterior Cingulate Cortex Connectivity in Mesial Temporal Lobe Epilepsy with Hippocampal Sclerosis.

PubMed

Shih, Y C; Tseng, C E; Lin, F-H; Liou, H H; Tseng, W Y I

2017-03-01

Unilateral mesial temporal lobe epilepsy and hippocampal sclerosis have structural and functional abnormalities in the mesial temporal regions. To gain insight into the pathophysiology of the epileptic network in mesial temporal lobe epilepsy with hippocampal sclerosis, we aimed to clarify the relationships between hippocampal atrophy and the altered connection between the hippocampus and the posterior cingulate cortex in patients with mesial temporal lobe epilepsy with hippocampal sclerosis. Fifteen patients with left mesial temporal lobe epilepsy with hippocampal sclerosis and 15 healthy controls were included in the study. Multicontrast MR imaging, including high-resolution T1WI, diffusion spectrum imaging, and resting-state fMRI, was performed to measure the hippocampal volume, structural connectivity of the inferior cingulum bundle, and intrinsic functional connectivity between the hippocampus and the posterior cingulate cortex, respectively. Compared with controls, patients had decreased left hippocampal volume (volume ratio of the hippocampus and controls, 0.366% ± 0.029%; patients, 0.277% ± 0.063%, corrected P = .002), structural connectivity of the bilateral inferior cingulum bundle (generalized fractional anisotropy, left: controls, 0.234 ± 0.020; patients, 0.193 ± 0.022, corrected P = .0001, right: controls, 0.226 ± 0.022; patients, 0.208 ± 0.017, corrected P = .047), and intrinsic functional connectivity between the left hippocampus and the left posterior cingulate cortex (averaged z-value: controls, 0.314 ± 0.152; patients, 0.166 ± 0.062). The left hippocampal volume correlated with structural connectivity positively (standardized β = 0.864, P = .001), but it had little correlation with intrinsic functional connectivity (standardized β = -0.329, P = .113). On the contralesional side, the hippocampal volume did not show any significant correlation with structural connectivity or intrinsic functional connectivity ( F 2,12 = 0.284, P = .757, R 2

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.

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.

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

PubMed Central

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

2012-01-01

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

Multisynchronization of Coupled Heterogeneous Genetic Oscillator Networks via Partial Impulsive Control.

PubMed

He, Ding-Xin; Ling, Guang; Guan, Zhi-Hong; Hu, Bin; Liao, Rui-Quan

2018-02-01

This paper focuses on the collective dynamics of multisynchronization among heterogeneous genetic oscillators under a partial impulsive control strategy. The coupled nonidentical genetic oscillators are modeled by differential equations with uncertainties. The definition of multisynchronization is proposed to describe some more general synchronization behaviors in the real. Considering that each genetic oscillator consists of a large number of biochemical molecules, we design a more manageable impulsive strategy for dynamic networks to achieve multisynchronization. Not all the molecules but only a small fraction of them in each genetic oscillator are controlled at each impulsive instant. Theoretical analysis of multisynchronization is carried out by the control theory approach, and a sufficient condition of partial impulsive controller for multisynchronization with given error bounds is established. At last, numerical simulations are exploited to demonstrate the effectiveness of our results.

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.

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.

Emergence of self-sustained oscillations in excitable Erdös-Rényi random networks.

PubMed

Qian, Yu

2014-09-01

We investigate the emergence of self-sustained oscillations in excitable Erdös-Rényi random networks (EERRNs). Interestingly, periodical self-sustained oscillations have been found at a moderate connection probability P. For smaller or larger P, the system evolves into a homogeneous rest state with distinct mechanisms. One-dimensional Winfree loops are discovered as the sources to maintain the oscillations. Moreover, by analyzing these oscillation sources, we propose two criteria to explain the spatiotemporal dynamics obtained in EERRNs. Finally, the two critical connection probabilities for which self-sustained oscillations can emerge are approximately predicted based on these two criteria.

Interplay of intrinsic and synaptic conductances in the generation of high-frequency oscillations in interneuronal networks with irregular spiking.

PubMed

Baroni, Fabiano; Burkitt, Anthony N; Grayden, David B

2014-05-01

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

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

High-Frequency Network Oscillations in Cerebellar Cortex

PubMed Central

Middleton, Steven J.; Racca, Claudia; Cunningham, Mark O.; Traub, Roger D.; Monyer, Hannah; Knöpfel, Thomas; Schofield, Ian S.; Jenkins, Alistair; Whittington, Miles A.

2016-01-01

SUMMARY Both cerebellum and neocortex receive input from the somatosensory system. Interaction between these regions has been proposed to underpin the correct selection and execution of motor commands, but it is not clear how such interactions occur. In neocortex, inputs give rise to population rhythms, providing a spatiotemporal coding strategy for inputs and consequent outputs. Here, we show that similar patterns of rhythm generation occur in cerebellum during nicotinic receptor subtype activation. Both gamma oscillations (30–80 Hz) and very fast oscillations (VFOs, 80–160 Hz) were generated by intrinsic cerebellar cortical circuitry in the absence of functional glutamatergic connections. As in neocortex, gamma rhythms were dependent on GABAA receptor-mediated inhibition, whereas VFOs required only nonsynaptically connected intercellular networks. The ability of cerebellar cortex to generate population rhythms within the same frequency bands as neocortex suggests that they act as a common spatiotemporal code within which corticocerebellar dialog may occur. PMID:18549787

Interaction of oscillations, and their suppression via deep brain stimulation, in a model of the cortico-basal ganglia network.

PubMed

Kang, Guiyeom; Lowery, Madeleine M

2013-03-01

Growing evidence suggests that synchronized neural oscillations in the cortico-basal ganglia network may play a critical role in the pathophysiology of Parkinson's disease. In this study, a new model of the closed loop network is used to explore the generation and interaction of network oscillations and their suppression through deep brain stimulation (DBS). Under simulated dopamine depletion conditions, increased gain through the hyperdirect pathway resulted in the interaction of neural oscillations at different frequencies in the cortex and subthalamic nucleus (STN), leading to the emergence of synchronized oscillations at a new intermediate frequency. Further increases in synaptic gain resulted in the cortex driving synchronous oscillatory activity throughout the network. When DBS was added to the model a progressive reduction in STN power at the tremor and beta frequencies was observed as the frequency of stimulation was increased, with resonance effects occurring for low frequency DBS (40 Hz) in agreement with experimental observations. The results provide new insights into the mechanisms by which synchronous oscillations can arise within the network and how DBS may suppress unwanted oscillatory activity.

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.

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

Numerical and analytical investigation of the chimera state excitation conditions in the Kuramoto-Sakaguchi oscillator network

NASA Astrophysics Data System (ADS)

Frolov, Nikita S.; Goremyko, Mikhail V.; Makarov, Vladimir V.; Maksimenko, Vladimir A.; Hramov, Alexander E.

2017-03-01

In this paper we study the conditions of chimera states excitation in ensemble of non-locally coupled Kuramoto-Sakaguchi (KS) oscillators. In the framework of current research we analyze the dynamics of the homogeneous network containing identical oscillators. We show the chimera state formation process is sensitive to the parameters of coupling kernel and to the KS network initial state. To perform the analysis we have used the Ott-Antonsen (OA) ansatz to consider the behavior of infinitely large KS network.

Minimum Winfree loop determines self-sustained oscillations in excitable Erdös-Rényi random networks.

PubMed

Qian, Yu; Cui, Xiaohua; Zheng, Zhigang

2017-07-18

The investigation of self-sustained oscillations in excitable complex networks is very important in understanding various activities in brain systems, among which the exploration of the key determinants of oscillations is a challenging task. In this paper, by investigating the influence of system parameters on self-sustained oscillations in excitable Erdös-Rényi random networks (EERRNs), the minimum Winfree loop (MWL) is revealed to be the key factor in determining the emergence of collective oscillations. Specifically, the one-to-one correspondence between the optimal connection probability (OCP) and the MWL length is exposed. Moreover, many important quantities such as the lower critical connection probability (LCCP), the OCP, and the upper critical connection probability (UCCP) are determined by the MWL. Most importantly, they can be approximately predicted by the network structure analysis, which have been verified in numerical simulations. Our results will be of great importance to help us in understanding the key factors in determining persistent activities in biological systems.

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

PubMed

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

2015-11-21

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

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.

Long-Lasting Increase of Corticosterone After Fear Memory Reactivation: Anxiolytic Effects and Network Activity Modulation in the Ventral Hippocampus

PubMed Central

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

2013-01-01

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. PMID:22968818

Thalamic Spindles Promote Memory Formation during Sleep through Triple Phase-Locking of Cortical, Thalamic, and Hippocampal Rhythms.

PubMed

Latchoumane, Charles-Francois V; Ngo, Hong-Viet V; Born, Jan; Shin, Hee-Sup

2017-07-19

While the interaction of the cardinal rhythms of non-rapid-eye-movement (NREM) sleep-the thalamo-cortical spindles, hippocampal ripples, and the cortical slow oscillations-is thought to be critical for memory consolidation during sleep, the role spindles play in this interaction is elusive. Combining optogenetics with a closed-loop stimulation approach in mice, we show here that only thalamic spindles induced in-phase with cortical slow oscillation up-states, but not out-of-phase-induced spindles, improve consolidation of hippocampus-dependent memory during sleep. Whereas optogenetically stimulated spindles were as efficient as spontaneous spindles in nesting hippocampal ripples within their excitable troughs, stimulation in-phase with the slow oscillation up-state increased spindle co-occurrence and frontal spindle-ripple co-occurrence, eventually resulting in increased triple coupling of slow oscillation-spindle-ripple events. In-phase optogenetic suppression of thalamic spindles impaired hippocampus-dependent memory. Our results suggest a causal role for thalamic sleep spindles in hippocampus-dependent memory consolidation, conveyed through triple coupling of slow oscillations, spindles, and ripples. Copyright © 2017 Elsevier Inc. All rights reserved.

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.

Network properties of interstitial cells of Cajal affect intestinal pacemaker activity and motor patterns, according to a mathematical model of weakly coupled oscillators.

PubMed

Wei, Ruihan; Parsons, Sean P; Huizinga, Jan D

2017-03-01

What is the central question of this study? What are the effects of interstitial cells of Cajal (ICC) network perturbations on intestinal pacemaker activity and motor patterns? What is the main finding and its importance? Two-dimensional modelling of the ICC pacemaker activity according to a phase model of weakly coupled oscillators showed that network properties (coupling strength between oscillators, frequency gradient and frequency noise) strongly influence pacemaker network activity and subsequent motor patterns. The model explains motor patterns observed in physiological conditions and provides predictions and testable hypotheses for effects of ICC loss and frequency modulation on the motor patterns. Interstitial cells of Cajal (ICC) are the pacemaker cells of gut motility and are associated with motility disorders. Interstitial cells of Cajal form a network, but the contributions of its network properties to gut physiology and dysfunction are poorly understood. We modelled an ICC network as a two-dimensional network of weakly coupled oscillators with a frequency gradient and showed changes over time in video and graphical formats. Model parameters were obtained from slow-wave-driven contraction patterns in the mouse intestine and pacemaker slow-wave activities from the cat intestine. Marked changes in propagating oscillation patterns (including changes from propagation to non-propagating) were observed by changing network parameters (coupling strength between oscillators, the frequency gradient and frequency noise), which affected synchronization, propagation velocity and occurrence of dislocations (termination of an oscillation). Complete uncoupling of a circumferential ring of oscillators caused the proximal and distal section to desynchronize, but complete synchronization was maintained with only a single oscillator connecting the sections with high enough coupling. The network of oscillators could withstand loss; even with 40% of oscillators lost randomly

Alterations of cortical GABA neurons and network oscillations in schizophrenia.

PubMed

Gonzalez-Burgos, Guillermo; Hashimoto, Takanori; Lewis, David A

2010-08-01

The hypothesis that alterations of cortical inhibitory gamma-aminobutyric acid (GABA) neurons are a central element in the pathology of schizophrenia has emerged from a series of postmortem studies. How such abnormalities may contribute to the clinical features of schizophrenia has been substantially informed by a convergence with basic neuroscience studies revealing complex details of GABA neuron function in the healthy brain. Importantly, activity of the parvalbumin-containing class of GABA neurons has been linked to the production of cortical network oscillations. Furthermore, growing knowledge supports the concept that gamma band oscillations (30-80 Hz) are an essential mechanism for cortical information transmission and processing. Herein we review recent studies further indicating that inhibition from parvalbumin-positive GABA neurons is necessary to produce gamma oscillations in cortical circuits; provide an update on postmortem studies documenting that deficits in the expression of glutamic acid decarboxylase67, which accounts for most GABA synthesis in the cortex, are widely observed in schizophrenia; and describe studies using novel, noninvasive approaches directly assessing potential relations between alterations in GABA, oscillations, and cognitive function in schizophrenia.

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

NASA Astrophysics Data System (ADS)

Nishimura, Joel

2015-01-01

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

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

PubMed Central

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

2016-01-01

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

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

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

PubMed

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

2015-08-01

This article is part of a Special Issue "Estradiol and cognition". Estradiol (E2) is locally synthesized within the hippocampus and the gonads. Rapid modulation of hippocampal synaptic plasticity by E2 is essential for synaptic regulation. The molecular mechanisms of modulation through the synaptic estrogen receptor (ER) and its downstream signaling, however, are largely unknown in the dentate gyrus (DG). We investigated the E2-induced modulation of dendritic spines in male adult rat hippocampal slices by imaging Lucifer Yellow-injected DG granule cells. Treatments with 1 nM E2 increased the density of spines by approximately 1.4-fold within 2h. Spine head diameter analysis showed that the density of middle-head spines (0.4-0.5 μm) was significantly increased. The E2-induced spine density increase was suppressed by blocking Erk MAPK, PKA, PKC and LIMK. These suppressive effects by kinase inhibitors are not non-specific ones because the GSK-3β antagonist did not inhibit E2-induced spine increase. The ER antagonist ICI 182,780 also blocked the E2-induced spine increase. Taken together, these results suggest that E2 rapidly increases the density of spines through kinase networks that are driven by synaptic ER. Copyright © 2015 Elsevier Inc. All rights reserved.

Generating macroscopic chaos in a network of globally coupled phase oscillators

PubMed Central

So, Paul; Barreto, Ernest

2011-01-01

We consider an infinite network of globally coupled phase oscillators in which the natural frequencies of the oscillators are drawn from a symmetric bimodal distribution. We demonstrate that macroscopic chaos can occur in this system when the coupling strength varies periodically in time. We identify period-doubling cascades to chaos, attractor crises, and horseshoe dynamics for the macroscopic mean field. Based on recent work that clarified the bifurcation structure of the static bimodal Kuramoto system, we qualitatively describe the mechanism for the generation of such complicated behavior in the time varying case. PMID:21974662

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

PubMed

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

2005-04-01

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

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

Stable amplitude chimera states in a network of locally coupled Stuart-Landau oscillators.

PubMed

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

2018-03-01

We investigate the occurrence of collective dynamical states such as transient amplitude chimera, stable amplitude chimera, and imperfect breathing chimera states in a locally coupled network of Stuart-Landau oscillators. In an imperfect breathing chimera state, the synchronized group of oscillators exhibits oscillations with large amplitudes, while the desynchronized group of oscillators oscillates with small amplitudes, and this behavior of coexistence of synchronized and desynchronized oscillations fluctuates with time. Then, we analyze the stability of the amplitude chimera states under various circumstances, including variations in system parameters and coupling strength, and perturbations in the initial states of the oscillators. For an increase in the value of the system parameter, namely, the nonisochronicity parameter, the transient chimera state becomes a stable chimera state for a sufficiently large value of coupling strength. In addition, we also analyze the stability of these states by perturbing the initial states of the oscillators. We find that while a small perturbation allows one to perturb a large number of oscillators resulting in a stable amplitude chimera state, a large perturbation allows one to perturb a small number of oscillators to get a stable amplitude chimera state. We also find the stability of the transient and stable amplitude chimera states and traveling wave states for an appropriate number of oscillators using Floquet theory. In addition, we also find the stability of the incoherent oscillation death states.

Stable amplitude chimera states in a network of locally coupled Stuart-Landau oscillators

NASA Astrophysics Data System (ADS)

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

2018-03-01

We investigate the occurrence of collective dynamical states such as transient amplitude chimera, stable amplitude chimera, and imperfect breathing chimera states in a locally coupled network of Stuart-Landau oscillators. In an imperfect breathing chimera state, the synchronized group of oscillators exhibits oscillations with large amplitudes, while the desynchronized group of oscillators oscillates with small amplitudes, and this behavior of coexistence of synchronized and desynchronized oscillations fluctuates with time. Then, we analyze the stability of the amplitude chimera states under various circumstances, including variations in system parameters and coupling strength, and perturbations in the initial states of the oscillators. For an increase in the value of the system parameter, namely, the nonisochronicity parameter, the transient chimera state becomes a stable chimera state for a sufficiently large value of coupling strength. In addition, we also analyze the stability of these states by perturbing the initial states of the oscillators. We find that while a small perturbation allows one to perturb a large number of oscillators resulting in a stable amplitude chimera state, a large perturbation allows one to perturb a small number of oscillators to get a stable amplitude chimera state. We also find the stability of the transient and stable amplitude chimera states and traveling wave states for an appropriate number of oscillators using Floquet theory. In addition, we also find the stability of the incoherent oscillation death states.

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

NASA Astrophysics Data System (ADS)

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

2017-08-01

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

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

PubMed Central

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

2016-01-01

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

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. Copyright © 2014 Elsevier B.V. All rights reserved.

The Lyapunov-Krasovskii theorem and a sufficient criterion for local stability of isochronal synchronization in networks of delay-coupled oscillators

NASA Astrophysics Data System (ADS)

Grzybowski, J. M. V.; Macau, E. E. N.; Yoneyama, T.

2017-05-01

This paper presents a self-contained framework for the stability assessment of isochronal synchronization in networks of chaotic and limit-cycle oscillators. The results were based on the Lyapunov-Krasovskii theorem and they establish a sufficient condition for local synchronization stability of as a function of the system and network parameters. With this in mind, a network of mutually delay-coupled oscillators subject to direct self-coupling is considered and then the resulting error equations are block-diagonalized for the purpose of studying their stability. These error equations are evaluated by means of analytical stability results derived from the Lyapunov-Krasovskii theorem. The proposed approach is shown to be a feasible option for the investigation of local stability of isochronal synchronization for a variety of oscillators coupled through linear functions of the state variables under a given undirected graph structure. This ultimately permits the systematic identification of stability regions within the high-dimensionality of the network parameter space. Examples of applications of the results to a number of networks of delay-coupled chaotic and limit-cycle oscillators are provided, such as Lorenz, Rössler, Cubic Chua's circuit, Van der Pol oscillator and the Hindmarsh-Rose neuron.

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

PubMed

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

2017-01-01

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

Resource-Competing Oscillator Network as a Model of Amoeba-Based Neurocomputer

NASA Astrophysics Data System (ADS)

Aono, Masashi; Hirata, Yoshito; Hara, Masahiko; Aihara, Kazuyuki

An amoeboid organism, Physarum, exhibits rich spatiotemporal oscillatory behavior and various computational capabilities. Previously, the authors created a recurrent neurocomputer incorporating the amoeba as a computing substrate to solve optimization problems. In this paper, considering the amoeba to be a network of oscillators coupled such that they compete for constant amounts of resources, we present a model of the amoeba-based neurocomputer. The model generates a number of oscillation modes and produces not only simple behavior to stabilize a single mode but also complex behavior to spontaneously switch among different modes, which reproduces well the experimentally observed behavior of the amoeba. To explore the significance of the complex behavior, we set a test problem used to compare computational performances of the oscillation modes. The problem is a kind of optimization problem of how to allocate a limited amount of resource to oscillators such that conflicts among them can be minimized. We show that the complex behavior enables to attain a wider variety of solutions to the problem and produces better performances compared with the simple behavior.

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.

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

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

PubMed Central

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

2005-01-01

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

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

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

Freitas, Celso, E-mail: cbnfreitas@gmail.com; Macau, Elbert, E-mail: elbert.macau@inpe.br; Pikovsky, Arkady, E-mail: pikovsky@uni-potsdam.de

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 fullmore » 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.« less

On synchronization in power-grids modelled as networks of second-order Kuramoto oscillators

NASA Astrophysics Data System (ADS)

Grzybowski, J. M. V.; Macau, E. E. N.; Yoneyama, T.

2016-11-01

This work concerns analytical results on the role of coupling strength in the phenomenon of onset of complete frequency locking in power-grids modelled as a network of second-order Kuramoto oscillators. Those results allow estimation of the coupling strength for the onset of complete frequency locking and to assess the features of network and oscillators that favor synchronization. The analytical results are evaluated using an order parameter defined as the normalized sum of absolute values of phase deviations of the oscillators over time. The investigation of the frequency synchronization within the subsets of the parameter space involved in the synchronization problem is also carried out. It is shown that the analytical results are in good agreement with those observed in the numerical simulations. In order to illustrate the methodology, a case study is presented, involving the Brazilian high-voltage transmission system under a load peak condition to study the effect of load on the syncronizability of the grid. The results show that both the load and the centralized generation might have concurred to the 2014 blackout.

Hippocampal coupling with cortical and subcortical structures in the context of memory consolidation.

PubMed

Skelin, Ivan; Kilianski, Scott; McNaughton, Bruce L

2018-04-13

Memory consolidation is a gradual process through which episodic memories become incorporated into long-term 'semantic' representations. It likely involves reactivation of neural activity encoding the recent experience during non-REM sleep. A critical prerequisite for memory consolidation is precise coordination of reactivation events between the hippocampus and cortical/subcortical structures, facilitated by the coupling of local field potential (LFP) oscillations (slow oscillations, sleep spindles and sharp wave/ripples) between these structures. We review the rapidly expanding literature on the qualitative and quantitative aspects of hippocampal oscillatory and neuronal coupling with cortical/subcortical structures in the context of memory reactivation. Reactivation in the hippocampus and cortical/subcortical structures is tightly coupled with sharp wave/ripples. Hippocampal-cortical/subcortical coupling is rich in dimensionality and this dimensionality is likely underestimated due to the limitations of the current methodology. Copyright © 2018 Elsevier Inc. All rights reserved.

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

PubMed Central

Mori, Hiroki; Okuyama, Yuji; Asada, Minoru

2017-01-01

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

Cortical networks dynamically emerge with the interplay of slow and fast oscillations for memory of a natural scene.

PubMed

Mizuhara, Hiroaki; Sato, Naoyuki; Yamaguchi, Yoko

2015-05-01

Neural oscillations are crucial for revealing dynamic cortical networks and for serving as a possible mechanism of inter-cortical communication, especially in association with mnemonic function. The interplay of the slow and fast oscillations might dynamically coordinate the mnemonic cortical circuits to rehearse stored items during working memory retention. We recorded simultaneous EEG-fMRI during a working memory task involving a natural scene to verify whether the cortical networks emerge with the neural oscillations for memory of the natural scene. The slow EEG power was enhanced in association with the better accuracy of working memory retention, and accompanied cortical activities in the mnemonic circuits for the natural scene. Fast oscillation showed a phase-amplitude coupling to the slow oscillation, and its power was tightly coupled with the cortical activities for representing the visual images of natural scenes. The mnemonic cortical circuit with the slow neural oscillations would rehearse the distributed natural scene representations with the fast oscillation for working memory retention. The coincidence of the natural scene representations could be obtained by the slow oscillation phase to create a coherent whole of the natural scene in the working memory. Copyright © 2015 Elsevier Inc. All rights reserved.

Chimera states in bipartite networks of FitzHugh-Nagumo oscillators

NASA Astrophysics Data System (ADS)

Wu, Zhi-Min; Cheng, Hong-Yan; Feng, Yuee; Li, Hai-Hong; Dai, Qiong-Lin; Yang, Jun-Zhong

2018-04-01

Chimera states consisting of spatially coherent and incoherent domains have been observed in different topologies such as rings, spheres, and complex networks. In this paper, we investigate bipartite networks of nonlocally coupled FitzHugh-Nagumo (FHN) oscillators in which the units are allocated evenly to two layers, and FHN units interact with each other only when they are in different layers. We report the existence of chimera states in bipartite networks. Owing to the interplay between chimera states in the two layers, many types of chimera states such as in-phase chimera states, antiphase chimera states, and out-of-phase chimera states are classified. Stability diagrams of several typical chimera states in the coupling strength-coupling radius plane, which show strong multistability of chimera states, are explored.

Hippocampal memory consolidation during sleep: a comparison of mammals and birds

PubMed Central

Rattenborg, Niels C.; Martinez-Gonzalez, Dolores; Roth, Timothy C.; Pravosudov, Vladimir V.

2010-01-01

The transition from wakefulness to sleep is marked by pronounced changes in brain activity. The brain rhythms that characterize the two main types of mammalian sleep, slow-wave sleep (SWS) and rapid eye movement (REM) sleep, are thought to be involved in the functions of sleep. In particular, recent theories suggest that the synchronous slow-oscillation of neocortical neuronal membrane potentials, the defining feature of SWS, is involved in processing information acquired during wakefulness. According to the Standard Model of memory consolidation, during wakefulness the hippocampus receives input from neocortical regions involved in the initial encoding of an experience and binds this information into a coherent memory trace that is then transferred to the neocortex during SWS where it is stored and integrated within preexisting memory traces. Evidence suggests that this process selectively involves direct connections from the hippocampus to the prefrontal cortex (PFC), a multimodal, high-order association region implicated in coordinating the storage and recall of remote memories in the neocortex. The slow-oscillation is thought to orchestrate the transfer of information from the hippocampus by temporally coupling hippocampal sharp-wave/ripples (SWRs) and thalamocortical spindles. SWRs are synchronous bursts of hippocampal activity, during which waking neuronal firing patterns are reactivated in the hippocampus and neocortex in a coordinated manner. Thalamocortical spindles are brief 7–14 Hz oscillations that may facilitate the encoding of information reactivated during SWRs. By temporally coupling the readout of information from the hippocampus with conditions conducive to encoding in the neocortex, the slow-oscillation is thought to mediate the transfer of information from the hippocampus to the neocortex. Although several lines of evidence are consistent with this function for mammalian SWS, it is unclear whether SWS serves a similar function in birds, the

Hippocampal memory consolidation during sleep: a comparison of mammals and birds.

PubMed

Rattenborg, Niels C; Martinez-Gonzalez, Dolores; Roth, Timothy C; Pravosudov, Vladimir V

2011-08-01

The transition from wakefulness to sleep is marked by pronounced changes in brain activity. The brain rhythms that characterize the two main types of mammalian sleep, slow-wave sleep (SWS) and rapid eye movement (REM) sleep, are thought to be involved in the functions of sleep. In particular, recent theories suggest that the synchronous slow-oscillation of neocortical neuronal membrane potentials, the defining feature of SWS, is involved in processing information acquired during wakefulness. According to the Standard Model of memory consolidation, during wakefulness the hippocampus receives input from neocortical regions involved in the initial encoding of an experience and binds this information into a coherent memory trace that is then transferred to the neocortex during SWS where it is stored and integrated within preexisting memory traces. Evidence suggests that this process selectively involves direct connections from the hippocampus to the prefrontal cortex (PFC), a multimodal, high-order association region implicated in coordinating the storage and recall of remote memories in the neocortex. The slow-oscillation is thought to orchestrate the transfer of information from the hippocampus by temporally coupling hippocampal sharp-wave/ripples (SWRs) and thalamocortical spindles. SWRs are synchronous bursts of hippocampal activity, during which waking neuronal firing patterns are reactivated in the hippocampus and neocortex in a coordinated manner. Thalamocortical spindles are brief 7-14 Hz oscillations that may facilitate the encoding of information reactivated during SWRs. By temporally coupling the readout of information from the hippocampus with conditions conducive to encoding in the neocortex, the slow-oscillation is thought to mediate the transfer of information from the hippocampus to the neocortex. Although several lines of evidence are consistent with this function for mammalian SWS, it is unclear whether SWS serves a similar function in birds, the only

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

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

PubMed

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. © 2013 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

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.

Learning-enhanced coupling between ripple oscillations in association cortices and hippocampus.

PubMed

Khodagholy, Dion; Gelinas, Jennifer N; Buzsáki, György

2017-10-20

Consolidation of declarative memories requires hippocampal-neocortical communication. Although experimental evidence supports the role of sharp-wave ripples in transferring hippocampal information to the neocortex, the exact cortical destinations and the physiological mechanisms of such transfer are not known. We used a conducting polymer-based conformable microelectrode array (NeuroGrid) to record local field potentials and neural spiking across the dorsal cortical surface of the rat brain, combined with silicon probe recordings in the hippocampus, to identify candidate physiological patterns. Parietal, midline, and prefrontal, but not primary cortical areas, displayed localized ripple (100 to 150 hertz) oscillations during sleep, concurrent with hippocampal ripples. Coupling between hippocampal and neocortical ripples was strengthened during sleep following learning. These findings suggest that ripple-ripple coupling supports hippocampal-association cortical transfer of memory traces. Copyright © 2017 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

Fast global oscillations in networks of integrate-and-fire neurons with low firing rates.

PubMed

Brunel, N; Hakim, V

1999-10-01

We study analytically the dynamics of a network of sparsely connected inhibitory integrate-and-fire neurons in a regime where individual neurons emit spikes irregularly and at a low rate. In the limit when the number of neurons --> infinity, the network exhibits a sharp transition between a stationary and an oscillatory global activity regime where neurons are weakly synchronized. The activity becomes oscillatory when the inhibitory feedback is strong enough. The period of the global oscillation is found to be mainly controlled by synaptic times but depends also on the characteristics of the external input. In large but finite networks, the analysis shows that global oscillations of finite coherence time generically exist both above and below the critical inhibition threshold. Their characteristics are determined as functions of systems parameters in these two different regions. The results are found to be in good agreement with numerical simulations.

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.

Hydrodynamically induced oscillations and traffic dynamics in 1D microfludic networks

NASA Astrophysics Data System (ADS)

Bartolo, Denis; Jeanneret, Raphael

2011-03-01

We report on the traffic dynamics of particles driven through a minimal microfluidic network. Even in the minimal network consisting in a single loop, the traffic dynamics has proven to yield complex temporal patterns, including periodic, multi-periodic or chaotic sequences. This complex dynamics arises from the strongly nonlinear hydrodynamic interactions between the particles, that takes place at a junction. To better understand the consequences of this nontrivial coupling, we combined theoretical, numerical and experimental efforts and solved the 3-body problem in a 1D loop network. This apparently simple dynamical system revealed a rich and unexpected dynamics, including coherent spontaneous oscillations along closed orbits. Striking similarities between Hamiltonian systems and this driven dissipative system will be explained.

Effortful Retrieval Reduces Hippocampal Activity and Impairs Incidental Encoding

PubMed Central

Reas, Emilie T.; Brewer, James B.

2014-01-01

Functional imaging studies frequently report that the hippocampus is engaged by successful episodic memory retrieval. However, considering that concurrent encoding of the background environment occurs during retrieval and influences medial temporal lobe activity, it is plausible that hippocampal encoding functions are reduced with increased attentional engagement during effortful retrieval. Expanding upon evidence that retrieval efforts suppress activity in hippocampal regions implicated in encoding, this study examines the influence of retrieval effort on encoding performance and the interactive effects of encoding and retrieval on hippocampal and neocortical activity. Functional magnetic resonance imaging was conducted while subjects performed a word recognition task with incidental picture encoding. Both lower memory strength and increased search duration were associated with encoding failure and reduced hippocampal and default network activity. Activity in the anterior hippocampus tracked encoding, which was more strongly deactivated when incidental encoding was unsuccessful. These findings highlight potential contributions from background encoding processes to hippocampal activations during neuroimaging studies of episodic memory retrieval. PMID:23378272

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

PubMed

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

2017-01-01

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

Chimeras and clusters in networks of hyperbolic chaotic oscillators

NASA Astrophysics Data System (ADS)

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

2017-03-01

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

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

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.

Multifaceted roles for low-frequency oscillations in bottom-up and top-down processing during navigation and memory.

PubMed

Ekstrom, Arne D; Watrous, Andrew J

2014-01-15

A prominent and replicated finding is the correlation between running speed and increases in low-frequency oscillatory activity in the hippocampal local field potential. A more recent finding concerns low-frequency oscillations that increase in coherence between the hippocampus and neocortical brain areas such as prefrontal cortex during memory-related behaviors (i.e., remembering the correct location to visit). In this review, we tie together movement-related and memory-related low-frequency oscillations in the rodent with similar findings in humans. We argue that although movement-related low-frequency oscillations, in particular, may have slightly different characteristics in humans than rodents, placing important constraints on our thinking about this issue, both phenomena have similar functional foundations. We review four prominent theoretical models that provide partially conflicting accounts of movement-related low-frequency oscillations. We attempt to tie together these theoretical proposals, and existing data in rodents and humans, with memory-related low-frequency oscillations. We propose that movement-related low-frequency oscillations and memory-related low-frequency oscillatory activity, both of which show significant coherence with oscillations in other brain regions, represent different facets of "spectral fingerprints," or different resonant frequencies within the same brain networks underlying different cognitive processes. Together, movement-related and memory-related low-frequency oscillatory coupling may be linked by their distinct contributions to bottom-up, sensorimotor driven processing and top-down, controlled processing characterizing aspects of memory encoding and retrieval. Copyright © 2013. Published by Elsevier Inc.

Multifaceted roles for low-frequency oscillations in bottom-up and top-down processing during navigation and memory

PubMed Central

Ekstrom, Arne D.; Watrous, Andrew J.

2014-01-01

A prominent and replicated finding is the correlation between running speed and increases in low-frequency oscillatory activity in the hippocampal local field potential. A more recent finding concerns low-frequency oscillations that increase in coherence between the hippocampus and neocortical brain areas such as prefrontal cortex during memory-related behaviors (i.e., remembering the correct arm to explore). In this review, we tie together movement-related and memory-related low-frequency oscillations in the rodent with similar findings in humans. We argue that although movement-related low-frequency oscillations, in particular, may have slightly different characteristics in humans than rodents, placing important constraints on our thinking about this issue, both phenomena have similar functional foundations. We review four prominent theoretical models that provide partially conflicting accounts of movement-related low-frequency oscillations. We attempt to tie together these theoretical proposals, and existing data in rodents and humans, with memory-related low-frequency oscillations. We propose that movement-related low-frequency oscillations and memory-related low-frequency oscillatory activity, both of which show significant coherence with oscillations in other brain regions, represent different facets of “spectral fingerprints,” or different resonant frequencies within the same brain networks underlying different cognitive processes. Together, movement-related and memory-related low-frequency oscillatory coupling may be linked by their distinct contributions to bottom-up, sensorimotor driven processing and top-down, controlled processing characterizing aspects of memory encoding and retrieval. PMID:23792985

Transformation of a Spatial Map across the Hippocampal-Lateral Septal Circuit.

PubMed

Tingley, David; Buzsáki, György

2018-05-15

The hippocampus constructs a map of the environment. How this "cognitive map" is utilized by other brain regions to guide behavior remains unexplored. To examine how neuronal firing patterns in the hippocampus are transmitted and transformed, we recorded neurons in its principal subcortical target, the lateral septum (LS). We observed that LS neurons carry reliable spatial information in the phase of action potentials, relative to hippocampal theta oscillations, while the firing rates of LS neurons remained uninformative. Furthermore, this spatial phase code had an anatomical microstructure within the LS and was bound to the hippocampal spatial code by synchronous gamma frequency cell assemblies. Using a data-driven model, we show that rate-independent spatial tuning arises through the dynamic weighting of CA1 and CA3 cell assemblies. Our findings demonstrate that transformation of the hippocampal spatial map depends on higher-order theta-dependent neuronal sequences. Copyright © 2018 Elsevier Inc. All rights reserved.

Hippocampal-targeted Theta-burst Stimulation Enhances Associative Memory Formation.

PubMed

Tambini, Arielle; Nee, Derek Evan; D'Esposito, Mark

2018-06-19

The hippocampus plays a critical role in episodic memory, among other cognitive functions. However, few tools exist to causally manipulate hippocampal function in healthy human participants. Recent work has targeted hippocampal-cortical networks by performing TMS to a region interconnected with the hippocampus, posterior inferior parietal cortex (pIPC). Such hippocampal-targeted TMS enhances associative memory and influences hippocampal functional connectivity. However, it is currently unknown which stages of mnemonic processing (encoding or retrieval) are affected by hippocampal-targeted TMS. Here, we examined whether hippocampal-targeted TMS influences the initial encoding of associations (vs. items) into memory. To selectively influence encoding and not retrieval, we performed continuous theta-burst TMS before participants encoded object-location associations and assessed memory after the direct effect of stimulation dissipated. Relative to control TMS and baseline memory, pIPC TMS enhanced associative memory success and confidence. Item memory was unaffected, demonstrating a selective influence on associative versus item memory. The strength of hippocampal-pIPC functional connectivity predicted TMS-related memory benefits, which was mediated by parahippocampal and retrosplenial cortices. Our findings indicate that hippocampal-targeted TMS can specifically modulate the encoding of new associations into memory without directly influencing retrieval processes and suggest that the ability to influence associative memory may be related to the fidelity of hippocampal TMS targeting. Our results support the notion that pIPC TMS may serve as a potential tool for manipulating hippocampal function in healthy participants. Nonetheless, future work combining hippocampal-targeted continuous theta-burst TMS with neuroimaging is needed to better understand the neural basis of TMS-induced memory changes.

Brain state-dependent recruitment of high-frequency oscillations in the human hippocampus.

PubMed

Billeke, Pablo; Ossandon, Tomas; Stockle, Marcelo; Perrone-Bertolotti, Marcela; Kahane, Philippe; Lachaux, Jean-Philippe; Fuentealba, Pablo

2017-09-01

Ripples are high-frequency bouts of coordinated hippocampal activity believed to be crucial for information transfer and memory formation. We used intracortical macroelectrodes to record neural activity in the human hippocampus of awake subjects undergoing surgical treatment for refractory epilepsy and distinguished two populations of ripple episodes based on their frequency spectrum. The phase-coupling of one population, slow ripples (90-110 Hz), to cortical delta oscillations was differentially modulated by cognitive task; whereas the second population, fast ripples (130-170 Hz), was not seemingly correlated to local neural activity. Furthermore, as cognitive tasks changed, the ongoing coordination of neural activity associated to slow ripples progressively augmented along the parahippocampal axis. Thus, during resting states, slow ripples were coordinated in restricted hippocampal territories; whereas during active states, such as attentionally-demanding tasks, high frequency activity emerged across the hippocampus and parahippocampal cortex, that was synchronized with slow ripples, consistent with ripples supporting information transfer and coupling anatomically distant regions. Hence, our results provide further evidence of neural diversity in hippocampal high-frequency oscillations and their association to cognitive processing in humans. Copyright © 2017 Elsevier Ltd. All rights reserved.

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

Modeling hippocampal neurogenesis using human pluripotent stem cells.

PubMed

Yu, Diana Xuan; Di Giorgio, Francesco Paolo; Yao, Jun; Marchetto, Maria Carolina; Brennand, Kristen; Wright, Rebecca; Mei, Arianna; McHenry, Lauren; Lisuk, David; Grasmick, Jaeson Michael; Silberman, Pedro; Silberman, Giovanna; Jappelli, Roberto; Gage, Fred H

2014-03-11

The availability of human pluripotent stem cells (hPSCs) offers the opportunity to generate lineage-specific cells to investigate mechanisms of human diseases specific to brain regions. Here, we report a differentiation paradigm for hPSCs that enriches for hippocampal dentate gyrus (DG) granule neurons. This differentiation paradigm recapitulates the expression patterns of key developmental genes during hippocampal neurogenesis, exhibits characteristics of neuronal network maturation, and produces PROX1+ neurons that functionally integrate into the DG. Because hippocampal neurogenesis has been implicated in schizophrenia (SCZD), we applied our protocol to SCZD patient-derived human induced pluripotent stem cells (hiPSCs). We found deficits in the generation of DG granule neurons from SCZD hiPSC-derived hippocampal NPCs with lowered levels of NEUROD1, PROX1, and TBR1, reduced neuronal activity, and reduced levels of spontaneous neurotransmitter release. Our approach offers important insights into the neurodevelopmental aspects of SCZD and may be a promising tool for drug screening and personalized medicine.

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.

Acupuncture analgesia involves modulation of pain-induced gamma oscillations and cortical network connectivity.

PubMed

Hauck, Michael; Schröder, Sven; Meyer-Hamme, Gesa; Lorenz, Jürgen; Friedrichs, Sunja; Nolte, Guido; Gerloff, Christian; Engel, Andreas K

2017-11-24

Recent studies support the view that cortical sensory, limbic and executive networks and the autonomic nervous system might interact in distinct manners under the influence of acupuncture to modulate pain. We performed a double-blind crossover design study to investigate subjective ratings, EEG and ECG following experimental laser pain under the influence of sham and verum acupuncture in 26 healthy volunteers. We analyzed neuronal oscillations and inter-regional coherence in the gamma band of 128-channel-EEG recordings as well as heart rate variability (HRV) on two experimental days. Pain ratings and pain-induced gamma oscillations together with vagally-mediated power in the high-frequency bandwidth (vmHF) of HRV decreased significantly stronger during verum than sham acupuncture. Gamma oscillations were localized in the prefrontal cortex (PFC), mid-cingulate cortex (MCC), primary somatosensory cortex and insula. Reductions of pain ratings and vmHF-power were significantly correlated with increase of connectivity between the insula and MCC. In contrast, connectivity between left and right PFC and between PFC and insula correlated positively with vmHF-power without a relationship to acupuncture analgesia. Overall, these findings highlight the influence of the insula in integrating activity in limbic-saliency networks with vagally mediated homeostatic control to mediate antinociception under the influence of acupuncture.

Circuit mechanisms of hippocampal reactivation during sleep.

PubMed

Malerba, Paola; Bazhenov, Maxim

2018-05-01

The hippocampus is important for memory and learning, being a brain site where initial memories are formed and where sharp wave - ripples (SWR) are found, which are responsible for mapping recent memories to long-term storage during sleep-related memory replay. While this conceptual schema is well established, specific intrinsic and network-level mechanisms driving spatio-temporal patterns of hippocampal activity during sleep, and specifically controlling off-line memory reactivation are unknown. In this study, we discuss a model of hippocampal CA1-CA3 network generating spontaneous characteristic SWR activity. Our study predicts the properties of CA3 input which are necessary for successful CA1 ripple generation and the role of synaptic interactions and intrinsic excitability in spike sequence replay during SWRs. Specifically, we found that excitatory synaptic connections promote reactivation in both CA3 and CA1, but the different dynamics of sharp waves in CA3 and ripples in CA1 result in a differential role for synaptic inhibition in modulating replay: promoting spike sequence specificity in CA3 but not in CA1 areas. Finally, we describe how awake learning of spatial trajectories leads to synaptic changes sufficient to drive hippocampal cells' reactivation during sleep, as required for sleep-related memory consolidation. Copyright © 2018 Elsevier Inc. All rights reserved.

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.

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

PubMed

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.

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

PubMed

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

2015-01-01

Several recent studies have compared episodic and spatial memory in neuroimaging paradigms in order to understand better the contribution of the hippocampus to each of these tasks. In the present study, we build on previous findings showing common neural activation in default network areas during episodic and spatial memory tasks based on familiar, real-world environments (Hirshhorn et al. (2012) Neuropsychologia 50:3094-3106). Following previous demonstrations of the presence of functionally connected sub-networks within the default network, we performed seed-based functional connectivity analyses to determine how, depending on the task, the hippocampus and prefrontal cortex differentially couple with one another and with distinct whole-brain networks. We found evidence for a medial prefrontal-parietal network and a medial temporal lobe network, which were functionally connected to the prefrontal and hippocampal seeds, respectively, regardless of the nature of the memory task. However, these two networks were functionally connected with one another during the episodic memory task, but not during spatial memory tasks. Replicating previous reports of fractionation of the default network into stable sub-networks, this study also shows how these sub-networks may flexibly couple and uncouple with one another based on task demands. These findings support the hypothesis that episodic memory and spatial memory share a common medial temporal lobe-based neural substrate, with episodic memory recruiting additional prefrontal sub-networks. © 2014 Wiley Periodicals, Inc.

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.

To Break or to Brake Neuronal Network Accelerated by Ammonium Ions?

PubMed Central

Dynnik, Vladimir V.; Kononov, Alexey V.; Sergeev, Alexander I.; Teplov, Iliya Y.; Tankanag, Arina V.; Zinchenko, Valery P.

2015-01-01

Purpose The aim of present study was to investigate the effects of ammonium ions on in vitro neuronal network activity and to search alternative methods of acute ammonia neurotoxicity prevention. Methods Rat hippocampal neuronal and astrocytes co-cultures in vitro, fluorescent microscopy and perforated patch clamp were used to monitor the changes in intracellular Ca2+- and membrane potential produced by ammonium ions and various modulators in the cells implicated in neural networks. Results Low concentrations of NH4Cl (0.1–4 mM) produce short temporal effects on network activity. Application of 5–8 mM NH4Cl: invariably transforms diverse network firing regimen to identical burst patterns, characterized by substantial neuronal membrane depolarization at plateau phase of potential and high-amplitude Ca2+-oscillations; raises frequency and average for period of oscillations Ca2+-level in all cells implicated in network; results in the appearance of group of «run out» cells with high intracellular Ca2+ and steadily diminished amplitudes of oscillations; increases astrocyte Ca2+-signalling, characterized by the appearance of groups of cells with increased intracellular Ca2+-level and/or chaotic Ca2+-oscillations. Accelerated network activity may be suppressed by the blockade of NMDA or AMPA/kainate-receptors or by overactivation of AMPA/kainite-receptors. Ammonia still activate neuronal firing in the presence of GABA(A) receptors antagonist bicuculline, indicating that «disinhibition phenomenon» is not implicated in the mechanisms of networks acceleration. Network activity may also be slowed down by glycine, agonists of metabotropic inhibitory receptors, betaine, L-carnitine, L-arginine, etc. Conclusions Obtained results demonstrate that ammonium ions accelerate neuronal networks firing, implicating ionotropic glutamate receptors, having preserved the activities of group of inhibitory ionotropic and metabotropic receptors. This may mean, that ammonia

Acute Hippocampal Slice Preparation and Hippocampal Slice Cultures

PubMed Central

Lein, Pamela J.; Barnhart, Christopher D.; Pessah, Isaac N.

2012-01-01

A major advantage of hippocampal slice preparations is that the cytoarchitecture and synaptic circuits of the hippocampus are largely retained. In neurotoxicology research, organotypic hippocampal slices have mostly been used as acute ex vivo preparations for investigating the effects of neurotoxic chemicals on synaptic function. More recently, hippocampal slice cultures, which can be maintained for several weeks to several months in vitro, have been employed to study how neurotoxic chemicals influence the structural and functional plasticity in hippocampal neurons. This chapter provides protocols for preparing hippocampal slices to be used acutely for electrophysiological measurements using glass microelectrodes or microelectrode arrays or to be cultured for morphometric assessments of individual neurons labeled using biolistics. PMID:21815062

Modeling spike-wave discharges by a complex network of neuronal oscillators.

PubMed

Medvedeva, Tatiana M; Sysoeva, Marina V; van Luijtelaar, Gilles; Sysoev, Ilya V

2018-02-01

The organization of neural networks and the mechanisms, which generate the highly stereotypical for absence epilepsy spike-wave discharges (SWDs) is heavily debated. Here we describe such a model which can both reproduce the characteristics of SWDs and dynamics of coupling between brain regions, relying mainly on properties of hierarchically organized networks of a large number of neuronal oscillators. We used a two level mesoscale model. The first level consists of three structures: the nervus trigeminus serving as an input, the thalamus and the somatosensory cortex; the second level of a group of nearby situated neurons belonging to one of three modeled structures. The model reproduces the main features of the transition from normal to epileptiformic activity and its spontaneous abortion: an increase in the oscillation amplitude, the emergence of the main frequency and its higher harmonics, and the ability to generate trains of seizures. The model was stable with respect to variations in the structure of couplings and to scaling. The analyzes of the interactions between model structures from their time series using Granger causality method showed that the model reproduced the preictal coupling increase detected previously from experimental data. SWDs can be generated by changes in network organization. It is proposed that a specific pathological architecture of couplings in the brain is necessary to allow the transition from normal to epileptiformic activity, next to by others modeled and reported factors referring to complex, intrinsic, and synaptic mechanisms. Copyright © 2017 Elsevier Ltd. All rights reserved.

Self-Organized Supercriticality and Oscillations in Networks of Stochastic Spiking Neurons

NASA Astrophysics Data System (ADS)

Costa, Ariadne; Brochini, Ludmila; Kinouchi, Osame

2017-08-01

Networks of stochastic spiking neurons are interesting models in the area of Theoretical Neuroscience, presenting both continuous and discontinuous phase transitions. Here we study fully connected networks analytically, numerically and by computational simulations. The neurons have dynamic gains that enable the network to converge to a stationary slightly supercritical state (self-organized supercriticality or SOSC) in the presence of the continuous transition. We show that SOSC, which presents power laws for neuronal avalanches plus some large events, is robust as a function of the main parameter of the neuronal gain dynamics. We discuss the possible applications of the idea of SOSC to biological phenomena like epilepsy and dragon king avalanches. We also find that neuronal gains can produce collective oscillations that coexists with neuronal avalanches, with frequencies compatible with characteristic brain rhythms.

Transient oxytocin signaling primes the development and function of excitatory hippocampal neurons

PubMed Central

Ripamonti, Silvia; Ambrozkiewicz, Mateusz C; Guzzi, Francesca; Gravati, Marta; Biella, Gerardo; Bormuth, Ingo; Hammer, Matthieu; Tuffy, Liam P; Sigler, Albrecht; Kawabe, Hiroshi; Nishimori, Katsuhiko; Toselli, Mauro; Brose, Nils; Parenti, Marco; Rhee, JeongSeop

2017-01-01

Beyond its role in parturition and lactation, oxytocin influences higher brain processes that control social behavior of mammals, and perturbed oxytocin signaling has been linked to the pathogenesis of several psychiatric disorders. However, it is still largely unknown how oxytocin exactly regulates neuronal function. We show that early, transient oxytocin exposure in vitro inhibits the development of hippocampal glutamatergic neurons, leading to reduced dendrite complexity, synapse density, and excitatory transmission, while sparing GABAergic neurons. Conversely, genetic elimination of oxytocin receptors increases the expression of protein components of excitatory synapses and excitatory synaptic transmission in vitro. In vivo, oxytocin-receptor-deficient hippocampal pyramidal neurons develop more complex dendrites, which leads to increased spine number and reduced γ-oscillations. These results indicate that oxytocin controls the development of hippocampal excitatory neurons and contributes to the maintenance of a physiological excitation/inhibition balance, whose disruption can cause neurobehavioral disturbances. DOI: http://dx.doi.org/10.7554/eLife.22466.001 PMID:28231043

Investigating Synchronous Oscillation and Deep Brain Stimulation Treatment in A Model of Cortico-Basal Ganglia Network.

PubMed

Lu, Meili; Wei, Xile; Loparo, Kenneth A

2017-11-01

Altered firing properties and increased pathological oscillations in the basal ganglia have been proven to be hallmarks of Parkinson's disease (PD). Increasing evidence suggests that abnormal synchronous oscillations and suppression in the cortex may also play a critical role in the pathogenic process and treatment of PD. In this paper, a new closed-loop network including the cortex and basal ganglia using the Izhikevich models is proposed to investigate the synchrony and pathological oscillations in motor circuits and their modulation by deep brain stimulation (DBS). Results show that more coherent dynamics in the cortex may cause stronger effects on the synchrony and pathological oscillations of the subthalamic nucleus (STN). The pathological beta oscillations of the STN can both be efficiently suppressed with DBS applied directly to the STN or to cortical neurons, respectively, but the underlying mechanisms by which DBS suppresses the beta oscillations are different. This research helps to understand the dynamics of pathological oscillations in PD-related motor regions and supports the therapeutic potential of stimulation of cortical neurons.

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

PubMed

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

2012-12-01

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

Progressive Functional Impairments of Hippocampal Neurons in a Tauopathy Mouse Model

PubMed Central

Ciupek, Sarah M.; Cheng, Jingheng; Ali, Yousuf O.; Lu, Hui-Chen

2015-01-01

The age-dependent progression of tau pathology is a major characteristic of tauopathies, including Alzheimer's disease (AD), and plays an important role in the behavioral phenotypes of AD, including memory deficits. Despite extensive molecular and cellular studies on tau pathology, it remains to be determined how it alters the neural circuit functions underlying learning and memory in vivo. In rTg4510 mice, a Tau-P301L tauopathy model, hippocampal place fields that support spatial memories are abnormal at old age (7–9 months) when tau tangles and neurodegeneration are extensive. However, it is unclear how the abnormality in the hippocampal circuit function arises and progresses with the age-dependent progression of tau pathology. Here we show that in young (2–4 months of age) rTg4510 mice, place fields of hippocampal CA1 cells are largely normal, with only subtle differences from those of age-matched wild-type control mice. Second, high-frequency ripple oscillations of local field potentials in the hippocampal CA1 area are significantly reduced in young rTg4510 mice, and even further deteriorated in old rTg4510 mice. The ripple reduction is associated with less bursty firing and altered synchrony of CA1 cells. Together, the data indicate that deficits in ripples and neuronal synchronization occur before overt deficits in place fields in these mice. The results reveal a tau-pathology-induced progression of hippocampal functional changes in vivo. PMID:26019329

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)

Harnessing the power of theta: natural manipulations of cognitive performance during hippocampal theta-contingent eyeblink conditioning

PubMed Central

Hoffmann, Loren C.; Cicchese, Joseph J.; Berry, Stephen D.

2015-01-01

Neurobiological oscillations are regarded as essential to normal information processing, including coordination and timing of cells and assemblies within structures as well as in long feedback loops of distributed neural systems. The hippocampal theta rhythm is a 3–12 Hz oscillatory potential observed during cognitive processes ranging from spatial navigation to associative learning. The lower range, 3–7 Hz, can occur during immobility and depends upon the integrity of cholinergic forebrain systems. Several studies have shown that the amount of pre-training theta in the rabbit strongly predicts the acquisition rate of classical eyeblink conditioning and that impairment of this system substantially slows the rate of learning. Our lab has used a brain-computer interface (BCI) that delivers eyeblink conditioning trials contingent upon the explicit presence or absence of hippocampal theta. A behavioral benefit of theta-contingent training has been demonstrated in both delay and trace forms of the paradigm with a two- to four-fold increase in learning speed. This behavioral effect is accompanied by enhanced amplitude and synchrony of hippocampal local field potential (LFP)s, multi-unit excitation, and single-unit response patterns that depend on theta state. Additionally, training in the presence of hippocampal theta has led to increases in the salience of tone-induced unit firing patterns in the medial prefrontal cortex, followed by persistent multi-unit activity during the trace interval. In cerebellum, rhythmicity and precise synchrony of stimulus time-locked LFPs with those of hippocampus occur preferentially under the theta condition. Here we review these findings, integrate them into current models of hippocampal-dependent learning and suggest how improvement in our understanding of neurobiological oscillations is critical for theories of medial temporal lobe processes underlying intact and pathological learning. PMID:25918501

Harnessing the power of theta: natural manipulations of cognitive performance during hippocampal theta-contingent eyeblink conditioning.

PubMed

Hoffmann, Loren C; Cicchese, Joseph J; Berry, Stephen D

2015-01-01

Neurobiological oscillations are regarded as essential to normal information processing, including coordination and timing of cells and assemblies within structures as well as in long feedback loops of distributed neural systems. The hippocampal theta rhythm is a 3-12 Hz oscillatory potential observed during cognitive processes ranging from spatial navigation to associative learning. The lower range, 3-7 Hz, can occur during immobility and depends upon the integrity of cholinergic forebrain systems. Several studies have shown that the amount of pre-training theta in the rabbit strongly predicts the acquisition rate of classical eyeblink conditioning and that impairment of this system substantially slows the rate of learning. Our lab has used a brain-computer interface (BCI) that delivers eyeblink conditioning trials contingent upon the explicit presence or absence of hippocampal theta. A behavioral benefit of theta-contingent training has been demonstrated in both delay and trace forms of the paradigm with a two- to four-fold increase in learning speed. This behavioral effect is accompanied by enhanced amplitude and synchrony of hippocampal local field potential (LFP)s, multi-unit excitation, and single-unit response patterns that depend on theta state. Additionally, training in the presence of hippocampal theta has led to increases in the salience of tone-induced unit firing patterns in the medial prefrontal cortex, followed by persistent multi-unit activity during the trace interval. In cerebellum, rhythmicity and precise synchrony of stimulus time-locked LFPs with those of hippocampus occur preferentially under the theta condition. Here we review these findings, integrate them into current models of hippocampal-dependent learning and suggest how improvement in our understanding of neurobiological oscillations is critical for theories of medial temporal lobe processes underlying intact and pathological learning.

Hippocampal Non-Theta-Contingent Eyeblink Classical Conditioning: A Model System for Neurobiological Dysfunction

PubMed Central

Cicchese, Joseph J.; Berry, Stephen D.

2016-01-01

Typical information processing is thought to depend on the integrity of neurobiological oscillations that may underlie coordination and timing of cells and assemblies within and between structures. The 3–7 Hz bandwidth of hippocampal theta rhythm is associated with cognitive processes essential to learning and depends on the integrity of cholinergic, GABAergic, and glutamatergic forebrain systems. Since several significant psychiatric disorders appear to result from dysfunction of medial temporal lobe (MTL) neurochemical systems, preclinical studies on animal models may be an important step in defining and treating such syndromes. Many studies have shown that the amount of hippocampal theta in the rabbit strongly predicts the acquisition rate of classical eyeblink conditioning and that impairment of this system substantially slows the rate of learning and attainment of asymptotic performance. Our lab has developed a brain–computer interface that makes eyeblink training trials contingent upon the explicit presence or absence of hippocampal theta. The behavioral benefit of theta-contingent training has been demonstrated in both delay and trace forms of the paradigm with a two- to fourfold increase in learning speed over non-theta states. The non-theta behavioral impairment is accompanied by disruption of the amplitude and synchrony of hippocampal local field potentials, multiple-unit excitation, and single-unit response patterns dependent on theta state. Our findings indicate a significant electrophysiological and behavioral impact of the pretrial state of the hippocampus that suggests an important role for this MTL system in associative learning and a significant deleterious impact in the absence of theta. Here, we focus on the impairments in the non-theta state, integrate them into current models of psychiatric disorders, and suggest how improvement in our understanding of neurobiological oscillations is critical for theories and treatment of psychiatric

Multimodal Approaches to Define Network Oscillations in Depression

PubMed Central

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

2018-01-01

The renaissance in the use of encephalography-based research methods to probe the pathophysiology of neuropsychiatric disorders is well afoot and continues to advance. Building on the platform of neuroimaging evidence on brain circuit models, magnetoencephalography, scalp electroencephalography, and even invasive electroencephalography are now being used to characterize brain network dysfunctions that underlie major depressive disorder using brain oscillation measurements and associated treatment responses. Such multiple encephalography modalities provide avenues to study pathologic network dynamics with high temporal resolution and over long time courses, opportunities to complement neuroimaging methods and findings, and new approaches to identify quantitative biomarkers that indicate critical targets for brain therapy. Such goals have been facilitated by the ongoing testing of novel invasive neuromodulation therapies, notably, deep brain stimulation, where clinically relevant treatment effects can be monitored at multiple brain sites in a time-locked causal manner. We review key brain rhythms identified in major depressive disorder as foundation for development of putative biomarkers for objectively evaluating neuromodulation success and for guiding deep brain stimulation or other target-based neuromodulation strategies for treatment-resistant depression patients. PMID:25681871

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.

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

PubMed Central

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

1990-01-01

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

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. Copyright © 2015 Elsevier Inc. All rights reserved.

Resurgence of oscillation in coupled oscillators under delayed cyclic interaction

NASA Astrophysics Data System (ADS)

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

2017-07-01

This paper investigates the emergence of amplitude death and revival of oscillations from the suppression states in a system of coupled dynamical units interacting through delayed cyclic mode. In order to resurrect the oscillation from amplitude death state, we introduce asymmetry and feedback parameter in the cyclic coupling forms as a result of which the death region shrinks due to higher asymmetry and lower feedback parameter values for coupled oscillatory systems. Some analytical conditions are derived for amplitude death and revival of oscillations in two coupled limit cycle oscillators and corresponding numerical simulations confirm the obtained theoretical results. We also report that the death state and revival of oscillations from quenched state are possible in the network of identical coupled oscillators. The proposed mechanism has also been examined using chaotic Lorenz oscillator.

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

PubMed

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

2008-06-01

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

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

NASA Astrophysics Data System (ADS)

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

2012-12-01

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

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.

Activity patterns in networks stabilized by background oscillations.

PubMed

Hoppensteadt, Frank

2009-07-01

The brain operates in a highly oscillatory environment. We investigate here how such an oscillating background can create stable organized behavior in an array of neuro-oscillators that is not observable in the absence of oscillation, much like oscillating the support point of an inverted pendulum can stabilize its up position, which is unstable without the oscillation. We test this idea in an array of electronic circuits coming from neuroengineering: we show how the frequencies of the background oscillation create a partition of the state space into distinct basins of attraction. Thus, background signals can stabilize persistent activity that is otherwise not observable. This suggests that an image, represented as a stable firing pattern which is triggered by a voltage pulse and is sustained in synchrony or resonance with the background oscillation, can persist as a stable behavior long after the initial stimulus is removed. The background oscillations provide energy for organized behavior in the array, and these behaviors are categorized by the basins of attraction determined by the oscillation frequencies.

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.

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. Copyright 2004 American Institute of Physics

Enantioselectivity of 2,2',3,5',6-Pentachlorobiphenyl (PCB 95) Atropisomers toward Ryanodine Receptors (RyRs) and Their Influences on Hippocampal Neuronal Networks.

PubMed

Feng, Wei; Zheng, Jing; Robin, Gaëlle; Dong, Yao; Ichikawa, Makoto; Inoue, Yoshihisa; Mori, Tadashi; Nakano, Takeshi; Pessah, Isaac N

2017-12-19

Nineteen ortho-substituted PCBs are chiral and found enantioselectively enriched in ecosystems. Their differential actions on biological targets are not understood. PCB 95 (2,2',3,5',6-pentachlorobiphenyl), a chiral PCB of current environmental relevance, is among the most potent toward modifying ryanodine receptors (RyR) function and Ca 2+ signaling. PCB 95 enantiomers are separated and assigned aR- and aS-PCB 95 using three chiral-column HPLC and circular dichroism spectroscopy. Studies of RyR1-enriched microsomes show aR-PCB 95 with >4× greater potency (EC 50 = 0.20 ± 0.05 μM), ∼ 1.3× higher efficacy (B max = 3.74 ± 0.07 μM) in [ 3 H]Ryanodine-binding and >3× greater rates (R = 7.72 ± 0.31 nmol/sec/mg) of Ca 2+ efflux compared with aS-PCB 95, whereas racemate has intermediate activity. aR-PCB 95 has modest selectivity for RyR2, and lower potency than racemate toward the RyR isoform mixture in brain membranes. Chronic exposure of hippocampal neuronal networks to nanomolar PCB 95 during a critical developmental period shows divergent influences on synchronous Ca 2+ oscillation (SCO): rac-PCB 95 increasing and aR-PCB 95 decreasing SCO frequency at 50 nM, although the latter's effects are nonmonotonic at higher concentration. aS-PCB95 shows the greatest influence on inhibiting responses to 20 Hz electrical pulse trains. Considering persistence of PCB 95 in the environment, stereoselectivity toward RyRs and developing neuronal networks may clarify health risks associated with enantioisomeric enrichment of PCBs.

Hippocampal gamma-band Synchrony and pupillary responses index memory during visual search.

PubMed

Montefusco-Siegmund, Rodrigo; Leonard, Timothy K; Hoffman, Kari L

2017-04-01

Memory for scenes is supported by the hippocampus, among other interconnected structures, but the neural mechanisms related to this process are not well understood. To assess the role of the hippocampus in memory-guided scene search, we recorded local field potentials and multiunit activity from the hippocampus of macaques as they performed goal-directed search tasks using natural scenes. We additionally measured pupil size during scene presentation, which in humans is modulated by recognition memory. We found that both pupil dilation and search efficiency accompanied scene repetition, thereby indicating memory for scenes. Neural correlates included a brief increase in hippocampal multiunit activity and a sustained synchronization of unit activity to gamma band oscillations (50-70 Hz). The repetition effects on hippocampal gamma synchronization occurred when pupils were most dilated, suggesting an interaction between aroused, attentive processing and hippocampal correlates of recognition memory. These results suggest that the hippocampus may support memory-guided visual search through enhanced local gamma synchrony. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Average spectral power changes at the hippocampal electroencephalogram in schizophrenia model induced by ketamine.

PubMed

Sampaio, Luis Rafael L; Borges, Lucas T N; Silva, Joyse M F; de Andrade, Francisca Roselin O; Barbosa, Talita M; Oliveira, Tatiana Q; Macedo, Danielle; Lima, Ricardo F; Dantas, Leonardo P; Patrocinio, Manoel Cláudio A; do Vale, Otoni C; Vasconcelos, Silvânia M M

2018-02-01

The use of ketamine (Ket) as a pharmacological model of schizophrenia is an important tool for understanding the main mechanisms of glutamatergic regulated neural oscillations. Thus, the aim of the current study was to evaluate Ket-induced changes in the average spectral power using the hippocampal quantitative electroencephalography (QEEG). To this end, male Wistar rats were submitted to a stereotactic surgery for the implantation of an electrode in the right hippocampus. After three days, the animals were divided into four groups that were treated for 10 consecutive days with Ket (10, 50, or 100 mg/kg). Brainwaves were captured on the 1st or 10th day, respectively, to acute or repeated treatments. The administration of Ket (10, 50, or 100 mg/kg), compared with controls, induced changes in the hippocampal average spectral power of delta, theta, alpha, gamma low or high waves, after acute or repeated treatments. Therefore, based on the alterations in the average spectral power of hippocampal waves induced by Ket, our findings might provide a basis for the use of hippocampal QEEG in animal models of schizophrenia. © 2017 Société Française de Pharmacologie et de Thérapeutique.

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

PubMed

Berke, J D

2009-09-01

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 rats, distinct frequencies of ventral striatal local field potential oscillations show coherence with different cortical inputs. The approximately 50 Hz gamma oscillations that normally predominate in awake ventral striatum are coherent with piriform cortex, whereas approximately 80-100 Hz high-gamma oscillations are coherent with frontal cortex. Within striatum, entrainment to gamma rhythms is selective to fast-spiking interneurons, with distinct fast-spiking interneuron populations entrained to different gamma frequencies. Administration of the psychomotor stimulant amphetamine or the dopamine agonist apomorphine causes a prolonged decrease in approximately 50 Hz power and increase in approximately 80-100 Hz power. The same frequency switch is observed for shorter epochs spontaneously in awake, undrugged animals and is consistently provoked for < 1 s 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.

Parvalbumin-positive interneurons mediate neocortical-hippocampal interactions that are necessary for memory consolidation

PubMed Central

Xia, Frances; Richards, Blake A; Tran, Matthew M; Josselyn, Sheena A

2017-01-01

Following learning, increased coupling between spindle oscillations in the medial prefrontal cortex (mPFC) and ripple oscillations in the hippocampus is thought to underlie memory consolidation. However, whether learning-induced increases in ripple-spindle coupling are necessary for successful memory consolidation has not been tested directly. In order to decouple ripple-spindle oscillations, here we chemogenetically inhibited parvalbumin-positive (PV+) interneurons, since their activity is important for regulating the timing of spiking activity during oscillations. We found that contextual fear conditioning increased ripple-spindle coupling in mice. However, inhibition of PV+ cells in either CA1 or mPFC eliminated this learning-induced increase in ripple-spindle coupling without affecting ripple or spindle incidence. Consistent with the hypothesized importance of ripple-spindle coupling in memory consolidation, post-training inhibition of PV+ cells disrupted contextual fear memory consolidation. These results indicate that successful memory consolidation requires coherent hippocampal-neocortical communication mediated by PV+ cells. PMID:28960176

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…

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

PubMed Central

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. PMID:26840529

Synchronisation of networked Kuramoto oscillators under stable Lévy noise

NASA Astrophysics Data System (ADS)

Kalloniatis, Alexander C.; Roberts, Dale O.

2017-01-01

We study the Kuramoto model on several classes of network topologies examining the dynamics under the influence of Lévy noise. Such noise exhibits heavier tails than Gaussian and allows us to understand how 'shocks' influence the individual oscillator and collective system behaviour. Skewed α-stable Lévy noise, equivalent to fractional diffusion perturbations, are considered. We perform numerical simulations for Erdős-Rényi (ER) and Barabási-Albert (BA) scale free networks of size N = 1000 while varying the Lévy index α for the noise. We find that synchrony now assumes a surprising variety of forms, not seen for Gaussian-type noise, and changing with α: a noise-generated drift, a smooth α dependence of the point of cross-over of ER and BA networks in the degree of synchronisation, and a severe loss of synchronisation at low values of α. We also show that this robustness of the BA network across most values of α can also be understood as a consequence of the Laplacian of the graph working within the fractional Fokker-Planck equation of the linearised system, close to synchrony, with both eigenvalues and eigenvectors alternately contributing in different regimes of α.

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

PubMed Central

Murty, Vishnu P.; Adcock, R. Alison

2014-01-01

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

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 Central

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

2011-01-01

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 Ca2+ 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 Ca2+ 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. PMID:21893530

Hippocampal ripples down-regulate synapses.

PubMed

Norimoto, Hiroaki; Makino, Kenichi; Gao, Mengxuan; Shikano, Yu; Okamoto, Kazuki; Ishikawa, Tomoe; Sasaki, Takuya; Hioki, Hiroyuki; Fujisawa, Shigeyoshi; Ikegaya, Yuji

2018-03-30

The specific effects of sleep on synaptic plasticity remain unclear. We report that mouse hippocampal sharp-wave ripple oscillations serve as intrinsic events that trigger long-lasting synaptic depression. Silencing of sharp-wave ripples during slow-wave states prevented the spontaneous down-regulation of net synaptic weights and impaired the learning of new memories. The synaptic down-regulation was dependent on the N -methyl-d-aspartate receptor and selective for a specific input pathway. Thus, our findings are consistent with the role of slow-wave states in refining memory engrams by reducing recent memory-irrelevant neuronal activity and suggest a previously unrecognized function for sharp-wave ripples. Copyright © 2018 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

Inflammation Subverts Hippocampal Synaptic Plasticity in Experimental Multiple Sclerosis

PubMed Central

Mandolesi, Georgia; Piccinin, Sonia; Berretta, Nicola; Pignatelli, Marco; Feligioni, Marco; Musella, Alessandra; Gentile, Antonietta; Mori, Francesco; Bernardi, Giorgio; Nicoletti, Ferdinando; Mercuri, Nicola B.; Centonze, Diego

2013-01-01

Abnormal use-dependent synaptic plasticity is universally accepted as the main physiological correlate of memory deficits in neurodegenerative disorders. It is unclear whether synaptic plasticity deficits take place during neuroinflammatory diseases, such as multiple sclerosis (MS) and its mouse model, experimental autoimmune encephalomyelitis (EAE). In EAE mice, we found significant alterations of synaptic plasticity rules in the hippocampus. When compared to control mice, in fact, hippocampal long-term potentiation (LTP) induction was favored over long-term depression (LTD) in EAE, as shown by a significant rightward shift in the frequency–synaptic response function. Notably, LTP induction was also enhanced in hippocampal slices from control mice following interleukin-1β (IL-1β) perfusion, and both EAE and IL-1β inhibited GABAergic spontaneous inhibitory postsynaptic currents (sIPSC) without affecting glutamatergic transmission and AMPA/NMDA ratio. EAE was also associated with selective loss of GABAergic interneurons and with reduced gamma-frequency oscillations in the CA1 region of the hippocampus. Finally, we provided evidence that microglial activation in the EAE hippocampus was associated with IL-1β expression, and hippocampal slices from control mice incubated with activated microglia displayed alterations of GABAergic transmission similar to those seen in EAE brains, through a mechanism dependent on enhanced IL-1β signaling. These data may yield novel insights into the basis of cognitive deficits in EAE and possibly of MS. PMID:23355887

Repetition reveals ups and downs of hippocampal, thalamic, and neocortical engagement during mnemonic decisions

PubMed Central

Reagh, Zachariah M.; Murray, Elizabeth A.; Yassa, Michael A.

2017-01-01

The extent to which current information is consistent with past experiences and our capacity to recognize or discriminate accordingly are key factors in flexible memory-guided behavior. Despite a wealth of evidence linking hippocampal and neocortical computations to these phenomena, many important factors remain poorly understood. One such factor is repeated encoding of learned information. In this experiment, participants completed a task in which study stimuli were incidentally encoded either once or three separate times during high-resolution fMRI scanning. We asked how repetition influenced recognition and discrimination memory judgments, and how this affects engagement of hippocampal and neocortical regions. Repetition revealed shifts in engagement in an anterior (ventral) CA1-thalamic-medial prefrontal network related to true and false recognition. Conversely, repetition revealed shifts in a posterior (dorsal) dentate/CA3-parahippocampal-restrosplenial network related to accurate discrimination. These differences in engagement were accompanied by task-related correlations in respective anterior and posterior networks. In particular, the anterior thalamic region observed during recognition judgments is functionally and anatomically consistent with nucleus reuniens in humans, and was found to mediate correlations between the anterior CA1 and medial prefrontal cortex. These findings offer new insights into how repeated experience affects memory and its neural substrates in hippocampal-neocortical networks. PMID:27859884

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.

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

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

PubMed

Murty, Vishnu P; Adcock, R Alison

2014-08-01

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

Multiple hippocampal transections for intractable hippocampal epilepsy: Seizure outcome.

PubMed

Koubeissi, Mohamad Z; Kahriman, Emine; Fastenau, Philip; Bailey, Christopher; Syed, Tanvir; Amina, Shahram; Miller, Jonathan; Munyon, Charles; Tanner, Adriana; Karanec, Kristina; Tuxhorn, Ingrid; Lüders, Hans

2016-05-01

The purpose of this study was to evaluate the seizure outcomes after transverse multiple hippocampal transections (MHTs) in 13 patients with intractable TLE. Thirteen patients with normal memory scores, including 8 with nonlesional hippocampi on MRI, had temporal lobe epilepsy (TLE) necessitating depth electrode implantation. After confirming hippocampal seizure onset, they underwent MHT. Intraoperative monitoring was done with 5-6 hippocampal electrodes spaced at approximately 1-cm intervals and spike counting for 5-8min before each cut. The number of transections ranged between 4 and 7. Neuropsychological assessment was completed preoperatively and postoperatively for all patients and will be reported separately. Duration of epilepsy ranged between 5 and 55years. There were no complications. Intraoperatively, MHT resulted in marked spike reduction (p=0.003, paired t-test). Ten patients (77%) are seizure-free (average follow-up was 33months, range 20-65months) without medication changes. One of the 3 patients with persistent seizures had an MRI revealing incomplete transections, another had an additional neocortical seizure focus (as suggested by pure aphasic seizures), and the third had only 2 seizures in 4years, one of which occurred during antiseizure medication withdrawal. Verbal and visual memory outcomes will be reported separately. Right and left hippocampal volumes were not different preoperatively (n=12, p=0.64, Wilcoxon signed-rank test), but the transected hippocampal volume decreased postoperatively (p=0.0173). Multiple hippocampal transections provide an effective intervention and a safe alternative to temporal lobectomy in patients with hippocampal epilepsy. Copyright © 2016 Elsevier Inc. All rights reserved.

Effects of third trimester-equivalent ethanol exposure on Cl(-) co-transporter expression, network activity, and GABAergic transmission in the CA3 hippocampal region of neonatal rats.

PubMed

Everett, Julie C; Licón-Muñoz, Yamhilette; Valenzuela, C Fernando

2012-09-01

Fetal alcohol spectrum disorders are often associated with structural and functional hippocampal abnormalities, leading to long-lasting learning and memory deficits. The mechanisms underlying these abnormalities are not fully understood. Here, we investigated whether ethanol exposure during the 3rd trimester-equivalent period alters spontaneous network activity that is involved in neuronal circuit development in the CA3 hippocampal region. This activity is driven by GABA(A) receptors, which can have excitatory actions in developing neurons as a consequence of greater expression of the Cl(-) importer, NKCC1, with respect to expression of the Cl(-) exporter, KCC2, resulting in high [Cl(-)](i). Rat pups were exposed to ethanol vapor from postnatal day (P) 2-16 (4 h/day). Weight gain was significantly reduced in pups exposed to ethanol compared to control at P15 and 16. Brain slices were prepared immediately after the end of the 4-h exposure on P4-16 and experiments were also performed under ethanol-free conditions at the end of the exposure paradigm (P17-22). Ethanol exposure did not significantly affect expression of KCC2 or NKCC1, nor did it affect network activity in the CA3 hippocampal region. Ethanol exposure significantly decreased the frequency (at P9-11) and increased the amplitude (at P5-8 and P17-21) of GABA(A) receptor-mediated miniature postsynaptic currents. These data suggest that repeated in vivo exposure to ethanol during the 3rd trimester-equivalent period alters GABAergic transmission in the CA3 hippocampal region, an effect that could lead to abnormal circuit maturation and perhaps contribute to the pathophysiology of fetal alcohol spectrum disorders. Copyright © 2012 Elsevier Inc. All rights reserved.

Rapid cell-free forward engineering of novel genetic ring oscillators

PubMed Central

Niederholtmeyer, Henrike; Sun, Zachary Z; Hori, Yutaka; Yeung, Enoch; Verpoorte, Amanda; Murray, Richard M; Maerkl, Sebastian J

2015-01-01

While complex dynamic biological networks control gene expression in all living organisms, the forward engineering of comparable synthetic networks remains challenging. The current paradigm of characterizing synthetic networks in cells results in lengthy design-build-test cycles, minimal data collection, and poor quantitative characterization. Cell-free systems are appealing alternative environments, but it remains questionable whether biological networks behave similarly in cell-free systems and in cells. We characterized in a cell-free system the ‘repressilator’, a three-node synthetic oscillator. We then engineered novel three, four, and five-gene ring architectures, from characterization of circuit components to rapid analysis of complete networks. When implemented in cells, our novel 3-node networks produced population-wide oscillations and 95% of 5-node oscillator cells oscillated for up to 72 hr. Oscillation periods in cells matched the cell-free system results for all networks tested. An alternate forward engineering paradigm using cell-free systems can thus accurately capture cellular behavior. DOI: http://dx.doi.org/10.7554/eLife.09771.001 PMID:26430766

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

EEG Oscillations Are Modulated in Different Behavior-Related Networks during Rhythmic Finger Movements.

PubMed

Seeber, Martin; Scherer, Reinhold; Müller-Putz, Gernot R

2016-11-16

Sequencing and timing of body movements are essential to perform motoric tasks. In this study, we investigate the temporal relation between cortical oscillations and human motor behavior (i.e., rhythmic finger movements). High-density EEG recordings were used for source imaging based on individual anatomy. We separated sustained and movement phase-related EEG source amplitudes based on the actual finger movements recorded by a data glove. Sustained amplitude modulations in the contralateral hand area show decrease for α (10-12 Hz) and β (18-24 Hz), but increase for high γ (60-80 Hz) frequencies during the entire movement period. Additionally, we found movement phase-related amplitudes, which resembled the flexion and extension sequence of the fingers. Especially for faster movement cadences, movement phase-related amplitudes included high β (24-30 Hz) frequencies in prefrontal areas. Interestingly, the spectral profiles and source patterns of movement phase-related amplitudes differed from sustained activities, suggesting that they represent different frequency-specific large-scale networks. First, networks were signified by the sustained element, which statically modulate their synchrony levels during continuous movements. These networks may upregulate neuronal excitability in brain regions specific to the limb, in this study the right hand area. Second, movement phase-related networks, which modulate their synchrony in relation to the movement sequence. We suggest that these frequency-specific networks are associated with distinct functions, including top-down control, sensorimotor prediction, and integration. The separation of different large-scale networks, we applied in this work, improves the interpretation of EEG sources in relation to human motor behavior. EEG recordings provide high temporal resolution suitable to relate cortical oscillations to actual movements. Investigating EEG sources during rhythmic finger movements, we distinguish sustained from

Napping to renew learning capacity: enhanced encoding after stimulation of sleep slow oscillations.

PubMed

Antonenko, Daria; Diekelmann, Susanne; Olsen, Cathrin; Born, Jan; Mölle, Matthias

2013-04-01

As well as consolidating memory, sleep has been proposed to serve a second important function for memory, i.e. to free capacities for the learning of new information during succeeding wakefulness. The slow wave activity (SWA) that is a hallmark of slow wave sleep could be involved in both functions. Here, we aimed to demonstrate a causative role for SWA in enhancing the capacity for encoding of information during subsequent wakefulness, using transcranial slow oscillation stimulation (tSOS) oscillating at 0.75 Hz to induce SWA in healthy humans during an afternoon nap. Encoding following the nap was tested for hippocampus-dependent declarative materials (pictures, word pairs, and word lists) and procedural skills (finger sequence tapping). As compared with a sham stimulation control condition, tSOS during the nap enhanced SWA and significantly improved subsequent encoding on all three declarative tasks (picture recognition, cued recall of word pairs, and free recall of word lists), whereas procedural finger sequence tapping skill was not affected. Our results indicate that sleep SWA enhances the capacity for encoding of declarative materials, possibly by down-scaling hippocampal synaptic networks that were potentiated towards saturation during the preceding period of wakefulness. © 2013 Federation of European Neuroscience Societies and Blackwell Publishing Ltd.

MRI uncovers disrupted hippocampal microstructure that underlies memory impairments after early-life adversity.

PubMed

Molet, Jenny; Maras, Pamela M; Kinney-Lang, Eli; Harris, Neil G; Rashid, Faisal; Ivy, Autumn S; Solodkin, Ana; Obenaus, Andre; Baram, Tallie Z

2016-12-01

Memory and related cognitive functions are progressively impaired in a subgroup of individuals experiencing childhood adversity and stress. However, it is not possible to identify vulnerable individuals early, a crucial step for intervention. In this study, high-resolution magnetic resonance imaging (MRI) and intra-hippocampal diffusion tensor imaging (DTI) were employed to examine for structural signatures of cognitive adolescent vulnerabilities in a rodent model of early-life adversity. These methods were complemented by neuroanatomical and functional assessments of hippocampal network integrity during adolescence, adulthood and middle-age. The high-resolution MRI identified selective loss of dorsal hippocampal volume, and intra-hippocampal DTI uncovered disruption of dendritic structure, consistent with disrupted local connectivity, already during late adolescence in adversity-experiencing rats. Memory deteriorated over time, and stunting of hippocampal dendritic trees was apparent on neuroanatomical analyses. Thus, disrupted hippocampal neuronal structure and connectivity, associated with cognitive impairments, are detectable via non-invasive imaging modalities in rats experiencing early-life adversity. These high-resolution imaging approaches may constitute promising tools for prediction and assessment of at-risk individuals in the clinic. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Neuromorphic computing with nanoscale spintronic oscillators.

PubMed

Torrejon, Jacob; Riou, Mathieu; Araujo, Flavio Abreu; Tsunegi, Sumito; Khalsa, Guru; Querlioz, Damien; Bortolotti, Paolo; Cros, Vincent; Yakushiji, Kay; Fukushima, Akio; Kubota, Hitoshi; Yuasa, Shinji; Stiles, Mark D; Grollier, Julie

2017-07-26

Neurons in the brain behave as nonlinear oscillators, which develop rhythmic activity and interact to process information. Taking inspiration from this behaviour to realize high-density, low-power neuromorphic computing will require very large numbers of nanoscale nonlinear oscillators. A simple estimation indicates that to fit 10 8 oscillators organized in a two-dimensional array inside a chip the size of a thumb, the lateral dimension of each oscillator must be smaller than one micrometre. However, nanoscale devices tend to be noisy and to lack the stability that is required to process data in a reliable way. For this reason, despite multiple theoretical proposals and several candidates, including memristive and superconducting oscillators, a proof of concept of neuromorphic computing using nanoscale oscillators has yet to be demonstrated. Here we show experimentally that a nanoscale spintronic oscillator (a magnetic tunnel junction) can be used to achieve spoken-digit recognition with an accuracy similar to that of state-of-the-art neural networks. We also determine the regime of magnetization dynamics that leads to the greatest performance. These results, combined with the ability of the spintronic oscillators to interact with each other, and their long lifetime and low energy consumption, open up a path to fast, parallel, on-chip computation based on networks of oscillators.

What does the functional organization of cortico-hippocampal networks tell us about the functional organization of memory?

PubMed

Reagh, Zachariah M; Ranganath, Charan

2018-04-25

Historically, research on the cognitive processes that support human memory proceeded, to a large extent, independently of research on the neural basis of memory. Accumulating evidence from neuroimaging, however, has enabled the field to develop a broader and more integrative perspective. Here, we briefly outline how advances in cognitive neuroscience can potentially shed light on concepts and controversies in human memory research. We argue that research on the functional properties of cortico-hippocampal networks informs us about how memories might be organized in the brain, which, in turn, helps to reconcile seemingly disparate perspectives in cognitive psychology. Finally, we discuss several open questions and directions for future research. Copyright © 2018 Elsevier B.V. All rights reserved.

Identification of the miRNA targetome in hippocampal neurons using RIP-seq.

PubMed

Malmevik, Josephine; Petri, Rebecca; Klussendorf, Thies; Knauff, Pina; Åkerblom, Malin; Johansson, Jenny; Soneji, Shamit; Jakobsson, Johan

2015-07-28

MicroRNAs (miRNAs) are key players in the regulation of neuronal processes by targeting a large network of target messenger RNAs (mRNAs). However, the identity and function of mRNAs targeted by miRNAs in specific cells of the brain are largely unknown. Here, we established an adeno-associated viral vector (AAV)-based neuron-specific Argonaute2:GFP-RNA immunoprecipitation followed by high-throughput sequencing to analyse the regulatory role of miRNAs in mouse hippocampal neurons. Using this approach, we identified more than two thousand miRNA targets in hippocampal neurons, regulating essential neuronal features such as cell signalling, transcription and axon guidance. Furthermore, we found that stable inhibition of the highly expressed miR-124 and miR-125 in hippocampal neurons led to significant but distinct changes in the AGO2 binding of target mRNAs, resulting in subsequent upregulation of numerous miRNA target genes. These findings greatly enhance our understanding of the miRNA targetome in hippocampal neurons.

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

PubMed

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

2015-04-08

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. Copyright © 2015 the authors 0270-6474/15/355459-12$15.00/0.

Sparse and Specific Coding during Information Transmission between Co-cultured Dentate Gyrus and CA3 Hippocampal Networks

PubMed Central

Poli, Daniele; Thiagarajan, Srikanth; DeMarse, Thomas B.; Wheeler, Bruce C.; Brewer, Gregory J.

2017-01-01

To better understand encoding and decoding of stimulus information in two specific hippocampal sub-regions, we isolated and co-cultured rat primary dentate gyrus (DG) and CA3 neurons within a two-chamber device with axonal connectivity via micro-tunnels. We tested the hypothesis that, in these engineered networks, decoding performance of stimulus site information would be more accurate when stimuli and information flow occur in anatomically correct feed-forward DG to CA3 vs. CA3 back to DG. In particular, we characterized the neural code of these sub-regions by measuring sparseness and uniqueness of the responses evoked by specific paired-pulse stimuli. We used the evoked responses in CA3 to decode the stimulation sites in DG (and vice-versa) by means of learning algorithms for classification (support vector machine, SVM). The device was placed over an 8 × 8 grid of extracellular electrodes (micro-electrode array, MEA) in order to provide a platform for monitoring development, self-organization, and improved access to stimulation and recording at multiple sites. The micro-tunnels were designed with dimensions 3 × 10 × 400 μm allowing axonal growth but not migration of cell bodies and long enough to exclude traversal by dendrites. Paired-pulse stimulation (inter-pulse interval 50 ms) was applied at 22 different sites and repeated 25 times in each chamber for each sub-region to evoke time-locked activity. DG-DG and CA3-CA3 networks were used as controls. Stimulation in DG drove signals through the axons in the tunnels to activate a relatively small set of specific electrodes in CA3 (sparse code). CA3-CA3 and DG-DG controls were less sparse in coding than CA3 in DG-CA3 networks. Using all target electrodes with the three highest spike rates (14%), the evoked responses in CA3 specified each stimulation site in DG with optimum uniqueness of 64%. Finally, by SVM learning, these evoked responses in CA3 correctly decoded the stimulation sites in DG for 43% of the

Two forms of electrical resonance at theta frequencies, generated by M-current, h-current and persistent Na+ current in rat hippocampal pyramidal cells

PubMed Central

Hu, Hua; Vervaeke, Koen; Storm, Johan F

2002-01-01

Coherent network oscillations in the brain are correlated with different behavioural states. Intrinsic resonance properties of neurons provide a basis for such oscillations. In the hippocampus, CA1 pyramidal neurons show resonance at theta (θ) frequencies (2-7 Hz). To study the mechanisms underlying θ-resonance, we performed whole-cell recordings from CA1 pyramidal cells (n = 73) in rat hippocampal slices. Oscillating current injections at different frequencies (ZAP protocol), revealed clear resonance with peak impedance at 2-5 Hz at ≈33 °C (increasing to ≈7 Hz at ≈38 °C). The θ-resonance showed a U-shaped voltage dependence, being strong at subthreshold, depolarized (≈-60 mV) and hyperpolarized (≈-80 mV) potentials, but weaker near the resting potential (-72 mV). Voltage clamp experiments revealed three non-inactivating currents operating in the subthresold voltage range: (1) M-current (IM), which activated positive to -65 mV and was blocked by the M/KCNQ channel blocker XE991 (10 μm); (2) h-current (Ih), which activated negative to -65 mV and was blocked by the h/HCN channel blocker ZD7288 (10 μm); and (3) a persistent Na+ current (INaP), which activated positive to -65 mV and was blocked by tetrodotoxin (TTX, 1 μm). In current clamp, XE991 or TTX suppressed the resonance at depolarized, but not hyperpolarized membrane potentials, whereas ZD7288 abolished the resonance only at hyperpolarized potentials. We conclude that these cells show two forms of θ-resonance: ‘M-resonance’ generated by the M-current and persistent Na+ current in depolarized cells, and ‘H-resonance’ generated by the h-current in hyperpolarized cells. Computer simulations supported this interpretation. These results suggest a novel function for M/KCNQ channels in the brain: to facilitate neuronal resonance and network oscillations in cortical neurons, thus providing a basis for an oscillation-based neural code. PMID:12482886

Endogenous Cortical Oscillations Constrain Neuromodulation by Weak Electric Fields

PubMed Central

Schmidt, Stephen L.; Iyengar, Apoorva K.; Foulser, A. Alban; Boyle, Michael R.; Fröhlich, Flavio

2014-01-01

Background Transcranial alternating current stimulation (tACS) is a non-invasive brain stimulation modality that may modulate cognition by enhancing endogenous neocortical oscillations with the application of sine-wave electric fields. Yet, the role of endogenous network activity in enabling and shaping the effects of tACS has remained unclear. Objective We combined optogenetic stimulation and multichannel slice electrophysiology to elucidate how the effect of weak sine-wave electric field depends on the ongoing cortical oscillatory activity. We hypothesized that the structure of the response to stimulation depended on matching the stimulation frequency to the endogenous cortical oscillation. Methods We studied the effect of weak sine-wave electric fields on oscillatory activity in mouse neocortical slices. Optogenetic control of the network activity enabled the generation of in vivo like cortical oscillations for studying the temporal relationship between network activity and sine-wave electric field stimulation. Results Weak electric fields enhanced endogenous oscillations but failed to induce a frequency shift of the ongoing oscillation for stimulation frequencies that were not matched to the endogenous oscillation. This constraint on the effect of electric field stimulation imposed by endogenous network dynamics was limited to the case of weak electric fields targeting in vivo-like network dynamics. Together, these results suggest that the key mechanism of tACS may be enhancing but not overriding of intrinsic network dynamics. Conclusion Our results contribute to understanding the inconsistent tACS results from human studies and propose that stimulation precisely adjusted in frequency to the endogenous oscillations is key to rational design of non-invasive brain stimulation paradigms. PMID:25129402

Abnormalities of hippocampal-cortical connectivity in temporal lobe epilepsy patients with hippocampal sclerosis

NASA Astrophysics Data System (ADS)

Li, Wenjing; He, Huiguang; Lu, Jingjing; Wang, Chunheng; Li, Meng; Lv, Bin; Jin, Zhengyu

2011-03-01

Hippocampal sclerosis (HS) is the most common damage seen in the patients with temporal lobe epilepsy (TLE). In the present study, the hippocampal-cortical connectivity was defined as the correlation between the hippocampal volume and cortical thickness at each vertex throughout the whole brain. We aimed to investigate the differences of ipsilateral hippocampal-cortical connectivity between the unilateral TLE-HS patients and the normal controls. In our study, the bilateral hippocampal volumes were first measured in each subject, and we found that the ipsilateral hippocampal volume significantly decreased in the left TLE-HS patients. Then, group analysis showed significant thinner average cortical thickness of the whole brain in the left TLE-HS patients compared with the normal controls. We found significantly increased ipsilateral hippocampal-cortical connectivity in the bilateral superior temporal gyrus, the right cingulate gyrus and the left parahippocampal gyrus of the left TLE-HS patients, which indicated structural vulnerability related to the hippocampus atrophy in the patient group. However, for the right TLE-HS patients, no significant differences were found between the patients and the normal controls, regardless of the ipsilateral hippocampal volume, the average cortical thickness or the patterns of hippocampal-cortical connectivity, which might be related to less atrophies observed in the MRI scans. Our study provided more evidence for the structural abnormalities in the unilateral TLE-HS patients.

The frequency of hippocampal theta rhythm is modulated on a circadian period and is entrained by food availability.

PubMed

Munn, Robert G K; Tyree, Susan M; McNaughton, Neil; Bilkey, David K

2015-01-01

The hippocampal formation plays a critical role in the generation of episodic memory. While the encoding of the spatial and contextual components of memory have been extensively studied, how the hippocampus encodes temporal information, especially at long time intervals, is less well understood. The activity of place cells in hippocampus has previously been shown to be modulated at a circadian time-scale, entrained by a behavioral stimulus, but not entrained by light. The experimental procedures used in the previous study of this phenomenon, however, necessarily conflated two alternative entraining stimuli, the exposure to the recording environment and the availability of food, making it impossible to distinguish between these possibilities. Here we demonstrate that the frequency of theta-band hippocampal EEG varies with a circadian period in freely moving animals and that this periodicity mirrors changes in the firing rate of hippocampal neurons. Theta activity serves, therefore, as a proxy of circadian-modulated hippocampal neuronal activity. We then demonstrate that the frequency of hippocampal theta driven by stimulation of the reticular formation also varies with a circadian period. Because this effect can be observed without having to feed the animal to encourage movement we were able to identify what stimulus entrains the circadian oscillation. We show that with reticular-activated recordings started at various times of the day the frequency of theta varies quasi-sinusoidally with a 25 h period and phase-aligned when referenced to the animal's regular feeding time, but not the recording start time. Furthermore, we show that theta frequency consistently varied with a circadian period when the data obtained from repeated recordings started at various times of the day were referenced to the start of food availability in the recording chamber. This pattern did not occur when data were referenced to the start of the recording session or to the actual time of day

Synchronization transition in neuronal networks composed of chaotic or non-chaotic oscillators.

PubMed

Xu, Kesheng; Maidana, Jean Paul; Castro, Samy; Orio, Patricio

2018-05-30

Chaotic dynamics has been shown in the dynamics of neurons and neural networks, in experimental data and numerical simulations. Theoretical studies have proposed an underlying role of chaos in neural systems. Nevertheless, whether chaotic neural oscillators make a significant contribution to network behaviour and whether the dynamical richness of neural networks is sensitive to the dynamics of isolated neurons, still remain open questions. We investigated synchronization transitions in heterogeneous neural networks of neurons connected by electrical coupling in a small world topology. The nodes in our model are oscillatory neurons that - when isolated - can exhibit either chaotic or non-chaotic behaviour, depending on conductance parameters. We found that the heterogeneity of firing rates and firing patterns make a greater contribution than chaos to the steepness of the synchronization transition curve. We also show that chaotic dynamics of the isolated neurons do not always make a visible difference in the transition to full synchrony. Moreover, macroscopic chaos is observed regardless of the dynamics nature of the neurons. However, performing a Functional Connectivity Dynamics analysis, we show that chaotic nodes can promote what is known as multi-stable behaviour, where the network dynamically switches between a number of different semi-synchronized, metastable states.

Aged rats show dominant modulation of lower frequency hippocampal theta rhythm during running.

PubMed

Li, Jia-Yi; Kuo, Terry B J; Yang, Cheryl C H

2016-10-01

Aging causes considerable decline in both physiological and mental functions, particularly cognitive function. The hippocampal theta rhythm (4-12Hz) is related to both cognition and locomotion. Aging-related findings of the frequency and amplitude of hippocampal theta oscillations are inconsistent and occasionally contradictory. This inconsistency may be due to the effects of the sleep/wake state and different frequency subbands being overlooked. We assumed that aged rats have lower responses of the hippocampal theta rhythm during running, which is mainly due to the dominant modulation of theta frequency subbands related to cognition. By simultaneously recording electroencephalography, physical activity (PA), and the heart rate (HR), this experiment explored the theta oscillations before, during, and after treadmill running at a constant speed in 8-week-old (adult) and 60-week-old (middle-aged) rats. Compared with adult rats, the middle-aged rats exhibited lower theta activity in all frequency ranges before running. Running increased the theta frequency (Frq, 4-12Hz), total activity of the whole theta band (total power, TP), activity of the middle theta frequency (MT, 6.5-9.5Hz), and PA in both age groups. However, the middle-aged rats still showed fewer changes in these parameters during the whole running process. After the waking baseline values were substracted, middle-aged rats showed significantly fewer differences in ΔFrq, ΔTP, and ΔMT but significantly more differences in low-frequency theta activity (4.0-6.5Hz) and HR than the adult rats did. Therefore, the decreasing activity and response of the whole theta band in the middle-aged rats resulted in dominant modulation of the middle to lower frequency (4.0-9.5Hz) theta rhythm. The different alterations in the theta rhythm during treadmill running in the two groups may reflect that learning decline with age. Copyright © 2016 Elsevier Inc. All rights reserved.

Neuromorphic computing with nanoscale spintronic oscillators

PubMed Central

Torrejon, Jacob; Riou, Mathieu; Araujo, Flavio Abreu; Tsunegi, Sumito; Khalsa, Guru; Querlioz, Damien; Bortolotti, Paolo; Cros, Vincent; Fukushima, Akio; Kubota, Hitoshi; Yuasa, Shinji; Stiles, M. D.; Grollier, Julie

2017-01-01

Neurons in the brain behave as non-linear oscillators, which develop rhythmic activity and interact to process information1. Taking inspiration from this behavior to realize high density, low power neuromorphic computing will require huge numbers of nanoscale non-linear oscillators. Indeed, a simple estimation indicates that, in order to fit a hundred million oscillators organized in a two-dimensional array inside a chip the size of a thumb, their lateral dimensions must be smaller than one micrometer. However, despite multiple theoretical proposals2–5, and several candidates such as memristive6 or superconducting7 oscillators, there is no proof of concept today of neuromorphic computing with nano-oscillators. Indeed, nanoscale devices tend to be noisy and to lack the stability required to process data in a reliable way. Here, we show experimentally that a nanoscale spintronic oscillator8,9 can achieve spoken digit recognition with accuracies similar to state of the art neural networks. We pinpoint the regime of magnetization dynamics leading to highest performance. These results, combined with the exceptional ability of these spintronic oscillators to interact together, their long lifetime, and low energy consumption, open the path to fast, parallel, on-chip computation based on networks of oscillators. PMID:28748930

Two different mechanisms associated with ripple-like oscillations (100-250 Hz) in the human epileptic subiculum in vitro

PubMed Central

Alvarado-Rojas, C; Huberfeld, G; Baulac, M; Clemenceau, S; Charpier, S; Miles, R; Menendez de la Prida, L; Le Van Quyen, M

2015-01-01

Transient high-frequency oscillations (150-600 Hz) in local field potential generated by human hippocampal and parahippocampal areas have been related to both physiological and pathological processes. The cellular basis and effects of normal and abnormal forms of high-frequency oscillations (HFO) has been controversial. Here, we searched for HFOs in slices of the subiculum prepared from human hippocampal tissue resected for treatment of pharmacoresistant epilepsy. HFOs occurred spontaneously in extracellular field potentials during interictal discharges (IID) and also during pharmacologically induced preictal discharges (PID) preceding ictal-like events. While most of these events might be considered pathological since they invaded the fast ripple band (>250 Hz), others were spectrally similar to physiological ripples (150-250 Hz). Do similar cellular mechanisms underly IID-ripples and PID-ripples? Are ripple-like oscillations a valid proxy of epileptogenesis in human TLE? With combined intra- or juxta-cellular and extracellular recordings, we showed that, despite overlapping spectral components, ripple-like IID and PID oscillations were associated with different cellular and synaptic mechanisms. IID-ripples were associated with rhythmic GABAergic and glutamatergic synaptic potentials with moderate neuronal firing. In contrast, PID-ripples were associated with depolarizing synaptic inputs frequently reaching the threshold for bursting in most cells. Thus ripple-like oscillations (100-250 Hz) in the human epileptic hippocampus are associated with different mechanisms for synchrony reflecting distinct dynamic changes in inhibition and excitation during interictal and pre-ictal states. PMID:25448920

Classic hippocampal sclerosis and hippocampal-onset epilepsy produced by a single “cryptic” episode of focal hippocampal excitation in awake rats

PubMed Central

Norwood, Braxton A.; Bumanglag, Argyle V.; Osculati, Francesco; Sbarbati, Andrea; Marzola, Pasquina; Nicolato, Elena; Fabene, Paolo F.; Sloviter, Robert S.

2010-01-01

In refractory temporal lobe epilepsy, seizures often arise from a shrunken hippocampus exhibiting a pattern of selective neuron loss called “classic hippocampal sclerosis.” No single experimental injury has reproduced this specific pathology, suggesting that hippocampal atrophy might be a progressive “endstage” pathology resulting from years of spontaneous seizures. We posed the alternate hypothesis that classic hippocampal sclerosis results from a single excitatory event that has never been successfully modeled experimentally because convulsive status epilepticus, the insult most commonly used to produce epileptogenic brain injury, is too severe and necessarily terminated before the hippocampus receives the needed duration of excitation. We tested this hypothesis by producing prolonged hippocampal excitation in awake rats without causing convulsive status epilepticus. Two daily 30-minute episodes of perforant pathway stimulation in Sprague-Dawley rats increased granule cell paired-pulse inhibition, decreased epileptiform afterdischarge durations during 8 hours of subsequent stimulation, and prevented convulsive status epilepticus. Similarly, one 8-hour episode of reduced-intensity stimulation in Long-Evans rats, which are relatively resistant to developing status epilepticus, produced hippocampal discharges without causing status epilepticus. Both paradigms immediately produced the extensive neuronal injury that defines classic hippocampal sclerosis, without giving any clinical indication during the insult that an injury was being inflicted. Spontaneous hippocampal-onset seizures began 16–25 days post-injury, before hippocampal atrophy developed, as demonstrated by sequential magnetic resonance imaging. These results indicate that classic hippocampal sclerosis is uniquely produced by a single episode of clinically “cryptic” excitation. Epileptogenic insults may often involve prolonged excitation that goes undetected at the time of injury. PMID

Passive synchronization for Markov jump genetic oscillator networks with time-varying delays.

PubMed

Lu, Li; He, Bing; Man, Chuntao; Wang, Shun

2015-04-01

In this paper, the synchronization problem of coupled Markov jump genetic oscillator networks with time-varying delays and external disturbances is investigated. By introducing the drive-response concept, a novel mode-dependent control scheme is proposed, which guarantees that the synchronization can be achieved. By applying the Lyapunov-Krasovskii functional method and stochastic analysis, sufficient conditions are established based on passivity theory in terms of linear matrix inequalities. A numerical example is provided to demonstrate the effectiveness of our theoretical results. Copyright © 2015 Elsevier Inc. All rights reserved.

High frequency inductive lamp and power oscillator

DOEpatents

Kirkpatrick, Douglas A.; Gitsevich, Aleksandr

2005-09-27

An oscillator includes an amplifier having an input and an output, a feedback network connected between the input of the amplifier and the output of the amplifier, the feedback network being 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 a tuning circuit connected to the input of the amplifier, wherein the tuning circuit is continuously variable and consists of solid state electrical components with no mechanically adjustable devices including a pair of diodes connected to each other at their respective cathodes with a control voltage connected at the junction of the diodes. Another oscillator includes an amplifier having an input and an output, a feedback network connected between the input of the amplifier and the output of the amplifier, the feedback network being 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 transmission lines connected to the input of the amplifier with an input pad and a perpendicular transmission line extending from the input pad and forming a leg of a resonant "T", and wherein the feedback network is coupled to the leg of the resonant "T".

Review: Hippocampal sclerosis in epilepsy: a neuropathology review

PubMed Central

Thom, Maria

2014-01-01

Hippocampal sclerosis (HS) is a common pathology encountered in mesial temporal lobe epilepsy (MTLE) as well as other epilepsy syndromes and in both surgical and post-mortem practice. The 2013 International League Against Epilepsy (ILAE) classification segregates HS into typical (type 1) and atypical (type 2 and 3) groups, based on the histological patterns of subfield neuronal loss and gliosis. In addition, granule cell reorganization and alterations of interneuronal populations, neuropeptide fibre networks and mossy fibre sprouting are distinctive features of HS associated with epilepsies; they can be useful diagnostic aids to discriminate from other causes of HS, as well as highlighting potential mechanisms of hippocampal epileptogenesis. The cause of HS remains elusive and may be multifactorial; the contribution of febrile seizures, genetic susceptibility, inflammatory and neurodevelopmental factors are discussed. Post-mortem based research in HS, as an addition to studies on surgical samples, has the added advantage of enabling the study of the wider network changes associated with HS, the long-term effects of epilepsy on the pathology and associated comorbidities. It is likely that HS is heterogeneous in aspects of its cause, epileptogenetic mechanisms, network alterations and response to medical and surgical treatments. Future neuropathological studies will contribute to better recognition and understanding of these clinical and patho-aetiological subtypes of HS. PMID:24762203

Long-term neuropsychological, neuroanatomical, and life outcome in hippocampal amnesia

PubMed Central

Warren, David E.; Duff, Melissa C.; Magnotta, Vincent; Capizzano, Aristides A; Cassell, Martin D.; Tranel, Daniel

2012-01-01

Focal bilateral hippocampal damage typically causes severe and selective amnesia for new declarative information (facts and events), a cognitive deficit that greatly impacts the ability to live a normal, fully-independent life. We describe the case of 1846, a 48-year-old woman with profound hippocampal amnesia following status epilepticus and an associated anoxic episode at age 30. 1846 has undergone extensive neuropsychological testing on many occasions over the 18 years since her injury, and we present data indicating that her memory impairment has remained severe and stable during that time. New, high-resolution structural MRI studies of 1846's brain reveal substantial bilateral hippocampal atrophy resembling that of other well-known amnesic patients. In spite of severe amnesia, 1846 lives a full and mostly independent adult life, facilitated by an extensive social support network of family and friends. Her case provides an example of a rare and unlikely positive outcome in the face of severe memory problems. PMID:22401298

Hippocampal Synaptic Expansion Induced by Spatial Experience in Rats Correlates with Improved Information Processing in the Hippocampus.

PubMed

Carasatorre, Mariana; Ochoa-Alvarez, Adrian; Velázquez-Campos, Giovanna; Lozano-Flores, Carlos; Ramírez-Amaya, Víctor; Díaz-Cintra, Sofía Y

2015-01-01

Spatial water maze (WM) overtraining induces hippocampal mossy fiber (MF) expansion, and it has been suggested that spatial pattern separation depends on the MF pathway. We hypothesized that WM experience inducing MF expansion in rats would improve spatial pattern separation in the hippocampal network. We first tested this by using the the delayed non-matching to place task (DNMP), in animals that had been previously trained on the water maze (WM) and found that these animals, as well as animals treated as swim controls (SC), performed better than home cage control animals the DNMP task. The "catFISH" imaging method provided neurophysiological evidence that hippocampal pattern separation improved in animals treated as SC, and this improvement was even clearer in animals that experienced the WM training. Moreover, these behavioral treatments also enhance network reliability and improve partial pattern separation in CA1 and pattern completion in CA3. By measuring the area occupied by synaptophysin staining in both the stratum oriens and the stratun lucidum of the distal CA3, we found evidence of structural synaptic plasticity that likely includes MF expansion. Finally, the measures of hippocampal network coding obtained with catFISH correlate significantly with the increased density of synaptophysin staining, strongly suggesting that structural synaptic plasticity in the hippocampus induced by the WM and SC experience is related to the improvement of spatial information processing in the hippocampus.

Oscillations contribute to memory consolidation by changing criticality and stability in the brain

NASA Astrophysics Data System (ADS)

Wu, Jiaxing; Skilling, Quinton; Ognjanovski, Nicolette; Aton, Sara; Zochowski, Michal

Oscillations are a universal feature of every level of brain dynamics and have been shown to contribute to many brain functions. To investigate the fundamental mechanism underpinning oscillatory activity, the properties of heterogeneous networks are compared in situations with and without oscillations. Our results show that both network criticality and stability are changed in the presence of oscillations. Criticality describes the network state of neuronal avalanche, a cascade of bursts of action potential firing in neural network. Stability measures how stable the spike timing relationship between neuron pairs is over time. Using a detailed spiking model, we found that the branching parameter σ changes relative to oscillation and structural network properties, corresponding to transmission among different critical states. Also, analysis of functional network structures shows that the oscillation helps to stabilize neuronal representation of memory. Further, quantitatively similar results are observed in biological data recorded in vivo. In summary, we have observed that, by regulating the neuronal firing pattern, oscillations affect both criticality and stability properties of the network, and thus contribute to memory formation.

Control analysis for autonomously oscillating biochemical networks.

PubMed Central

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

2002-01-01

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

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

PubMed

Petsophonsakul, Petnoi; Richetin, Kevin; Andraini, Trinovita; Roybon, Laurent; Rampon, Claire

2017-08-01

During memory formation, structural rearrangements of dendritic spines provide a mean to durably modulate synaptic connectivity within neuronal networks. New neurons generated throughout the adult life in the dentate gyrus of the hippocampus contribute to learning and memory. As these neurons become incorporated into the network, they generate huge numbers of new connections that modify hippocampal circuitry and functioning. However, it is yet unclear as to how the dynamic process of memory formation influences their synaptic integration into neuronal circuits. New memories are established according to a multistep process during which new information is first acquired and then consolidated to form a stable memory trace. Upon recall, memory is transiently destabilized and vulnerable to modification. Using contextual fear conditioning, we found that learning was associated with an acceleration of dendritic spines formation of adult-born neurons, and that spine connectivity becomes strengthened after memory consolidation. Moreover, we observed that afferent connectivity onto adult-born neurons is enhanced after memory retrieval, while extinction training induces a change of spine shapes. Together, these findings reveal that the neuronal activity supporting memory processes strongly influences the structural dendritic integration of adult-born neurons into pre-existing neuronal circuits. Such change of afferent connectivity is likely to impact the overall wiring of hippocampal network, and consequently, to regulate hippocampal function.

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

PubMed

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

2016-01-01

This paper describes a million-plus granule cell compartmental model of the rat hippocampal dentate gyrus, including excitatory, perforant path input from the entorhinal cortex, and feedforward and feedback inhibitory input from dentate interneurons. The model includes experimentally determined morphological and biophysical properties of granule cells, together with glutamatergic AMPA-like EPSP and GABAergic GABAA-like IPSP synaptic excitatory and inhibitory inputs, respectively. Each granule cell was composed of approximately 200 compartments having passive and active conductances distributed throughout the somatic and dendritic regions. Modeling excitatory input from the entorhinal cortex was guided by axonal transport studies documenting the topographical organization of projections from subregions of the medial and lateral entorhinal cortex, plus other important details of the distribution of glutamatergic inputs to the dentate gyrus. Information contained within previously published maps of this major hippocampal afferent were systematically converted to scales that allowed the topographical distribution and relative synaptic densities of perforant path inputs to be quantitatively estimated for inclusion in the current model. Results showed that when medial and lateral entorhinal cortical neurons maintained Poisson random firing, dentate granule cells expressed, throughout the million-cell network, a robust nonrandom pattern of spiking best described as a spatiotemporal "clustering." To identify the network property or properties responsible for generating such firing "clusters," we progressively eliminated from the model key mechanisms, such as feedforward and feedback inhibition, intrinsic membrane properties underlying rhythmic burst firing, and/or topographical organization of entorhinal afferents. Findings conclusively identified topographical organization of inputs as the key element responsible for generating a spatiotemporal distribution of clustered

Stochastic oscillations in models of epidemics on a network of cities

NASA Astrophysics Data System (ADS)

Rozhnova, G.; Nunes, A.; McKane, A. J.

2011-11-01

We carry out an analytic investigation of stochastic oscillations in a susceptible-infected-recovered model of disease spread on a network of n cities. In the model a fraction fjk of individuals from city k commute to city j, where they may infect, or be infected by, others. Starting from a continuous-time Markov description of the model the deterministic equations, which are valid in the limit when the population of each city is infinite, are recovered. The stochastic fluctuations about the fixed point of these equations are derived by use of the van Kampen system-size expansion. The fixed point structure of the deterministic equations is remarkably simple: A unique nontrivial fixed point always exists and has the feature that the fraction of susceptible, infected, and recovered individuals is the same for each city irrespective of its size. We find that the stochastic fluctuations have an analogously simple dynamics: All oscillations have a single frequency, equal to that found in the one-city case. We interpret this phenomenon in terms of the properties of the spectrum of the matrix of the linear approximation of the deterministic equations at the fixed point.

Dual coding with STDP in a spiking recurrent neural network model of the hippocampus.

PubMed

Bush, Daniel; Philippides, Andrew; Husbands, Phil; O'Shea, Michael

2010-07-01

The firing rate of single neurons in the mammalian hippocampus has been demonstrated to encode for a range of spatial and non-spatial stimuli. It has also been demonstrated that phase of firing, with respect to the theta oscillation that dominates the hippocampal EEG during stereotype learning behaviour, correlates with an animal's spatial location. These findings have led to the hypothesis that the hippocampus operates using a dual (rate and temporal) coding system. To investigate the phenomenon of dual coding in the hippocampus, we examine a spiking recurrent network model with theta coded neural dynamics and an STDP rule that mediates rate-coded Hebbian learning when pre- and post-synaptic firing is stochastic. We demonstrate that this plasticity rule can generate both symmetric and asymmetric connections between neurons that fire at concurrent or successive theta phase, respectively, and subsequently produce both pattern completion and sequence prediction from partial cues. This unifies previously disparate auto- and hetero-associative network models of hippocampal function and provides them with a firmer basis in modern neurobiology. Furthermore, the encoding and reactivation of activity in mutually exciting Hebbian cell assemblies demonstrated here is believed to represent a fundamental mechanism of cognitive processing in the brain.

A fast, robust and tunable synthetic gene oscillator.

PubMed

Stricker, Jesse; Cookson, Scott; Bennett, Matthew R; Mather, William H; Tsimring, Lev S; Hasty, Jeff

2008-11-27

One defining goal of synthetic biology is the development of engineering-based approaches that enable the construction of gene-regulatory networks according to 'design specifications' generated from computational modelling. This approach provides a systematic framework for exploring how a given regulatory network generates a particular phenotypic behaviour. Several fundamental gene circuits have been developed using this approach, including toggle switches and oscillators, and these have been applied in new contexts such as triggered biofilm development and cellular population control. Here we describe an engineered genetic oscillator in Escherichia coli that is fast, robust and persistent, with tunable oscillatory periods as fast as 13 min. The oscillator was designed using a previously modelled network architecture comprising linked positive and negative feedback loops. Using a microfluidic platform tailored for single-cell microscopy, we precisely control environmental conditions and monitor oscillations in individual cells through multiple cycles. Experiments reveal remarkable robustness and persistence of oscillations in the designed circuit; almost every cell exhibited large-amplitude fluorescence oscillations throughout observation runs. The oscillatory period can be tuned by altering inducer levels, temperature and the media source. Computational modelling demonstrates that the key design principle for constructing a robust oscillator is a time delay in the negative feedback loop, which can mechanistically arise from the cascade of cellular processes involved in forming a functional transcription factor. The positive feedback loop increases the robustness of the oscillations and allows for greater tunability. Examination of our refined model suggested the existence of a simplified oscillator design without positive feedback, and we construct an oscillator strain confirming this computational prediction.

Requiring collaboration: Hippocampal-prefrontal networks needed in spatial working memory and ageing. A multivariate analysis approach.

PubMed

Zancada-Menendez, C; Alvarez-Suarez, P; Sampedro-Piquero, P; Cuesta, M; Begega, A

2017-04-01

Ageing is characterized by a decline in the processes of retention and storage of spatial information. We have examined the behavioural performance of adult rats (3months old) and aged rats (18months old) in a spatial complex task (delayed match to sample). The spatial task was performed in the Morris water maze and consisted of three sessions per day over a period of three consecutive days. Each session consisted of two trials (one sample and retention) and inter-session intervals of 5min. Behavioural results showed that the spatial task was difficult for middle aged group. This worse execution could be associated with impairments of processing speed and spatial information retention. We examined the changes in the neuronal metabolic activity of different brain regions through cytochrome C oxidase histochemistry. Then, we performed MANOVA and Discriminant Function Analyses to determine the functional profile of the brain networks that are involved in the spatial learning of the adult and middle-aged groups. This multivariate analysis showed two principal functional networks that necessarily participate in this spatial learning. The first network was composed of the supramammillary nucleus, medial mammillary nucleus, CA3, and CA1. The second one included the anterior cingulate, prelimbic, and infralimbic areas of the prefrontal cortex, dentate gyrus, and amygdala complex (basolateral l and central subregions). There was a reduction in the hippocampal-supramammilar network in both learning groups, whilst there was an overactivation in the executive network, especially in the aged group. This response could be due to a higher requirement of the executive control in a complex spatial memory task in older animals. Copyright © 2017 Elsevier Inc. All rights reserved.

On influences of global and local cues on the rate of synchronization of oscillator networks

PubMed Central

Wang, Yongqiang; Doyle, Francis J.

2011-01-01

Synchronization of connected oscillator networks under global and local cues is ubiquitous in both science and engineering. Over the last few decades, enormous attention has been paid to study synchronization conditions of connected oscillators in chemistry, physics, mechanics, and particularly in biology. However, the influences of global and local cues on the rate of synchronization have not been fully studied. It is widespread that synchronization is achieved in the simultaneous presence of both global and local cues, such as intercellular coupling signals and external entrainment signals in terms of biological oscillators, and inter-neighbor coupling signals between follower nodes and central guiding signals in terms of groups of mobile autonomous agents. We prove in this paper that strength of the global cue is the only determinant of the rate of synchronization. More specifically, we prove that a stronger global cue means a faster rate of synchronization whereas a stronger local cue does not necessarily make the synchronization rate faster. Our results not only apply to the noise free case, but also apply to the case that the oscillator natural frequencies are subject to white noise. The analysis does not require the interplay to be symmetric or balanced. Simulation results are given to illustrate the proposed results. PMID:21607201

Excitation and inhibition compete to control spiking during hippocampal ripples: intracellular study in behaving mice.

PubMed

English, Daniel F; Peyrache, Adrien; Stark, Eran; Roux, Lisa; Vallentin, Daniela; Long, Michael A; Buzsáki, György

2014-12-03

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 of the rhythm and the recruitment of spikes from pyramidal neurons are still poorly understood. Using intracellular, sharp electrode recordings in freely moving, drug-free mice, we observed consistent large depolarizations in CA1 pyramidal cells during sharp wave ripples, which are associated with ripple frequency fluctuation of the membrane potential ("intracellular ripple"). Despite consistent depolarization, often exceeding pre-ripple spike threshold values, current pulse-induced spikes were strongly suppressed, indicating that spiking was under the control of concurrent shunting inhibition. Ripple events were followed by a prominent afterhyperpolarization and spike suppression. Action potentials during and outside ripples were orthodromic, arguing against ectopic spike generation, which has been postulated by computational models of ripple generation. These findings indicate that dendritic excitation of pyramidal neurons during ripples is countered by shunting of the membrane and postripple silence is mediated by hyperpolarizing inhibition. Copyright © 2014 the authors 0270-6474/14/3316509-09$15.00/0.

Disrupted hippocampal sharp‐wave ripple‐associated spike dynamics in a transgenic mouse model of dementia

PubMed Central

Witton, Jonathan; Staniaszek, Lydia E.; Bartsch, Ullrich; Randall, Andrew D.; Jones, Matthew W.

2015-01-01

Key points High frequency (100–250 Hz) neuronal oscillations in the hippocampus, known as sharp‐wave ripples (SWRs), synchronise the firing behaviour of groups of neurons and play a key role in memory consolidation.Learning and memory are severely compromised in dementias such as Alzheimer's disease; however, the effects of dementia‐related pathology on SWRs are unknown.The frequency and temporal structure of SWRs was disrupted in a transgenic mouse model of tauopathy (one of the major hallmarks of several dementias).Excitatory pyramidal neurons were more likely to fire action potentials in a phase‐locked manner during SWRs in the mouse model of tauopathy; conversely, inhibitory interneurons were less likely to fire phase‐locked spikes during SWRs.These findings indicate there is reduced inhibitory control of hippocampal network events and point to a novel mechanism which may underlie the cognitive impairments in this model of dementia. Abstract Neurons within the CA1 region of the hippocampus are co‐activated during high frequency (100–250 Hz) sharp‐wave ripple (SWR) activity in a manner that probably drives synaptic plasticity and promotes memory consolidation. In this study we have used a transgenic mouse model of dementia (rTg4510 mice), which overexpresses a mutant form of tau protein, to examine the effects of tauopathy on hippocampal SWRs and associated neuronal firing. Tetrodes were used to record simultaneous extracellular action potentials and local field potentials from the dorsal CA1 pyramidal cell layer of 7‐ to 8‐month‐old wild‐type and rTg4510 mice at rest in their home cage. At this age point these mice exhibit neurofibrillary tangles, neurodegeneration and cognitive deficits. Epochs of sleep or quiet restfulness were characterised by minimal locomotor activity and a low theta/delta ratio in the local field potential power spectrum. SWRs detected off‐line were significantly lower in amplitude and had an altered temporal

Disrupted hippocampal sharp-wave ripple-associated spike dynamics in a transgenic mouse model of dementia.

PubMed

Witton, Jonathan; Staniaszek, Lydia E; Bartsch, Ullrich; Randall, Andrew D; Jones, Matthew W; Brown, Jonathan T

2016-08-15

High frequency (100-250 Hz) neuronal oscillations in the hippocampus, known as sharp-wave ripples (SWRs), synchronise the firing behaviour of groups of neurons and play a key role in memory consolidation. Learning and memory are severely compromised in dementias such as Alzheimer's disease; however, the effects of dementia-related pathology on SWRs are unknown. The frequency and temporal structure of SWRs was disrupted in a transgenic mouse model of tauopathy (one of the major hallmarks of several dementias). Excitatory pyramidal neurons were more likely to fire action potentials in a phase-locked manner during SWRs in the mouse model of tauopathy; conversely, inhibitory interneurons were less likely to fire phase-locked spikes during SWRs. These findings indicate there is reduced inhibitory control of hippocampal network events and point to a novel mechanism which may underlie the cognitive impairments in this model of dementia. Neurons within the CA1 region of the hippocampus are co-activated during high frequency (100-250 Hz) sharp-wave ripple (SWR) activity in a manner that probably drives synaptic plasticity and promotes memory consolidation. In this study we have used a transgenic mouse model of dementia (rTg4510 mice), which overexpresses a mutant form of tau protein, to examine the effects of tauopathy on hippocampal SWRs and associated neuronal firing. Tetrodes were used to record simultaneous extracellular action potentials and local field potentials from the dorsal CA1 pyramidal cell layer of 7- to 8-month-old wild-type and rTg4510 mice at rest in their home cage. At this age point these mice exhibit neurofibrillary tangles, neurodegeneration and cognitive deficits. Epochs of sleep or quiet restfulness were characterised by minimal locomotor activity and a low theta/delta ratio in the local field potential power spectrum. SWRs detected off-line were significantly lower in amplitude and had an altered temporal structure in rTg4510 mice. Nevertheless

Impact of symmetry breaking in networks of globally coupled oscillators

NASA Astrophysics Data System (ADS)

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

2015-05-01

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

Membrane Potential Dynamics of CA1 Pyramidal Neurons During Hippocampal Ripples in Awake Mice

PubMed Central

Hulse, Brad K.; Moreaux, Laurent C.; Lubenov, Evgueniy V.; Siapas, Athanassios G.

2016-01-01

Ripples are high-frequency oscillations associated with population bursts in area CA1 of the hippocampus that play a prominent role in theories of memory consolidation. While spiking during ripples has been extensively studied, our understanding of the subthreshold behavior of hippocampal neurons during these events remains incomplete. Here, we combine in vivo whole-cell and multisite extracellular recordings to characterize the membrane potential dynamics of identified CA1 pyramidal neurons during ripples. We find that the subthreshold depolarization during ripples is uncorrelated with the net excitatory input to CA1, while the post-ripple hyperpolarization varies proportionately. This clarifies the circuit mechanism keeping most neurons silent during ripples. On a finer time scale, the phase delay between intracellular and extracellular ripple oscillations varies systematically with membrane potential. Such smoothly varying delays are inconsistent with models of intracellular ripple generation involving perisomatic inhibition alone. Instead, they suggest that ripple-frequency excitation leading inhibition shapes intracellular ripple oscillations. PMID:26889811

Network-induced oscillatory behavior in material flow networks and irregular business cycles

NASA Astrophysics Data System (ADS)

Helbing, Dirk; Lämmer, Stefen; Witt, Ulrich; Brenner, Thomas

2004-11-01

Network theory is rapidly changing our understanding of complex systems, but the relevance of topological features for the dynamic behavior of metabolic networks, food webs, production systems, information networks, or cascade failures of power grids remains to be explored. Based on a simple model of supply networks, we offer an interpretation of instabilities and oscillations observed in biological, ecological, economic, and engineering systems. We find that most supply networks display damped oscillations, even when their units—and linear chains of these units—behave in a nonoscillatory way. Moreover, networks of damped oscillators tend to produce growing oscillations. This surprising behavior offers, for example, a different interpretation of business cycles and of oscillating or pulsating processes. The network structure of material flows itself turns out to be a source of instability, and cyclical variations are an inherent feature of decentralized adjustments.

Nasal Respiration Entrains Human Limbic Oscillations and Modulates Cognitive Function

PubMed Central

Jiang, Heidi; Zhou, Guangyu; Arora, Nikita; Schuele, Stephan; Rosenow, Joshua; Gottfried, Jay A.

2016-01-01

The need to breathe links the mammalian olfactory system inextricably to the respiratory rhythms that draw air through the nose. In rodents and other small animals, slow oscillations of local field potential activity are driven at the rate of breathing (∼2–12 Hz) in olfactory bulb and cortex, and faster oscillatory bursts are coupled to specific phases of the respiratory cycle. These dynamic rhythms are thought to regulate cortical excitability and coordinate network interactions, helping to shape olfactory coding, memory, and behavior. However, while respiratory oscillations are a ubiquitous hallmark of olfactory system function in animals, direct evidence for such patterns is lacking in humans. In this study, we acquired intracranial EEG data from rare patients (Ps) with medically refractory epilepsy, enabling us to test the hypothesis that cortical oscillatory activity would be entrained to the human respiratory cycle, albeit at the much slower rhythm of ∼0.16–0.33 Hz. Our results reveal that natural breathing synchronizes electrical activity in human piriform (olfactory) cortex, as well as in limbic-related brain areas, including amygdala and hippocampus. Notably, oscillatory power peaked during inspiration and dissipated when breathing was diverted from nose to mouth. Parallel behavioral experiments showed that breathing phase enhances fear discrimination and memory retrieval. Our findings provide a unique framework for understanding the pivotal role of nasal breathing in coordinating neuronal oscillations to support stimulus processing and behavior. SIGNIFICANCE STATEMENT Animal studies have long shown that olfactory oscillatory activity emerges in line with the natural rhythm of breathing, even in the absence of an odor stimulus. Whether the breathing cycle induces cortical oscillations in the human brain is poorly understood. In this study, we collected intracranial EEG data from rare patients with medically intractable epilepsy, and found evidence

Nasal Respiration Entrains Human Limbic Oscillations and Modulates Cognitive Function.

PubMed

Zelano, Christina; Jiang, Heidi; Zhou, Guangyu; Arora, Nikita; Schuele, Stephan; Rosenow, Joshua; Gottfried, Jay A

2016-12-07

The need to breathe links the mammalian olfactory system inextricably to the respiratory rhythms that draw air through the nose. In rodents and other small animals, slow oscillations of local field potential activity are driven at the rate of breathing (∼2-12 Hz) in olfactory bulb and cortex, and faster oscillatory bursts are coupled to specific phases of the respiratory cycle. These dynamic rhythms are thought to regulate cortical excitability and coordinate network interactions, helping to shape olfactory coding, memory, and behavior. However, while respiratory oscillations are a ubiquitous hallmark of olfactory system function in animals, direct evidence for such patterns is lacking in humans. In this study, we acquired intracranial EEG data from rare patients (Ps) with medically refractory epilepsy, enabling us to test the hypothesis that cortical oscillatory activity would be entrained to the human respiratory cycle, albeit at the much slower rhythm of ∼0.16-0.33 Hz. Our results reveal that natural breathing synchronizes electrical activity in human piriform (olfactory) cortex, as well as in limbic-related brain areas, including amygdala and hippocampus. Notably, oscillatory power peaked during inspiration and dissipated when breathing was diverted from nose to mouth. Parallel behavioral experiments showed that breathing phase enhances fear discrimination and memory retrieval. Our findings provide a unique framework for understanding the pivotal role of nasal breathing in coordinating neuronal oscillations to support stimulus processing and behavior. Animal studies have long shown that olfactory oscillatory activity emerges in line with the natural rhythm of breathing, even in the absence of an odor stimulus. Whether the breathing cycle induces cortical oscillations in the human brain is poorly understood. In this study, we collected intracranial EEG data from rare patients with medically intractable epilepsy, and found evidence for respiratory entrainment

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.

At clinically relevant concentrations the anaesthetic/amnesic thiopental but not the anticonvulsant phenobarbital interferes with hippocampal sharp wave-ripple complexes

PubMed Central

Papatheodoropoulos, Costas; Sotiriou, Evangelos; Kotzadimitriou, Dimitrios; Drimala, Panagiota

2007-01-01

Background Many sedative agents, including anesthetics, produce explicit memory impairment by largely unknown mechanisms. Sharp-wave ripple (SPW-R) complexes are network activity thought to represent the neuronal substrate for information transfer from the hippocampal to neocortical circuits, contributing to the explicit memory consolidation. In this study we examined and compared the actions of two barbiturates with distinct amnesic actions, the general anesthetic thiopental and the anticonvulsant phenobarbital, on in vitro SPW-R activity. Results Using an in vitro model of SPW-R activity we found that thiopental (50–200 μM) significantly and concentration-dependently reduced the incidence of SPW-R events (it increased the inter-event period by 70–430 %). At the concentration of 25 μM, which clinically produces mild sedation and explicit memory impairment, thiopental significantly reduced the quantity of ripple oscillation (it reduced the number of ripples and the duration of ripple episodes by 20 ± 5%, n = 12, P < 0.01), and suppressed the rhythmicity of SPWs by 43 ± 15% (n = 6, P < 0.05). The drug disrupted the synchrony of SPWs within the CA1 region at 50 μM (by 19 ± 12%; n = 5, P < 0.05). Similar effects of thiopental were observed at higher concentrations. Thiopental did not affect the frequency of ripple oscillation at any of the concentrations tested (10–200 μM). Furthermore, the drug significantly prolonged single SPWs at concentrations ≥50 μM (it increased the half-width and the duration of SPWs by 35–90 %). Thiopental did not affect evoked excitatory synaptic potentials and its results on SPW-R complexes were also observed under blockade of NMDA receptors. Phenobarbital significantly accelerated SPWs at 50 and 100 μM whereas it reduced their rate at 200 and 400 μM. Furthermore, it significantly prolonged SPWs, reduced their synchrony and reduced the quantity of ripples only at the clinically very high concentration of 400 �

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…

Hippocampal microRNA-mRNA regulatory network is affected by physical exercise.

PubMed

Fernandes, Jansen; Vieira, Andre Schwambach; Kramer-Soares, Juliana Carlota; Da Silva, Eduardo Alves; Lee, Kil Sun; Lopes-Cendes, Iscia; Arida, Ricardo Mario

2018-05-08

It is widely known that physical activity positively affects the overall health and brain function. Recently, microRNAs (miRNAs) have emerged as potential regulators of numerous biological processes within the brain. These molecules modulate gene expression post-transcriptionally by inducing mRNA degradation and inhibiting the translation of target mRNAs. To verify whether the procognitive effects of physical exercise are accompanied by changes in the activity of miRNA-mRNA network in the brain, differential expression analysis was performed in the hippocampus of control (CTL) and exercised (Ex) rats subjected to 4 weeks of treadmill exercise. Cognition was evaluated by a multiple trial inhibitory avoidance (MTIA) task and Illumina next-generation sequencing (NGS) was used for miRNA and mRNA profiling. Exercise improved memory retention but not acquisition in the MTIA task. It was observed that 4 miRNAs and 54 mRNAs were significantly altered in the hippocampus of Ex2 (euthanized 2 h after the last exercise bout) group when compared to CTL group. Bioinformatic analysis showed an inverse correlation between 3 miRNAs and 6 target mRNAs. The miRNAs miR-129-1-3p and miR-144-5p were inversely correlated to the Igfbp5 and Itm2a, respectively, and the miR-708-5p presented an inverse correlation with Cdkn1a, Per2, Rt1-a2. The exercise-induced memory improvements are accompanied by changes in hippocampal miRNA-mRNA regulatory network. Physical exercise can affect brain function through modulation of epigenetics mechanisms involving miRNA regulation. Copyright © 2018 Elsevier B.V. All rights reserved.

Cluster dynamics of pulse coupled oscillators

NASA Astrophysics Data System (ADS)

O'Keeffe, Kevin; Strogatz, Steven; Krapivsky, Paul

2015-03-01

We study the dynamics of networks of pulse coupled oscillators. Much attention has been devoted to the ultimate fate of the system: which conditions lead to a steady state in which all the oscillators are firing synchronously. But little is known about how synchrony builds up from an initially incoherent state. The current work addresses this question. Oscillators start to synchronize by forming clusters of different sizes that fire in unison. First pairs of oscillators, then triplets and so on. These clusters progressively grow by coalescing with others, eventually resulting in the fully synchronized state. We study the mean field model in which the coupling between oscillators is all to all. We use probabilistic arguments to derive a recursive set of evolution equations for these clusters. Using a generating function formalism, we derive simple equations for the moments of these clusters. Our results are in good agreement simulation. We then numerically explore the effects of non-trivial connectivity. Our results have potential application to ultra-low power ``impulse radio'' & sensor networks.

Three-dimensional chimera patterns in networks of spiking neuron oscillators

NASA Astrophysics Data System (ADS)

Kasimatis, T.; Hizanidis, J.; Provata, A.

2018-05-01

We study the stable spatiotemporal patterns that arise in a three-dimensional (3D) network of neuron oscillators, whose dynamics is described by the leaky integrate-and-fire (LIF) model. More specifically, we investigate the form of the chimera states induced by a 3D coupling matrix with nonlocal topology. The observed patterns are in many cases direct generalizations of the corresponding two-dimensional (2D) patterns, e.g., spheres, layers, and cylinder grids. We also find cylindrical and "cross-layered" chimeras that do not have an equivalent in 2D systems. Quantitative measures are calculated, such as the ratio of synchronized and unsynchronized neurons as a function of the coupling range, the mean phase velocities, and the distribution of neurons in mean phase velocities. Based on these measures, the chimeras are categorized in two families. The first family of patterns is observed for weaker coupling and exhibits higher mean phase velocities for the unsynchronized areas of the network. The opposite holds for the second family, where the unsynchronized areas have lower mean phase velocities. The various measures demonstrate discontinuities, indicating criticality as the parameters cross from the first family of patterns to the second.

Rhythmic coordination of hippocampal neurons during associative memory processing

PubMed Central

Rangel, Lara M; Rueckemann, Jon W; Riviere, Pamela D; Keefe, Katherine R; Porter, Blake S; Heimbuch, Ian S; Budlong, Carl H; Eichenbaum, Howard

2016-01-01

Hippocampal oscillations are dynamic, with unique oscillatory frequencies present during different behavioral states. To examine the extent to which these oscillations reflect neuron engagement in distinct local circuit processes that are important for memory, we recorded single cell and local field potential activity from the CA1 region of the hippocampus as rats performed a context-guided odor-reward association task. We found that theta (4–12 Hz), beta (15–35 Hz), low gamma (35–55 Hz), and high gamma (65–90 Hz) frequencies exhibited dynamic amplitude profiles as rats sampled odor cues. Interneurons and principal cells exhibited unique engagement in each of the four rhythmic circuits in a manner that related to successful performance of the task. Moreover, principal cells coherent to each rhythm differentially represented task dimensions. These results demonstrate that distinct processing states arise from the engagement of rhythmically identifiable circuits, which have unique roles in organizing task-relevant processing in the hippocampus. DOI: http://dx.doi.org/10.7554/eLife.09849.001 PMID:26751780

Hippocampal closed-loop modeling and implications for seizure stimulation design.

PubMed

Sandler, Roman A; Song, Dong; Hampson, Robert E; Deadwyler, Sam A; Berger, Theodore W; Marmarelis, Vasilis Z

2015-10-01

Traditional hippocampal modeling has focused on the series of feedforward synapses known as the trisynaptic pathway. However, feedback connections from CA1 back to the hippocampus through the entorhinal cortex (EC) actually make the hippocampus a closed-loop system. By constructing a functional closed-loop model of the hippocampus, one may learn how both physiological and epileptic oscillations emerge and design efficient neurostimulation patterns to abate such oscillations. Point process input-output models where estimated from recorded rodent hippocampal data to describe the nonlinear dynamical transformation from CA3 → CA1, via the schaffer-collateral synapse, and CA1 → CA3 via the EC. Each Volterra-like subsystem was composed of linear dynamics (principal dynamic modes) followed by static nonlinearities. The two subsystems were then wired together to produce the full closed-loop model of the hippocampus. Closed-loop connectivity was found to be necessary for the emergence of theta resonances as seen in recorded data, thus validating the model. The model was then used to identify frequency parameters for the design of neurostimulation patterns to abate seizures. Deep-brain stimulation (DBS) is a new and promising therapy for intractable seizures. Currently, there is no efficient way to determine optimal frequency parameters for DBS, or even whether periodic or broadband stimuli are optimal. Data-based computational models have the potential to be used as a testbed for designing optimal DBS patterns for individual patients. However, in order for these models to be successful they must incorporate the complex closed-loop structure of the seizure focus. This study serves as a proof-of-concept of using such models to design efficient personalized DBS patterns for epilepsy.

Acute Stress Affects the Expression of Hippocampal Mu Oscillations in an Age-Dependent Manner

PubMed Central

Takillah, Samir; Naudé, Jérémie; Didienne, Steve; Sebban, Claude; Decros, Brigitte; Schenker, Esther; Spedding, Michael; Mourot, Alexandre; Mariani, Jean; Faure, Philippe

2017-01-01

Anxiolytic drugs are widely used in the elderly, a population particularly sensitive to stress. Stress, aging and anxiolytics all affect low-frequency oscillations in the hippocampus and prefrontal cortex (PFC) independently, but the interactions between these factors remain unclear. Here, we compared the effects of stress (elevated platform, EP) and anxiolytics (diazepam, DZP) on extracellular field potentials (EFP) in the PFC, parietal cortex and hippocampus (dorsal and ventral parts) of adult (8 months) and aged (18 months) Wistar rats. A potential source of confusion in the experimental studies in rodents comes from locomotion-related theta (6–12 Hz) oscillations, which may overshadow the direct effects of anxiety on low-frequency and especially on the high-amplitude oscillations in the Mu range (7–12 Hz), related to arousal. Animals were restrained to avoid any confound and isolate the direct effects of stress from theta oscillations related to stress-induced locomotion. We identified transient, high-amplitude oscillations in the 7–12 Hz range (“Mu-bursts”) in the PFC, parietal cortex and only in the dorsal part of hippocampus. At rest, aged rats displayed more Mu-bursts than adults. Stress acted differently on Mu-bursts depending on age: it increases vs. decreases burst, in adult and aged animals, respectively. In contrast DZP (1 mg/kg) acted the same way in stressed adult and age animal: it decreased the occurrence of Mu-bursts, as well as their co-occurrence. This is consistent with DZP acting as a positive allosteric modulator of GABAA receptors, which globally potentiates inhibition and has anxiolytic effects. Overall, the effect of benzodiazepines on stressed animals was to restore Mu burst activity in adults but to strongly diminish them in aged rats. This work suggests Mu-bursts as a neural marker to study the impact of stress and DZP on age. PMID:29033825

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. Copyright © 2016 Elsevier Inc. All rights reserved.

Slowing of the hippocampal θ-rhythm correlates with anesthetic-induced amnesia

PubMed Central

Perouansky, Misha; Rau, Vinuta; Ford, Tim; Oh, S. Irene; Perkins, Mark; Eger, Edmond I.; Pearce, Robert A.

2010-01-01

Background Temporary, antegrade amnesia is one of the core desirable endpoints of general anesthesia. Multiple lines of evidence support a role for the hippocampal θ-rhythm, a synchronized rhythmic oscillation of field potentials at 4–12 Hz, in memory formation. Previous studies have revealed a disruption of the θ-rhythm at surgical levels of anesthesia. We hypothesized that modulation of θ-rhythm would also occur at subhypnotic but amnestic concentrations. Therefore we examined the effect of three inhaled agents on properties of the θ-rhythm that are considered to be critical for the formation of hippocampus-dependent memories. Methods We studied the effects of halothane and nitrous oxide, two agents known to modulate different molecular targets (GABAergic vs. non-GABAergic, respectively), and isoflurane (both GABAergic and non-GABAergic targets), on fear-conditioned learning and θ-oscillations in freely behaving rats. Results All three anesthetics slowed θ-peak frequency in proportion to their inhibition of fear conditioning (by 1 Hz, 0.7 Hz and 0.5 Hz for 0.32% isoflurane, 60% N2O and 0.24% halothane). The anesthetics inconsistently affected other characteristics of θ-oscillations. Conclusions At sub-hypnotic amnestic concentrations, θ-oscillation frequency was the parameter most consistently affected by these three anesthetics. These results are consistent with the hypothesis that modulation of the θ-rhythm contributes to anesthetic-induced amnesia. PMID:21042201

Temporal lobe epilepsy patients with severe hippocampal neuron loss but normal hippocampal volume: Extracellular matrix molecules are important for the maintenance of hippocampal volume.

PubMed

Peixoto-Santos, Jose Eduardo; Velasco, Tonicarlo Rodrigues; Galvis-Alonso, Orfa Yineth; Araujo, David; Kandratavicius, Ludmyla; Assirati, Joao Alberto; Carlotti, Carlos Gilberto; Scandiuzzi, Renata Caldo; Santos, Antonio Carlos dos; Leite, Joao Pereira

2015-10-01

Hippocampal sclerosis is a common finding in patients with temporal lobe epilepsy (TLE), and magnetic resonance imaging (MRI) studies associate the reduction of hippocampal volume with the neuron loss seen on histologic evaluation. Astrogliosis and increased levels of chondroitin sulfate, a major component of brain extracellular matrix, are also seen in hippocampal sclerosis. Our aim was to evaluate the association between hippocampal volume and chondroitin sulfate, as well as neuronal and astroglial populations in the hippocampus of patients with TLE. Patients with drug-resistant TLE were subdivided, according to hippocampal volume measured by MRI, into two groups: hippocampal atrophy (HA) or normal volume (NV) cases. Hippocampi from TLE patients and age-matched controls were submitted to immunohistochemistry to evaluate neuronal population, astroglial population, and chondroitin sulfate expression with antibodies against neuron nuclei protein (NeuN), glial fibrillary acidic protein (GFAP), and chondroitin sulfate (CS-56) antigens, respectively. Both TLE groups were clinically similar. NV cases had higher hippocampal volume, both ipsilateral and contralateral, when compared to HA. Compared to controls, NV and HA patients had reduced neuron density, and increased GFAP and CS-56 immunopositive area. There was no statistical difference between NV and HA groups in neuron density or immunopositive areas for GFAP and CS-56. Hippocampal volume correlated positively with neuron density in CA1 and prosubiculum, and with immunopositive areas for CS-56 in CA1, and negatively with immunopositive area for GFAP in CA1. Multiple linear regression analysis indicated that both neuron density and CS-56 immunopositive area in CA1 were statistically significant predictors of hippocampal volume. Our findings indicate that neuron density and chondroitin sulfate immunopositive area in the CA1 subfield are crucial for the hippocampal volume, and that chondroitin sulfate is important for

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

PubMed Central

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

2016-01-01

Goal This manuscript describes a million-plus granule cell compartmental model of the rat hippocampal dentate gyrus, including excitatory, perforant path input from the entorhinal cortex, and feedforward and feedback inhibitory input from dentate interneurons. Methods The model includes experimentally determined morphological and biophysical properties of granule cells, together with glutamatergic AMPA-like EPSP and GABAergic GABAA-like IPSP synaptic excitatory and inhibitory inputs, respectively. Each granule cell was composed of approximately 200 compartments having passive and active conductances distributed throughout the somatic and dendritic regions. Modeling excitatory input from the entorhinal cortex was guided by axonal transport studies documenting the topographical organization of projections from subregions of the medial and lateral entorhinal cortex, plus other important details of the distribution of glutamatergic inputs to the dentate gyrus. Information contained within previously published maps of this major hippocampal afferent were systematically converted to scales that allowed the topographical distribution and relative synaptic densities of perforant path inputs to be quantitatively estimated for inclusion in the current model. Results Results showed that when medial and lateral entorhinal cortical neurons maintained Poisson random firing, dentate granule cells expressed, throughout the million-cell network, a robust, non-random pattern of spiking best described as spatio-temporal “clustering”. To identify the network property or properties responsible for generating such firing “clusters”, we progressively eliminated from the model key mechanisms such as feedforward and feedback inhibition, intrinsic membrane properties underlying rhythmic burst firing, and/or topographical organization of entorhinal afferents. Conclusion Findings conclusively identified topographical organization of inputs as the key element responsible for generating

Travelling Wave Pulse Coupled Oscillator (TWPCO) Using a Self-Organizing Scheme for Energy-Efficient Wireless Sensor Networks.

PubMed

Al-Mekhlafi, Zeyad Ghaleb; Hanapi, Zurina Mohd; Othman, Mohamed; Zukarnain, Zuriati Ahmad

2017-01-01

Recently, Pulse Coupled Oscillator (PCO)-based travelling waves have attracted substantial attention by researchers in wireless sensor network (WSN) synchronization. Because WSNs are generally artificial occurrences that mimic natural phenomena, the PCO utilizes firefly synchronization of attracting mating partners for modelling the WSN. However, given that sensor nodes are unable to receive messages while transmitting data packets (due to deafness), the PCO model may not be efficient for sensor network modelling. To overcome this limitation, this paper proposed a new scheme called the Travelling Wave Pulse Coupled Oscillator (TWPCO). For this, the study used a self-organizing scheme for energy-efficient WSNs that adopted travelling wave biologically inspired network systems based on phase locking of the PCO model to counteract deafness. From the simulation, it was found that the proposed TWPCO scheme attained a steady state after a number of cycles. It also showed superior performance compared to other mechanisms, with a reduction in the total energy consumption of 25%. The results showed that the performance improved by 13% in terms of data gathering. Based on the results, the proposed scheme avoids the deafness that occurs in the transmit state in WSNs and increases the data collection throughout the transmission states in WSNs.

Travelling Wave Pulse Coupled Oscillator (TWPCO) Using a Self-Organizing Scheme for Energy-Efficient Wireless Sensor Networks

PubMed Central

Hanapi, Zurina Mohd; Othman, Mohamed; Zukarnain, Zuriati Ahmad

2017-01-01

Recently, Pulse Coupled Oscillator (PCO)-based travelling waves have attracted substantial attention by researchers in wireless sensor network (WSN) synchronization. Because WSNs are generally artificial occurrences that mimic natural phenomena, the PCO utilizes firefly synchronization of attracting mating partners for modelling the WSN. However, given that sensor nodes are unable to receive messages while transmitting data packets (due to deafness), the PCO model may not be efficient for sensor network modelling. To overcome this limitation, this paper proposed a new scheme called the Travelling Wave Pulse Coupled Oscillator (TWPCO). For this, the study used a self-organizing scheme for energy-efficient WSNs that adopted travelling wave biologically inspired network systems based on phase locking of the PCO model to counteract deafness. From the simulation, it was found that the proposed TWPCO scheme attained a steady state after a number of cycles. It also showed superior performance compared to other mechanisms, with a reduction in the total energy consumption of 25%. The results showed that the performance improved by 13% in terms of data gathering. Based on the results, the proposed scheme avoids the deafness that occurs in the transmit state in WSNs and increases the data collection throughout the transmission states in WSNs. PMID:28056020

Interaction function of oscillating coupled neurons

PubMed Central

Dodla, Ramana; Wilson, Charles J.

2013-01-01

Large scale simulations of electrically coupled neuronal oscillators often employ the phase coupled oscillator paradigm to understand and predict network behavior. We study the nature of the interaction between such coupled oscillators using weakly coupled oscillator theory. By employing piecewise linear approximations for phase response curves and voltage time courses, and parameterizing their shapes, we compute the interaction function for all such possible shapes and express it in terms of discrete Fourier modes. We find that reasonably good approximation is achieved with four Fourier modes that comprise of both sine and cosine terms. PMID:24229210

Intrinsic evolution of controllable oscillators in FPTA-2

NASA Technical Reports Server (NTRS)

Sekanina, Lukas; Zebulum, Ricardo S.

2005-01-01

Simple one- and two-bit controllable oscillators were intrinsically evolved using only four cells of Field Programmable Transistor Array (FPTA-2). These oscillators can produce different oscillations for different setting of control signals. Therefore, they could be used, in principle, to compose complex networks of oscillators that could exhibit rich dynamical behavior in order to perform a computation or to model a desired system.

Synchronization Dynamics of Coupled Chemical Oscillators

NASA Astrophysics Data System (ADS)

Tompkins, Nathan

The synchronization dynamics of complex networks have been extensively studied over the past few decades due to their ubiquity in the natural world. Prominent examples include cardiac rhythms, circadian rhythms, the flashing of fireflies, predator/prey population dynamics, mammalian gait, human applause, pendulum clocks, the electrical grid, and of the course the brain. Detailed experiments have been done to map the topology of many of these systems and significant advances have been made to describe the mathematics of these networks. Compared to these bodies of work relatively little has been done to directly test the role of topology in the synchronization dynamics of coupled oscillators. This Dissertation develops technology to examine the dynamics due to topology within networks of discrete oscillatory components. The oscillatory system used here consists of the photo-inhibitable Belousov-Zhabotinsky (BZ) reaction water-in-oil emulsion where the oscillatory drops are diffusively coupled to one another and the topology is defined by the geometry of the diffusive connections. Ring networks are created from a close-packed 2D array of drops using the Programmable Illumination Microscope (PIM) in order to test Turing's theory of morphogenesis directly. Further technology is developed to create custom planar networks of BZ drops in more complicated topologies which can be individually perturbed using illumination from the PIM. The work presented here establishes the validity of using the BZ emulsion system with a PIM to study the topology induced effects on the synchronization dynamics of coupled chemical oscillators, tests the successes and limitations of Turing's theory of morphogenesis, and develops new technology to further probe the effects of network topology on a system of coupled oscillators. Finally, this Dissertation concludes by describing ongoing experiments which utilize this new technology to examine topology induced transitions of synchronization

Solitary states for coupled oscillators with inertia.

PubMed

Jaros, Patrycja; Brezetsky, Serhiy; Levchenko, Roman; Dudkowski, Dawid; Kapitaniak, Tomasz; Maistrenko, Yuri

2018-01-01

Networks of identical oscillators with inertia can display remarkable spatiotemporal patterns in which one or a few oscillators split off from the main synchronized cluster and oscillate with different averaged frequency. Such "solitary states" are impossible for the classical Kuramoto model with sinusoidal coupling. However, if inertia is introduced, these states represent a solid part of the system dynamics, where each solitary state is characterized by the number of isolated oscillators and their disposition in space. We present system parameter regions for the existence of solitary states in the case of local, non-local, and global network couplings and show that they preserve in both thermodynamic and conservative limits. We give evidence that solitary states arise in a homoclinic bifurcation of a saddle-type synchronized state and die eventually in a crisis bifurcation after essential variation of the parameters.

Solitary states for coupled oscillators with inertia

NASA Astrophysics Data System (ADS)

Jaros, Patrycja; Brezetsky, Serhiy; Levchenko, Roman; Dudkowski, Dawid; Kapitaniak, Tomasz; Maistrenko, Yuri

2018-01-01

Networks of identical oscillators with inertia can display remarkable spatiotemporal patterns in which one or a few oscillators split off from the main synchronized cluster and oscillate with different averaged frequency. Such "solitary states" are impossible for the classical Kuramoto model with sinusoidal coupling. However, if inertia is introduced, these states represent a solid part of the system dynamics, where each solitary state is characterized by the number of isolated oscillators and their disposition in space. We present system parameter regions for the existence of solitary states in the case of local, non-local, and global network couplings and show that they preserve in both thermodynamic and conservative limits. We give evidence that solitary states arise in a homoclinic bifurcation of a saddle-type synchronized state and die eventually in a crisis bifurcation after essential variation of the parameters.

Astrocytes contribute to gamma oscillations and recognition memory.

PubMed

Lee, Hosuk Sean; Ghetti, Andrea; Pinto-Duarte, António; Wang, Xin; Dziewczapolski, Gustavo; Galimi, Francesco; Huitron-Resendiz, Salvador; Piña-Crespo, Juan C; Roberts, Amanda J; Verma, Inder M; Sejnowski, Terrence J; Heinemann, Stephen F

2014-08-12

Glial cells are an integral part of functional communication in the brain. Here we show that astrocytes contribute to the fast dynamics of neural circuits that underlie normal cognitive behaviors. In particular, we found that the selective expression of tetanus neurotoxin (TeNT) in astrocytes significantly reduced the duration of carbachol-induced gamma oscillations in hippocampal slices. These data prompted us to develop a novel transgenic mouse model, specifically with inducible tetanus toxin expression in astrocytes. In this in vivo model, we found evidence of a marked decrease in electroencephalographic (EEG) power in the gamma frequency range in awake-behaving mice, whereas neuronal synaptic activity remained intact. The reduction in cortical gamma oscillations was accompanied by impaired behavioral performance in the novel object recognition test, whereas other forms of memory, including working memory and fear conditioning, remained unchanged. These results support a key role for gamma oscillations in recognition memory. Both EEG alterations and behavioral deficits in novel object recognition were reversed by suppression of tetanus toxin expression. These data reveal an unexpected role for astrocytes as essential contributors to information processing and cognitive behavior.

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

PubMed Central

Mangan, Patrick S.; Kapur, Jaideep

2010-01-01

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

Serotonin Modulation of Prefronto-Hippocampal Rhythms in Health and Disease.

PubMed

Puig, M Victoria; Gener, Thomas

2015-07-15

There is mounting evidence that most cognitive functions depend upon the coordinated activity of neuronal networks often located far from each other in the brain. Ensembles of neurons synchronize their activity, generating oscillations at different frequencies that may encode behavior by allowing an efficient communication between brain areas. The serotonin system, by virtue of the widespread arborisation of serotonergic neurons, is in an excellent position to exert strong modulatory actions on brain rhythms. These include specific oscillatory activities in the prefrontal cortex and the hippocampus, two brain areas essential for many higher-order cognitive functions. Psychiatric patients show abnormal oscillatory activities in these areas, notably patients with schizophrenia who display psychotic symptoms as well as affective and cognitive impairments. Synchronization of neural activity between the prefrontal cortex and the hippocampus seems to be important for cognition and, in fact, reduced prefronto-hippocampal synchrony has been observed in a genetic mouse model of schizophrenia. Here, we review recent advances in the field of neuromodulation of brain rhythms by serotonin, focusing on the actions of serotonin in the prefrontal cortex and the hippocampus. Considering that the serotonergic system plays a crucial role in cognition and mood and is a target of many psychiatric treatments, it is surprising that this field of research is still in its infancy. In that regard, we point to future investigations that are much needed in this field.

Coexistence of Stochastic Oscillations and Self-Organized Criticality in a Neuronal Network: Sandpile Model Application.

PubMed

Saeedi, Alireza; Jannesari, Mostafa; Gharibzadeh, Shahriar; Bakouie, Fatemeh

2018-04-01

Self-organized criticality (SOC) and stochastic oscillations (SOs) are two theoretically contradictory phenomena that are suggested to coexist in the brain. Recently it has been shown that an accumulation-release process like sandpile dynamics can generate SOC and SOs simultaneously. We considered the effect of the network structure on this coexistence and showed that the sandpile dynamics on a small-world network can produce two power law regimes along with two groups of SOs-two peaks in the power spectrum of the generated signal simultaneously. We also showed that external stimuli in the sandpile dynamics do not affect the coexistence of SOC and SOs but increase the frequency of SOs, which is consistent with our knowledge of the brain.

"Small World" architecture in brain connectivity and hippocampal volume in Alzheimer's disease: a study via graph theory from EEG data.

PubMed

Vecchio, Fabrizio; Miraglia, Francesca; Piludu, Francesca; Granata, Giuseppe; Romanello, Roberto; Caulo, Massimo; Onofrj, Valeria; Bramanti, Placido; Colosimo, Cesare; Rossini, Paolo Maria

2017-04-01

Brain imaging plays an important role in the study of Alzheimer's disease (AD), where atrophy has been found to occur in the hippocampal formation during the very early disease stages and to progress in parallel with the disease's evolution. The aim of the present study was to evaluate a possible correlation between "Small World" characteristics of the brain connectivity architecture-as extracted from EEG recordings-and hippocampal volume in AD patients. A dataset of 144 subjects, including 110 AD (MMSE 21.3) and 34 healthy Nold (MMSE 29.8) individuals, was evaluated. Weighted and undirected networks were built by the eLORETA solutions of the cortical sources' activities moving from EEG recordings. The evaluation of the hippocampal volume was carried out on a subgroup of 60 AD patients who received a high-resolution T1-weighted sequence and underwent processing for surface-based cortex reconstruction and volumetric segmentation using the Freesurfer image analysis software. Results showed that, quantitatively, more correlation was observed in the right hemisphere, but the same trend was seen in both hemispheres. Alpha band connectivity was negatively correlated, while slow (delta) and fast-frequency (beta, gamma) bands positively correlated with hippocampal volume. Namely, the larger the hippocampal volume, the lower the alpha and the higher the delta, beta, and gamma Small World characteristics of connectivity. Accordingly, the Small World connectivity pattern could represent a functional counterpart of structural hippocampal atrophying and related-network disconnection.

Cell type-specific genetic and optogenetic tools reveal hippocampal CA2 circuits.

PubMed

Kohara, Keigo; Pignatelli, Michele; Rivest, Alexander J; Jung, Hae-Yoon; Kitamura, Takashi; Suh, Junghyup; Frank, Dominic; Kajikawa, Koichiro; Mise, Nathan; Obata, Yuichi; Wickersham, Ian R; Tonegawa, Susumu

2014-02-01

The formation and recall of episodic memory requires precise information processing by the entorhinal-hippocampal network. For several decades, the trisynaptic circuit entorhinal cortex layer II (ECII)→dentate gyrus→CA3→CA1 and the monosynaptic circuit ECIII→CA1 have been considered the primary substrates of the network responsible for learning and memory. Circuits linked to another hippocampal region, CA2, have only recently come to light. Using highly cell type-specific transgenic mouse lines, optogenetics and patch-clamp recordings, we found that dentate gyrus cells, long believed to not project to CA2, send functional monosynaptic inputs to CA2 pyramidal cells through abundant longitudinal projections. CA2 innervated CA1 to complete an alternate trisynaptic circuit, but, unlike CA3, projected preferentially to the deep, rather than to the superficial, sublayer of CA1. Furthermore, contrary to existing knowledge, ECIII did not project to CA2. Our results allow a deeper understanding of the biology of learning and memory.

Real Time Distributed Embedded Oscillator Operating Frequency Monitoring

NASA Technical Reports Server (NTRS)

Pollock, Julie (Inventor); Oliver, Brett D. (Inventor); Brickner, Christopher (Inventor)

2013-01-01

A method for clock monitoring in a network is provided. The method comprises receiving a first network clock signal at a network device and comparing the first network clock signal to a local clock signal from a primary oscillator coupled to the network device.

Control of amplitude chimeras by time delay in oscillator networks

NASA Astrophysics Data System (ADS)

Gjurchinovski, Aleksandar; Schöll, Eckehard; Zakharova, Anna

2017-04-01

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

Hippocampal CA1 local field potential oscillations induced by olfactory cue of liked food.

PubMed

Samerphob, Nifareeda; Cheaha, Dania; Chatpun, Surapong; Kumarnsit, Ekkasit

2017-07-01

Eating motivation is induced not only by negative energy balance but also food related cues. However, neural processing for acquisition of learned food preference remains to be established. This study aimed to identify hippocampal neural signaling in response to olfactory cue (chocolate scent) after completion of repetitive chocolate sessions. Male Swiss albino mice implanted with intracranial electrode into the hippocampus were used for local field potential (LFP) recording. Animals were given chocolate sessions (a piece of 2g chocolate per each mouse to eat on day 1, 3, 5 and 7). Hippocampal CA1 LFP signals and exploratory behavior of animals receiving chocolate scent were analyzed before and after chocolate sessions. The experiment was performed in a place preference-like apparatus with the zones of normal food pellet and chocolate (both kept in a small perforated cup for smell dispersion) at the opposite ends. Following chocolate sessions, time spent in a chocolate zone and CA1 LFP patterns were analyzed in comparison to control levels. Two-way ANOVA revealed significant increase in time spent seeking for chocolate. Frequency analysis of LFP power spectra revealed significant increases in delta and theta powers. Phase-amplitude analysis showed significant increase in maximal modulation index and decrease in frequency for phase of theta-high gamma coupling. Taken together, neural signaling in the hippocampus was sensitive to chocolate olfactory cue that might underlie learning process in response to repeated chocolate consumptions that primed intense food approaching behavior. Ultimately, these LFP patterns might reflect motivation to eat and predict feeding probability. Copyright © 2017 Elsevier Inc. All rights reserved.

A comparative study of the dentate gyrus in hippocampal sclerosis in epilepsy and dementia

PubMed Central

Bandopadhyay, R; Liu, J Y W; Sisodiya, S M; Thom, M

2014-01-01

Aims: Hippocampal sclerosis (HS) is long-recognized in association with epilepsy (HSE) and more recently in the context of cognitive decline or dementia in the elderly (HSD), in some cases as a component of neurodegenerative diseases, including Alzheimer's disease (AD) and fronto-temporal lobe dementia (FTLD). There is an increased risk of seizures in AD and spontaneous epileptiform discharges in the dentate gyrus of transgenic AD models; epilepsy can be associated with an age-accelerated increase in AD-type pathology and cognitive decline. The convergence between these disease processes could be related to hippocampal pathology. HSE typically shows re-organization of both excitatory and inhibitory neuronal networks in the dentate gyrus, and is considered to be relevant to hippocampal excitability. We sought to compare the pathology of HSE and HSD, focusing on re-organization in the dentate gyrus. Methods: In nine post mortem cases with HSE and bilateral damage, 18 HSD and 11 controls we carried out immunostaining for mossy fibres (dynorphin), and interneuronal networks (NPY, calbindin and calretinin) on sections from the mid-hippocampal body. Fibre sprouting (FS) or loss of expression in the dentate gyrus was semi-quantitatively graded from grade 0 (normal) to grade 3 (marked alteration). Results: Significantly more re-organization was seen with all four markers in the HSE than HSD group (P < 0.01). Mild alterations were noted in HSD group with dynorphin (FS in 3 cases), calretinin (FS in 6 cases), NPY (FS in 11 cases) and calbindin (loss in 10 cases). In eight HSD cases, alteration was seen with more than one antibody but in no cases were the highest grades seen. We also noted NPY and, to a lesser extent, calretinin labelling of Hirano bodies in CA1 of AD cases and some older controls, but not in HSE. Conclusion: Reorganization of excitatory and inhibitory networks in the dentate gyrus is more typical of HSE. Subtle alterations in HSD may be a result of

Boltzmann sampling for an XY model using a non-degenerate optical parametric oscillator network

NASA Astrophysics Data System (ADS)

Takeda, Y.; Tamate, S.; Yamamoto, Y.; Takesue, H.; Inagaki, T.; Utsunomiya, S.

2018-01-01

We present an experimental scheme of implementing multiple spins in a classical XY model using a non-degenerate optical parametric oscillator (NOPO) network. We built an NOPO network to simulate a one-dimensional XY Hamiltonian with 5000 spins and externally controllable effective temperatures. The XY spin variables in our scheme are mapped onto the phases of multiple NOPO pulses in a single ring cavity and interactions between XY spins are implemented by mutual injections between NOPOs. We show the steady-state distribution of optical phases of such NOPO pulses is equivalent to the Boltzmann distribution of the corresponding XY model. Estimated effective temperatures converged to the setting values, and the estimated temperatures and the mean energy exhibited good agreement with the numerical simulations of the Langevin dynamics of NOPO phases.

The effect of hippocampal function, volume and connectivity on posterior cingulate cortex functioning during episodic memory fMRI in mild cognitive impairment.

PubMed

Papma, Janne M; Smits, Marion; de Groot, Marius; Mattace Raso, Francesco U; van der Lugt, Aad; Vrooman, Henri A; Niessen, Wiro J; Koudstaal, Peter J; van Swieten, John C; van der Veen, Frederik M; Prins, Niels D

2017-09-01

Diminished function of the posterior cingulate cortex (PCC) is a typical finding in early Alzheimer's disease (AD). It is hypothesized that in early stage AD, PCC functioning relates to or reflects hippocampal dysfunction or atrophy. The aim of this study was to examine the relationship between hippocampus function, volume and structural connectivity, and PCC activation during an episodic memory task-related fMRI study in mild cognitive impairment (MCI). MCI patients (n = 27) underwent episodic memory task-related fMRI, 3D-T1w MRI, 2D T2-FLAIR MRI and diffusion tensor imaging. Stepwise linear regression analysis was performed to examine the relationship between PCC activation and hippocampal activation, hippocampal volume and diffusion measures within the cingulum along the hippocampus. We found a significant relationship between PCC and hippocampus activation during successful episodic memory encoding and correct recognition in MCI patients. We found no relationship between the PCC and structural hippocampal predictors. Our results indicate a relationship between PCC and hippocampus activation during episodic memory engagement in MCI. This may suggest that during episodic memory, functional network deterioration is the most important predictor of PCC functioning in MCI. • PCC functioning during episodic memory relates to hippocampal functioning in MCI. • PCC functioning during episodic memory does not relate to hippocampal structure in MCI. • Functional network changes are an important predictor of PCC functioning in MCI.

Hippocampal closed-loop modeling and implications for seizure stimulation design

NASA Astrophysics Data System (ADS)

Sandler, Roman A.; Song, Dong; Hampson, Robert E.; Deadwyler, Sam A.; Berger, Theodore W.; Marmarelis, Vasilis Z.

2015-10-01

Objective. Traditional hippocampal modeling has focused on the series of feedforward synapses known as the trisynaptic pathway. However, feedback connections from CA1 back to the hippocampus through the entorhinal cortex (EC) actually make the hippocampus a closed-loop system. By constructing a functional closed-loop model of the hippocampus, one may learn how both physiological and epileptic oscillations emerge and design efficient neurostimulation patterns to abate such oscillations. Approach. Point process input-output models where estimated from recorded rodent hippocampal data to describe the nonlinear dynamical transformation from CA3 → CA1, via the schaffer-collateral synapse, and CA1 → CA3 via the EC. Each Volterra-like subsystem was composed of linear dynamics (principal dynamic modes) followed by static nonlinearities. The two subsystems were then wired together to produce the full closed-loop model of the hippocampus. Main results. Closed-loop connectivity was found to be necessary for the emergence of theta resonances as seen in recorded data, thus validating the model. The model was then used to identify frequency parameters for the design of neurostimulation patterns to abate seizures. Significance. Deep-brain stimulation (DBS) is a new and promising therapy for intractable seizures. Currently, there is no efficient way to determine optimal frequency parameters for DBS, or even whether periodic or broadband stimuli are optimal. Data-based computational models have the potential to be used as a testbed for designing optimal DBS patterns for individual patients. However, in order for these models to be successful they must incorporate the complex closed-loop structure of the seizure focus. This study serves as a proof-of-concept of using such models to design efficient personalized DBS patterns for epilepsy.

Hippocampal Closed-Loop Modeling and Implications for Seizure Stimulation Design

PubMed Central

Sandler, Roman A.; Song, Dong; Hampson, Robert E.; Deadwyler, Sam A.; Berger, Theodore W.; Marmarelis, Vasilis Z.

2016-01-01

Objective Traditional hippocampal modeling has focused on the series of feedforward synapses known as the trisynaptic pathway. However, feedback connections from CA1 back to the hippocampus through the Entorhinal Cortex (EC) actually make the hippocampus a closed-loop system. By constructing a functional closed-loop model of the hippocampus, one may learn how both physiological and epileptic oscillations emerge and design efficient neurostimulation patterns to abate such oscillations. Approach Point process input-output models where estimated from recorded rodent hippocampal data to describe the nonlinear dynamical transformation from CA3→CA1, via the Schaffer-Collateral synapse, and CA1→CA3 via the EC. Each Volterra-like subsystem was composed of linear dynamics (Principal Dynamic Modes) followed by static nonlinearities. The two subsystems were then wired together to produce the full closed-loop model of the hippocampus. Main Results Closed-loop connectivity was found to be necessary for the emergence of theta resonances as seen in recorded data, thus validating the model. The model was then used to identify frequency parameters for the design of neurostimulation patterns to abate seizures. Significance DBS is a new and promising therapy for intractable seizures. Currently, there is no efficient way to determine optimal frequency parameters for DBS, or even whether periodic or broadband stimuli are optimal. Data-based computational models have the potential to be used as a testbed for designing optimal DBS patterns for individual patients. However, in order for these models to be successful they must incorporate the complex closed-loop structure of the seizure focus. This study serves as a proof-of-concept of using such models to design efficient personalized DBS patterns for epilepsy. PMID:26355815

Optimal Recall from Bounded Metaplastic Synapses: Predicting Functional Adaptations in Hippocampal Area CA3

PubMed Central

Savin, Cristina; Dayan, Peter; Lengyel, Máté

2014-01-01

A venerable history of classical work on autoassociative memory has significantly shaped our understanding of several features of the hippocampus, and most prominently of its CA3 area, in relation to memory storage and retrieval. However, existing theories of hippocampal memory processing ignore a key biological constraint affecting memory storage in neural circuits: the bounded dynamical range of synapses. Recent treatments based on the notion of metaplasticity provide a powerful model for individual bounded synapses; however, their implications for the ability of the hippocampus to retrieve memories well and the dynamics of neurons associated with that retrieval are both unknown. Here, we develop a theoretical framework for memory storage and recall with bounded synapses. We formulate the recall of a previously stored pattern from a noisy recall cue and limited-capacity (and therefore lossy) synapses as a probabilistic inference problem, and derive neural dynamics that implement approximate inference algorithms to solve this problem efficiently. In particular, for binary synapses with metaplastic states, we demonstrate for the first time that memories can be efficiently read out with biologically plausible network dynamics that are completely constrained by the synaptic plasticity rule, and the statistics of the stored patterns and of the recall cue. Our theory organises into a coherent framework a wide range of existing data about the regulation of excitability, feedback inhibition, and network oscillations in area CA3, and makes novel and directly testable predictions that can guide future experiments. PMID:24586137

Basal Ganglia Beta Oscillations Accompany Cue Utilization

PubMed Central

Leventhal, Daniel K.; Gage, Gregory J.; Schmidt, Robert; Pettibone, Jeffrey R.; Case, Alaina C.; Berke, Joshua D.

2012-01-01

SUMMARY Beta oscillations in cortical-basal ganglia (BG) circuits have been implicated in normal movement suppression and motor impairment in Parkinson’s disease. To dissect the functional correlates of these rhythms we compared neural activity during four distinct variants of a cued choice task in rats. Brief beta (~20 Hz) oscillations occurred simultaneously throughout the cortical-BG network, both spontaneously and at precise moments of task performance. Beta phase was rapidly reset in response to salient cues, yet increases in beta power were not rigidly linked to cues, movements, or movement suppression. Rather, beta power was enhanced after cues were used to determine motor output. We suggest that beta oscillations reflect a postdecision stabilized state of cortical-BG networks, which normally reduces interference from alternative potential actions. The abnormally strong beta seen in Parkinson’s Disease may reflect overstabilization of these networks, producing pathological persistence of the current motor state. PMID:22325204

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

PubMed

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

2018-02-27

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

Classification of attractors for systems of identical coupled Kuramoto oscillators

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

Engelbrecht, Jan R.; Mirollo, Renato

2014-03-15

We present a complete classification of attractors for networks of coupled identical Kuramoto oscillators. In such networks, each oscillator is driven by the same first-order trigonometric function, with coefficients given by symmetric functions of the entire oscillator ensemble. For N≠3 oscillators, there are four possible types of attractors: completely synchronized fixed points or limit cycles, and fixed points or limit cycles where all but one of the oscillators are synchronized. The case N = 3 is exceptional; systems of three identical Kuramoto oscillators can also posses attracting fixed points or limit cycles with all three oscillators out of sync, as well asmore » chaotic attractors. Our results rely heavily on the invariance of the flow for such systems under the action of the three-dimensional group of Möbius transformations, which preserve the unit disc, and the analysis of the possible limiting configurations for this group action.« less

Dynamic states of a unidirectional ring of chen oscillators

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

Carvalho, Ana; Pinto, Carla M.A.

2015-03-10

We study curious dynamical patterns appearing in a network of a unidirectional ring of Chen oscillators coupled to a ‘buffer’ cell. The network has Z{sub 3} exact symmetry group. We simulate the coupled cell systems associated to the two networks and obtain steady-states, rotating waves, quasiperiodic behavior, and chaos. The different patterns appear to arise through a sequence of Hopf, period-doubling and period-halving bifurcations. The network architecture appears to explain some patterns, whereas the properties of the chaotic oscillator may explain others. We use XPPAUT and MATLAB to compute numerically the relevant states.

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

NASA Astrophysics Data System (ADS)

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

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

Single-cell axotomy of cultured hippocampal neurons integrated in neuronal circuits.

PubMed

Gomis-Rüth, Susana; Stiess, Michael; Wierenga, Corette J; Meyn, Liane; Bradke, Frank