Identifying the Oscillatory Mechanism of the Glucose Oxidase-Catalase Coupled Enzyme System.

PubMed

Muzika, František; Jurašek, Radovan; Schreiberová, Lenka; Radojković, Vuk; Schreiber, Igor

2017-10-12

We provide experimental evidence of periodic and aperiodic oscillations in an enzymatic system of glucose oxidase-catalase in a continuous-flow stirred reactor coupled by a membrane with a continuous-flow reservoir supplied with hydrogen peroxide. To describe such dynamics, we formulate a detailed mechanism based on partial results in the literature. Finally, we introduce a novel method for estimation of unknown kinetic parameters. The method is based on matching experimental data at an oscillatory instability with stoichiometric constraints of the mechanism formulated by applying the stability theory of reaction networks. This approach has been used to estimate rate coefficients in the catalase part of the mechanism. Remarkably, model simulations show good agreement with the observed oscillatory dynamics, including apparently chaotic intermittent behavior. Our method can be applied to any reaction system with an experimentally observable dynamical instability.

Structure and Topology Dynamics of Hyper-Frequency Networks during Rest and Auditory Oddball Performance.

PubMed

Müller, Viktor; Perdikis, Dionysios; von Oertzen, Timo; Sleimen-Malkoun, Rita; Jirsa, Viktor; Lindenberger, Ulman

2016-01-01

Resting-state and task-related recordings are characterized by oscillatory brain activity and widely distributed networks of synchronized oscillatory circuits. Electroencephalographic recordings (EEG) were used to assess network structure and network dynamics during resting state with eyes open and closed, and auditory oddball performance through phase synchronization between EEG channels. For this assessment, we constructed a hyper-frequency network (HFN) based on within- and cross-frequency coupling (WFC and CFC, respectively) at 10 oscillation frequencies ranging between 2 and 20 Hz. We found that CFC generally differentiates between task conditions better than WFC. CFC was the highest during resting state with eyes open. Using a graph-theoretical approach (GTA), we found that HFNs possess small-world network (SWN) topology with a slight tendency to random network characteristics. Moreover, analysis of the temporal fluctuations of HFNs revealed specific network topology dynamics (NTD), i.e., temporal changes of different graph-theoretical measures such as strength, clustering coefficient, characteristic path length (CPL), local, and global efficiency determined for HFNs at different time windows. The different topology metrics showed significant differences between conditions in the mean and standard deviation of these metrics both across time and nodes. In addition, using an artificial neural network approach, we found stimulus-related dynamics that varied across the different network topology metrics. We conclude that functional connectivity dynamics (FCD), or NTD, which was found using the HFN approach during rest and stimulus processing, reflects temporal and topological changes in the functional organization and reorganization of neuronal cell assemblies.

Structure and Topology Dynamics of Hyper-Frequency Networks during Rest and Auditory Oddball Performance

PubMed Central

Müller, Viktor; Perdikis, Dionysios; von Oertzen, Timo; Sleimen-Malkoun, Rita; Jirsa, Viktor; Lindenberger, Ulman

2016-01-01

Resting-state and task-related recordings are characterized by oscillatory brain activity and widely distributed networks of synchronized oscillatory circuits. Electroencephalographic recordings (EEG) were used to assess network structure and network dynamics during resting state with eyes open and closed, and auditory oddball performance through phase synchronization between EEG channels. For this assessment, we constructed a hyper-frequency network (HFN) based on within- and cross-frequency coupling (WFC and CFC, respectively) at 10 oscillation frequencies ranging between 2 and 20 Hz. We found that CFC generally differentiates between task conditions better than WFC. CFC was the highest during resting state with eyes open. Using a graph-theoretical approach (GTA), we found that HFNs possess small-world network (SWN) topology with a slight tendency to random network characteristics. Moreover, analysis of the temporal fluctuations of HFNs revealed specific network topology dynamics (NTD), i.e., temporal changes of different graph-theoretical measures such as strength, clustering coefficient, characteristic path length (CPL), local, and global efficiency determined for HFNs at different time windows. The different topology metrics showed significant differences between conditions in the mean and standard deviation of these metrics both across time and nodes. In addition, using an artificial neural network approach, we found stimulus-related dynamics that varied across the different network topology metrics. We conclude that functional connectivity dynamics (FCD), or NTD, which was found using the HFN approach during rest and stimulus processing, reflects temporal and topological changes in the functional organization and reorganization of neuronal cell assemblies. PMID:27799906

Ensemble methods for stochastic networks with special reference to the biological clock of Neurospora crassa.

PubMed

Caranica, C; Al-Omari, A; Deng, Z; Griffith, J; Nilsen, R; Mao, L; Arnold, J; Schüttler, H-B

2018-01-01

A major challenge in systems biology is to infer the parameters of regulatory networks that operate in a noisy environment, such as in a single cell. In a stochastic regime it is hard to distinguish noise from the real signal and to infer the noise contribution to the dynamical behavior. When the genetic network displays oscillatory dynamics, it is even harder to infer the parameters that produce the oscillations. To address this issue we introduce a new estimation method built on a combination of stochastic simulations, mass action kinetics and ensemble network simulations in which we match the average periodogram and phase of the model to that of the data. The method is relatively fast (compared to Metropolis-Hastings Monte Carlo Methods), easy to parallelize, applicable to large oscillatory networks and large (~2000 cells) single cell expression data sets, and it quantifies the noise impact on the observed dynamics. Standard errors of estimated rate coefficients are typically two orders of magnitude smaller than the mean from single cell experiments with on the order of ~1000 cells. We also provide a method to assess the goodness of fit of the stochastic network using the Hilbert phase of single cells. An analysis of phase departures from the null model with no communication between cells is consistent with a hypothesis of Stochastic Resonance describing single cell oscillators. Stochastic Resonance provides a physical mechanism whereby intracellular noise plays a positive role in establishing oscillatory behavior, but may require model parameters, such as rate coefficients, that differ substantially from those extracted at the macroscopic level from measurements on populations of millions of communicating, synchronized cells.

Charting epilepsy by searching for intelligence in network space with the help of evolving autonomous agents.

PubMed

Ohayon, Elan L; Kalitzin, Stiliyan; Suffczynski, Piotr; Jin, Frank Y; Tsang, Paul W; Borrett, Donald S; Burnham, W McIntyre; Kwan, Hon C

2004-01-01

The problem of demarcating neural network space is formidable. A simple fully connected recurrent network of five units (binary activations, synaptic weight resolution of 10) has 3.2 *10(26) possible initial states. The problem increases drastically with scaling. Here we consider three complementary approaches to help direct the exploration to distinguish epileptic from healthy networks. [1] First, we perform a gross mapping of the space of five-unit continuous recurrent networks using randomized weights and initial activations. The majority of weight patterns (>70%) were found to result in neural assemblies exhibiting periodic limit-cycle oscillatory behavior. [2] Next we examine the activation space of non-periodic networks demonstrating that the emergence of paroxysmal activity does not require changes in connectivity. [3] The next challenge is to focus the search of network space to identify networks with more complex dynamics. Here we rely on a major available indicator critical to clinical assessment but largely ignored by epilepsy modelers, namely: behavioral states. To this end, we connected the above network layout to an external robot in which interactive states were evolved. The first random generation showed a distribution in line with approach [1]. That is, the predominate phenotypes were fixed-point or oscillatory with seizure-like motor output. As evolution progressed the profile changed markedly. Within 20 generations the entire population was able to navigate a simple environment with all individuals exhibiting multiply-stable behaviors with no cases of default locked limit-cycle oscillatory motor behavior. The resultant population may thus afford us a view of the architectural principles demarcating healthy biological networks from the pathological. The approach has an advantage over other epilepsy modeling techniques in providing a way to clarify whether observed dynamics or suggested therapies are pointing to computational viability or dead space.

Robustness of Oscillatory Behavior in Correlated Networks

PubMed Central

Sasai, Takeyuki; Morino, Kai; Tanaka, Gouhei; Almendral, Juan A.; Aihara, Kazuyuki

2015-01-01

Understanding network robustness against failures of network units is useful for preventing large-scale breakdowns and damages in real-world networked systems. The tolerance of networked systems whose functions are maintained by collective dynamical behavior of the network units has recently been analyzed in the framework called dynamical robustness of complex networks. The effect of network structure on the dynamical robustness has been examined with various types of network topology, but the role of network assortativity, or degree–degree correlations, is still unclear. Here we study the dynamical robustness of correlated (assortative and disassortative) networks consisting of diffusively coupled oscillators. Numerical analyses for the correlated networks with Poisson and power-law degree distributions show that network assortativity enhances the dynamical robustness of the oscillator networks but the impact of network disassortativity depends on the detailed network connectivity. Furthermore, we theoretically analyze the dynamical robustness of correlated bimodal networks with two-peak degree distributions and show the positive impact of the network assortativity. PMID:25894574

Synchronization of heteroclinic circuits through learning in coupled neural networks

NASA Astrophysics Data System (ADS)

Selskii, Anton; Makarov, Valeri A.

2016-01-01

The synchronization of oscillatory activity in neural networks is usually implemented by coupling the state variables describing neuronal dynamics. Here we study another, but complementary mechanism based on a learning process with memory. A driver network, acting as a teacher, exhibits winner-less competition (WLC) dynamics, while a driven network, a learner, tunes its internal couplings according to the oscillations observed in the teacher. We show that under appropriate training the learner can "copy" the coupling structure and thus synchronize oscillations with the teacher. The replication of the WLC dynamics occurs for intermediate memory lengths only, consequently, the learner network exhibits a phenomenon of learning resonance.

Core regulatory network motif underlies the ocellar complex patterning in Drosophila melanogaster

NASA Astrophysics Data System (ADS)

Aguilar-Hidalgo, D.; Lemos, M. C.; Córdoba, A.

2015-03-01

During organogenesis, developmental programs governed by Gene Regulatory Networks (GRN) define the functionality, size and shape of the different constituents of living organisms. Robustness, thus, is an essential characteristic that GRNs need to fulfill in order to maintain viability and reproducibility in a species. In the present work we analyze the robustness of the patterning for the ocellar complex formation in Drosophila melanogaster fly. We have systematically pruned the GRN that drives the development of this visual system to obtain the minimum pathway able to satisfy this pattern. We found that the mechanism underlying the patterning obeys to the dynamics of a 3-nodes network motif with a double negative feedback loop fed by a morphogenetic gradient that triggers the inhibition in a French flag problem fashion. A Boolean modeling of the GRN confirms robustness in the patterning mechanism showing the same result for different network complexity levels. Interestingly, the network provides a steady state solution in the interocellar part of the patterning and an oscillatory regime in the ocelli. This theoretical result predicts that the ocellar pattern may underlie oscillatory dynamics in its genetic regulation.

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

Autocatalytic, bistable, oscillatory networks of biologically relevant organic reactions.

PubMed

Semenov, Sergey N; Kraft, Lewis J; Ainla, Alar; Zhao, Mengxia; Baghbanzadeh, Mostafa; Campbell, Victoria E; Kang, Kyungtae; Fox, Jerome M; Whitesides, George M

2016-09-29

Networks of organic chemical reactions are important in life and probably played a central part in its origin. Network dynamics regulate cell division, circadian rhythms, nerve impulses and chemotaxis, and guide the development of organisms. Although out-of-equilibrium networks of chemical reactions have the potential to display emergent network dynamics such as spontaneous pattern formation, bistability and periodic oscillations, the principles that enable networks of organic reactions to develop complex behaviours are incompletely understood. Here we describe a network of biologically relevant organic reactions (amide formation, thiolate-thioester exchange, thiolate-disulfide interchange and conjugate addition) that displays bistability and oscillations in the concentrations of organic thiols and amides. Oscillations arise from the interaction between three subcomponents of the network: an autocatalytic cycle that generates thiols and amides from thioesters and dialkyl disulfides; a trigger that controls autocatalytic growth; and inhibitory processes that remove activating thiol species that are produced during the autocatalytic cycle. In contrast to previous studies that have demonstrated oscillations and bistability using highly evolved biomolecules (enzymes and DNA) or inorganic molecules of questionable biochemical relevance (for example, those used in Belousov-Zhabotinskii-type reactions), the organic molecules we use are relevant to metabolism and similar to those that might have existed on the early Earth. By using small organic molecules to build a network of organic reactions with autocatalytic, bistable and oscillatory behaviour, we identify principles that explain the ways in which dynamic networks relevant to life could have developed. Modifications of this network will clarify the influence of molecular structure on the dynamics of reaction networks, and may enable the design of biomimetic networks and of synthetic self-regulating and evolving chemical systems.

Autocatalytic, bistable, oscillatory networks of biologically relevant organic reactions

NASA Astrophysics Data System (ADS)

Semenov, Sergey N.; Kraft, Lewis J.; Ainla, Alar; Zhao, Mengxia; Baghbanzadeh, Mostafa; Campbell, Victoria E.; Kang, Kyungtae; Fox, Jerome M.; Whitesides, George M.

2016-09-01

Networks of organic chemical reactions are important in life and probably played a central part in its origin. Network dynamics regulate cell division, circadian rhythms, nerve impulses and chemotaxis, and guide the development of organisms. Although out-of-equilibrium networks of chemical reactions have the potential to display emergent network dynamics such as spontaneous pattern formation, bistability and periodic oscillations, the principles that enable networks of organic reactions to develop complex behaviours are incompletely understood. Here we describe a network of biologically relevant organic reactions (amide formation, thiolate-thioester exchange, thiolate-disulfide interchange and conjugate addition) that displays bistability and oscillations in the concentrations of organic thiols and amides. Oscillations arise from the interaction between three subcomponents of the network: an autocatalytic cycle that generates thiols and amides from thioesters and dialkyl disulfides; a trigger that controls autocatalytic growth; and inhibitory processes that remove activating thiol species that are produced during the autocatalytic cycle. In contrast to previous studies that have demonstrated oscillations and bistability using highly evolved biomolecules (enzymes and DNA) or inorganic molecules of questionable biochemical relevance (for example, those used in Belousov-Zhabotinskii-type reactions), the organic molecules we use are relevant to metabolism and similar to those that might have existed on the early Earth. By using small organic molecules to build a network of organic reactions with autocatalytic, bistable and oscillatory behaviour, we identify principles that explain the ways in which dynamic networks relevant to life could have developed. Modifications of this network will clarify the influence of molecular structure on the dynamics of reaction networks, and may enable the design of biomimetic networks and of synthetic self-regulating and evolving chemical systems.

On the Inference of Functional Circadian Networks Using Granger Causality

PubMed Central

Pourzanjani, Arya; Herzog, Erik D.; Petzold, Linda R.

2015-01-01

Being able to infer one way direct connections in an oscillatory network such as the suprachiastmatic nucleus (SCN) of the mammalian brain using time series data is difficult but crucial to understanding network dynamics. Although techniques have been developed for inferring networks from time series data, there have been no attempts to adapt these techniques to infer directional connections in oscillatory time series, while accurately distinguishing between direct and indirect connections. In this paper an adaptation of Granger Causality is proposed that allows for inference of circadian networks and oscillatory networks in general called Adaptive Frequency Granger Causality (AFGC). Additionally, an extension of this method is proposed to infer networks with large numbers of cells called LASSO AFGC. The method was validated using simulated data from several different networks. For the smaller networks the method was able to identify all one way direct connections without identifying connections that were not present. For larger networks of up to twenty cells the method shows excellent performance in identifying true and false connections; this is quantified by an area-under-the-curve (AUC) 96.88%. We note that this method like other Granger Causality-based methods, is based on the detection of high frequency signals propagating between cell traces. Thus it requires a relatively high sampling rate and a network that can propagate high frequency signals. PMID:26413748

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.

Dynamic information routing in complex networks

PubMed Central

Kirst, Christoph; Timme, Marc; Battaglia, Demian

2016-01-01

Flexible information routing fundamentally underlies the function of many biological and artificial networks. Yet, how such systems may specifically communicate and dynamically route information is not well understood. Here we identify a generic mechanism to route information on top of collective dynamical reference states in complex networks. Switching between collective dynamics induces flexible reorganization of information sharing and routing patterns, as quantified by delayed mutual information and transfer entropy measures between activities of a network's units. We demonstrate the power of this mechanism specifically for oscillatory dynamics and analyse how individual unit properties, the network topology and external inputs co-act to systematically organize information routing. For multi-scale, modular architectures, we resolve routing patterns at all levels. Interestingly, local interventions within one sub-network may remotely determine nonlocal network-wide communication. These results help understanding and designing information routing patterns across systems where collective dynamics co-occurs with a communication function. PMID:27067257

Oscillatory dynamics in the dorsal and ventral attention networks during the reorienting of attention.

PubMed

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

2018-05-01

The ability to reorient attention within the visual field is central to daily functioning, and numerous fMRI studies have shown that the dorsal and ventral attention networks (DAN, VAN) are critical to such processes. However, despite the instantaneous nature of attentional shifts, the dynamics of oscillatory activity serving attentional reorientation remain poorly characterized. In this study, we utilized magnetoencephalography (MEG) and a Posner task to probe the dynamics of attentional reorienting in 29 healthy adults. MEG data were transformed into the time-frequency domain and significant oscillatory responses were imaged using a beamformer. Voxel time series were then extracted from peak voxels in the functional beamformer images. These time series were used to quantify the dynamics of attentional reorienting, and to compute dynamic functional connectivity. Our results indicated strong increases in theta and decreases in alpha and beta activity across many nodes in the DAN and VAN. Interestingly, theta responses were generally stronger during trials that required attentional reorienting relative to those that did not, while alpha and beta oscillations were more dynamic, with many regions exhibiting significantly stronger responses during non-reorienting trials initially, and the opposite pattern during later processing. Finally, stronger functional connectivity was found following target presentation (575-700 ms) between bilateral superior parietal lobules during attentional reorienting. In sum, these data show that visual attention is served by multiple cortical regions within the DAN and VAN, and that attentional reorienting processes are often associated with spectrally-specific oscillations that have largely distinct spatiotemporal dynamics. © 2018 Wiley Periodicals, Inc.

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

Midfrontal Theta and Posterior Parietal Alpha Band Oscillations Support Conflict Resolution in a Masked Affective Priming Task.

PubMed

Jiang, Jun; Bailey, Kira; Xiao, Xiao

2018-01-01

Past attempts to characterize the neural mechanisms of affective priming have conceptualized it in terms of classic cognitive conflict, but have not examined the neural oscillatory mechanisms of subliminal affective priming. Using behavioral and electroencephalogram (EEG) time frequency (TF) analysis, the current study examines the oscillatory dynamics of unconsciously triggered conflict in an emotional facial expressions version of the masked affective priming task. The results demonstrate that the power dynamics of conflict are characterized by increased midfrontal theta activity and suppressed parieto-occipital alpha activity. Across-subject and within-trial correlation analyses further confirmed this pattern. Phase synchrony and Granger causality analyses (GCAs) revealed that the fronto-parietal network was involved in unconscious conflict detection and resolution. Our findings support a response conflict account of affective priming, and reveal the role of the fronto-parietal network in unconscious conflict control.

Influence of parameter values on the oscillation sensitivities of two p53-Mdm2 models.

PubMed

Cuba, Christian E; Valle, Alexander R; Ayala-Charca, Giancarlo; Villota, Elizabeth R; Coronado, Alberto M

2015-09-01

Biomolecular networks that present oscillatory behavior are ubiquitous in nature. While some design principles for robust oscillations have been identified, it is not well understood how these oscillations are affected when the kinetic parameters are constantly changing or are not precisely known, as often occurs in cellular environments. Many models of diverse complexity level, for systems such as circadian rhythms, cell cycle or the p53 network, have been proposed. Here we assess the influence of hundreds of different parameter sets on the sensitivities of two configurations of a well-known oscillatory system, the p53 core network. We show that, for both models and all parameter sets, the parameter related to the p53 positive feedback, i.e. self-promotion, is the only one that presents sizeable sensitivities on extrema, periods and delay. Moreover, varying the parameter set values to change the dynamical characteristics of the response is more restricted in the simple model, whereas the complex model shows greater tunability. These results highlight the importance of the presence of specific network patterns, in addition to the role of parameter values, when we want to characterize oscillatory biochemical systems.

Linking Essential Tremor to the Cerebellum: Physiological Evidence.

PubMed

Filip, Pavel; Lungu, Ovidiu V; Manto, Mario-Ubaldo; Bareš, Martin

2016-12-01

Essential tremor (ET), clinically characterized by postural and kinetic tremors, predominantly in the upper extremities, originates from pathological activity in the dynamic oscillatory network comprising the majority of nodes in the central motor network. Evidence indicates dysfunction in the thalamus, the olivocerebellar loops, and intermittent cortical engagement. Pathology of the cerebellum, a structure with architecture intrinsically predisposed to oscillatory activity, has also been implicated in ET as shown by clinical, neuroimaging, and pathological studies. Despite electrophysiological studies assessing cerebellar impairment in ET being scarce, their impact is tangible, as summarized in this review. The electromyography-magnetoencephalography combination provided the first direct evidence of pathological alteration in cortico-subcortical communication, with a significant emphasis on the cerebellum. Furthermore, complex electromyography studies showed disruptions in the timing of agonist and antagonist muscle activation, a process generally attributed to the cerebellum. Evidence pointing to cerebellar engagement in ET has also been found in electrooculography measurements, cerebellar repetitive transcranial magnetic stimulation studies, and, indirectly, in complex analyses of the activity of the ventral intermediate thalamic nucleus (an area primarily receiving inputs from the cerebellum), which is also used in the advanced treatment of ET. In summary, further progress in therapy will require comprehensive electrophysiological and physiological analyses to elucidate the precise mechanisms leading to disease symptoms. The cerebellum, as a major node of this dynamic oscillatory network, requires further study to aid this endeavor.

A Role of Phase-Resetting in Coordinating Large Scale Neural Networks During Attention and Goal-Directed Behavior

PubMed Central

Voloh, Benjamin; Womelsdorf, Thilo

2016-01-01

Short periods of oscillatory activation are ubiquitous signatures of neural circuits. A broad range of studies documents not only their circuit origins, but also a fundamental role for oscillatory activity in coordinating information transfer during goal directed behavior. Recent studies suggest that resetting the phase of ongoing oscillatory activity to endogenous or exogenous cues facilitates coordinated information transfer within circuits and between distributed brain areas. Here, we review evidence that pinpoints phase resetting as a critical marker of dynamic state changes of functional networks. Phase resets: (1) set a “neural context” in terms of narrow band frequencies that uniquely characterizes the activated circuits; (2) impose coherent low frequency phases to which high frequency activations can synchronize, identifiable as cross-frequency correlations across large anatomical distances; (3) are critical for neural coding models that depend on phase, increasing the informational content of neural representations; and (4) likely originate from the dynamics of canonical E-I circuits that are anatomically ubiquitous. These multiple signatures of phase resets are directly linked to enhanced information transfer and behavioral success. We survey how phase resets re-organize oscillations in diverse task contexts, including sensory perception, attentional stimulus selection, cross-modal integration, Pavlovian conditioning, and spatial navigation. The evidence we consider suggests that phase-resets can drive changes in neural excitability, ensemble organization, functional networks, and ultimately, overt behavior. PMID:27013986

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.

Hidden long evolutionary memory in a model biochemical network

NASA Astrophysics Data System (ADS)

Ali, Md. Zulfikar; Wingreen, Ned S.; Mukhopadhyay, Ranjan

2018-04-01

We introduce a minimal model for the evolution of functional protein-interaction networks using a sequence-based mutational algorithm, and apply the model to study neutral drift in networks that yield oscillatory dynamics. Starting with a functional core module, random evolutionary drift increases network complexity even in the absence of specific selective pressures. Surprisingly, we uncover a hidden order in sequence space that gives rise to long-term evolutionary memory, implying strong constraints on network evolution due to the topology of accessible sequence space.

The power law and dynamic rheology in food analysis

USDA-ARS?s Scientific Manuscript database

Protein networks impart functional and structural characteristics to food, and should be examined to gain an understanding of properties of the product. Food matrices are investigated nondestructively by small amplitude oscillatory shear analysis, which provides information on viscoelasticity, incl...

Processing oscillatory signals by incoherent feedforward loops

NASA Astrophysics Data System (ADS)

Zhang, Carolyn; Wu, Feilun; Tsoi, Ryan; Shats, Igor; You, Lingchong

From the timing of amoeba development to the maintenance of stem cell pluripotency,many biological signaling pathways exhibit the ability to differentiate between pulsatile and sustained signals in the regulation of downstream gene expression.While networks underlying this signal decoding are diverse,many are built around a common motif, the incoherent feedforward loop (IFFL),where an input simultaneously activates an output and an inhibitor of the output.With appropriate parameters,this motif can generate temporal adaptation,where the system is desensitized to a sustained input.This property serves as the foundation for distinguishing signals with varying temporal profiles.Here,we use quantitative modeling to examine another property of IFFLs,the ability to process oscillatory signals.Our results indicate that the system's ability to translate pulsatile dynamics is limited by two constraints.The kinetics of IFFL components dictate the input range for which the network can decode pulsatile dynamics.In addition,a match between the network parameters and signal characteristics is required for optimal ``counting''.We elucidate one potential mechanism by which information processing occurs in natural networks with implications in the design of synthetic gene circuits for this purpose. This work was partially supported by the National Science Foundation Graduate Research Fellowship (CZ).

Processing Oscillatory Signals by Incoherent Feedforward Loops

PubMed Central

Zhang, Carolyn; You, Lingchong

2016-01-01

From the timing of amoeba development to the maintenance of stem cell pluripotency, many biological signaling pathways exhibit the ability to differentiate between pulsatile and sustained signals in the regulation of downstream gene expression. While the networks underlying this signal decoding are diverse, many are built around a common motif, the incoherent feedforward loop (IFFL), where an input simultaneously activates an output and an inhibitor of the output. With appropriate parameters, this motif can exhibit temporal adaptation, where the system is desensitized to a sustained input. This property serves as the foundation for distinguishing input signals with varying temporal profiles. Here, we use quantitative modeling to examine another property of IFFLs—the ability to process oscillatory signals. Our results indicate that the system’s ability to translate pulsatile dynamics is limited by two constraints. The kinetics of the IFFL components dictate the input range for which the network is able to decode pulsatile dynamics. In addition, a match between the network parameters and input signal characteristics is required for optimal “counting”. We elucidate one potential mechanism by which information processing occurs in natural networks, and our work has implications in the design of synthetic gene circuits for this purpose. PMID:27623175

Corticomuscular transmission of tremor signals by propriospinal neurons in Parkinson's disease.

PubMed

Hao, Manzhao; He, Xin; Xiao, Qin; Alstermark, Bror; Lan, Ning

2013-01-01

Cortical oscillatory signals of single and double tremor frequencies act together to cause tremor in the peripheral limbs of patients with Parkinson's disease (PD). But the corticospinal pathway that transmits the tremor signals has not been clarified, and how alternating bursts of antagonistic muscle activations are generated from the cortical oscillatory signals is not well understood. This paper investigates the plausible role of propriospinal neurons (PN) in C3-C4 in transmitting the cortical oscillatory signals to peripheral muscles. Kinematics data and surface electromyogram (EMG) of tremor in forearm were collected from PD patients. A PN network model was constructed based on known neurophysiological connections of PN. The cortical efferent signal of double tremor frequencies were integrated at the PN network, whose outputs drove the muscles of a virtual arm (VA) model to simulate tremor behaviors. The cortical efferent signal of single tremor frequency actuated muscle spindles. By comparing tremor data of PD patients and the results of model simulation, we examined two hypotheses regarding the corticospinal transmission of oscillatory signals in Parkinsonian tremor. Hypothesis I stated that the oscillatory cortical signals were transmitted via the mono-synaptic corticospinal pathways bypassing the PN network. The alternative hypothesis II stated that they were transmitted by way of PN multi-synaptic corticospinal pathway. Simulations indicated that without the PN network, the alternating burst patterns of antagonistic muscle EMGs could not be reliably generated, rejecting the first hypothesis. However, with the PN network, the alternating burst patterns of antagonist EMGs were naturally reproduced under all conditions of cortical oscillations. The results suggest that cortical commands of single and double tremor frequencies are further processed at PN to compute the alternating burst patterns in flexor and extensor muscles, and the neuromuscular dynamics demonstrated a frequency dependent damping on tremor, which may prevent tremor above 8 Hz to occur.

Corticomuscular Transmission of Tremor Signals by Propriospinal Neurons in Parkinson's Disease

PubMed Central

Hao, Manzhao; He, Xin; Xiao, Qin; Alstermark, Bror; Lan, Ning

2013-01-01

Cortical oscillatory signals of single and double tremor frequencies act together to cause tremor in the peripheral limbs of patients with Parkinson's disease (PD). But the corticospinal pathway that transmits the tremor signals has not been clarified, and how alternating bursts of antagonistic muscle activations are generated from the cortical oscillatory signals is not well understood. This paper investigates the plausible role of propriospinal neurons (PN) in C3–C4 in transmitting the cortical oscillatory signals to peripheral muscles. Kinematics data and surface electromyogram (EMG) of tremor in forearm were collected from PD patients. A PN network model was constructed based on known neurophysiological connections of PN. The cortical efferent signal of double tremor frequencies were integrated at the PN network, whose outputs drove the muscles of a virtual arm (VA) model to simulate tremor behaviors. The cortical efferent signal of single tremor frequency actuated muscle spindles. By comparing tremor data of PD patients and the results of model simulation, we examined two hypotheses regarding the corticospinal transmission of oscillatory signals in Parkinsonian tremor. Hypothesis I stated that the oscillatory cortical signals were transmitted via the mono-synaptic corticospinal pathways bypassing the PN network. The alternative hypothesis II stated that they were transmitted by way of PN multi-synaptic corticospinal pathway. Simulations indicated that without the PN network, the alternating burst patterns of antagonistic muscle EMGs could not be reliably generated, rejecting the first hypothesis. However, with the PN network, the alternating burst patterns of antagonist EMGs were naturally reproduced under all conditions of cortical oscillations. The results suggest that cortical commands of single and double tremor frequencies are further processed at PN to compute the alternating burst patterns in flexor and extensor muscles, and the neuromuscular dynamics demonstrated a frequency dependent damping on tremor, which may prevent tremor above 8 Hz to occur. PMID:24278189

Nanomotor dynamics in a chemically oscillating medium

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

Robertson, Bryan, E-mail: bryan.robertson@mail.utoronto.ca; Kapral, Raymond, E-mail: rkapral@chem.utoronto.ca

2015-04-21

Synthetic nanomotors powered by chemical reactions have potential uses as cargo transport vehicles in both in vivo and in vitro applications. In many situations, motors will have to operate in out-of-equilibrium complex chemically reacting media, which supply fuel to the motors and remove the products they produce. Using molecular simulation and mean-field theory, this paper describes some of the new features that arise when a chemically powered nanomotor, operating through a diffusiophoretic mechanism, moves in an environment that supports an oscillatory chemical reaction network. It is shown how oscillations in the concentrations in chemical species in the environment give risemore » to oscillatory motor dynamics. More importantly, since the catalytic reactions on the motor that are responsible for its propulsion couple to the bulk phase reaction network, the motor can change its local environment. This process can give rise to distinctive spatiotemporal structures in reaction-diffusion media that occur as a result of active motor motion. Such locally induced nonequilibrium structure will play an important role in applications that involve motor dynamics in complex chemical media.« less

Dynamic rheology of food protein networks

USDA-ARS?s Scientific Manuscript database

Small amplitude oscillatory shear analyses of samples containing protein are useful for determining the nature of the protein matrix without damaging it. Elastic modulus, viscous modulus, and loss tangent (the ratio of viscous modulus to elastic modulus) give information on the strength of the netw...

Dynamic rheology of food protein networks

USDA-ARS?s Scientific Manuscript database

Small amplitude oscillatory shear analyses (SAOSA) of samples containing protein are useful for determining the nature of the protein matrix without damaging it. The Dairy Processing and Products Research Unit of the Agricultural Research Service, USDA has pioneered the use of SAOSA in understandin...

The power law and dynamic rheology in cheese analysis

USDA-ARS?s Scientific Manuscript database

The protein networks of food such as cheese are investigated nondestructively by small amplitude oscillatory shear analysis, which provides information on elastic modulus and viscous modulus. Relationships between frequency and viscoelastic data may be obtained from frequency sweeps by applying the...

Living on the edge of chaos: minimally nonlinear models of genetic regulatory dynamics.

PubMed

Hanel, Rudolf; Pöchacker, Manfred; Thurner, Stefan

2010-12-28

Linearized catalytic reaction equations (modelling, for example, the dynamics of genetic regulatory networks), under the constraint that expression levels, i.e. molecular concentrations of nucleic material, are positive, exhibit non-trivial dynamical properties, which depend on the average connectivity of the reaction network. In these systems, an inflation of the edge of chaos and multi-stability have been demonstrated to exist. The positivity constraint introduces a nonlinearity, which makes chaotic dynamics possible. Despite the simplicity of such minimally nonlinear systems, their basic properties allow us to understand the fundamental dynamical properties of complex biological reaction networks. We analyse the Lyapunov spectrum, determine the probability of finding stationary oscillating solutions, demonstrate the effect of the nonlinearity on the effective in- and out-degree of the active interaction network, and study how the frequency distributions of oscillatory modes of such a system depend on the average connectivity.

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.

Brain clock driven by neuropeptides and second messengers

NASA Astrophysics Data System (ADS)

Miro-Bueno, Jesus; Sosík, Petr

2014-09-01

The master circadian pacemaker in mammals is localized in a small portion of the brain called the suprachiasmatic nucleus (SCN). It is unclear how the SCN produces circadian rhythms. A common interpretation is that the SCN produces oscillations through the coupling of genetic oscillators in the neurons. The coupling is effected by a network of neuropeptides and second messengers. This network is crucial for the correct function of the SCN. However, models that study a possible oscillatory behavior of the network itself have received little attention. Here we propose and analyze a model to examine this oscillatory potential. We show that an intercellular oscillator emerges in the SCN as a result of the neuropeptide and second messenger dynamics. We find that this intercellular clock can produce circadian rhythms by itself with and without genetic clocks. We also found that the model is robust to perturbation of parameters and can be entrained by light-dark cycles.

Brain clock driven by neuropeptides and second messengers.

PubMed

Miro-Bueno, Jesus; Sosík, Petr

2014-09-01

The master circadian pacemaker in mammals is localized in a small portion of the brain called the suprachiasmatic nucleus (SCN). It is unclear how the SCN produces circadian rhythms. A common interpretation is that the SCN produces oscillations through the coupling of genetic oscillators in the neurons. The coupling is effected by a network of neuropeptides and second messengers. This network is crucial for the correct function of the SCN. However, models that study a possible oscillatory behavior of the network itself have received little attention. Here we propose and analyze a model to examine this oscillatory potential. We show that an intercellular oscillator emerges in the SCN as a result of the neuropeptide and second messenger dynamics. We find that this intercellular clock can produce circadian rhythms by itself with and without genetic clocks. We also found that the model is robust to perturbation of parameters and can be entrained by light-dark cycles.

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

Cellular-based modeling of oscillatory dynamics in brain networks.

PubMed

Skinner, Frances K

2012-08-01

Oscillatory, population activities have long been known to occur in our brains during different behavioral states. We know that many different cell types exist and that they contribute in distinct ways to the generation of these activities. I review recent papers that involve cellular-based models of brain networks, most of which include theta, gamma and sharp wave-ripple activities. To help organize the modeling work, I present it from a perspective of three different types of cellular-based modeling: 'Generic', 'Biophysical' and 'Linking'. Cellular-based modeling is taken to encompass the four features of experiment, model development, theory/analyses, and model usage/computation. The three modeling types are shown to include these features and interactions in different ways. Copyright © 2012 Elsevier Ltd. All rights reserved.

Combinatorial Optimization by Amoeba-Based Neurocomputer with Chaotic Dynamics

NASA Astrophysics Data System (ADS)

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

We demonstrate a computing system based on an amoeba of a true slime mold Physarum capable of producing rich spatiotemporal oscillatory behavior. Our system operates as a neurocomputer because an optical feedback control in accordance with a recurrent neural network algorithm leads the amoeba's photosensitive branches to search for a stable configuration concurrently. We show our system's capability of solving the traveling salesman problem. Furthermore, we apply various types of nonlinear time series analysis to the amoeba's oscillatory behavior in the problem-solving process. The results suggest that an individual amoeba might be characterized as a set of coupled chaotic oscillators.

Comparison of stationary and oscillatory dynamics described by differential equations and Boolean maps in transcriptional regulatory circuits

NASA Astrophysics Data System (ADS)

Ye, Weiming; Li, Pengfei; Huang, Xuhui; Xia, Qinzhi; Mi, Yuanyuan; Chen, Runsheng; Hu, Gang

2010-10-01

Exploring the principle and relationship of gene transcriptional regulations (TR) has been becoming a generally researched issue. So far, two major mathematical methods, ordinary differential equation (ODE) method and Boolean map (BM) method have been widely used for these purposes. It is commonly believed that simplified BMs are reasonable approximations of more realistic ODEs, and both methods may reveal qualitatively the same essential features though the dynamical details of both systems may show some differences. In this Letter we exhaustively enumerated all the 3-gene networks and many autonomous randomly constructed TR networks with more genes by using both the ODE and BM methods. In comparison we found that both methods provide practically identical results in most of cases of steady solutions. However, to our great surprise, most of network structures showing periodic cycles with the BM method possess only stationary states in ODE descriptions. These observations strongly suggest that many periodic oscillations and other complicated oscillatory states revealed by the BM rule may be related to the computational errors of variable and time discretizations and rarely have correspondence in realistic biology transcriptional regulatory circuits.

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.

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.

microRNA as a Potential Vector for the Propagation of Robustness in Protein Expression and Oscillatory Dynamics within a ceRNA Network

PubMed Central

Gérard, Claude; Novák, Béla

2013-01-01

microRNAs (miRNAs) are small noncoding RNAs that are important post-transcriptional regulators of gene expression. miRNAs can induce thresholds in protein synthesis. Such thresholds in protein output can be also achieved by oligomerization of transcription factors (TF) for the control of gene expression. First, we propose a minimal model for protein expression regulated by miRNA and by oligomerization of TF. We show that miRNA and oligomerization of TF generate a buffer, which increases the robustness of protein output towards molecular noise as well as towards random variation of kinetics parameters. Next, we extend the model by considering that the same miRNA can bind to multiple messenger RNAs, which accounts for the dynamics of a minimal competing endogenous RNAs (ceRNAs) network. The model shows that, through common miRNA regulation, TF can control the expression of all proteins formed by the ceRNA network, even if it drives the expression of only one gene in the network. The model further suggests that the threshold in protein synthesis mediated by the oligomerization of TF can be propagated to the other genes, which can increase the robustness of the expression of all genes in such ceRNA network. Furthermore, we show that a miRNA could increase the time delay of a “Goodwin-like” oscillator model, which may favor the occurrence of oscillations of large amplitude. This result predicts important roles of miRNAs in the control of the molecular mechanisms leading to the emergence of biological rhythms. Moreover, a model for the latter oscillator embedded in a ceRNA network indicates that the oscillatory behavior can be propagated, via the shared miRNA, to all proteins formed by such ceRNA network. Thus, by means of computational models, we show that miRNAs could act as vectors allowing the propagation of robustness in protein synthesis as well as oscillatory behaviors within ceRNA networks. PMID:24376695

Short-term memory in olfactory network dynamics

NASA Astrophysics Data System (ADS)

Stopfer, Mark; Laurent, Gilles

1999-12-01

Neural assemblies in a number of animal species display self-organized, synchronized oscillations in response to sensory stimuli in a variety of brain areas.. In the olfactory system of insects, odour-evoked oscillatory synchronization of antennal lobe projection neurons (PNs) is superimposed on slower and stimulus-specific temporal activity patterns. Hence, each odour activates a specific and dynamic projection neuron assembly whose evolution during a stimulus is locked to the oscillation clock. Here we examine, using locusts, the changes in population dynamics of projection-neuron assemblies over repeated odour stimulations, as would occur when an animal first encounters and then repeatedly samples an odour for identification or localization. We find that the responses of these assemblies rapidly decrease in intensity, while they show a marked increase in spike time precision and inter-neuronal oscillatory coherence. Once established, this enhanced precision in the representation endures for several minutes. This change is stimulus-specific, and depends on events within the antennal lobe circuits, independent of olfactory receptor adaptation: it may thus constitute a form of sensory memory. Our results suggest that this progressive change in olfactory network dynamics serves to converge, over repeated odour samplings, on a more precise and readily classifiable odour representation, using relational information contained across neural assemblies.

Evolution of the dynamic properties of the cortex-basal ganglia network after dopaminergic depletion in rats.

PubMed

Dejean, Cyril; Nadjar, Agnes; Le Moine, Catherine; Bioulac, Bernard; Gross, Christian E; Boraud, Thomas

2012-05-01

It is well established that parkinsonian syndrome is associated with alterations of neuronal activity temporal pattern basal ganglia (BG). An increase in synchronized oscillations has been observed in different BG nuclei in Parkinson's disease patients as well as animal models such as 6-hydroxydopamine treated rats. We recently demonstrated that this increase in oscillatory synchronization is present during high-voltage spindles (HVS) probably underpinned by the disorganization of cortex-BG interactions. Here we investigated the time course of both oscillatory and motor alterations. For that purpose we performed daily simultaneous recordings of neuronal activity in motor cortex, striatum and substantia nigra pars reticulata (SNr), before and after 6-hydroxydopamine lesion in awake rats. After a brief non-dopamine-specific desynchronization, oscillatory activity first increased during HVS followed by progressive motor impairment and the shortening of SNr activation delay. While the oscillatory firing increase reflects dopaminergic depletion, response alteration in SNr neurons is closely related to motor symptom. Copyright © 2012 Elsevier Inc. All rights reserved.

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

Subthalamic stimulation, oscillatory activity and connectivity reveal functional role of STN and network mechanisms during decision making under conflict.

PubMed

Hell, Franz; Taylor, Paul C J; Mehrkens, Jan H; Bötzel, Kai

2018-05-01

Inhibitory control is an important executive function that is necessary to suppress premature actions and to block interference from irrelevant stimuli. Current experimental studies and models highlight proactive and reactive mechanisms and claim several cortical and subcortical structures to be involved in response inhibition. However, the involved structures, network mechanisms and the behavioral relevance of the underlying neural activity remain debated. We report cortical EEG and invasive subthalamic local field potential recordings from a fully implanted sensing neurostimulator in Parkinson's patients during a stimulus- and response conflict task with and without deep brain stimulation (DBS). DBS made reaction times faster overall while leaving the effects of conflict intact: this lack of any effect on conflict may have been inherent to our task encouraging a high level of proactive inhibition. Drift diffusion modelling hints that DBS influences decision thresholds and drift rates are modulated by stimulus conflict. Both cortical EEG and subthalamic (STN) LFP oscillations reflected reaction times (RT). With these results, we provide a different interpretation of previously conflict-related oscillations in the STN and suggest that the STN implements a general task-specific decision threshold. The timecourse and topography of subthalamic-cortical oscillatory connectivity suggest the involvement of motor, frontal midline and posterior regions in a larger network with complementary functionality, oscillatory mechanisms and structures. While beta oscillations are functionally associated with motor cortical-subthalamic connectivity, low frequency oscillations reveal a subthalamic-frontal-posterior network. With our results, we suggest that proactive as well as reactive mechanisms and structures are involved in implementing a task-related dynamic inhibitory signal. We propose that motor and executive control networks with complementary oscillatory mechanisms are tonically active, react to stimuli and release inhibition at the response when uncertainty is resolved and return to their default state afterwards. Copyright © 2018 Elsevier Inc. All rights reserved.

Cortical oscillatory dynamics in a social interaction model.

PubMed

Knyazev, Gennady G; Slobodskoj-Plusnin, Jaroslav Y; Bocharov, Andrey V; Pylkova, Liudmila V

2013-03-15

In this study we sought to investigate cortical oscillatory dynamics accompanying three major kinds of social behavior: aggressive, friendly, and avoidant. Behavioral and EEG data were collected in 48 participants during a computer game modeling social interactions with virtual 'persons'. 3D source reconstruction and independent component analysis were applied to EEG data. Results showed that social behavior was partly reactive and partly proactive with subject's personality playing an important role in shaping this behavior. Most salient differences were found between avoidance and approach behaviors, whereas the two kinds of approach behavior (i.e., aggression and friendship) did not differ from each other. Comparative to avoidance, approach behaviors were associated with higher induced responses in most frequency bands which were mostly observed in cortical areas overlapping with the default mode network. The difference between approach- and avoidance-related oscillatory dynamics was more salient in subjects predisposed to approach behaviors (i.e., in aggressive or sociable subjects) and was less pronounced in subjects predisposed to avoidance behavior (i.e., in high trait anxiety scorers). There was a trend to higher low frequency phase-locking in motor area in approach than in avoid condition. Results are discussed in light of the concept linking induced responses with top-down and evoked responses with bottom-up processes. Copyright © 2012 Elsevier B.V. All rights reserved.

Optical Communication among Oscillatory Reactions and Photo-Excitable Systems: UV and Visible Radiation Can Synchronize Artificial Neuron Models.

PubMed

Gentili, Pier Luigi; Giubila, Maria Sole; Germani, Raimondo; Romani, Aldo; Nicoziani, Andrea; Spalletti, Anna; Heron, B Mark

2017-06-19

Neuromorphic engineering promises to have a revolutionary impact in our societies. A strategy to develop artificial neurons (ANs) is to use oscillatory and excitable chemical systems. Herein, we use UV and visible radiation as both excitatory and inhibitory signals for the communication among oscillatory reactions, such as the Belousov-Zhabotinsky and the chemiluminescent Orban transformations, and photo-excitable photochromic and fluorescent species. We present the experimental results and the simulations regarding pairs of ANs communicating by either one or two optical signals, and triads of ANs arranged in both feed-forward and recurrent networks. We find that the ANs, powered chemically and/or by the energy of electromagnetic radiation, can give rise to the emergent properties of in-phase, out-of-phase, anti-phase synchronizations and phase-locking, dynamically mimicking the communication among real neurons. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Self-Organized Information Processing in Neuronal Networks: Replacing Layers in Deep Networks by Dynamics

NASA Astrophysics Data System (ADS)

Kirst, Christoph

It is astonishing how the sub-parts of a brain co-act to produce coherent behavior. What are mechanism that coordinate information processing and communication and how can those be changed flexibly in order to cope with variable contexts? Here we show that when information is encoded in the deviations around a collective dynamical reference state of a recurrent network the propagation of these fluctuations is strongly dependent on precisely this underlying reference. Information here 'surfs' on top of the collective dynamics and switching between states enables fast and flexible rerouting of information. This in turn affects local processing and consequently changes in the global reference dynamics that re-regulate the distribution of information. This provides a generic mechanism for self-organized information processing as we demonstrate with an oscillatory Hopfield network that performs contextual pattern recognition. Deep neural networks have proven to be very successful recently. Here we show that generating information channels via collective reference dynamics can effectively compress a deep multi-layer architecture into a single layer making this mechanism a promising candidate for the organization of information processing in biological neuronal networks.

A Subcortical Oscillatory Network Contributes to Recovery of Hand Dexterity after Spinal Cord Injury

ERIC Educational Resources Information Center

Nishimura, Yukio; Morichika, Yosuke; Isa, Tadashi

2009-01-01

Recent studies have shown that after partial spinal-cord lesion at the mid-cervical segment, the remaining pathways compensate for restoring finger dexterity; however, how they control hand/arm muscles has remained unclear. To elucidate the changes in dynamic properties of neural circuits connecting the motor cortex and hand/arm muscles, we…

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 is found to be correlated, instantiating the empirically observed RSNs. Between clusters, patterns of positive and negative correlations are observed, as described in experimental studies. These results are found to be robust with respect to a biologically plausible range of model parameters. In conclusion, our model suggests how resting-state neural activity can originate from the interplay between the local neural dynamics and the large-scale structure of the brain. Copyright © 2011 Elsevier Inc. All rights reserved.

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.

A biophysical model of dynamic balancing of excitation and inhibition in fast oscillatory large-scale networks

PubMed Central

Sotiropoulos, Stamatios N.; Brookes, Matthew J.; Woolrich, Mark W.

2018-01-01

Over long timescales, neuronal dynamics can be robust to quite large perturbations, such as changes in white matter connectivity and grey matter structure through processes including learning, aging, development and certain disease processes. One possible explanation is that robust dynamics are facilitated by homeostatic mechanisms that can dynamically rebalance brain networks. In this study, we simulate a cortical brain network using the Wilson-Cowan neural mass model with conduction delays and noise, and use inhibitory synaptic plasticity (ISP) to dynamically achieve a spatially local balance between excitation and inhibition. Using MEG data from 55 subjects we find that ISP enables us to simultaneously achieve high correlation with multiple measures of functional connectivity, including amplitude envelope correlation and phase locking. Further, we find that ISP successfully achieves local E/I balance, and can consistently predict the functional connectivity computed from real MEG data, for a much wider range of model parameters than is possible with a model without ISP. PMID:29474352

Olfactory system gamma oscillations: the physiological dissection of a cognitive neural system

PubMed Central

Rojas-Líbano, Daniel

2008-01-01

Oscillatory phenomena have been a focus of dynamical systems research since the time of the classical studies on the pendulum by Galileo. Fast cortical oscillations also have a long and storied history in neurophysiology, and olfactory oscillations have led the way with a depth of explanation not present in the literature of most other cortical systems. From the earliest studies of odor-evoked oscillations by Adrian, many reports have focused on mechanisms and functional associations of these oscillations, in particular for the so-called gamma oscillations. As a result, much information is now available regarding the biophysical mechanisms that underlie the oscillations in the mammalian olfactory system. Recent studies have expanded on these and addressed functionality directly in mammals and in the analogous insect system. Sub-bands within the rodent gamma oscillatory band associated with specific behavioral and cognitive states have also been identified. All this makes oscillatory neuronal networks a unique interdisciplinary platform from which to study neurocognitive and dynamical phenomena in intact, freely behaving animals. We present here a summary of what has been learned about the functional role and mechanisms of gamma oscillations in the olfactory system as a guide for similar studies in other cortical systems. PMID:19003484

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

PubMed

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

2017-11-01

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

Some Physical Principles Governing Spatial and Temporal Organization in Living Systems

NASA Astrophysics Data System (ADS)

Ali, Md Zulfikar

Spatial and temporal organization in living organisms are crucial for a variety of biological functions and arise from the interplay of large number of interacting molecules. One of the central questions in systems biology is to understand how such an intricate organization emerges from the molecular biochemistry of the cell. In this dissertation we explore two projects. The first project relates to pattern formation in a cell membrane as an example of spatial organization, and the second project relates to the evolution of oscillatory networks as a simple example of temporal organization. For the first project, we introduce a model for pattern formation in a two-component lipid bilayer and study the interplay between membrane composition and membrane geometry, demonstrating the existence of a rich phase diagram. Pattern formation is governed by the interplay between phase separation driven by lipid-lipid interactions and tendency of lipid domains with high intrinsic curvature to deform the membrane away from its preferred position. Depending on membrane parameters, we find the formation of compact lipid micro-clusters or of striped domains. We calculate the stripe width analytically and find good agreement with stripe widths obtained from the simulations. For the second project, we introduce a minimal model for the evolution of functional protein-interaction networks using a sequence-based mutational algorithm and apply it to study the following problems. Using the model, we study robustness and designabilty of a 2-component network that generate oscillations. We completely enumerate the sequence space and the phenotypic space, and discuss the relationship between designabilty, robustness and evolvability. We further apply the model to studies of neutral drift in networks that yield oscillatory dynamics, e.g. starting with a relatively simple network and allowing it to evolve by adding nodes and connections while requiring that oscillatory dynamics be preserved. Our studies demonstrate both the importance of employing a sequence-based evolutionary scheme and the relative rapidity (in evolutionary time) for the redistribution of function over new nodes via neutral drift. In addition we discovered another much slower timescale for network evolution, reflecting hidden order in sequence space that we interpret in terms of sparsely connected domains. Finally, we use the model to study the evolution of an oscillator from a non-oscillatory network under the influence of external periodic forcing as a model for evolution of circadian rhythm in living systems. We use a greedy algorithm based on optimizing biologically motivated fitness functions and find that the algorithm successfully produces oscillators. However, the distribution of free-period of evolved oscillators depends on the choice of fitness functions and the nature of forcing.

Investigation of Dynamic Algorithms for Pattern Recognition Identified in Cerebral Cortex

DTIC Science & Technology

1991-12-02

oscillatory and possibly chaotic activity forin the actual cortical substrate of the diverse sensory, motor, and cognitive operations now studied in...September Neural Information Processing Systems - Natural and Synthetic, Denver, Colo., November 1989 U.C. San Diego, Cognitive Science Dept...Baird. Biologically applied neural networks may foster the co-evolution of neurobiology and cognitive psychology. Brain and Behavioral Sciences, 37

Thalamic synchrony and dynamic regulation of global forebrain oscillations.

PubMed

Huguenard, John R; McCormick, David A

2007-07-01

The circuitry within the thalamus creates an intrinsic oscillatory unit whose function depends critically on reciprocal synaptic connectivity between excitatory thalamocortical relay neurons and inhibitory thalamic reticular neurons along with a robust post-inhibitory rebound mechanism in relay neurons. Feedforward and feedback connections between cortex and thalamus reinforce the thalamic oscillatory activity into larger thalamocortical networks to generate sleep spindles and spike-wave discharge of generalized absence epilepsy. The degree of synchrony within the thalamic network seems to be crucial in determining whether normal (spindle) or pathological (spike-wave) oscillations occur, and recent studies show that regulation of excitability in the reticular nucleus leads to dynamical modulation of the state of the thalamic circuit and provide a basis for explaining how a variety of unrelated genetic alterations might lead to the spike-wave phenotype. In addition, given the central role of the reticular nucleus in generating spike-wave discharge, these studies have suggested specific interventions that would prevent seizures while still allowing normal spindle generation to occur. 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).

Dynamic decomposition of spatiotemporal neural signals

PubMed Central

2017-01-01

Neural signals are characterized by rich temporal and spatiotemporal dynamics that reflect the organization of cortical networks. Theoretical research has shown how neural networks can operate at different dynamic ranges that correspond to specific types of information processing. Here we present a data analysis framework that uses a linearized model of these dynamic states in order to decompose the measured neural signal into a series of components that capture both rhythmic and non-rhythmic neural activity. The method is based on stochastic differential equations and Gaussian process regression. Through computer simulations and analysis of magnetoencephalographic data, we demonstrate the efficacy of the method in identifying meaningful modulations of oscillatory signals corrupted by structured temporal and spatiotemporal noise. These results suggest that the method is particularly suitable for the analysis and interpretation of complex temporal and spatiotemporal neural signals. PMID:28558039

Quantifying Neural Oscillatory Synchronization: A Comparison between Spectral Coherence and Phase-Locking Value Approaches

PubMed Central

Lowet, Eric; Roberts, Mark J.; Bonizzi, Pietro; Karel, Joël; De Weerd, Peter

2016-01-01

Synchronization or phase-locking between oscillating neuronal groups is considered to be important for coordination of information among cortical networks. Spectral coherence is a commonly used approach to quantify phase locking between neural signals. We systematically explored the validity of spectral coherence measures for quantifying synchronization among neural oscillators. To that aim, we simulated coupled oscillatory signals that exhibited synchronization dynamics using an abstract phase-oscillator model as well as interacting gamma-generating spiking neural networks. We found that, within a large parameter range, the spectral coherence measure deviated substantially from the expected phase-locking. Moreover, spectral coherence did not converge to the expected value with increasing signal-to-noise ratio. We found that spectral coherence particularly failed when oscillators were in the partially (intermittent) synchronized state, which we expect to be the most likely state for neural synchronization. The failure was due to the fast frequency and amplitude changes induced by synchronization forces. We then investigated whether spectral coherence reflected the information flow among networks measured by transfer entropy (TE) of spike trains. We found that spectral coherence failed to robustly reflect changes in synchrony-mediated information flow between neural networks in many instances. As an alternative approach we explored a phase-locking value (PLV) method based on the reconstruction of the instantaneous phase. As one approach for reconstructing instantaneous phase, we used the Hilbert Transform (HT) preceded by Singular Spectrum Decomposition (SSD) of the signal. PLV estimates have broad applicability as they do not rely on stationarity, and, unlike spectral coherence, they enable more accurate estimations of oscillatory synchronization across a wide range of different synchronization regimes, and better tracking of synchronization-mediated information flow among networks. PMID:26745498

Synchrony-induced modes of oscillation of a neural field model

NASA Astrophysics Data System (ADS)

Esnaola-Acebes, Jose M.; Roxin, Alex; Avitabile, Daniele; Montbrió, Ernest

2017-11-01

We investigate the modes of oscillation of heterogeneous ring networks of quadratic integrate-and-fire (QIF) neurons with nonlocal, space-dependent coupling. Perturbations of the equilibrium state with a particular wave number produce transient standing waves with a specific temporal frequency, analogously to those in a tense string. In the neuronal network, the equilibrium corresponds to a spatially homogeneous, asynchronous state. Perturbations of this state excite the network's oscillatory modes, which reflect the interplay of episodes of synchronous spiking with the excitatory-inhibitory spatial interactions. In the thermodynamic limit, an exact low-dimensional neural field model describing the macroscopic dynamics of the network is derived. This allows us to obtain formulas for the Turing eigenvalues of the spatially homogeneous state and hence to obtain its stability boundary. We find that the frequency of each Turing mode depends on the corresponding Fourier coefficient of the synaptic pattern of connectivity. The decay rate instead is identical for all oscillation modes as a consequence of the heterogeneity-induced desynchronization of the neurons. Finally, we numerically compute the spectrum of spatially inhomogeneous solutions branching from the Turing bifurcation, showing that similar oscillatory modes operate in neural bump states and are maintained away from onset.

Synchrony-induced modes of oscillation of a neural field model.

PubMed

Esnaola-Acebes, Jose M; Roxin, Alex; Avitabile, Daniele; Montbrió, Ernest

2017-11-01

We investigate the modes of oscillation of heterogeneous ring networks of quadratic integrate-and-fire (QIF) neurons with nonlocal, space-dependent coupling. Perturbations of the equilibrium state with a particular wave number produce transient standing waves with a specific temporal frequency, analogously to those in a tense string. In the neuronal network, the equilibrium corresponds to a spatially homogeneous, asynchronous state. Perturbations of this state excite the network's oscillatory modes, which reflect the interplay of episodes of synchronous spiking with the excitatory-inhibitory spatial interactions. In the thermodynamic limit, an exact low-dimensional neural field model describing the macroscopic dynamics of the network is derived. This allows us to obtain formulas for the Turing eigenvalues of the spatially homogeneous state and hence to obtain its stability boundary. We find that the frequency of each Turing mode depends on the corresponding Fourier coefficient of the synaptic pattern of connectivity. The decay rate instead is identical for all oscillation modes as a consequence of the heterogeneity-induced desynchronization of the neurons. Finally, we numerically compute the spectrum of spatially inhomogeneous solutions branching from the Turing bifurcation, showing that similar oscillatory modes operate in neural bump states and are maintained away from onset.

Neural dynamics in Parkinsonian brain: The boundary between synchronized and nonsynchronized dynamics

NASA Astrophysics Data System (ADS)

Park, Choongseok; Worth, Robert M.; Rubchinsky, Leonid L.

2011-04-01

Synchronous oscillatory dynamics is frequently observed in the human brain. We analyze the fine temporal structure of phase-locking in a realistic network model and match it with the experimental data from Parkinsonian patients. We show that the experimentally observed intermittent synchrony can be generated just by moderately increased coupling strength in the basal ganglia circuits due to the lack of dopamine. Comparison of the experimental and modeling data suggest that brain activity in Parkinson's disease resides in the large boundary region between synchronized and nonsynchronized dynamics. Being on the edge of synchrony may allow for easy formation of transient neuronal assemblies.

Bifurcation of synchronous oscillations into torus in a system of two reciprocally inhibitory silicon neurons: experimental observation and modeling.

PubMed

Bondarenko, Vladimir E; Cymbalyuk, Gennady S; Patel, Girish; Deweerth, Stephen P; Calabrese, Ronald L

2004-12-01

Oscillatory activity in the central nervous system is associated with various functions, like motor control, memory formation, binding, and attention. Quasiperiodic oscillations are rarely discussed in the neurophysiological literature yet they may play a role in the nervous system both during normal function and disease. Here we use a physical system and a model to explore scenarios for how quasiperiodic oscillations might arise in neuronal networks. An oscillatory system of two mutually inhibitory neuronal units is a ubiquitous network module found in nervous systems and is called a half-center oscillator. Previously we created a half-center oscillator of two identical oscillatory silicon (analog Very Large Scale Integration) neurons and developed a mathematical model describing its dynamics. In the mathematical model, we have shown that an in-phase limit cycle becomes unstable through a subcritical torus bifurcation. However, the existence of this torus bifurcation in experimental silicon two-neuron system was not rigorously demonstrated or investigated. Here we demonstrate the torus predicted by the model for the silicon implementation of a half-center oscillator using complex time series analysis, including bifurcation diagrams, mapping techniques, correlation functions, amplitude spectra, and correlation dimensions, and we investigate how the properties of the quasiperiodic oscillations depend on the strengths of coupling between the silicon neurons. The potential advantages and disadvantages of quasiperiodic oscillations (torus) for biological neural systems and artificial neural networks are discussed.

Collective phase description of oscillatory convection

NASA Astrophysics Data System (ADS)

Kawamura, Yoji; Nakao, Hiroya

2013-12-01

We formulate a theory for the collective phase description of oscillatory convection in Hele-Shaw cells. It enables us to describe the dynamics of the oscillatory convection by a single degree of freedom which we call the collective phase. The theory can be considered as a phase reduction method for limit-cycle solutions in infinite-dimensional dynamical systems, namely, stable time-periodic solutions to partial differential equations, representing the oscillatory convection. We derive the phase sensitivity function, which quantifies the phase response of the oscillatory convection to weak perturbations applied at each spatial point, and analyze the phase synchronization between two weakly coupled Hele-Shaw cells exhibiting oscillatory convection on the basis of the derived phase equations.

Oscillatory neural network for pattern recognition: trajectory based classification and supervised learning.

PubMed

Miller, Vonda H; Jansen, Ben H

2008-12-01

Computer algorithms that match human performance in recognizing written text or spoken conversation remain elusive. The reasons why the human brain far exceeds any existing recognition scheme to date in the ability to generalize and to extract invariant characteristics relevant to category matching are not clear. However, it has been postulated that the dynamic distribution of brain activity (spatiotemporal activation patterns) is the mechanism by which stimuli are encoded and matched to categories. This research focuses on supervised learning using a trajectory based distance metric for category discrimination in an oscillatory neural network model. Classification is accomplished using a trajectory based distance metric. Since the distance metric is differentiable, a supervised learning algorithm based on gradient descent is demonstrated. Classification of spatiotemporal frequency transitions and their relation to a priori assessed categories is shown along with the improved classification results after supervised training. The results indicate that this spatiotemporal representation of stimuli and the associated distance metric is useful for simple pattern recognition tasks and that supervised learning improves classification results.

Graph properties of synchronized cortical networks during visual working memory maintenance.

PubMed

Palva, Satu; Monto, Simo; Palva, J Matias

2010-02-15

Oscillatory synchronization facilitates communication in neuronal networks and is intimately associated with human cognition. Neuronal activity in the human brain can be non-invasively imaged with magneto- (MEG) and electroencephalography (EEG), but the large-scale structure of synchronized cortical networks supporting cognitive processing has remained uncharacterized. We combined simultaneous MEG and EEG (MEEG) recordings with minimum-norm-estimate-based inverse modeling to investigate the structure of oscillatory phase synchronized networks that were active during visual working memory (VWM) maintenance. Inter-areal phase-synchrony was quantified as a function of time and frequency by single-trial phase-difference estimates of cortical patches covering the entire cortical surfaces. The resulting networks were characterized with a number of network metrics that were then compared between delta/theta- (3-6 Hz), alpha- (7-13 Hz), beta- (16-25 Hz), and gamma- (30-80 Hz) frequency bands. We found several salient differences between frequency bands. Alpha- and beta-band networks were more clustered and small-world like but had smaller global efficiency than the networks in the delta/theta and gamma bands. Alpha- and beta-band networks also had truncated-power-law degree distributions and high k-core numbers. The data converge on showing that during the VWM-retention period, human cortical alpha- and beta-band networks have a memory-load dependent, scale-free small-world structure with densely connected core-like structures. These data further show that synchronized dynamic networks underlying a specific cognitive state can exhibit distinct frequency-dependent network structures that could support distinct functional roles. Copyright 2009 Elsevier Inc. All rights reserved.

Oscillatory patterns in the light curves of five long-term monitored type 1 active galactic nuclei

NASA Astrophysics Data System (ADS)

Kovačević, Andjelka B.; Pérez-Hernández, Ernesto; Popović, Luka Č.; Shapovalova, Alla I.; Kollatschny, Wolfram; Ilić, Dragana

2018-04-01

New combined data of five well-known type 1 active galactic nuclei (AGNs) are probed with a novel hybrid method in a search for oscillatory behaviour. Additional analysis of artificial light curves obtained from the coupled oscillatory models gives confirmation for detected periods that could have a physical background. We find periodic variations in the long-term light curves of 3C 390.3, NGC 4151 and NGC 5548, and E1821 + 643, with correlation coefficients larger than 0.6. We show that the oscillatory patterns of two binary black hole candidates, NGC 5548 and E1821 + 643, correspond to qualitatively different dynamical regimes of chaos and stability, respectively. We demonstrate that the absence of oscillatory patterns in Arp 102B could be the result of a weak coupling between oscillatory mechanisms. This is the first good evidence that 3C 390.3 and Arp 102B, categorized as double-peaked Balmer line objects, have qualitative different dynamics. Our analysis shows a novelty in the oscillatory dynamical patterns of the light curves of these type 1 AGNs.

Design principles for robust oscillatory behavior.

PubMed

Castillo-Hair, Sebastian M; Villota, Elizabeth R; Coronado, Alberto M

2015-09-01

Oscillatory responses are ubiquitous in regulatory networks of living organisms, a fact that has led to extensive efforts to study and replicate the circuits involved. However, to date, design principles that underlie the robustness of natural oscillators are not completely known. Here we study a three-component enzymatic network model in order to determine the topological requirements for robust oscillation. First, by simulating every possible topological arrangement and varying their parameter values, we demonstrate that robust oscillators can be obtained by augmenting the number of both negative feedback loops and positive autoregulations while maintaining an appropriate balance of positive and negative interactions. We then identify network motifs, whose presence in more complex topologies is a necessary condition for obtaining oscillatory responses. Finally, we pinpoint a series of simple architectural patterns that progressively render more robust oscillators. Together, these findings can help in the design of more reliable synthetic biomolecular networks and may also have implications in the understanding of other oscillatory systems.

Collective phase description of oscillatory convection

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

Kawamura, Yoji, E-mail: ykawamura@jamstec.go.jp; Nakao, Hiroya

We formulate a theory for the collective phase description of oscillatory convection in Hele-Shaw cells. It enables us to describe the dynamics of the oscillatory convection by a single degree of freedom which we call the collective phase. The theory can be considered as a phase reduction method for limit-cycle solutions in infinite-dimensional dynamical systems, namely, stable time-periodic solutions to partial differential equations, representing the oscillatory convection. We derive the phase sensitivity function, which quantifies the phase response of the oscillatory convection to weak perturbations applied at each spatial point, and analyze the phase synchronization between two weakly coupled Hele-Shawmore » cells exhibiting oscillatory convection on the basis of the derived phase equations.« less

A time-frequency analysis of the dynamics of cortical networks of sleep spindles from MEG-EEG recordings

PubMed Central

Zerouali, Younes; Lina, Jean-Marc; Sekerovic, Zoran; Godbout, Jonathan; Dube, Jonathan; Jolicoeur, Pierre; Carrier, Julie

2014-01-01

Sleep spindles are a hallmark of NREM sleep. They result from a widespread thalamo-cortical loop and involve synchronous cortical networks that are still poorly understood. We investigated whether brain activity during spindles can be characterized by specific patterns of functional connectivity among cortical generators. For that purpose, we developed a wavelet-based approach aimed at imaging the synchronous oscillatory cortical networks from simultaneous MEG-EEG recordings. First, we detected spindles on the EEG and extracted the corresponding frequency-locked MEG activity under the form of an analytic ridge signal in the time-frequency plane (Zerouali et al., 2013). Secondly, we performed source reconstruction of the ridge signal within the Maximum Entropy on the Mean framework (Amblard et al., 2004), yielding a robust estimate of the cortical sources producing observed oscillations. Lastly, we quantified functional connectivity among cortical sources using phase-locking values. The main innovations of this methodology are (1) to reveal the dynamic behavior of functional networks resolved in the time-frequency plane and (2) to characterize functional connectivity among MEG sources through phase interactions. We showed, for the first time, that the switch from fast to slow oscillatory mode during sleep spindles is required for the emergence of specific patterns of connectivity. Moreover, we show that earlier synchrony during spindles was associated with mainly intra-hemispheric connectivity whereas later synchrony was associated with global long-range connectivity. We propose that our methodology can be a valuable tool for studying the connectivity underlying neural processes involving sleep spindles, such as memory, plasticity or aging. PMID:25389381

Delay selection by spike-timing-dependent plasticity in recurrent networks of spiking neurons receiving oscillatory inputs.

PubMed

Kerr, Robert R; Burkitt, Anthony N; Thomas, Doreen A; Gilson, Matthieu; Grayden, David B

2013-01-01

Learning rules, such as spike-timing-dependent plasticity (STDP), change the structure of networks of neurons based on the firing activity. A network level understanding of these mechanisms can help infer how the brain learns patterns and processes information. Previous studies have shown that STDP selectively potentiates feed-forward connections that have specific axonal delays, and that this underlies behavioral functions such as sound localization in the auditory brainstem of the barn owl. In this study, we investigate how STDP leads to the selective potentiation of recurrent connections with different axonal and dendritic delays during oscillatory activity. We develop analytical models of learning with additive STDP in recurrent networks driven by oscillatory inputs, and support the results using simulations with leaky integrate-and-fire neurons. Our results show selective potentiation of connections with specific axonal delays, which depended on the input frequency. In addition, we demonstrate how this can lead to a network becoming selective in the amplitude of its oscillatory response to this frequency. We extend this model of axonal delay selection within a single recurrent network in two ways. First, we show the selective potentiation of connections with a range of both axonal and dendritic delays. Second, we show axonal delay selection between multiple groups receiving out-of-phase, oscillatory inputs. We discuss the application of these models to the formation and activation of neuronal ensembles or cell assemblies in the cortex, and also to missing fundamental pitch perception in the auditory brainstem.

Delay Selection by Spike-Timing-Dependent Plasticity in Recurrent Networks of Spiking Neurons Receiving Oscillatory Inputs

PubMed Central

Kerr, Robert R.; Burkitt, Anthony N.; Thomas, Doreen A.; Gilson, Matthieu; Grayden, David B.

2013-01-01

Learning rules, such as spike-timing-dependent plasticity (STDP), change the structure of networks of neurons based on the firing activity. A network level understanding of these mechanisms can help infer how the brain learns patterns and processes information. Previous studies have shown that STDP selectively potentiates feed-forward connections that have specific axonal delays, and that this underlies behavioral functions such as sound localization in the auditory brainstem of the barn owl. In this study, we investigate how STDP leads to the selective potentiation of recurrent connections with different axonal and dendritic delays during oscillatory activity. We develop analytical models of learning with additive STDP in recurrent networks driven by oscillatory inputs, and support the results using simulations with leaky integrate-and-fire neurons. Our results show selective potentiation of connections with specific axonal delays, which depended on the input frequency. In addition, we demonstrate how this can lead to a network becoming selective in the amplitude of its oscillatory response to this frequency. We extend this model of axonal delay selection within a single recurrent network in two ways. First, we show the selective potentiation of connections with a range of both axonal and dendritic delays. Second, we show axonal delay selection between multiple groups receiving out-of-phase, oscillatory inputs. We discuss the application of these models to the formation and activation of neuronal ensembles or cell assemblies in the cortex, and also to missing fundamental pitch perception in the auditory brainstem. PMID:23408878

The prisoner’s dilemma on co-evolving networks under perfect rationality

NASA Astrophysics Data System (ADS)

Biely, Christoly; Dragosits, Klaus; Thurner, Stefan

2007-04-01

We consider the prisoner’s dilemma being played repeatedly on a dynamic network, where agents may choose their actions as well as their co-players. This leads to co-evolution of network structure and strategy patterns of the players. Individual decisions are made fully rationally and are based on local information only. They are made such that links to defecting agents are resolved and that cooperating agents build up new links. The exact form of the updating scheme is motivated by profit maximization and not by imitation. If players update their decisions in a synchronized way the system exhibits oscillatory dynamics: Periods of growing cooperation (and total linkage) alternate with periods of increasing defection. The cyclical behavior is reduced and the system stabilizes at significant total cooperation levels when players are less synchronized. In this regime we find emergent network structures resembling ‘complex’ and hierarchical topology. The exponent of the power-law degree distribution ( γ∼8.6) perfectly matches empirical results for human communication networks.

Decision-making ability of Physarum polycephalum enhanced by its coordinated spatiotemporal oscillatory dynamics.

PubMed

Iwayama, Koji; Zhu, Liping; Hirata, Yoshito; Aono, Masashi; Hara, Masahiko; Aihara, Kazuyuki

2016-04-12

An amoeboid unicellular organism, a plasmodium of the true slime mold Physarum polycephalum, exhibits complex spatiotemporal oscillatory dynamics and sophisticated information processing capabilities while deforming its amorphous body. We previously devised an 'amoeba-based computer (ABC),' that implemented optical feedback control to lead this amoeboid organism to search for a solution to the traveling salesman problem (TSP). In the ABC, the shortest TSP route (the optimal solution) is represented by the shape of the organism in which the body area (nutrient absorption) is maximized while the risk of being exposed to aversive light stimuli is minimized. The shortness of the TSP route found by ABC, therefore, serves as a quantitative measure of the optimality of the decision made by the organism. However, it remains unclear how the decision-making ability of the organism originates from the oscillatory dynamics of the organism. We investigated the number of coexisting traveling waves in the spatiotemporal patterns of the oscillatory dynamics of the organism. We show that a shorter TSP route can be found when the organism exhibits a lower number of traveling waves. The results imply that the oscillatory dynamics are highly coordinated throughout the global body. Based on the results, we discuss the fact that the decision-making ability of the organism can be enhanced not by uncorrelated random fluctuations, but by its highly coordinated oscillatory dynamics.

An Evolutionary Game Theory Model of Spontaneous Brain Functioning.

PubMed

Madeo, Dario; Talarico, Agostino; Pascual-Leone, Alvaro; Mocenni, Chiara; Santarnecchi, Emiliano

2017-11-22

Our brain is a complex system of interconnected regions spontaneously organized into distinct networks. The integration of information between and within these networks is a continuous process that can be observed even when the brain is at rest, i.e. not engaged in any particular task. Moreover, such spontaneous dynamics show predictive value over individual cognitive profile and constitute a potential marker in neurological and psychiatric conditions, making its understanding of fundamental importance in modern neuroscience. Here we present a theoretical and mathematical model based on an extension of evolutionary game theory on networks (EGN), able to capture brain's interregional dynamics by balancing emulative and non-emulative attitudes among brain regions. This results in the net behavior of nodes composing resting-state networks identified using functional magnetic resonance imaging (fMRI), determining their moment-to-moment level of activation and inhibition as expressed by positive and negative shifts in BOLD fMRI signal. By spontaneously generating low-frequency oscillatory behaviors, the EGN model is able to mimic functional connectivity dynamics, approximate fMRI time series on the basis of initial subset of available data, as well as simulate the impact of network lesions and provide evidence of compensation mechanisms across networks. Results suggest evolutionary game theory on networks as a new potential framework for the understanding of human brain network dynamics.

Disrupted global metastability and static and dynamic brain connectivity across individuals in the Alzheimer’s disease continuum

NASA Astrophysics Data System (ADS)

Córdova-Palomera, Aldo; Kaufmann, Tobias; Persson, Karin; Alnæs, Dag; Doan, Nhat Trung; Moberget, Torgeir; Lund, Martina Jonette; Barca, Maria Lage; Engvig, Andreas; Brækhus, Anne; Engedal, Knut; Andreassen, Ole A.; Selbæk, Geir; Westlye, Lars T.

2017-01-01

As findings on the neuropathological and behavioral components of Alzheimer’s disease (AD) continue to accrue, converging evidence suggests that macroscale brain functional disruptions may mediate their association. Recent developments on theoretical neuroscience indicate that instantaneous patterns of brain connectivity and metastability may be a key mechanism in neural communication underlying cognitive performance. However, the potential significance of these patterns across the AD spectrum remains virtually unexplored. We assessed the clinical sensitivity of static and dynamic functional brain disruptions across the AD spectrum using resting-state fMRI in a sample consisting of AD patients (n = 80) and subjects with either mild (n = 44) or subjective (n = 26) cognitive impairment (MCI, SCI). Spatial maps constituting the nodes in the functional brain network and their associated time-series were estimated using spatial group independent component analysis and dual regression, and whole-brain oscillatory activity was analyzed both globally (metastability) and locally (static and dynamic connectivity). Instantaneous phase metrics showed functional coupling alterations in AD compared to MCI and SCI, both static (putamen, dorsal and default-mode) and dynamic (temporal, frontal-superior and default-mode), along with decreased global metastability. The results suggest that brains of AD patients display altered oscillatory patterns, in agreement with theoretical premises on cognitive dynamics.

Fast fMRI can detect oscillatory neural activity in humans.

PubMed

Lewis, Laura D; Setsompop, Kawin; Rosen, Bruce R; Polimeni, Jonathan R

2016-10-25

Oscillatory neural dynamics play an important role in the coordination of large-scale brain networks. High-level cognitive processes depend on dynamics evolving over hundreds of milliseconds, so measuring neural activity in this frequency range is important for cognitive neuroscience. However, current noninvasive neuroimaging methods are not able to precisely localize oscillatory neural activity above 0.2 Hz. Electroencephalography and magnetoencephalography have limited spatial resolution, whereas fMRI has limited temporal resolution because it measures vascular responses rather than directly recording neural activity. We hypothesized that the recent development of fast fMRI techniques, combined with the extra sensitivity afforded by ultra-high-field systems, could enable precise localization of neural oscillations. We tested whether fMRI can detect neural oscillations using human visual cortex as a model system. We detected small oscillatory fMRI signals in response to stimuli oscillating at up to 0.75 Hz within single scan sessions, and these responses were an order of magnitude larger than predicted by canonical linear models. Simultaneous EEG-fMRI and simulations based on a biophysical model of the hemodynamic response to neuronal activity suggested that the blood oxygen level-dependent response becomes faster for rapidly varying stimuli, enabling the detection of higher frequencies than expected. Accounting for phase delays across voxels further improved detection, demonstrating that identifying vascular delays will be of increasing importance with higher-frequency activity. These results challenge the assumption that the hemodynamic response is slow, and demonstrate that fMRI has the potential to map neural oscillations directly throughout the brain.

Modeling delay in genetic networks: From delay birth-death processes to delay stochastic differential equations

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

Gupta, Chinmaya; López, José Manuel; Azencott, Robert

Delay is an important and ubiquitous aspect of many biochemical processes. For example, delay plays a central role in the dynamics of genetic regulatory networks as it stems from the sequential assembly of first mRNA and then protein. Genetic regulatory networks are therefore frequently modeled as stochastic birth-death processes with delay. Here, we examine the relationship between delay birth-death processes and their appropriate approximating delay chemical Langevin equations. We prove a quantitative bound on the error between the pathwise realizations of these two processes. Our results hold for both fixed delay and distributed delay. Simulations demonstrate that the delay chemicalmore » Langevin approximation is accurate even at moderate system sizes. It captures dynamical features such as the oscillatory behavior in negative feedback circuits, cross-correlations between nodes in a network, and spatial and temporal information in two commonly studied motifs of metastability in biochemical systems. Overall, these results provide a foundation for using delay stochastic differential equations to approximate the dynamics of birth-death processes with delay.« less

The frequency preference of neurons and synapses in a recurrent oscillatory network.

PubMed

Tseng, Hua-an; Martinez, Diana; Nadim, Farzan

2014-09-17

A variety of neurons and synapses shows a maximal response at a preferred frequency, generally considered to be important in shaping network activity. We are interested in whether all neurons and synapses in a recurrent oscillatory network can have preferred frequencies and, if so, whether these frequencies are the same or correlated, and whether they influence the network activity. We address this question using identified neurons in the pyloric network of the crab Cancer borealis. Previous work has shown that the pyloric pacemaker neurons exhibit membrane potential resonance whose resonance frequency is correlated with the network frequency. The follower lateral pyloric (LP) neuron makes reciprocally inhibitory synapses with the pacemakers. We find that LP shows resonance at a higher frequency than the pacemakers and the network frequency falls between the two. We also find that the reciprocal synapses between the pacemakers and LP have preferred frequencies but at significantly lower values. The preferred frequency of the LP to pacemaker synapse is correlated with the presynaptic preferred frequency, which is most pronounced when the peak voltage of the LP waveform is within the dynamic range of the synaptic activation curve and a shift in the activation curve by the modulatory neuropeptide proctolin shifts the frequency preference. Proctolin also changes the power of the LP neuron resonance without significantly changing the resonance frequency. These results indicate that different neuron types and synapses in a network may have distinct preferred frequencies, which are subject to neuromodulation and may interact to shape network oscillations. Copyright © 2014 the authors 0270-6474/14/3412933-13$15.00/0.

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.

Adaptive Control of Synchronization in Delay-Coupled Heterogeneous Networks of FitzHugh-Nagumo Nodes

NASA Astrophysics Data System (ADS)

Plotnikov, S. A.; Lehnert, J.; Fradkov, A. L.; Schöll, E.

We study synchronization in delay-coupled neural networks of heterogeneous nodes. It is well known that heterogeneities in the nodes hinder synchronization when becoming too large. We show that an adaptive tuning of the overall coupling strength can be used to counteract the effect of the heterogeneity. Our adaptive controller is demonstrated on ring networks of FitzHugh-Nagumo systems which are paradigmatic for excitable dynamics but can also — depending on the system parameters — exhibit self-sustained periodic firing. We show that the adaptively tuned time-delayed coupling enables synchronization even if parameter heterogeneities are so large that excitable nodes coexist with oscillatory ones.

A fluid-filled soft robot that exhibits spontaneous switching among versatile spatiotemporal oscillatory patterns inspired by the true slime mold.

PubMed

Umedachi, Takuya; Idei, Ryo; Ito, Kentaro; Ishiguro, Akio

2013-01-01

Behavioral diversity is an essential feature of living systems, enabling them to exhibit adaptive behavior in hostile and dynamically changing environments. However, traditional engineering approaches strive to avoid, or suppress, the behavioral diversity in artificial systems to achieve high performance in specific environments for given tasks. The goals of this research include understanding how living systems exhibit behavioral diversity and using these findings to build lifelike robots that exhibit truly adaptive behaviors. To this end, we have focused on one of the most primitive forms of intelligence concerning behavioral diversity, namely, a plasmodium of true slime mold. The plasmodium is a large amoeba-like unicellular organism that does not possess any nervous system or specialized organs. However, it exhibits versatile spatiotemporal oscillatory patterns and switches spontaneously between these. Inspired by the plasmodium, we built a mathematical model that exhibits versatile oscillatory patterns and spontaneously transitions between these patterns. This model demonstrates that, in contrast to coupled nonlinear oscillators with a well-designed complex diffusion network, physically interacting mechanosensory oscillators are capable of generating versatile oscillatory patterns without changing any parameters. Thus, the results are expected to shed new light on the design scheme for lifelike robots that exhibit amazingly versatile and adaptive behaviors.

Irregular behavior in an excitatory-inhibitory neuronal network

NASA Astrophysics Data System (ADS)

Park, Choongseok; Terman, David

2010-06-01

Excitatory-inhibitory networks arise in many regions throughout the central nervous system and display complex spatiotemporal firing patterns. These neuronal activity patterns (of individual neurons and/or the whole network) are closely related to the functional status of the system and differ between normal and pathological states. For example, neurons within the basal ganglia, a group of subcortical nuclei that are responsible for the generation of movement, display a variety of dynamic behaviors such as correlated oscillatory activity and irregular, uncorrelated spiking. Neither the origins of these firing patterns nor the mechanisms that underlie the patterns are well understood. We consider a biophysical model of an excitatory-inhibitory network in the basal ganglia and explore how specific biophysical properties of the network contribute to the generation of irregular spiking. We use geometric dynamical systems and singular perturbation methods to systematically reduce the model to a simpler set of equations, which is suitable for analysis. The results specify the dependence on the strengths of synaptic connections and the intrinsic firing properties of the cells in the irregular regime when applied to the subthalamopallidal network of the basal ganglia.

In-silico studies of neutral drift for functional protein interaction networks

NASA Astrophysics Data System (ADS)

Ali, Md Zulfikar; Wingreen, Ned S.; Mukhopadhyay, Ranjan

We have developed a minimal physically-motivated model of protein-protein interaction networks. Our system consists of two classes of enzymes, activators (e.g. kinases) and deactivators (e.g. phosphatases), and the enzyme-mediated activation/deactivation rates are determined by sequence-dependent binding strengths between enzymes and their targets. The network is evolved by introducing random point mutations in the binding sequences where we assume that each new mutation is either fixed or entirely lost. We apply this model to studies of neutral drift in networks that yield oscillatory dynamics, where we start, for example, with a relatively simple network and allow it to evolve by adding nodes and connections while requiring that dynamics be conserved. Our studies demonstrate both the importance of employing a sequence-based evolutionary scheme and the relative rapidity (in evolutionary time) for the redistribution of function over new nodes via neutral drift. Surprisingly, in addition to this redistribution time we discovered another much slower timescale for network evolution, reflecting hidden order in sequence space that we interpret in terms of sparsely connected domains.

Synchronization properties of networks of electrically coupled neurons in the presence of noise and heterogeneities.

PubMed

Ostojic, Srdjan; Brunel, Nicolas; Hakim, Vincent

2009-06-01

We investigate how synchrony can be generated or induced in networks of electrically coupled integrate-and-fire neurons subject to noisy and heterogeneous inputs. Using analytical tools, we find that in a network under constant external inputs, synchrony can appear via a Hopf bifurcation from the asynchronous state to an oscillatory state. In a homogeneous net work, in the oscillatory state all neurons fire in synchrony, while in a heterogeneous network synchrony is looser, many neurons skipping cycles of the oscillation. If the transmission of action potentials via the electrical synapses is effectively excitatory, the Hopf bifurcation is supercritical, while effectively inhibitory transmission due to pronounced hyperpolarization leads to a subcritical bifurcation. In the latter case, the network exhibits bistability between an asynchronous state and an oscillatory state where all the neurons fire in synchrony. Finally we show that for time-varying external inputs, electrical coupling enhances the synchronization in an asynchronous network via a resonance at the firing-rate frequency.

DNA Molecules in Microfluidic Oscillatory Flow

PubMed Central

Chen, Y.-L.; Graham, M.D.; de Pablo, J.J.; Jo, K.; Schwartz, D.C.

2008-01-01

The conformation and dynamics of a single DNA molecule undergoing oscillatory pressure-driven flow in microfluidic channels is studied using Brownian dynamics simulations, accounting for hydrodynamic interactions between segments in the bulk and between the chain and the walls. Oscillatory flow provides a scenario under which the polymers may remain in the channel for an indefinite amount of time as they are stretched and migrate away from the channel walls. We show that by controlling the chain length, flow rate and oscillatory flow frequency, we are able to manipulate the chain extension and the chain migration from the channel walls. The chain stretch and the chain depletion layer thickness near the wall are found to increase as the Weissenberg number increases and as the oscillatory frequency decreases. PMID:19057656

Spatiotemporal oscillatory dynamics of visual selective attention during a flanker task.

PubMed

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

2017-08-01

The flanker task is a test of visual selective attention that has been widely used to probe error monitoring, response conflict, and related constructs. However, to date, few studies have focused on the selective attention component of this task and imaged the underlying oscillatory dynamics serving task performance. In this study, 21 healthy adults successfully completed an arrow-based version of the Eriksen flanker task during magnetoencephalography (MEG). All MEG data were pre-processed and transformed into the time-frequency domain. Significant oscillatory brain responses were imaged using a beamforming approach, and voxel time series were extracted from the peak responses to identify the temporal dynamics. Across both congruent and incongruent flanker conditions, our results indicated robust decreases in alpha (9-12Hz) activity in medial and lateral occipital regions, bilateral parietal cortices, and cerebellar areas during task performance. In parallel, increases in theta (3-7Hz) oscillatory activity were detected in dorsal and ventral frontal regions, and the anterior cingulate. As per conditional effects, stronger alpha responses (i.e., greater desynchronization) were observed in parietal, occipital, and cerebellar cortices during incongruent relative to congruent trials, whereas the opposite pattern emerged for theta responses (i.e., synchronization) in the anterior cingulate, left dorsolateral prefrontal, and ventral prefrontal cortices. Interestingly, the peak latency of theta responses in these latter brain regions was significantly correlated with reaction time, and may partially explain the amplitude difference observed between congruent and incongruent trials. Lastly, whole-brain exploratory analyses implicated the frontal eye fields, right temporoparietal junction, and premotor cortices. These findings suggest that regions of both the dorsal and ventral attention networks contribute to visual selective attention processes during incongruent trials, and that such differential processes are transient and fully completed shortly after the behavioral response in most trials. Copyright © 2017 Elsevier Inc. All rights reserved.

How heart rate variability affects emotion regulation brain networks.

PubMed

Mather, Mara; Thayer, Julian

2018-02-01

Individuals with high heart rate variability tend to have better emotional well-being than those with low heart rate variability, but the mechanisms of this association are not yet clear. In this paper, we propose the novel hypothesis that by inducing oscillatory activity in the brain, high amplitude oscillations in heart rate enhance functional connectivity in brain networks associated with emotion regulation. Recent studies using daily biofeedback sessions to increase the amplitude of heart rate oscillations suggest that high amplitude physiological oscillations have a causal impact on emotional well-being. Because blood flow timing helps determine brain network structure and function, slow oscillations in heart rate have the potential to strengthen brain network dynamics, especially in medial prefrontal regulatory regions that are particularly sensitive to physiological oscillations.

Network Events on Multiple Space and Time Scales in Cultured Neural Networks and in a Stochastic Rate Model

PubMed Central

Gigante, Guido; Deco, Gustavo; Marom, Shimon; Del Giudice, Paolo

2015-01-01

Cortical networks, in-vitro as well as in-vivo, can spontaneously generate a variety of collective dynamical events such as network spikes, UP and DOWN states, global oscillations, and avalanches. Though each of them has been variously recognized in previous works as expression of the excitability of the cortical tissue and the associated nonlinear dynamics, a unified picture of the determinant factors (dynamical and architectural) is desirable and not yet available. Progress has also been partially hindered by the use of a variety of statistical measures to define the network events of interest. We propose here a common probabilistic definition of network events that, applied to the firing activity of cultured neural networks, highlights the co-occurrence of network spikes, power-law distributed avalanches, and exponentially distributed ‘quasi-orbits’, which offer a third type of collective behavior. A rate model, including synaptic excitation and inhibition with no imposed topology, synaptic short-term depression, and finite-size noise, accounts for all these different, coexisting phenomena. We find that their emergence is largely regulated by the proximity to an oscillatory instability of the dynamics, where the non-linear excitable behavior leads to a self-amplification of activity fluctuations over a wide range of scales in space and time. In this sense, the cultured network dynamics is compatible with an excitation-inhibition balance corresponding to a slightly sub-critical regime. Finally, we propose and test a method to infer the characteristic time of the fatigue process, from the observed time course of the network’s firing rate. Unlike the model, possessing a single fatigue mechanism, the cultured network appears to show multiple time scales, signalling the possible coexistence of different fatigue mechanisms. PMID:26558616

A generalized locomotion CPG architecture based on oscillatory building blocks.

PubMed

Yang, Zhijun; França, Felipe M G

2003-07-01

Neural oscillation is one of the most extensively investigated topics of artificial neural networks. Scientific approaches to the functionalities of both natural and artificial intelligences are strongly related to mechanisms underlying oscillatory activities. This paper concerns itself with the assumption of the existence of central pattern generators (CPGs), which are the plausible neural architectures with oscillatory capabilities, and presents a discrete and generalized approach to the functionality of locomotor CPGs of legged animals. Based on scheduling by multiple edge reversal (SMER), a primitive and deterministic distributed algorithm, it is shown how oscillatory building block (OBB) modules can be created and, hence, how OBB-based networks can be formulated as asymmetric Hopfield-like neural networks for the generation of complex coordinated rhythmic patterns observed among pairs of biological motor neurons working during different gait patterns. It is also shown that the resulting Hopfield-like network possesses the property of reproducing the whole spectrum of different gaits intrinsic to the target locomotor CPGs. Although the new approach is not restricted to the understanding of the neurolocomotor system of any particular animal, hexapodal and quadrupedal gait patterns are chosen as illustrations given the wide interest expressed by the ongoing research in the area.

Microstructural Origins of Nonlinear Response in Associating Polymers under Oscillatory Shear

DOE PAGES

Wilson, Mark A.; Baljon, Arlette R. C.

2017-10-26

The response of associating polymers with oscillatory shear is studied through large-scale simulations. A hybrid molecular dynamics (MD), Monte Carlo (MC) algorithm is employed. Polymer chains are modeled as a coarse-grained bead-spring system. Functionalized end groups, at both ends of the polymer chains, can form reversible bonds according to MC rules. Stress-strain curves show nonlinearities indicated by a non-ellipsoidal shape. We consider two types of nonlinearities. Type I occurs at a strain amplitude much larger than one, type II at a frequency at which the elastic storage modulus dominates the viscous loss modulus. In this last case, the network topologymore » resembles that of the system at rest. The reversible bonds are broken and chains stretch when the system moves away from the zero-strain position. For type I, the chains relax and the number of reversible bonds peaks when the system is near an extreme of the motion. During the movement to the other extreme of the cycle, first a stress overshoot occurs, then a yield accompanied by shear-banding. Lastly, the network restructures. Interestingly, the system periodically restores bonds between the same associating groups. Even though major restructuring occurs, the system remembers previous network topologies.« less

A brief historical perspective on the advent of brain oscillations in the biological and psychological disciplines.

PubMed

Karakaş, Sirel; Barry, Robert J

2017-04-01

We aim to review the historical evolution that has led to the study of the brain (body)-mind relationship based on brain oscillations, to outline and illustrate the principles of neuro-oscillatory dynamics using research findings. The paper addresses the relevant developments in behavioral sciences after Wundt established the science of psychology, and developments in the neurosciences after alpha and gamma oscillations were discovered by Berger and Adrian, respectively. Basic neuroscientific studies have led to a number of principles: (1) spontaneous EEG is composed of a set of oscillatory components, (2) the brain responds with oscillatory activity, (3) poststimulus oscillatory activity is a function of prestimulus activity, (4) the brain response results from a superposition of oscillatory components, (5) there are multiplicities with regard to oscillations and functions, and (6) oscillations are spatially integrated. Findings of clinical studies suggest that oscillatory responses can serve as biomarkers for neuropsychiatric disorders. However, the field of psychology is still making limited use of neuro-oscillatory dynamics for a bio-behavioral understanding of cognitive-affective processes. Copyright © 2016 Elsevier Ltd. All rights reserved.

Energetic Constraints Produce Self-sustained Oscillatory Dynamics in Neuronal Networks

PubMed Central

Burroni, Javier; Taylor, P.; Corey, Cassian; Vachnadze, Tengiz; Siegelmann, Hava T.

2017-01-01

Overview: We model energy constraints in a network of spiking neurons, while exploring general questions of resource limitation on network function abstractly. Background: Metabolic states like dietary ketosis or hypoglycemia have a large impact on brain function and disease outcomes. Glia provide metabolic support for neurons, among other functions. Yet, in computational models of glia-neuron cooperation, there have been no previous attempts to explore the effects of direct realistic energy costs on network activity in spiking neurons. Currently, biologically realistic spiking neural networks assume that membrane potential is the main driving factor for neural spiking, and do not take into consideration energetic costs. Methods: We define local energy pools to constrain a neuron model, termed Spiking Neuron Energy Pool (SNEP), which explicitly incorporates energy limitations. Each neuron requires energy to spike, and resources in the pool regenerate over time. Our simulation displays an easy-to-use GUI, which can be run locally in a web browser, and is freely available. Results: Energy dependence drastically changes behavior of these neural networks, causing emergent oscillations similar to those in networks of biological neurons. We analyze the system via Lotka-Volterra equations, producing several observations: (1) energy can drive self-sustained oscillations, (2) the energetic cost of spiking modulates the degree and type of oscillations, (3) harmonics emerge with frequencies determined by energy parameters, and (4) varying energetic costs have non-linear effects on energy consumption and firing rates. Conclusions: Models of neuron function which attempt biological realism may benefit from including energy constraints. Further, we assert that observed oscillatory effects of energy limitations exist in networks of many kinds, and that these findings generalize to abstract graphs and technological applications. PMID:28289370

Comodulation of dopamine and serotonin on prefrontal cortical rhythms: a theoretical study

PubMed Central

Wang, Da-Hui; Wong-Lin, KongFatt

2013-01-01

The prefrontal cortex (PFC) is implicated to play an important role in cognitive control. Abnormal PFC activities and rhythms have been observed in some neurological and neuropsychiatric disorders, and evidences suggest influences from the neuromodulators dopamine (DA) and serotonin (5-HT). Despite the high level of interest in these brain systems, the combined effects of DA and 5-HT modulation on PFC dynamics remain unknown. In this work, we build a mathematical model that incorporates available experimental findings to systematically study the comodulation of DA and 5-HT on the network behavior, focusing on beta and gamma band oscillations. Single neuronal model shows pyramidal cells with 5-HT1A and 2A receptors can be non-monotonically modulated by 5-HT. Two-population excitatory-inhibitory type network consisting of pyramidal cells with D1 receptors can provide rich repertoires of oscillatory behavior. In particular, 5-HT and DA can modulate the amplitude and frequency of the oscillations, which can emerge or cease, depending on receptor types. Certain receptor combinations are conducive for the robustness of the oscillatory regime, or the existence of multiple discrete oscillatory regimes. In a multi-population heterogeneous model that takes into account possible combination of receptors, we demonstrate that robust network oscillations require high DA concentration. We also show that selective D1 receptor antagonists (agonists) tend to suppress (enhance) network oscillations, increase the frequency from beta toward gamma band, while selective 5-HT1A antagonists (agonists) act in opposite ways. Selective D2 or 5-HT2A receptor antagonists (agonists) can lead to decrease (increase) in oscillation amplitude, but only 5-HT2A antagonists (agonists) can increase (decrease) the frequency. These results are comparable to some pharmacological effects. Our work illustrates the complex mechanisms of DA and 5-HT when operating simultaneously through multiple receptors. PMID:23935568

Epoch Lifetimes in the Dynamics of a Competing Population

NASA Astrophysics Data System (ADS)

Yeung, C. H.; Ma, Y. P.; Wong, K. Y. Michael

We propose a dynamical model of a competing population whose agents have a tendency to balance their decisions in time. The model is applicable to financial markets in which the agents trade with finite capital, or other multiagent systems such as routers in communication networks attempting to transmit multiclass traffic in a fair way. We find an oscillatory behavior due to the segregation of agents into two groups. Each group remains winning over epochs. The aggregation of smart agents is able to explain the lifetime distribution of epochs to 8 decades of probability. The existence of the super agents further refines the lifetime distribution of short epochs.

Differential Go/NoGo Activity in Both Contingent Negative Variation and Spectral Power

PubMed Central

Funderud, Ingrid; Lindgren, Magnus; Løvstad, Marianne; Endestad, Tor; Voytek, Bradley; Knight, Robert T.; Solbakk, Anne-Kristin

2012-01-01

We investigated whether both the contingent negative variation (CNV), an event-related potential index of preparatory brain activity, and event-related oscillatory EEG activity differentiated Go and NoGo trials in a delayed response task. CNV and spectral power (4–100 Hz) were calculated from EEG activity in the preparatory interval in 16 healthy adult participants. As previously reported, CNV amplitudes were higher in Go compared to NoGo trials. In addition, event-related spectral power of the Go condition was reduced in the theta to low gamma range compared to the NoGo condition, confirming that preparing to respond is associated with modulation of event-related spectral activity as well as the CNV. Altogether, the impact of the experimental manipulation on both slow event-related potentials and oscillatory EEG activity may reflect coordinated dynamic changes in the excitability of distributed neural networks involved in preparation. PMID:23119040

Attention training improves aberrant neural dynamics during working memory processing in veterans with PTSD.

PubMed

McDermott, Timothy J; Badura-Brack, Amy S; Becker, Katherine M; Ryan, Tara J; Bar-Haim, Yair; Pine, Daniel S; Khanna, Maya M; Heinrichs-Graham, Elizabeth; Wilson, Tony W

2016-12-01

Posttraumatic stress disorder (PTSD) is associated with executive functioning deficits, including disruptions in working memory (WM). Recent studies suggest that attention training reduces PTSD symptomatology, but the underlying neural mechanisms are unknown. We used high-density magnetoencephalography (MEG) to evaluate whether attention training modulates brain regions serving WM processing in PTSD. Fourteen veterans with PTSD completed a WM task during a 306-sensor MEG recording before and after 8 sessions of attention training treatment. A matched comparison sample of 12 combat-exposed veterans without PTSD completed the same WM task during a single MEG session. To identify the spatiotemporal dynamics, each group's data were transformed into the time-frequency domain, and significant oscillatory brain responses were imaged using a beamforming approach. All participants exhibited activity in left hemispheric language areas consistent with a verbal WM task. Additionally, veterans with PTSD and combat-exposed healthy controls each exhibited oscillatory responses in right hemispheric homologue regions (e.g., right Broca's area); however, these responses were in opposite directions. Group differences in oscillatory activity emerged in the theta band (4-8 Hz) during encoding and in the alpha band (9-12 Hz) during maintenance and were significant in right prefrontal and right supramarginal and inferior parietal regions. Importantly, following attention training, these significant group differences were reduced or eliminated. This study provides initial evidence that attention training improves aberrant neural activity in brain networks serving WM processing.

Analysis of current-driven oscillatory dynamics of single-layer homoepitaxial islands on crystalline conducting substrates

NASA Astrophysics Data System (ADS)

Dasgupta, Dwaipayan; Kumar, Ashish; Maroudas, Dimitrios

2018-03-01

We report results of a systematic study on the complex oscillatory current-driven dynamics of single-layer homoepitaxial islands on crystalline substrate surfaces and the dependence of this driven dynamical behavior on important physical parameters, including island size, substrate surface orientation, and direction of externally applied electric field. The analysis is based on a nonlinear model of driven island edge morphological evolution that accounts for curvature-driven edge diffusion, edge electromigration, and edge diffusional anisotropy. Using a linear theory of island edge morphological stability, we calculate a critical island size at which the island's equilibrium edge shape becomes unstable, which sets a lower bound for the onset of time-periodic oscillatory dynamical response. Using direct dynamical simulations, we study the edge morphological dynamics of current-driven single-layer islands at larger-than-critical size, and determine the actual island size at which the migrating islands undergo a transition from steady to time-periodic asymptotic states through a subcritical Hopf bifurcation. At the highest symmetry of diffusional anisotropy examined, on {111} surfaces of face-centered cubic crystalline substrates, we find that more complex stable oscillatory states can be reached through period-doubling bifurcation at island sizes larger than those at the Hopf points. We characterize in detail the island morphology and dynamical response at the stable time-periodic asymptotic states, determine the range of stability of these oscillatory states terminated by island breakup, and explain the morphological features of the stable oscillating islands on the basis of linear stability theory.

Noisy Oscillations in the Actin Cytoskeleton of Chemotactic Amoeba.

PubMed

Negrete, Jose; Pumir, Alain; Hsu, Hsin-Fang; Westendorf, Christian; Tarantola, Marco; Beta, Carsten; Bodenschatz, Eberhard

2016-09-30

Biological systems with their complex biochemical networks are known to be intrinsically noisy. Here we investigate the dynamics of actin polymerization of amoeboid cells, which are close to the onset of oscillations. We show that the large phenotypic variability in the polymerization dynamics can be accurately captured by a generic nonlinear oscillator model in the presence of noise. We determine the relative role of the noise with a single dimensionless, experimentally accessible parameter, thus providing a quantitative description of the variability in a population of cells. Our approach, which rests on a generic description of a system close to a Hopf bifurcation and includes the effect of noise, can characterize the dynamics of a large class of noisy systems close to an oscillatory instability.

Noisy Oscillations in the Actin Cytoskeleton of Chemotactic Amoeba

NASA Astrophysics Data System (ADS)

Negrete, Jose; Pumir, Alain; Hsu, Hsin-Fang; Westendorf, Christian; Tarantola, Marco; Beta, Carsten; Bodenschatz, Eberhard

2016-09-01

Biological systems with their complex biochemical networks are known to be intrinsically noisy. Here we investigate the dynamics of actin polymerization of amoeboid cells, which are close to the onset of oscillations. We show that the large phenotypic variability in the polymerization dynamics can be accurately captured by a generic nonlinear oscillator model in the presence of noise. We determine the relative role of the noise with a single dimensionless, experimentally accessible parameter, thus providing a quantitative description of the variability in a population of cells. Our approach, which rests on a generic description of a system close to a Hopf bifurcation and includes the effect of noise, can characterize the dynamics of a large class of noisy systems close to an oscillatory instability.

Driving working memory with frequency-tuned noninvasive brain stimulation.

PubMed

Albouy, Philippe; Baillet, Sylvain; Zatorre, Robert J

2018-04-29

Frequency-tuned noninvasive brain stimulation is a recent approach in cognitive neuroscience that involves matching the frequency of transcranially applied electromagnetic fields to that of specific oscillatory components of the underlying neurophysiology. The objective of this method is to modulate ongoing/intrinsic brain oscillations, which correspond to rhythmic fluctuations of neural excitability, to causally change behavior. We review the impact of frequency-tuned noninvasive brain stimulation on the research field of human working memory. We argue that this is a powerful method to probe and understand the mechanisms of memory functions, targeting specifically task-related oscillatory dynamics, neuronal representations, and brain networks. We report the main behavioral and neurophysiological outcomes published to date, in particular, how functionally relevant oscillatory signatures in signal power and interregional connectivity yield causal changes of working memory abilities. We also present recent developments of the technique that aim to modulate cross-frequency coupling in polyrhythmic neural activity. Overall, the method has led to significant advances in our understanding of the mechanisms of systems neuroscience, and the role of brain oscillations in cognition and behavior. We also emphasize the translational impact of noninvasive brain stimulation techniques in the development of therapeutic approaches. © 2018 New York Academy of Sciences.

Coarse-Grained Clustering Dynamics of Heterogeneously Coupled Neurons.

PubMed

Moon, Sung Joon; Cook, Katherine A; Rajendran, Karthikeyan; Kevrekidis, Ioannis G; Cisternas, Jaime; Laing, Carlo R

2015-12-01

The formation of oscillating phase clusters in a network of identical Hodgkin-Huxley neurons is studied, along with their dynamic behavior. The neurons are synaptically coupled in an all-to-all manner, yet the synaptic coupling characteristic time is heterogeneous across the connections. In a network of N neurons where this heterogeneity is characterized by a prescribed random variable, the oscillatory single-cluster state can transition-through [Formula: see text] (possibly perturbed) period-doubling and subsequent bifurcations-to a variety of multiple-cluster states. The clustering dynamic behavior is computationally studied both at the detailed and the coarse-grained levels, and a numerical approach that can enable studying the coarse-grained dynamics in a network of arbitrarily large size is suggested. Among a number of cluster states formed, double clusters, composed of nearly equal sub-network sizes are seen to be stable; interestingly, the heterogeneity parameter in each of the double-cluster components tends to be consistent with the random variable over the entire network: Given a double-cluster state, permuting the dynamical variables of the neurons can lead to a combinatorially large number of different, yet similar "fine" states that appear practically identical at the coarse-grained level. For weak heterogeneity we find that correlations rapidly develop, within each cluster, between the neuron's "identity" (its own value of the heterogeneity parameter) and its dynamical state. For single- and double-cluster states we demonstrate an effective coarse-graining approach that uses the Polynomial Chaos expansion to succinctly describe the dynamics by these quickly established "identity-state" correlations. This coarse-graining approach is utilized, within the equation-free framework, to perform efficient computations of the neuron ensemble dynamics.

Prefrontal Cortex Networks Shift from External to Internal Modes during Learning.

PubMed

Brincat, Scott L; Miller, Earl K

2016-09-14

As we learn about items in our environment, their neural representations become increasingly enriched with our acquired knowledge. But there is little understanding of how network dynamics and neural processing related to external information changes as it becomes laden with "internal" memories. We sampled spiking and local field potential activity simultaneously from multiple sites in the lateral prefrontal cortex (PFC) and the hippocampus (HPC)-regions critical for sensory associations-of monkeys performing an object paired-associate learning task. We found that in the PFC, evoked potentials to, and neural information about, external sensory stimulation decreased while induced beta-band (∼11-27 Hz) oscillatory power and synchrony associated with "top-down" or internal processing increased. By contrast, the HPC showed little evidence of learning-related changes in either spiking activity or network dynamics. The results suggest that during associative learning, PFC networks shift their resources from external to internal processing. As we learn about items in our environment, their representations in our brain become increasingly enriched with our acquired "top-down" knowledge. We found that in the prefrontal cortex, but not the hippocampus, processing of external sensory inputs decreased while internal network dynamics related to top-down processing increased. The results suggest that during learning, prefrontal cortex networks shift their resources from external (sensory) to internal (memory) processing. Copyright © 2016 the authors 0270-6474/16/369739-16$15.00/0.

Prefrontal Cortex Networks Shift from External to Internal Modes during Learning

PubMed Central

Brincat, Scott L.

2016-01-01

As we learn about items in our environment, their neural representations become increasingly enriched with our acquired knowledge. But there is little understanding of how network dynamics and neural processing related to external information changes as it becomes laden with “internal” memories. We sampled spiking and local field potential activity simultaneously from multiple sites in the lateral prefrontal cortex (PFC) and the hippocampus (HPC)—regions critical for sensory associations—of monkeys performing an object paired-associate learning task. We found that in the PFC, evoked potentials to, and neural information about, external sensory stimulation decreased while induced beta-band (∼11–27 Hz) oscillatory power and synchrony associated with “top-down” or internal processing increased. By contrast, the HPC showed little evidence of learning-related changes in either spiking activity or network dynamics. The results suggest that during associative learning, PFC networks shift their resources from external to internal processing. SIGNIFICANCE STATEMENT As we learn about items in our environment, their representations in our brain become increasingly enriched with our acquired “top-down” knowledge. We found that in the prefrontal cortex, but not the hippocampus, processing of external sensory inputs decreased while internal network dynamics related to top-down processing increased. The results suggest that during learning, prefrontal cortex networks shift their resources from external (sensory) to internal (memory) processing. PMID:27629722

Rhythms of Consciousness: Binocular Rivalry Reveals Large-Scale Oscillatory Network Dynamics Mediating Visual Perception

PubMed Central

Doesburg, Sam M.; Green, Jessica J.; McDonald, John J.; Ward, Lawrence M.

2009-01-01

Consciousness has been proposed to emerge from functionally integrated large-scale ensembles of gamma-synchronous neural populations that form and dissolve at a frequency in the theta band. We propose that discrete moments of perceptual experience are implemented by transient gamma-band synchronization of relevant cortical regions, and that disintegration and reintegration of these assemblies is time-locked to ongoing theta oscillations. In support of this hypothesis we provide evidence that (1) perceptual switching during binocular rivalry is time-locked to gamma-band synchronizations which recur at a theta rate, indicating that the onset of new conscious percepts coincides with the emergence of a new gamma-synchronous assembly that is locked to an ongoing theta rhythm; (2) localization of the generators of these gamma rhythms reveals recurrent prefrontal and parietal sources; (3) theta modulation of gamma-band synchronization is observed between and within the activated brain regions. These results suggest that ongoing theta-modulated-gamma mechanisms periodically reintegrate a large-scale prefrontal-parietal network critical for perceptual experience. Moreover, activation and network inclusion of inferior temporal cortex and motor cortex uniquely occurs on the cycle immediately preceding responses signaling perceptual switching. This suggests that the essential prefrontal-parietal oscillatory network is expanded to include additional cortical regions relevant to tasks and perceptions furnishing consciousness at that moment, in this case image processing and response initiation, and that these activations occur within a time frame consistent with the notion that conscious processes directly affect behaviour. PMID:19582165

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

PubMed

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

2015-04-01

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

System identification of the Arabidopsis plant circadian system

NASA Astrophysics Data System (ADS)

Foo, Mathias; Somers, David E.; Kim, Pan-Jun

2015-02-01

The circadian system generates an endogenous oscillatory rhythm that governs the daily activities of organisms in nature. It offers adaptive advantages to organisms through a coordination of their biological functions with the optimal time of day. In this paper, a model of the circadian system in the plant Arabidopsis (species thaliana) is built by using system identification techniques. Prior knowledge about the physical interactions of the genes and the proteins in the plant circadian system is incorporated in the model building exercise. The model is built by using primarily experimentally-verified direct interactions between the genes and the proteins with the available data on mRNA and protein abundances from the circadian system. Our analysis reveals a great performance of the model in predicting the dynamics of the plant circadian system through the effect of diverse internal and external perturbations (gene knockouts and day-length changes). Furthermore, we found that the circadian oscillatory rhythm is robust and does not vary much with the biochemical parameters except those of a light-sensitive protein P and a transcription factor TOC1. In other words, the circadian rhythmic profile is largely a consequence of the network's architecture rather than its particular parameters. Our work suggests that the current experimental knowledge of the gene-to-protein interactions in the plant Arabidopsis, without considering any additional hypothetical interactions, seems to suffice for system-level modeling of the circadian system of this plant and to present an exemplary platform for the control of network dynamics in complex living organisms.

The Art of Grid Fields: Geometry of Neuronal Time

PubMed Central

Shilnikov, Andrey L.; Maurer, Andrew Porter

2016-01-01

The discovery of grid cells in the entorhinal cortex has both elucidated our understanding of spatial representations in the brain, and germinated a large number of theoretical models regarding the mechanisms of these cells’ striking spatial firing characteristics. These models cross multiple neurobiological levels that include intrinsic membrane resonance, dendritic integration, after hyperpolarization characteristics and attractor dynamics. Despite the breadth of the models, to our knowledge, parallels can be drawn between grid fields and other temporal dynamics observed in nature, much of which was described by Art Winfree and colleagues long before the initial description of grid fields. Using theoretical and mathematical investigations of oscillators, in a wide array of mediums far from the neurobiology of grid cells, Art Winfree has provided a substantial amount of research with significant and profound similarities. These theories provide specific inferences into the biological mechanisms and extraordinary resemblances across phenomenon. Therefore, this manuscript provides a novel interpretation on the phenomenon of grid fields, from the perspective of coupled oscillators, postulating that grid fields are the spatial representation of phase resetting curves in the brain. In contrast to prior models of gird cells, the current manuscript provides a sketch by which a small network of neurons, each with oscillatory components can operate to form grid cells, perhaps providing a unique hybrid between the competing attractor neural network and oscillatory interference models. The intention of this new interpretation of the data is to encourage novel testable hypotheses. PMID:27013981

Frontal Oscillatory Dynamics Predict Feedback Learning and Action Adjustment

ERIC Educational Resources Information Center

van de Vijver, Irene; Ridderinkhof, K. Richard; Cohen, Michael X.

2011-01-01

Frontal oscillatory dynamics in the theta (4-8 Hz) and beta (20-30 Hz) frequency bands have been implicated in cognitive control processes. Here we investigated the changes in coordinated activity within and between frontal brain areas during feedback-based response learning. In a time estimation task, participants learned to press a button after…

Oscillatory activity in neocortical networks during tactile discrimination near the limit of spatial acuity.

PubMed

Adhikari, Bhim M; Sathian, K; Epstein, Charles M; Lamichhane, Bidhan; Dhamala, Mukesh

2014-05-01

Oscillatory interactions within functionally specialized but distributed brain regions are believed to be central to perceptual and cognitive functions. Here, using human scalp electroencephalography (EEG) recordings combined with source reconstruction techniques, we study how oscillatory activity functionally organizes different neocortical regions during a tactile discrimination task near the limit of spatial acuity. While undergoing EEG recordings, blindfolded participants felt a linear three-dot array presented electromechanically, under computer control, and reported whether the central dot was offset to the left or right. The average brain response differed significantly for trials with correct and incorrect perceptual responses in the timeframe approximately between 130 and 175ms. During trials with correct responses, source-level peak activity appeared in the left primary somatosensory cortex (SI) at around 45ms, in the right lateral occipital complex (LOC) at 130ms, in the right posterior intraparietal sulcus (pIPS) at 160ms, and finally in the left dorsolateral prefrontal cortex (dlPFC) at 175ms. Spectral interdependency analysis of activity in these nodes showed two distinct distributed networks, a dominantly feedforward network in the beta band (12-30Hz) that included all four nodes and a recurrent network in the gamma band (30-100Hz) that linked SI, pIPS and dlPFC. Measures of network activity in both bands were correlated with the accuracy of task performance. These findings suggest that beta and gamma band oscillatory networks coordinate activity between neocortical regions mediating sensory and cognitive processing to arrive at tactile perceptual decisions. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

Chaos and Robustness in a Single Family of Genetic Oscillatory Networks

PubMed Central

Fu, Daniel; Tan, Patrick; Kuznetsov, Alexey; Molkov, Yaroslav I.

2014-01-01

Genetic oscillatory networks can be mathematically modeled with delay differential equations (DDEs). Interpreting genetic networks with DDEs gives a more intuitive understanding from a biological standpoint. However, it presents a problem mathematically, for DDEs are by construction infinitely-dimensional and thus cannot be analyzed using methods common for systems of ordinary differential equations (ODEs). In our study, we address this problem by developing a method for reducing infinitely-dimensional DDEs to two- and three-dimensional systems of ODEs. We find that the three-dimensional reductions provide qualitative improvements over the two-dimensional reductions. We find that the reducibility of a DDE corresponds to its robustness. For non-robust DDEs that exhibit high-dimensional dynamics, we calculate analytic dimension lines to predict the dependence of the DDEs’ correlation dimension on parameters. From these lines, we deduce that the correlation dimension of non-robust DDEs grows linearly with the delay. On the other hand, for robust DDEs, we find that the period of oscillation grows linearly with delay. We find that DDEs with exclusively negative feedback are robust, whereas DDEs with feedback that changes its sign are not robust. We find that non-saturable degradation damps oscillations and narrows the range of parameter values for which oscillations exist. Finally, we deduce that natural genetic oscillators with highly-regular periods likely have solely negative feedback. PMID:24667178

Measuring alterations in oscillatory brain networks in schizophrenia with resting-state MEG: State-of-the-art and methodological challenges.

PubMed

Alamian, Golnoush; Hincapié, Ana-Sofía; Pascarella, Annalisa; Thiery, Thomas; Combrisson, Etienne; Saive, Anne-Lise; Martel, Véronique; Althukov, Dmitrii; Haesebaert, Frédéric; Jerbi, Karim

2017-09-01

Neuroimaging studies provide evidence of disturbed resting-state brain networks in Schizophrenia (SZ). However, untangling the neuronal mechanisms that subserve these baseline alterations requires measurement of their electrophysiological underpinnings. This systematic review specifically investigates the contributions of resting-state Magnetoencephalography (MEG) in elucidating abnormal neural organization in SZ patients. A systematic literature review of resting-state MEG studies in SZ was conducted. This literature is discussed in relation to findings from resting-state fMRI and EEG, as well as to task-based MEG research in SZ population. Importantly, methodological limitations are considered and recommendations to overcome current limitations are proposed. Resting-state MEG literature in SZ points towards altered local and long-range oscillatory network dynamics in various frequency bands. Critical methodological challenges with respect to experiment design, and data collection and analysis need to be taken into consideration. Spontaneous MEG data show that local and global neural organization is altered in SZ patients. MEG is a highly promising tool to fill in knowledge gaps about the neurophysiology of SZ. However, to reach its fullest potential, basic methodological challenges need to be overcome. MEG-based resting-state power and connectivity findings could be great assets to clinical and translational research in psychiatry, and SZ in particular. Copyright © 2017 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

Hearing and seeing meaning in noise: Alpha, beta, and gamma oscillations predict gestural enhancement of degraded speech comprehension.

PubMed

Drijvers, Linda; Özyürek, Asli; Jensen, Ole

2018-05-01

During face-to-face communication, listeners integrate speech with gestures. The semantic information conveyed by iconic gestures (e.g., a drinking gesture) can aid speech comprehension in adverse listening conditions. In this magnetoencephalography (MEG) study, we investigated the spatiotemporal neural oscillatory activity associated with gestural enhancement of degraded speech comprehension. Participants watched videos of an actress uttering clear or degraded speech, accompanied by a gesture or not and completed a cued-recall task after watching every video. When gestures semantically disambiguated degraded speech comprehension, an alpha and beta power suppression and a gamma power increase revealed engagement and active processing in the hand-area of the motor cortex, the extended language network (LIFG/pSTS/STG/MTG), medial temporal lobe, and occipital regions. These observed low- and high-frequency oscillatory modulations in these areas support general unification, integration and lexical access processes during online language comprehension, and simulation of and increased visual attention to manual gestures over time. All individual oscillatory power modulations associated with gestural enhancement of degraded speech comprehension predicted a listener's correct disambiguation of the degraded verb after watching the videos. Our results thus go beyond the previously proposed role of oscillatory dynamics in unimodal degraded speech comprehension and provide first evidence for the role of low- and high-frequency oscillations in predicting the integration of auditory and visual information at a semantic level. © 2018 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

Hearing and seeing meaning in noise: Alpha, beta, and gamma oscillations predict gestural enhancement of degraded speech comprehension

PubMed Central

Özyürek, Asli; Jensen, Ole

2018-01-01

Abstract During face‐to‐face communication, listeners integrate speech with gestures. The semantic information conveyed by iconic gestures (e.g., a drinking gesture) can aid speech comprehension in adverse listening conditions. In this magnetoencephalography (MEG) study, we investigated the spatiotemporal neural oscillatory activity associated with gestural enhancement of degraded speech comprehension. Participants watched videos of an actress uttering clear or degraded speech, accompanied by a gesture or not and completed a cued‐recall task after watching every video. When gestures semantically disambiguated degraded speech comprehension, an alpha and beta power suppression and a gamma power increase revealed engagement and active processing in the hand‐area of the motor cortex, the extended language network (LIFG/pSTS/STG/MTG), medial temporal lobe, and occipital regions. These observed low‐ and high‐frequency oscillatory modulations in these areas support general unification, integration and lexical access processes during online language comprehension, and simulation of and increased visual attention to manual gestures over time. All individual oscillatory power modulations associated with gestural enhancement of degraded speech comprehension predicted a listener's correct disambiguation of the degraded verb after watching the videos. Our results thus go beyond the previously proposed role of oscillatory dynamics in unimodal degraded speech comprehension and provide first evidence for the role of low‐ and high‐frequency oscillations in predicting the integration of auditory and visual information at a semantic level. PMID:29380945

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

Oscillatory phase dynamics in neural entrainment underpin illusory percepts of time.

PubMed

Herrmann, Björn; Henry, Molly J; Grigutsch, Maren; Obleser, Jonas

2013-10-02

Neural oscillatory dynamics are a candidate mechanism to steer perception of time and temporal rate change. While oscillator models of time perception are strongly supported by behavioral evidence, a direct link to neural oscillations and oscillatory entrainment has not yet been provided. In addition, it has thus far remained unaddressed how context-induced illusory percepts of time are coded for in oscillator models of time perception. To investigate these questions, we used magnetoencephalography and examined the neural oscillatory dynamics that underpin pitch-induced illusory percepts of temporal rate change. Human participants listened to frequency-modulated sounds that varied over time in both modulation rate and pitch, and judged the direction of rate change (decrease vs increase). Our results demonstrate distinct neural mechanisms of rate perception: Modulation rate changes directly affected listeners' rate percept as well as the exact frequency of the neural oscillation. However, pitch-induced illusory rate changes were unrelated to the exact frequency of the neural responses. The rate change illusion was instead linked to changes in neural phase patterns, which allowed for single-trial decoding of percepts. That is, illusory underestimations or overestimations of perceived rate change were tightly coupled to increased intertrial phase coherence and changes in cerebro-acoustic phase lag. The results provide insight on how illusory percepts of time are coded for by neural oscillatory dynamics.

Oscillatory/chaotic thermocapillary flow induced by radiant heating

NASA Technical Reports Server (NTRS)

Hsieh, Kwang-Chung; Thompson, Robert L.; Vanzandt, David; Dewitt, Kenneth; Nash, Jon

1994-01-01

The objective of this paper is to conduct ground-based experiments to measure the onset conditions of oscillatory Marangoni flow in laser-heated silicone oil in a cylindrical container. For a single fluid, experimental data are presented using the aspect ratio and the dynamic Bond number. It is found that for a fixed aspect ratio, there seems to be an asymptotic limit of the dynamic Bond number beyond which no onset of flow oscillation could occur. Experimental results also suggested that there could be a lower limit of the aspect ratio below which there is no onset of oscillatory flow.

Theories of dynamical phenomena in sunspots

NASA Technical Reports Server (NTRS)

Thomas, J. H.

1981-01-01

Attempts that have been made to understand and explain observed dynamical phenomena in sunspots within the framework of magnetohydrodynamic theory are surveyed. The qualitative aspects of the theory and physical arguments are emphasized, with mathematical details generally avoided. The dynamical phenomena in sunspots are divided into two categories: aperiodic (quasi-steady) and oscillatory. For each phenomenon discussed, the salient observational features that any theory should explain are summarized. The two contending theoretical models that can account for the fine structure of the Evershed motion, namely the convective roll model and the siphon flow model, are described. With regard to oscillatory phenomena, attention is given to overstability and oscillatory convection, umbral oscillations and flashes. penumbral waves, five-minute oscillations in sunspots, and the wave cooling of sunspots.

Information-geometric measures estimate neural interactions during oscillatory brain states

PubMed Central

Nie, Yimin; Fellous, Jean-Marc; Tatsuno, Masami

2014-01-01

The characterization of functional network structures among multiple neurons is essential to understanding neural information processing. Information geometry (IG), a theory developed for investigating a space of probability distributions has recently been applied to spike-train analysis and has provided robust estimations of neural interactions. Although neural firing in the equilibrium state is often assumed in these studies, in reality, neural activity is non-stationary. The brain exhibits various oscillations depending on cognitive demands or when an animal is asleep. Therefore, the investigation of the IG measures during oscillatory network states is important for testing how the IG method can be applied to real neural data. Using model networks of binary neurons or more realistic spiking neurons, we studied how the single- and pairwise-IG measures were influenced by oscillatory neural activity. Two general oscillatory mechanisms, externally driven oscillations and internally induced oscillations, were considered. In both mechanisms, we found that the single-IG measure was linearly related to the magnitude of the external input, and that the pairwise-IG measure was linearly related to the sum of connection strengths between two neurons. We also observed that the pairwise-IG measure was not dependent on the oscillation frequency. These results are consistent with the previous findings that were obtained under the equilibrium conditions. Therefore, we demonstrate that the IG method provides useful insights into neural interactions under the oscillatory condition that can often be observed in the real brain. PMID:24605089

Information-geometric measures estimate neural interactions during oscillatory brain states.

PubMed

Nie, Yimin; Fellous, Jean-Marc; Tatsuno, Masami

2014-01-01

The characterization of functional network structures among multiple neurons is essential to understanding neural information processing. Information geometry (IG), a theory developed for investigating a space of probability distributions has recently been applied to spike-train analysis and has provided robust estimations of neural interactions. Although neural firing in the equilibrium state is often assumed in these studies, in reality, neural activity is non-stationary. The brain exhibits various oscillations depending on cognitive demands or when an animal is asleep. Therefore, the investigation of the IG measures during oscillatory network states is important for testing how the IG method can be applied to real neural data. Using model networks of binary neurons or more realistic spiking neurons, we studied how the single- and pairwise-IG measures were influenced by oscillatory neural activity. Two general oscillatory mechanisms, externally driven oscillations and internally induced oscillations, were considered. In both mechanisms, we found that the single-IG measure was linearly related to the magnitude of the external input, and that the pairwise-IG measure was linearly related to the sum of connection strengths between two neurons. We also observed that the pairwise-IG measure was not dependent on the oscillation frequency. These results are consistent with the previous findings that were obtained under the equilibrium conditions. Therefore, we demonstrate that the IG method provides useful insights into neural interactions under the oscillatory condition that can often be observed in the real brain.

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.

The prediction of nonlinear dynamic loads on helicopters from flight variables using artificial neural networks

NASA Technical Reports Server (NTRS)

Cook, A. B.; Fuller, C. R.; O'Brien, W. F.; Cabell, R. H.

1992-01-01

A method of indirectly monitoring component loads through common flight variables is proposed which requires an accurate model of the underlying nonlinear relationships. An artificial neural network (ANN) model learns relationships through exposure to a database of flight variable records and corresponding load histories from an instrumented military helicopter undergoing standard maneuvers. The ANN model, utilizing eight standard flight variables as inputs, is trained to predict normalized time-varying mean and oscillatory loads on two critical components over a range of seven maneuvers. Both interpolative and extrapolative capabilities are demonstrated with agreement between predicted and measured loads on the order of 90 percent to 95 percent. This work justifies pursuing the ANN method of predicting loads from flight variables.

Excito-oscillatory dynamics as a mechanism of ventricular fibrillation.

PubMed

Gray, Richard A; Huelsing, Delilah J

2008-04-01

The instabilities associated with reentrant spiral waves are of paramount importance to the initiation and maintenance of tachyarrhythmias, especially ventricular fibrillation (VF). In addition to tissue heterogeneities, there are only a few basic purported mechanisms of spiral wave breakup, most notably restitution. We test the hypothesis that oscillatory membrane properties act to destabilize spiral waves. We recorded transmembrane potential (V(m)) from isolated rabbit myocytes using a constant current stimulation protocol. We developed a mathematical model that included both the stable excitable equilibrium point at resting V(m) (-80 mV) and the unstable oscillatory equilibrium point at elevated V(m) (-10 mV). Spiral wave dynamics were studied in 2-dimensional grids using variants of the model. All models showed restitution and reproduced the experimental values of transmembrane resistance at rest and during the action potential plateau. Stable spiral waves were observed when the model showed only 1 equilibrium point. However, spatio-temporal complexity was observed if the model showed both excitable and oscillatory equilibrium points (i.e., excito-oscillatory models). The initial wave breaks resulted from oscillatory waves expanding in all directions; after a few beats, the patterns were characterized by a combination of unstable spiral waves and target patterns consistent with the patterns observed on the heart surface during VF. In our model, this VF-like activity only occurred when the single cell period of V(m) oscillations was within a specific range. The VF-like patterns observed in our excito-oscillatory models could not be explained by the existing proposed instability mechanisms. Our results introduce the important suggestion that membrane dynamics responsible for V(m) oscillations at elevated V(m) levels can destabilize spiral waves and thus may be a novel therapeutic target for preventing VF.

Phonon-assisted oscillatory exciton dynamics in monolayer MoSe 2

DOE PAGES

Chow, Colin M.; Yu, Hongyi; Jones, Aaron M.; ...

2017-10-13

In monolayer semiconductor transition metal dichalcogenides, the exciton–phonon interaction strongly affects the photocarrier dynamics. Here, we report on an unusual oscillatory enhancement of the neutral exciton photoluminescence with the excitation laser frequency in monolayer MoSe 2. The frequency of oscillation matches that of the M-point longitudinal acoustic phonon, LA(M), suggesting the significance of zone-edge acoustic phonons and hence the deformation potential in exciton-phonon coupling in MoSe 2. Moreover, oscillatory behavior is observed in the steady-state emission linewidth and in time-resolved PLE data, which reveals variation with excitation energy in the exciton lifetime. These results clearly expose the key role playedmore » by phonons in the exciton formation and relaxation dynamics of two-dimensional van der Waals semiconductors.« less

Effects of Electrical and Mechanical Overstimulus on Spontaneous Oscillations in Hair Bundles

NASA Astrophysics Data System (ADS)

Kao, Albert; Strimbu, C. Elliott; Bozovic, Dolores

2011-11-01

Spontaneous oscillations constitute one of the manifestations of the active process operant in hair cells and provides a sensitive probe for their internal dynamics. The influx of ions into the stereocilia can be modulated by applying an electrical current across the epithelium and has been previously shown to strongly affect the oscillatory profiles. We applied strong transient stimuli and demonstrated that they can induce a transition from the oscillatory to the quiescent state, an effect that can last over several seconds post stimulus cessation. The dynamics of recovery to the oscillatory state was found to be dependent on the amplitude and the duration of the stimulus. Similar dynamics were observed after high-amplitude mechanical stimulus, which mimics the effects of loud sound on an individual bundle.

EEG source reconstruction reveals frontal-parietal dynamics of spatial conflict processing.

PubMed

Cohen, Michael X; Ridderinkhof, K Richard

2013-01-01

Cognitive control requires the suppression of distracting information in order to focus on task-relevant information. We applied EEG source reconstruction via time-frequency linear constrained minimum variance beamforming to help elucidate the neural mechanisms involved in spatial conflict processing. Human subjects performed a Simon task, in which conflict was induced by incongruence between spatial location and response hand. We found an early (∼200 ms post-stimulus) conflict modulation in stimulus-contralateral parietal gamma (30-50 Hz), followed by a later alpha-band (8-12 Hz) conflict modulation, suggesting an early detection of spatial conflict and inhibition of spatial location processing. Inter-regional connectivity analyses assessed via cross-frequency coupling of theta (4-8 Hz), alpha, and gamma power revealed conflict-induced shifts in cortical network interactions: Congruent trials (relative to incongruent trials) had stronger coupling between frontal theta and stimulus-contrahemifield parietal alpha/gamma power, whereas incongruent trials had increased theta coupling between medial frontal and lateral frontal regions. These findings shed new light into the large-scale network dynamics of spatial conflict processing, and how those networks are shaped by oscillatory interactions.

Selective entrainment of brain oscillations drives auditory perceptual organization.

PubMed

Costa-Faidella, Jordi; Sussman, Elyse S; Escera, Carles

2017-10-01

Perceptual sound organization supports our ability to make sense of the complex acoustic environment, to understand speech and to enjoy music. However, the neuronal mechanisms underlying the subjective experience of perceiving univocal auditory patterns that can be listened to, despite hearing all sounds in a scene, are poorly understood. We hereby investigated the manner in which competing sound organizations are simultaneously represented by specific brain activity patterns and the way attention and task demands prime the internal model generating the current percept. Using a selective attention task on ambiguous auditory stimulation coupled with EEG recordings, we found that the phase of low-frequency oscillatory activity dynamically tracks multiple sound organizations concurrently. However, whereas the representation of ignored sound patterns is circumscribed to auditory regions, large-scale oscillatory entrainment in auditory, sensory-motor and executive-control network areas reflects the active perceptual organization, thereby giving rise to the subjective experience of a unitary percept. Copyright © 2017 Elsevier Inc. All rights reserved.

Distribution of chaos and periodic spikes in a three-cell population model of cancer. Auto-organization of oscillatory phases in parameter planes

NASA Astrophysics Data System (ADS)

Gallas, Michelle R.; Gallas, Marcia R.; Gallas, Jason A. C.

2014-10-01

We study complex oscillations generated by the de Pillis-Radunskaya model of cancer growth, a model including interactions between tumor cells, healthy cells, and activated immune system cells. We report a wide-ranging systematic numerical classification of the oscillatory states and of their relative abundance. The dynamical states of the cell populations are characterized here by two independent and complementary types of stability diagrams: Lyapunov and isospike diagrams. The model is found to display stability phases organized regularly in old and new ways: Apart from the familiar spirals of stability, it displays exceptionally long zig-zag networks and intermixed cascades of two- and three-doubling flanked stability islands previously detected only in feedback systems with delay. In addition, we also characterize the interplay between continuous spike-adding and spike-doubling mechanisms responsible for the unbounded complexification of periodic wave patterns. This article is dedicated to Prof. Hans Jürgen Herrmann on the occasion of his 60th birthday.

Selective Entrainment of Theta Oscillations in the Dorsal Stream Causally Enhances Auditory Working Memory Performance.

PubMed

Albouy, Philippe; Weiss, Aurélien; Baillet, Sylvain; Zatorre, Robert J

2017-04-05

The implication of the dorsal stream in manipulating auditory information in working memory has been recently established. However, the oscillatory dynamics within this network and its causal relationship with behavior remain undefined. Using simultaneous MEG/EEG, we show that theta oscillations in the dorsal stream predict participants' manipulation abilities during memory retention in a task requiring the comparison of two patterns differing in temporal order. We investigated the causal relationship between brain oscillations and behavior by applying theta-rhythmic TMS combined with EEG over the MEG-identified target (left intraparietal sulcus) during the silent interval between the two stimuli. Rhythmic TMS entrained theta oscillation and boosted participants' accuracy. TMS-induced oscillatory entrainment scaled with behavioral enhancement, and both gains varied with participants' baseline abilities. These effects were not seen for a melody-comparison control task and were not observed for arrhythmic TMS. These data establish theta activity in the dorsal stream as causally related to memory manipulation. VIDEO ABSTRACT. Copyright © 2017 Elsevier Inc. All rights reserved.

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

Characterization of oscillatory changes in hippocampus and amygdala after deep brain stimulation of the infralimbic prefrontal cortex.

PubMed

Cervera-Ferri, Ana; Teruel-Martí, Vicent; Barceló-Molina, Moises; Martínez-Ricós, Joana; Luque-García, Aina; Martínez-Bellver, Sergio; Adell, Albert

2016-07-01

Deep brain stimulation (DBS) is a new investigational therapy that has generated positive results in refractory depression. Although the neurochemical and behavioral effects of DBS have been examined, less attention has been paid to the influence of DBS on the network dynamics between different brain areas, which could contribute to its therapeutic effects. Herein, we set out to identify the effects of 1 h DBS in the infralimbic cortex (IL) on the oscillatory network dynamics between hippocampus and basolateral amygdala (BLA), two regions implicated in depression and its treatment. Urethane-anesthetized rats with bilaterally implanted electrodes in the IL were exposed to 1 h constant stimulation of 130 Hz of frequency, 60 μA of constant current intensity and biphasic pulse width of 80 μsec. After a period of baseline recording, local field potentials (LFP) were recorded with formvar-insulated stainless steel electrodes. DBS of the IL increased the power of slow wave (SW, <1.5 Hz) and theta (3-12 Hz) frequencies in the hippocampus and BLA Furthermore, IL DBS caused a precise coupling in different frequency bands between both brain structures. The increases in SW band synchronization in hippocampus and BLA after DBS suggest that these changes may be important for the improvement of depressive behavior. In addition, the augmentation in theta synchrony might contribute to improvement in emotional and cognitive processes. © 2016 The Authors. Physiological Reports published by Wiley Periodicals, Inc. on behalf of the American Physiological Society and The Physiological Society.

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

PubMed

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

2016-08-15

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

Dynamics of macroautophagy: Modeling and oscillatory behavior

NASA Astrophysics Data System (ADS)

Han, Kyungreem; Kwon, Hyun Woong; Kang, Hyuk; Kim, Jinwoong; Lee, Myung-Shik; Choi, M. Y.

2012-02-01

We propose a model for macroautophagy and study the resulting dynamics of autophagy in a system isolated from its extra-cellular environment. It is found that the intracellular concentrations of autophagosomes and autolysosomes display oscillations with their own natural frequencies. Such oscillatory behaviors, which are interrelated to the dynamics of intracellular ATP, amino acids, and proteins, are consistent with the very recent biological observations. Implications of this theoretical study of autophagy are discussed, with regard to the possibility of guiding molecular studies of autophagy.

Synchronisation effects on the behavioural performance and information dynamics of a simulated minimally cognitive robotic agent.

PubMed

Moioli, Renan C; Vargas, Patricia A; Husbands, Phil

2012-09-01

Oscillatory activity is ubiquitous in nervous systems, with solid evidence that synchronisation mechanisms underpin cognitive processes. Nevertheless, its informational content and relationship with behaviour are still to be fully understood. In addition, cognitive systems cannot be properly appreciated without taking into account brain-body- environment interactions. In this paper, we developed a model based on the Kuramoto Model of coupled phase oscillators to explore the role of neural synchronisation in the performance of a simulated robotic agent in two different minimally cognitive tasks. We show that there is a statistically significant difference in performance and evolvability depending on the synchronisation regime of the network. In both tasks, a combination of information flow and dynamical analyses show that networks with a definite, but not too strong, propensity for synchronisation are more able to reconfigure, to organise themselves functionally and to adapt to different behavioural conditions. The results highlight the asymmetry of information flow and its behavioural correspondence. Importantly, it also shows that neural synchronisation dynamics, when suitably flexible and reconfigurable, can generate minimally cognitive embodied behaviour.

Single molecules can operate as primitive biological sensors, switches and oscillators.

PubMed

Hernansaiz-Ballesteros, Rosa D; Cardelli, Luca; Csikász-Nagy, Attila

2018-06-18

Switch-like and oscillatory dynamical systems are widely observed in biology. We investigate the simplest biological switch that is composed of a single molecule that can be autocatalytically converted between two opposing activity forms. We test how this simple network can keep its switching behaviour under perturbations in the system. We show that this molecule can work as a robust bistable system, even for alterations in the reactions that drive the switching between various conformations. We propose that this single molecule system could work as a primitive biological sensor and show by steady state analysis of a mathematical model of the system that it could switch between possible states for changes in environmental signals. Particularly, we show that a single molecule phosphorylation-dephosphorylation switch could work as a nucleotide or energy sensor. We also notice that a given set of reductions in the reaction network can lead to the emergence of oscillatory behaviour. We propose that evolution could have converted this switch into a single molecule oscillator, which could have been used as a primitive timekeeper. We discuss how the structure of the simplest known circadian clock regulatory system, found in cyanobacteria, resembles the proposed single molecule oscillator. Besides, we speculate if such minimal systems could have existed in an RNA world.

Single polymer dynamics under large amplitude oscillatory extension

NASA Astrophysics Data System (ADS)

Zhou, Yuecheng; Schroeder, Charles M.

2016-09-01

Understanding the conformational dynamics of polymers in time-dependent flows is of key importance for controlling materials properties during processing. Despite this importance, however, it has been challenging to study polymer dynamics in controlled time-dependent or oscillatory extensional flows. In this work, we study the dynamics of single polymers in large-amplitude oscillatory extension (LAOE) using a combination of experiments and Brownian dynamics (BD) simulations. Two-dimensional LAOE flow is generated using a feedback-controlled stagnation point device known as the Stokes trap, thereby generating an oscillatory planar extensional flow with alternating principal axes of extension and compression. Our results show that polymers experience periodic cycles of compression, reorientation, and extension in LAOE, and dynamics are generally governed by a dimensionless flow strength (Weissenberg number Wi) and dimensionless frequency (Deborah number De). Single molecule experiments are compared to BD simulations with and without intramolecular hydrodynamic interactions (HI) and excluded volume (EV) interactions, and good agreement is obtained across a range of parameters. Moreover, transient bulk stress in LAOE is determined from simulations using the Kramers relation, which reveals interesting and unique rheological signatures for this time-dependent flow. We further construct a series of single polymer stretch-flow rate curves (defined as single molecule Lissajous curves) as a function of Wi and De, and we observe qualitatively different dynamic signatures (butterfly, bow tie, arch, and line shapes) across the two-dimensional Pipkin space defined by Wi and De. Finally, polymer dynamics spanning from the linear to nonlinear response regimes are interpreted in the context of accumulated fluid strain in LAOE.

Temporal evolution of oscillations and synchrony in GPi/muscle pairs in Parkinson's disease.

PubMed

Hurtado, José M; Rubchinsky, Leonid L; Sigvardt, Karen A; Wheelock, Vicki L; Pappas, Conrad T E

2005-03-01

Both standard spectral analysis and time-dependent phase correlation techniques were applied to 27 pairs of tremor-related single units in the globus pallidus internus (GPi) and EMG of patients with Parkinson's disease (PD) undergoing stereotactic neurosurgery. Over long time-scales (approximately 60 s), GPi tremor-related units were statistically coherent with restricted regions of the peripheral musculature displaying tremor. The distribution of pooled coherence across all pairs supports a classification of GPi cell/EMG oscillatory pairs into coherent or noncoherent. Analysis using approximately 2-s sliding windows shows that oscillatory activity in both GPi tremor units and muscles occurs intermittently over time. For brain/muscle pairs that are coherent, there is partial overlap in the times of oscillatory activity but, in most cases, no significant correlation between the times of oscillatory subepisodes in the two signals. Phase locking between coherent pairs occurs transiently; however, the phase delay is similar for different phase-locking subepisodes. Noncoherent pairs also show episodes of transient phase locking, but they occurred less frequently, and no preferred phase delay was seen across subepisodes. Tremor oscillations in pallidum and EMGs are punctuated by phase slips, which were classified as synchronizing or desynchronizing depending on their effect on phase locking. In coherent pairs, the incidence of synchronizing slips is higher than desynchronizing slips, whereas no significant difference was seen for noncoherent pairs. The results of this quantitative characterization of parkinsonian tremor provide a foundation for hypotheses about the structure and dynamical functioning of basal ganglia motor control networks involved in tremor generation.

Relationships between cortical myeloarchitecture and electrophysiological networks

PubMed Central

Hunt, Benjamin A. E.; Tewarie, Prejaas K.; Mougin, Olivier E.; Geades, Nicolas; Singh, Krish D.; Morris, Peter G.; Gowland, Penny A.; Brookes, Matthew J.

2016-01-01

The human brain relies upon the dynamic formation and dissolution of a hierarchy of functional networks to support ongoing cognition. However, how functional connectivities underlying such networks are supported by cortical microstructure remains poorly understood. Recent animal work has demonstrated that electrical activity promotes myelination. Inspired by this, we test a hypothesis that gray-matter myelin is related to electrophysiological connectivity. Using ultra-high field MRI and the principle of structural covariance, we derive a structural network showing how myelin density differs across cortical regions and how separate regions can exhibit similar myeloarchitecture. Building upon recent evidence that neural oscillations mediate connectivity, we use magnetoencephalography to elucidate networks that represent the major electrophysiological pathways of communication in the brain. Finally, we show that a significant relationship exists between our functional and structural networks; this relationship differs as a function of neural oscillatory frequency and becomes stronger when integrating oscillations over frequency bands. Our study sheds light on the way in which cortical microstructure supports functional networks. Further, it paves the way for future investigations of the gray-matter structure/function relationship and its breakdown in pathology. PMID:27830650

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.

An Extended Motor Network Generates Beta and Gamma Oscillatory Perturbations during Development

ERIC Educational Resources Information Center

Wilson, Tony W.; Slason, Erin; Asherin, Ryan; Kronberg, Eugene; Reite, Martin L.; Teale, Peter D.; Rojas, Donald C.

2010-01-01

This study examines the time course and neural generators of oscillatory beta and gamma motor responses in typically-developing children. Participants completed a unilateral flexion-extension task using each index finger as whole-head magnetoencephalography (MEG) data were acquired. These MEG data were imaged in the frequency-domain using spatial…

Temporal entrainment of cognitive functions: musical mnemonics induce brain plasticity and oscillatory synchrony in neural networks underlying memory.

PubMed

Thaut, Michael H; Peterson, David A; McIntosh, Gerald C

2005-12-01

In a series of experiments, we have begun to investigate the effect of music as a mnemonic device on learning and memory and the underlying plasticity of oscillatory neural networks. We used verbal learning and memory tests (standardized word lists, AVLT) in conjunction with electroencephalographic analysis to determine differences between verbal learning in either a spoken or musical (verbal materials as song lyrics) modality. In healthy adults, learning in both the spoken and music condition was associated with significant increases in oscillatory synchrony across all frequency bands. A significant difference between the spoken and music condition emerged in the cortical topography of the learning-related synchronization. When using EEG measures as predictors during learning for subsequent successful memory recall, significantly increased coherence (phase-locked synchronization) within and between oscillatory brain networks emerged for music in alpha and gamma bands. In a similar study with multiple sclerosis patients, superior learning and memory was shown in the music condition when controlled for word order recall, and subjects were instructed to sing back the word lists. Also, the music condition was associated with a significant power increase in the low-alpha band in bilateral frontal networks, indicating increased neuronal synchronization. Musical learning may access compensatory pathways for memory functions during compromised PFC functions associated with learning and recall. Music learning may also confer a neurophysiological advantage through the stronger synchronization of the neuronal cell assemblies underlying verbal learning and memory. Collectively our data provide evidence that melodic-rhythmic templates as temporal structures in music may drive internal rhythm formation in recurrent cortical networks involved in learning and memory.

Bicycling and Walking are Associated with Different Cortical Oscillatory Dynamics

PubMed Central

Storzer, Lena; Butz, Markus; Hirschmann, Jan; Abbasi, Omid; Gratkowski, Maciej; Saupe, Dietmar; Schnitzler, Alfons; Dalal, Sarang S.

2016-01-01

Although bicycling and walking involve similar complex coordinated movements, surprisingly Parkinson’s patients with freezing of gait typically remain able to bicycle despite severe difficulties in walking. This observation suggests functional differences in the motor networks subserving bicycling and walking. However, a direct comparison of brain activity related to bicycling and walking has never been performed, neither in healthy participants nor in patients. Such a comparison could potentially help elucidating the cortical involvement in motor control and the mechanisms through which bicycling ability may be preserved in patients with freezing of gait. The aim of this study was to contrast the cortical oscillatory dynamics involved in bicycling and walking in healthy participants. To this end, EEG and EMG data of 14 healthy participants were analyzed, who cycled on a stationary bicycle at a slow cadence of 40 revolutions per minute (rpm) and walked at 40 strides per minute (spm), respectively. Relative to walking, bicycling was associated with a stronger power decrease in the high beta band (23–35 Hz) during movement initiation and execution, followed by a stronger beta power increase after movement termination. Walking, on the other hand, was characterized by a stronger and persisting alpha power (8–12 Hz) decrease. Both bicycling and walking exhibited movement cycle-dependent power modulation in the 24–40 Hz range that was correlated with EMG activity. This modulation was significantly stronger in walking. The present findings reveal differential cortical oscillatory dynamics in motor control for two types of complex coordinated motor behavior, i.e., bicycling and walking. Bicycling was associated with a stronger sustained cortical activation as indicated by the stronger high beta power decrease during movement execution and less cortical motor control within the movement cycle. We speculate this to be due to the more continuous nature of bicycling demanding less phase-dependent sensory processing and motor planning, as opposed to walking. PMID:26924977

Beta Oscillatory Dynamics in the Prefrontal and Superior Temporal Cortices Predict Spatial Working Memory Performance.

PubMed

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

2018-05-31

The oscillatory dynamics serving spatial working memory (SWM), and how such dynamics relate to performance, are poorly understood. To address these topics, the present study recruited 22 healthy adults to perform a SWM task during magnetoencephalography (MEG). The resulting MEG data were transformed into the time-frequency domain, and significant oscillatory responses were imaged using a beamformer. Voxel time series data were extracted from the cluster peaks to quantify the dynamics, while whole-brain partial correlation maps were computed to identify regions where oscillatory strength varied with accuracy on the SWM task. The results indicated transient theta oscillations in spatially distinct subregions of the prefrontal cortices at the onset of encoding and maintenance, which may underlie selection of goal-relevant information. Additionally, strong and persistent decreases in alpha and beta oscillations were observed throughout encoding and maintenance in parietal, temporal, and occipital regions, which could serve sustained attention and maintenance processes during SWM performance. The neuro-behavioral correlations revealed that beta activity within left dorsolateral prefrontal control regions and bilateral superior temporal integration regions was negatively correlated with SWM accuracy. Notably, this is the first study to employ a whole-brain approach to significantly link neural oscillations to behavioral performance in the context of SWM.

Time-frequency analysis of neuronal populations with instantaneous resolution based on noise-assisted multivariate empirical mode decomposition.

PubMed

Alegre-Cortés, J; Soto-Sánchez, C; Pizá, Á G; Albarracín, A L; Farfán, F D; Felice, C J; Fernández, E

2016-07-15

Linear analysis has classically provided powerful tools for understanding the behavior of neural populations, but the neuron responses to real-world stimulation are nonlinear under some conditions, and many neuronal components demonstrate strong nonlinear behavior. In spite of this, temporal and frequency dynamics of neural populations to sensory stimulation have been usually analyzed with linear approaches. In this paper, we propose the use of Noise-Assisted Multivariate Empirical Mode Decomposition (NA-MEMD), a data-driven template-free algorithm, plus the Hilbert transform as a suitable tool for analyzing population oscillatory dynamics in a multi-dimensional space with instantaneous frequency (IF) resolution. The proposed approach was able to extract oscillatory information of neurophysiological data of deep vibrissal nerve and visual cortex multiunit recordings that were not evidenced using linear approaches with fixed bases such as the Fourier analysis. Texture discrimination analysis performance was increased when Noise-Assisted Multivariate Empirical Mode plus Hilbert transform was implemented, compared to linear techniques. Cortical oscillatory population activity was analyzed with precise time-frequency resolution. Similarly, NA-MEMD provided increased time-frequency resolution of cortical oscillatory population activity. Noise-Assisted Multivariate Empirical Mode Decomposition plus Hilbert transform is an improved method to analyze neuronal population oscillatory dynamics overcoming linear and stationary assumptions of classical methods. Copyright © 2016 Elsevier B.V. All rights reserved.

Relationships between music training, speech processing, and word learning: a network perspective.

PubMed

Elmer, Stefan; Jäncke, Lutz

2018-03-15

Numerous studies have documented the behavioral advantages conferred on professional musicians and children undergoing music training in processing speech sounds varying in the spectral and temporal dimensions. These beneficial effects have previously often been associated with local functional and structural changes in the auditory cortex (AC). However, this perspective is oversimplified, in that it does not take into account the intrinsic organization of the human brain, namely, neural networks and oscillatory dynamics. Therefore, we propose a new framework for extending these previous findings to a network perspective by integrating multimodal imaging, electrophysiology, and neural oscillations. In particular, we provide concrete examples of how functional and structural connectivity can be used to model simple neural circuits exerting a modulatory influence on AC activity. In addition, we describe how such a network approach can be used for better comprehending the beneficial effects of music training on more complex speech functions, such as word learning. © 2018 New York Academy of Sciences.

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 aging. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

On the spatial dynamics and oscillatory behavior of a predator-prey model based on cellular automata and local particle swarm optimization.

PubMed

Molina, Mario Martínez; Moreno-Armendáriz, Marco A; Carlos Seck Tuoh Mora, Juan

2013-11-07

A two-dimensional lattice model based on Cellular Automata theory and swarm intelligence is used to study the spatial and population dynamics of a theoretical ecosystem. It is found that the social interactions among predators provoke the formation of clusters, and that by increasing the mobility of predators the model enters into an oscillatory behavior. © 2013 Elsevier Ltd. All rights reserved.

Task-Dependent Changes in Cross-Level Coupling between Single Neurons and Oscillatory Activity in Multiscale Networks

PubMed Central

Canolty, Ryan T.; Ganguly, Karunesh; Carmena, Jose M.

2012-01-01

Understanding the principles governing the dynamic coordination of functional brain networks remains an important unmet goal within neuroscience. How do distributed ensembles of neurons transiently coordinate their activity across a variety of spatial and temporal scales? While a complete mechanistic account of this process remains elusive, evidence suggests that neuronal oscillations may play a key role in this process, with different rhythms influencing both local computation and long-range communication. To investigate this question, we recorded multiple single unit and local field potential (LFP) activity from microelectrode arrays implanted bilaterally in macaque motor areas. Monkeys performed a delayed center-out reach task either manually using their natural arm (Manual Control, MC) or under direct neural control through a brain-machine interface (Brain Control, BC). In accord with prior work, we found that the spiking activity of individual neurons is coupled to multiple aspects of the ongoing motor beta rhythm (10–45 Hz) during both MC and BC, with neurons exhibiting a diversity of coupling preferences. However, here we show that for identified single neurons, this beta-to-rate mapping can change in a reversible and task-dependent way. For example, as beta power increases, a given neuron may increase spiking during MC but decrease spiking during BC, or exhibit a reversible shift in the preferred phase of firing. The within-task stability of coupling, combined with the reversible cross-task changes in coupling, suggest that task-dependent changes in the beta-to-rate mapping play a role in the transient functional reorganization of neural ensembles. We characterize the range of task-dependent changes in the mapping from beta amplitude, phase, and inter-hemispheric phase differences to the spike rates of an ensemble of simultaneously-recorded neurons, and discuss the potential implications that dynamic remapping from oscillatory activity to spike rate and timing may hold for models of computation and communication in distributed functional brain networks. PMID:23284276

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

PubMed Central

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

2015-01-01

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

Dynamic evolution of the oscillatory Belousov--Zhabotinsky reaction upon addition of a non-ionic polymer

NASA Astrophysics Data System (ADS)

Sciascia, Luciana; Lombardo, Renato; Turco Liveri, Maria Liria

2006-10-01

The dynamic evolution of the oscillatory Belousov-Zhabotinsky reaction upon addition of increasing amount of the non-ionic polymer polypropylene glycol with molecular weight 425 g mol -1 (PPG-425) was investigated in a stirred-batch reactor by monitoring the Ce(IV) absorbance changes. The oscillatory parameters are significantly altered by the presence of the polymer. The findings obtained in the present work revealed that the PPG-425 is not only more effective, than other polymer previously [R. Lombardo, C. Sbriziolo, M.L. Turco Liveri, K. Pelle, M. Wittmann, Z. Noszticzius, in: J.A. Pojman, Q. Tran-Cong-Miyata (Eds.), Nonlinear Dynamics in Polymeric Systems, American Chemical Society, Washington, DC, 869 (2004) 292] studied, in perturbing the BZ systems but also more capable of producing key radical species, which in turn can be exploited for the preparation of new polymeric materials.

Forced phase-locked states and information retrieval in a two-layer network of oscillatory neurons with directional connectivity

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

Kazantsev, Victor; Pimashkin, Alexey; Department of Neurodynamics and Neurobiology, Nizhny Novgorod State University, 23 Gagarin Ave., 603950 Nizhny Novgorod

We propose two-layer architecture of associative memory oscillatory network with directional interlayer connectivity. The network is capable to store information in the form of phase-locked (in-phase and antiphase) oscillatory patterns. The first (input) layer takes an input pattern to be recognized and their units are unidirectionally connected with all units of the second (control) layer. The connection strengths are weighted using the Hebbian rule. The output (retrieved) patterns appear as forced-phase locked states of the control layer. The conditions are found and analytically expressed for pattern retrieval in response on incoming stimulus. It is shown that the system is capablemore » to recover patterns with a certain level of distortions or noises in their profiles. The architecture is implemented with the Kuramoto phase model and using synaptically coupled neural oscillators with spikes. It is found that the spiking model is capable to retrieve patterns using the spiking phase that translates memorized patterns into the spiking phase shifts at different time scales.« less

Pattern Storage, Bifurcations, and Groupwise Correlation Structure of an Exactly Solvable Asymmetric Neural Network Model.

PubMed

Fasoli, Diego; Cattani, Anna; Panzeri, Stefano

2018-05-01

Despite their biological plausibility, neural network models with asymmetric weights are rarely solved analytically, and closed-form solutions are available only in some limiting cases or in some mean-field approximations. We found exact analytical solutions of an asymmetric spin model of neural networks with arbitrary size without resorting to any approximation, and we comprehensively studied its dynamical and statistical properties. The network had discrete time evolution equations and binary firing rates, and it could be driven by noise with any distribution. We found analytical expressions of the conditional and stationary joint probability distributions of the membrane potentials and the firing rates. By manipulating the conditional probability distribution of the firing rates, we extend to stochastic networks the associating learning rule previously introduced by Personnaz and coworkers. The new learning rule allowed the safe storage, under the presence of noise, of point and cyclic attractors, with useful implications for content-addressable memories. Furthermore, we studied the bifurcation structure of the network dynamics in the zero-noise limit. We analytically derived examples of the codimension 1 and codimension 2 bifurcation diagrams of the network, which describe how the neuronal dynamics changes with the external stimuli. This showed that the network may undergo transitions among multistable regimes, oscillatory behavior elicited by asymmetric synaptic connections, and various forms of spontaneous symmetry breaking. We also calculated analytically groupwise correlations of neural activity in the network in the stationary regime. This revealed neuronal regimes where, statistically, the membrane potentials and the firing rates are either synchronous or asynchronous. Our results are valid for networks with any number of neurons, although our equations can be realistically solved only for small networks. For completeness, we also derived the network equations in the thermodynamic limit of infinite network size and we analytically studied their local bifurcations. All the analytical results were extensively validated by numerical simulations.

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

PubMed Central

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

2016-01-01

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

Cell-Free Optogenetic Gene Expression System.

PubMed

Jayaraman, Premkumar; Yeoh, Jing Wui; Jayaraman, Sudhaghar; Teh, Ai Ying; Zhang, Jingyun; Poh, Chueh Loo

2018-04-20

Optogenetic tools provide a new and efficient way to dynamically program gene expression with unmatched spatiotemporal precision. To date, their vast potential remains untapped in the field of cell-free synthetic biology, largely due to the lack of simple and efficient light-switchable systems. Here, to bridge the gap between cell-free systems and optogenetics, we studied our previously engineered one component-based blue light-inducible Escherichia coli promoter in a cell-free environment through experimental characterization and mathematical modeling. We achieved >10-fold dynamic expression and demonstrated rapid and reversible activation of the target gene to generate oscillatory response. The deterministic model developed was able to recapitulate the system behavior and helped to provide quantitative insights to optimize dynamic response. This in vitro optogenetic approach could be a powerful new high-throughput screening technology for rapid prototyping of complex biological networks in both space and time without the need for chemical induction.

Neocortical dynamics due to axon propagation delays in cortico-cortical fibers: EEG traveling and standing waves with implications for top-down influences on local networks and white matter disease

PubMed Central

Nunez, Paul L.; Srinivasan, Ramesh

2013-01-01

The brain is treated as a nested hierarchical complex system with substantial interactions across spatial scales. Local networks are pictured as embedded within global fields of synaptic action and action potentials. Global fields may act top-down on multiple networks, acting to bind remote networks. Because of scale-dependent properties, experimental electrophysiology requires both local and global models that match observational scales. Multiple local alpha rhythms are embedded in a global alpha rhythm. Global models are outlined in which cm-scale dynamic behaviors result largely from propagation delays in cortico-cortical axons and cortical background excitation level, controlled by neuromodulators on long time scales. The idealized global models ignore the bottom-up influences of local networks on global fields so as to employ relatively simple mathematics. The resulting models are transparently related to several EEG and steady state visually evoked potentials correlated with cognitive states, including estimates of neocortical coherence structure, traveling waves, and standing waves. The global models suggest that global oscillatory behavior of self-sustained (limit-cycle) modes lower than about 20 Hz may easily occur in neocortical/white matter systems provided: Background cortical excitability is sufficiently high; the strength of long cortico-cortical axon systems is sufficiently high; and the bottom-up influence of local networks on the global dynamic field is sufficiently weak. The global models provide "entry points" to more detailed studies of global top-down influences, including binding of weakly connected networks, modulation of gamma oscillations by theta or alpha rhythms, and the effects of white matter deficits. PMID:24505628

Spatially Nonlinear Interdependence of Alpha-Oscillatory Neural Networks under Chan Meditation

PubMed Central

Chang, Chih-Hao

2013-01-01

This paper reports the results of our investigation of the effects of Chan meditation on brain electrophysiological behaviors from the viewpoint of spatially nonlinear interdependence among regional neural networks. Particular emphasis is laid on the alpha-dominated EEG (electroencephalograph). Continuous-time wavelet transform was adopted to detect the epochs containing substantial alpha activities. Nonlinear interdependence quantified by similarity index S(X∣Y), the influence of source signal Y on sink signal X, was applied to the nonlinear dynamical model in phase space reconstructed from multichannel EEG. Experimental group involved ten experienced Chan-Meditation practitioners, while control group included ten healthy subjects within the same age range, yet, without any meditation experience. Nonlinear interdependence among various cortical regions was explored for five local neural-network regions, frontal, posterior, right-temporal, left-temporal, and central regions. In the experimental group, the inter-regional interaction was evaluated for the brain dynamics under three different stages, at rest (stage R, pre-meditation background recording), in Chan meditation (stage M), and the unique Chakra-focusing practice (stage C). Experimental group exhibits stronger interactions among various local neural networks at stages M and C compared with those at stage R. The intergroup comparison demonstrates that Chan-meditation brain possesses better cortical inter-regional interactions than the resting brain of control group. PMID:24489583

Differential recruitment of brain networks in single-digit addition and multiplication: Evidence from EEG oscillations in theta and lower alpha bands.

PubMed

Wang, Lihan; Gan, John Q; Zhang, Li; Wang, Haixian

2018-06-01

Previous neuroimaging research investigating dissociation between single-digit addition and multiplication has suggested that the former placed more reliance on the visuo-spatial processing whereas the latter on the verbal processing. However, there has been little exploration into the disassociation in spatio-temporal dynamics of the oscillatory brain activity in specific frequency bands during the two arithmetic operations. To address this issue, the electroencephalogram (EEG) data were recorded from 19 participants engaged in a delayed verification arithmetic task. By analyzing oscillatory EEG activity in theta (5-7 Hz) and lower alpha frequency (9-10 Hz) bands, we found different patterns of oscillatory brain activity between single-digit addition and multiplication during the early processing stage (0-400 ms post-operand onset). Experiment results in this study showed a larger phasic increase of theta-band power for addition than for multiplication in the midline and the right frontal and central regions during the operator and operands presentation intervals, which was extended to the right parietal and the right occipito-temporal regions during the interval immediately after the operands presentation. In contrast, during multiplication higher phase-locking in lower alpha band was evident in the centro-parietal regions during the operator presentation, which was extended to the left fronto-central and anterior regions during the operands presentation. Besides, we found stronger theta phase synchrony between the parietal areas and the right occipital areas for single-digit addition than for multiplication during operands encoding. These findings of oscillatory brain activity extend the previous observations on functional dissociation between the two arithmetic operations. Copyright © 2018 Elsevier B.V. All rights reserved.

A Long-Lived Oscillatory Space-Time Correlation Function of Two Dimensional Colloids

NASA Astrophysics Data System (ADS)

Kim, Jeongmin; Sung, Bong June

2014-03-01

Diffusion of a colloid in solution has drawn significant attention for a century. A well-known behavior of the colloid is called Brownian motion : the particle displacement probability distribution (PDPD) is Gaussian and the mean-square displacement (MSD) is linear with time. However, recent simulation and experimental studies revealed the heterogeneous dynamics of colloids near glass transitions or in complex environments such as entangled actin, PDPD exhibited the exponential tail at a large length instead of being Gaussian at all length scales. More interestingly, PDPD is still exponential even when MSD was still linear with time. It requires a refreshing insight on the colloidal diffusion in the complex environments. In this work, we study heterogeneous dynamics of two dimensional (2D) colloids using molecular dynamics simulations. Unlike in three dimensions, 2D solids do not follow the Lindemann melting criterion. The Kosterlitz-Thouless-Halperin-Nelson-Young theory predicts two-step phase transitions with an intermediate phase, the hexatic phase between isotropic liquids and solids. Near solid-hexatic transition, PDPD shows interesting oscillatory behavior between a central Gaussian part and an exponential tail. Until 12 times longer than translational relaxation time, the oscillatory behavior still persists even after entering the Fickian regime. We also show that multi-layered kinetic clusters account for heterogeneous dynamics of 2D colloids with the long-lived anomalous oscillatory PDPD.

EEG Source Reconstruction Reveals Frontal-Parietal Dynamics of Spatial Conflict Processing

PubMed Central

Cohen, Michael X; Ridderinkhof, K. Richard

2013-01-01

Cognitive control requires the suppression of distracting information in order to focus on task-relevant information. We applied EEG source reconstruction via time-frequency linear constrained minimum variance beamforming to help elucidate the neural mechanisms involved in spatial conflict processing. Human subjects performed a Simon task, in which conflict was induced by incongruence between spatial location and response hand. We found an early (∼200 ms post-stimulus) conflict modulation in stimulus-contralateral parietal gamma (30–50 Hz), followed by a later alpha-band (8–12 Hz) conflict modulation, suggesting an early detection of spatial conflict and inhibition of spatial location processing. Inter-regional connectivity analyses assessed via cross-frequency coupling of theta (4–8 Hz), alpha, and gamma power revealed conflict-induced shifts in cortical network interactions: Congruent trials (relative to incongruent trials) had stronger coupling between frontal theta and stimulus-contrahemifield parietal alpha/gamma power, whereas incongruent trials had increased theta coupling between medial frontal and lateral frontal regions. These findings shed new light into the large-scale network dynamics of spatial conflict processing, and how those networks are shaped by oscillatory interactions. PMID:23451201

Uncovering hidden nodes in complex networks in the presence of noise

PubMed Central

Su, Ri-Qi; Lai, Ying-Cheng; Wang, Xiao; Do, Younghae

2014-01-01

Ascertaining the existence of hidden objects in a complex system, objects that cannot be observed from the external world, not only is curiosity-driven but also has significant practical applications. Generally, uncovering a hidden node in a complex network requires successful identification of its neighboring nodes, but a challenge is to differentiate its effects from those of noise. We develop a completely data-driven, compressive-sensing based method to address this issue by utilizing complex weighted networks with continuous-time oscillatory or discrete-time evolutionary-game dynamics. For any node, compressive sensing enables accurate reconstruction of the dynamical equations and coupling functions, provided that time series from this node and all its neighbors are available. For a neighboring node of the hidden node, this condition cannot be met, resulting in abnormally large prediction errors that, counterintuitively, can be used to infer the existence of the hidden node. Based on the principle of differential signal, we demonstrate that, when strong noise is present, insofar as at least two neighboring nodes of the hidden node are subject to weak background noise only, unequivocal identification of the hidden node can be achieved. PMID:24487720

Altered Network Oscillations and Functional Connectivity Dynamics in Children Born Very Preterm.

PubMed

Moiseev, Alexander; Doesburg, Sam M; Herdman, Anthony T; Ribary, Urs; Grunau, Ruth E

2015-09-01

Structural brain connections develop atypically in very preterm children, and altered functional connectivity is also evident in fMRI studies. Such alterations in brain network connectivity are associated with cognitive difficulties in this population. Little is known, however, about electrophysiological interactions among specific brain networks in children born very preterm. In the present study, we recorded magnetoencephalography while very preterm children and full-term controls performed a visual short-term memory task. Regions expressing task-dependent activity changes were identified using beamformer analysis, and inter-regional phase synchrony was calculated. Very preterm children expressed altered regional recruitment in distributed networks of brain areas, across standard physiological frequency ranges including the theta, alpha, beta and gamma bands. Reduced oscillatory synchrony was observed among task-activated brain regions in very preterm children, particularly for connections involving areas critical for executive abilities, including middle frontal gyrus. These findings suggest that inability to recruit neurophysiological activity and interactions in distributed networks including frontal regions may contribute to difficulties in cognitive development in children born very preterm.

Phase Difference between Model Cortical Areas Determines Level of Information Transfer

PubMed Central

ter Wal, Marije; Tiesinga, Paul H.

2017-01-01

Communication between cortical sites is mediated by long-range synaptic connections. However, these connections are relatively static, while everyday cognitive tasks demand a fast and flexible routing of information in the brain. Synchronization of activity between distant cortical sites has been proposed as the mechanism underlying such a dynamic communication structure. Here, we study how oscillatory activity affects the excitability and input-output relation of local cortical circuits and how it alters the transmission of information between cortical circuits. To this end, we develop model circuits showing fast oscillations by the PING mechanism, of which the oscillatory characteristics can be altered. We identify conditions for synchronization between two brain circuits and show that the level of intercircuit coherence and the phase difference is set by the frequency difference between the intrinsic oscillations. We show that the susceptibility of the circuits to inputs, i.e., the degree of change in circuit output following input pulses, is not uniform throughout the oscillation period and that both firing rate, frequency and power are differentially modulated by inputs arriving at different phases. As a result, an appropriate phase difference between the circuits is critical for the susceptibility windows of the circuits in the network to align and for information to be efficiently transferred. We demonstrate that changes in synchrony and phase difference can be used to set up or abolish information transfer in a network of cortical circuits. PMID:28232796

Cross-frequency power coupling between hierarchically organized face-selective areas.

PubMed

Furl, Nicholas; Coppola, Richard; Averbeck, Bruno B; Weinberger, Daniel R

2014-09-01

Neural oscillations are linked to perception and behavior and may reflect mechanisms for long-range communication between brain areas. We developed a causal model of oscillatory dynamics in the face perception network using magnetoencephalographic data from 51 normal volunteers. This model predicted induced responses to faces by estimating oscillatory power coupling between source locations corresponding to bilateral occipital and fusiform face areas (OFA and FFA) and the right superior temporal sulcus (STS). These sources showed increased alpha and theta and decreased beta power as well as selective responses to fearful facial expressions. We then used Bayesian model comparison to compare hypothetical models, which were motivated by previous connectivity data and a well-known theory of temporal lobe function. We confirmed this theory in detail by showing that the OFA bifurcated into 2 independent, hierarchical, feedforward pathways, with fearful expressions modulating power coupling only in the more dorsal (STS) pathway. The power coupling parameters showed a common pattern over connections. Low-frequency bands showed same-frequency power coupling, which, in the dorsal pathway, was modulated by fearful faces. Also, theta power showed a cross-frequency suppression of beta power. This combination of linear and nonlinear mechanisms could reflect computational mechanisms in hierarchical feedforward networks. © The Author 2013. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Proteolytic crosstalk in multi-protease networks

NASA Astrophysics Data System (ADS)

Ogle, Curtis T.; Mather, William H.

2016-04-01

Processive proteases, such as ClpXP in E. coli, are conserved enzyme assemblies that can recognize and rapidly degrade proteins. These proteases are used for a number of purposes, including degrading mistranslated proteins and controlling cellular stress response. However, proteolytic machinery within the cell is limited in capacity and can lead to a bottleneck in protein degradation, whereby many proteins compete (‘queue’) for proteolytic resources. Previous work has demonstrated that such queueing can lead to pronounced statistical relationships between different protein counts when proteins compete for a single common protease. However, real cells contain many different proteases, e.g. ClpXP, ClpAP, and Lon in E. coli, and it is not clear how competition between proteins for multiple classes of protease would influence the dynamics of cellular networks. In the present work, we theoretically demonstrate that a multi-protease proteolytic bottleneck can substantially couple the dynamics for both simple and complex (oscillatory) networks, even between substrates with substantially different affinities for protease. For these networks, queueing often leads to strong positive correlations between protein counts, and these correlations are strongest near the queueing theoretic point of balance. Furthermore, we find that the qualitative behavior of these networks depends on the relative size of the absolute affinity of substrate to protease compared to the cross affinity of substrate to protease, leading in certain regimes to priority queue statistics.

Music mnemonics aid Verbal Memory and Induce Learning – Related Brain Plasticity in Multiple Sclerosis

PubMed Central

Thaut, Michael H.; Peterson, David A.; McIntosh, Gerald C.; Hoemberg, Volker

2014-01-01

Recent research on music and brain function has suggested that the temporal pattern structure in music and rhythm can enhance cognitive functions. To further elucidate this question specifically for memory, we investigated if a musical template can enhance verbal learning in patients with multiple sclerosis (MS) and if music-assisted learning will also influence short-term, system-level brain plasticity. We measured systems-level brain activity with oscillatory network synchronization during music-assisted learning. Specifically, we measured the spectral power of 128-channel electroencephalogram (EEG) in alpha and beta frequency bands in 54 patients with MS. The study sample was randomly divided into two groups, either hearing a spoken or a musical (sung) presentation of Rey’s auditory verbal learning test. We defined the “learning-related synchronization” (LRS) as the percent change in EEG spectral power from the first time the word was presented to the average of the subsequent word encoding trials. LRS differed significantly between the music and the spoken conditions in low alpha and upper beta bands. Patients in the music condition showed overall better word memory and better word order memory and stronger bilateral frontal alpha LRS than patients in the spoken condition. The evidence suggests that a musical mnemonic recruits stronger oscillatory network synchronization in prefrontal areas in MS patients during word learning. It is suggested that the temporal structure implicit in musical stimuli enhances “deep encoding” during verbal learning and sharpens the timing of neural dynamics in brain networks degraded by demyelination in MS. PMID:24982626

Oscillatory Dynamics Related to the Unagreement Pattern in Spanish

ERIC Educational Resources Information Center

Perez, Alejandro; Molinaro, Nicola; Mancini, Simona; Barraza, Paulo; Carreiras, Manuel

2012-01-01

Unagreement patterns consist in a person feature mismatch between subject and verb that is nonetheless grammatical in Spanish. The processing of this type of construction gives new insights into the understanding of agreement processes during language comprehension. Here, we contrasted oscillatory brain activity triggered by Unagreement in…

A Spiking Neurocomputational Model of High-Frequency Oscillatory Brain Responses to Words and Pseudowords

PubMed Central

Garagnani, Max; Lucchese, Guglielmo; Tomasello, Rosario; Wennekers, Thomas; Pulvermüller, Friedemann

2017-01-01

Experimental evidence indicates that neurophysiological responses to well-known meaningful sensory items and symbols (such as familiar objects, faces, or words) differ from those to matched but novel and senseless materials (unknown objects, scrambled faces, and pseudowords). Spectral responses in the high beta- and gamma-band have been observed to be generally stronger to familiar stimuli than to unfamiliar ones. These differences have been hypothesized to be caused by the activation of distributed neuronal circuits or cell assemblies, which act as long-term memory traces for learned familiar items only. Here, we simulated word learning using a biologically constrained neurocomputational model of the left-hemispheric cortical areas known to be relevant for language and conceptual processing. The 12-area spiking neural-network architecture implemented replicates physiological and connectivity features of primary, secondary, and higher-association cortices in the frontal, temporal, and occipital lobes of the human brain. We simulated elementary aspects of word learning in it, focussing specifically on semantic grounding in action and perception. As a result of spike-driven Hebbian synaptic plasticity mechanisms, distributed, stimulus-specific cell-assembly (CA) circuits spontaneously emerged in the network. After training, presentation of one of the learned “word” forms to the model correlate of primary auditory cortex induced periodic bursts of activity within the corresponding CA, leading to oscillatory phenomena in the entire network and spontaneous across-area neural synchronization. Crucially, Morlet wavelet analysis of the network's responses recorded during presentation of learned meaningful “word” and novel, senseless “pseudoword” patterns revealed stronger induced spectral power in the gamma-band for the former than the latter, closely mirroring differences found in neurophysiological data. Furthermore, coherence analysis of the simulated responses uncovered dissociated category specific patterns of synchronous oscillations in distant cortical areas, including indirectly connected primary sensorimotor areas. Bridging the gap between cellular-level mechanisms, neuronal-population behavior, and cognitive function, the present model constitutes the first spiking, neurobiologically, and anatomically realistic model able to explain high-frequency oscillatory phenomena indexing language processing on the basis of dynamics and competitive interactions of distributed cell-assembly circuits which emerge in the brain as a result of Hebbian learning and sensorimotor experience. PMID:28149276

Dynamics of the stochastic low concentration trimolecular oscillatory chemical system with jumps

NASA Astrophysics Data System (ADS)

Wei, Yongchang; Yang, Qigui

2018-06-01

This paper is devoted to discern long time dynamics through the stochastic low concentration trimolecular oscillatory chemical system with jumps. By Lyapunov technique, this system is proved to have a unique global positive solution, and the asymptotic stability in mean square of such model is further established. Moreover, the existence of random attractor and Lyapunov exponents are obtained for the stochastic homeomorphism flow generated by the corresponding global positive solution. And some numerical simulations are given to illustrate the presented results.

The effect of shear flow on the rotational diffusivity of a single axisymmetric particle

NASA Astrophysics Data System (ADS)

Leahy, Brian; Koch, Donald; Cohen, Itai

2014-11-01

Colloidal suspensions of nonspherical particles abound in the world around us, from red blood cells in arteries to kaolinite discs in clay. Understanding the orientation dynamics of these particles is important for suspension rheology and particle self-assembly. However, even for the simplest case of dilute suspensions in simple shear flow, the orientation dynamics of Brownian nonspherical particles are poorly understood at large shear rates. Here, we analytically calculate the time-dependent orientation distributions of particles confined to the flow-gradient plane when the rotary diffusion is small but nonzero. For both startup and oscillatory shear flows, we find a coordinate change that maps the convection-diffusion equation to a simple diffusion equation with an enhanced diffusion constant, simplifying the orientation dynamics. For oscillatory shear, this enhanced diffusion drastically alters the quasi-steady orientation distributions. Our theory of the unsteady orientation dynamics provides an understanding of a nonspherical particle suspension's rheology for a large class of unsteady flows. For particles with aspect ratio 10 under oscillatory shear, the rotary diffusion and intrinsic viscosity vary with amplitude by a factor of ~ 40 and ~ 2 , respectively.

Brain Oscillatory Correlates of Altered Executive Functioning in Positive and Negative Symptomatic Schizophrenia Patients and Healthy Controls.

PubMed

Berger, Barbara; Minarik, Tamas; Griesmayr, Birgit; Stelzig-Schoeler, Renate; Aichhorn, Wolfgang; Sauseng, Paul

2016-01-01

Working Memory and executive functioning deficits are core characteristics of patients suffering from schizophrenia. Electrophysiological research indicates that altered patterns of neural oscillatory mechanisms underpinning executive functioning are associated with the psychiatric disorder. Such brain oscillatory changes have been found in local amplitude differences at gamma and theta frequencies in task-specific cortical areas. Moreover, interregional interactions are also disrupted as signified by decreased phase coherence of fronto-posterior theta activity in schizophrenia patients. However, schizophrenia is not a one-dimensional psychiatric disorder but has various forms and expressions. A common distinction is between positive and negative symptomatology but most patients have both negative and positive symptoms to some extent. Here, we examined three groups-healthy controls, predominantly negative, and predominantly positive symptomatic schizophrenia patients-when performing a working memory task with increasing cognitive demand and increasing need for executive control. We analyzed brain oscillatory activity in the three groups separately and investigated how predominant symptomatology might explain differences in brain oscillatory patterns. Our results indicate that differences in task specific fronto-posterior network activity (i.e., executive control network) expressed by interregional phase synchronization are able to account for working memory dysfunctions between groups. Local changes in the theta and gamma frequency range also show differences between patients and healthy controls, and more importantly, between the two patient groups. We conclude that differences in oscillatory brain activation patterns related to executive processing can be an indicator for positive and negative symptomatology in schizophrenia. Furthermore, changes in cognitive and especially executive functioning in patients are expressed by alterations in a task-specific fronto-posterior connectivity even in the absence of behavioral impairment.

Center for Neural Engineering at Tennessee State University, ASSERT Annual Progress Report.

DTIC Science & Technology

1995-07-01

neural networks . Their research topics are: (1) developing frequency dependent oscillatory neural networks ; (2) long term pontentiation learning rules...as applied to spatial navigation; (3) design and build a servo joint robotic arm and (4) neural network based prothesis control. One graduate student

Laboratory Observations of Sand Ripple Evolution in a Small Oscillatory Flow Tunnel

NASA Astrophysics Data System (ADS)

Calantoni, J.; Palmsten, M. L.; Chu, J.; Landry, B. J.; Penko, A.

2014-12-01

The dynamics of sand ripples are vital to understanding numerous coastal processes such as sediment transport, wave attenuation, boundary layer development, and seafloor acoustic properties. Experimental work was conducted in a small oscillatory flow tunnel at the Sediment Dynamics Laboratory at the Naval Research Laboratory, Stennis Space Center. Six different monochromatic oscillatory forcings, three with velocity asymmetry and three without, were used to investigate sand ripple dynamics using a unimodal grain size distribution with D50=0.65 mm. The experiments represent an extension of previous work using bimodal grain size distributions. A DSLR camera with a 180-degree fisheye lens collected images of the sediment bed profile every 2 seconds to resolve changes in ripple geometries and migration rates resulting from the different flow conditions for over 127 hours (229,388 images). Matlab © algorithms undistorted the fisheye images and quantified the ripple geometries, wavelengths, heights, and migration rates as a function of flow forcing. The mobility number was kept nearly constant by increasing and decreasing the semi-excursion amplitude and the wave frequency, respectively. We observed distinct changes in ripple geometry and migration rate for the pair of oscillatory forcings having nearly identical mobility numbers. The results suggested that the commonly used mobility number might not be appropriate to characterize ripple geometry or migration rates.

Limit Cycle Analysis Applied to the Oscillations of Decelerating Blunt-Body Entry Vehicles

NASA Technical Reports Server (NTRS)

Schoenenberger, Mark; Queen, Eric M.

2008-01-01

Many blunt-body entry vehicles have nonlinear dynamic stability characteristics that produce self-limiting oscillations in flight. Several different test techniques can be used to extract dynamic aerodynamic coefficients to predict this oscillatory behavior for planetary entry mission design and analysis. Most of these test techniques impose boundary conditions that alter the oscillatory behavior from that seen in flight. Three sets of test conditions, representing three commonly used test techniques, are presented to highlight these effects. Analytical solutions to the constant-coefficient planar equations-of-motion for each case are developed to show how the same blunt body behaves differently depending on the imposed test conditions. The energy equation is applied to further illustrate the governing dynamics. Then, the mean value theorem is applied to the energy rate equation to find the effective damping for an example blunt body with nonlinear, self-limiting dynamic characteristics. This approach is used to predict constant-energy oscillatory behavior and the equilibrium oscillation amplitudes for the various test conditions. These predictions are verified with planar simulations. The analysis presented provides an overview of dynamic stability test techniques and illustrates the effects of dynamic stability, static aerodynamics and test conditions on observed dynamic motions. It is proposed that these effects may be leveraged to develop new test techniques and refine test matrices in future tests to better define the nonlinear functional forms of blunt body dynamic stability curves.

Pluripotency gene network dynamics: System views from parametric analysis.

PubMed

Akberdin, Ilya R; Omelyanchuk, Nadezda A; Fadeev, Stanislav I; Leskova, Natalya E; Oschepkova, Evgeniya A; Kazantsev, Fedor V; Matushkin, Yury G; Afonnikov, Dmitry A; Kolchanov, Nikolay A

2018-01-01

Multiple experimental data demonstrated that the core gene network orchestrating self-renewal and differentiation of mouse embryonic stem cells involves activity of Oct4, Sox2 and Nanog genes by means of a number of positive feedback loops among them. However, recent studies indicated that the architecture of the core gene network should also incorporate negative Nanog autoregulation and might not include positive feedbacks from Nanog to Oct4 and Sox2. Thorough parametric analysis of the mathematical model based on this revisited core regulatory circuit identified that there are substantial changes in model dynamics occurred depending on the strength of Oct4 and Sox2 activation and molecular complexity of Nanog autorepression. The analysis showed the existence of four dynamical domains with different numbers of stable and unstable steady states. We hypothesize that these domains can constitute the checkpoints in a developmental progression from naïve to primed pluripotency and vice versa. During this transition, parametric conditions exist, which generate an oscillatory behavior of the system explaining heterogeneity in expression of pluripotent and differentiation factors in serum ESC cultures. Eventually, simulations showed that addition of positive feedbacks from Nanog to Oct4 and Sox2 leads mainly to increase of the parametric space for the naïve ESC state, in which pluripotency factors are strongly expressed while differentiation ones are repressed.

Altering the threshold of an excitable signal transduction network changes cell migratory modes.

PubMed

Miao, Yuchuan; Bhattacharya, Sayak; Edwards, Marc; Cai, Huaqing; Inoue, Takanari; Iglesias, Pablo A; Devreotes, Peter N

2017-04-01

The diverse migratory modes displayed by different cell types are generally believed to be idiosyncratic. Here we show that the migratory behaviour of Dictyostelium was switched from amoeboid to keratocyte-like and oscillatory modes by synthetically decreasing phosphatidylinositol-4,5-bisphosphate levels or increasing Ras/Rap-related activities. The perturbations at these key nodes of an excitable signal transduction network initiated a causal chain of events: the threshold for network activation was lowered, the speed and range of propagating waves of signal transduction activity increased, actin-driven cellular protrusions expanded and, consequently, the cell migratory mode transitions ensued. Conversely, innately keratocyte-like and oscillatory cells were promptly converted to amoeboid by inhibition of Ras effectors with restoration of directed migration. We use computational analysis to explain how thresholds control cell migration and discuss the architecture of the signal transduction network that gives rise to excitability.

Designing synthetic networks in silico: a generalised evolutionary algorithm approach.

PubMed

Smith, Robert W; van Sluijs, Bob; Fleck, Christian

2017-12-02

Evolution has led to the development of biological networks that are shaped by environmental signals. Elucidating, understanding and then reconstructing important network motifs is one of the principal aims of Systems & Synthetic Biology. Consequently, previous research has focused on finding optimal network structures and reaction rates that respond to pulses or produce stable oscillations. In this work we present a generalised in silico evolutionary algorithm that simultaneously finds network structures and reaction rates (genotypes) that can satisfy multiple defined objectives (phenotypes). The key step to our approach is to translate a schema/binary-based description of biological networks into systems of ordinary differential equations (ODEs). The ODEs can then be solved numerically to provide dynamic information about an evolved networks functionality. Initially we benchmark algorithm performance by finding optimal networks that can recapitulate concentration time-series data and perform parameter optimisation on oscillatory dynamics of the Repressilator. We go on to show the utility of our algorithm by finding new designs for robust synthetic oscillators, and by performing multi-objective optimisation to find a set of oscillators and feed-forward loops that are optimal at balancing different system properties. In sum, our results not only confirm and build on previous observations but we also provide new designs of synthetic oscillators for experimental construction. In this work we have presented and tested an evolutionary algorithm that can design a biological network to produce desired output. Given that previous designs of synthetic networks have been limited to subregions of network- and parameter-space, the use of our evolutionary optimisation algorithm will enable Synthetic Biologists to construct new systems with the potential to display a wider range of complex responses.

Modelling chronotaxicity of cellular energy metabolism to facilitate the identification of altered metabolic states

NASA Astrophysics Data System (ADS)

Lancaster, Gemma; Suprunenko, Yevhen F.; Jenkins, Kirsten; Stefanovska, Aneta

2016-08-01

Altered cellular energy metabolism is a hallmark of many diseases, one notable example being cancer. Here, we focus on the identification of the transition from healthy to abnormal metabolic states. To do this, we study the dynamics of energy production in a cell. Due to the thermodynamic openness of a living cell, the inability to instantaneously match fluctuating supply and demand in energy metabolism results in nonautonomous time-varying oscillatory dynamics. However, such oscillatory dynamics is often neglected and treated as stochastic. Based on experimental evidence of metabolic oscillations, we show that changes in metabolic state can be described robustly by alterations in the chronotaxicity of the corresponding metabolic oscillations, i.e. the ability of an oscillator to resist external perturbations. We also present a method for the identification of chronotaxicity, applicable to general oscillatory signals and, importantly, apply this to real experimental data. Evidence of chronotaxicity was found in glycolytic oscillations in real yeast cells, verifying that chronotaxicity could be used to study transitions between metabolic states.

Male veterans with PTSD exhibit aberrant neural dynamics during working memory processing: an MEG study

PubMed Central

McDermott, Timothy J.; Badura-Brack, Amy S.; Becker, Katherine M.; Ryan, Tara J.; Khanna, Maya M.; Heinrichs-Graham, Elizabeth; Wilson, Tony W.

2016-01-01

Background Posttraumatic stress disorder (PTSD) is associated with executive functioning deficits, including disruptions in working memory. In this study, we examined the neural dynamics of working memory processing in veterans with PTSD and a matched healthy control sample using magnetoencephalography (MEG). Methods Our sample of recent combat veterans with PTSD and demographically matched participants without PTSD completed a working memory task during a 306-sensor MEG recording. The MEG data were preprocessed and transformed into the time-frequency domain. Significant oscillatory brain responses were imaged using a beamforming approach to identify spatiotemporal dynamics. Results Fifty-one men were included in our analyses: 27 combat veterans with PTSD and 24 controls. Across all participants, a dynamic wave of neural activity spread from posterior visual cortices to left frontotemporal regions during encoding, consistent with a verbal working memory task, and was sustained throughout maintenance. Differences related to PTSD emerged during early encoding, with patients exhibiting stronger α oscillatory responses than controls in the right inferior frontal gyrus (IFG). Differences spread to the right supramarginal and temporal cortices during later encoding where, along with the right IFG, they persisted throughout the maintenance period. Limitations This study focused on men with combat-related PTSD using a verbal working memory task. Future studies should evaluate women and the impact of various traumatic experiences using diverse tasks. Conclusion Posttraumatic stress disorder is associated with neurophysiological abnormalities during working memory encoding and maintenance. Veterans with PTSD engaged a bilateral network, including the inferior prefrontal cortices and supramarginal gyri. Right hemispheric neural activity likely reflects compensatory processing, as veterans with PTSD work to maintain accurate performance despite known cognitive deficits associated with the disorder. PMID:26645740

Bistability and State Transition of a Delay Differential Equation Model of Neutrophil Dynamics

NASA Astrophysics Data System (ADS)

Ma, Suqi; Zhu, Kaiyi; Lei, Jinzhi

This paper studies the existence of bistable states and control strategies to induce state transitions of a delay differential equation model of neutrophil dynamics. We seek the conditions that a stable steady state and an oscillatory state coexist in the neutrophil dynamical system. Physiologically, stable steady state represents the healthy state, while oscillatory state is usually associated with diseases such as cyclical neutropenia. We study the control strategies to induce the transitions from the disease state to the healthy state by introducing temporal perturbations to system parameters. This study is valuable in designing clinical protocols for the treatment of cyclical neutropenia.

Stationary and oscillatory bound states of dissipative solitons created by third-order dispersion

NASA Astrophysics Data System (ADS)

Sakaguchi, Hidetsugu; Skryabin, Dmitry V.; Malomed, Boris A.

2018-06-01

We consider the model of fiber-laser cavities near the zero-dispersion point, based on the complex Ginzburg-Landau equation with the cubic-quintic nonlinearity, including the third-order dispersion (TOD) term. It is well known that this model supports stable dissipative solitons. We demonstrate that the same model gives rise to several families of robust bound states of the solitons, which exists only in the presence of the TOD. There are both stationary and dynamical bound states, with oscillating separation between the bound solitons. Stationary states are multistable, corresponding to different values of the separation. With the increase of the TOD coefficient, the bound state with the smallest separation gives rise the oscillatory state through the Hopf bifurcation. Further growth of TOD leads to a bifurcation transforming the oscillatory limit cycle into a strange attractor, which represents a chaotically oscillating dynamical bound state. Families of multistable three- and four-soliton complexes are found too, the ones with the smallest separation between the solitons again ending by a transition to oscillatory states through the Hopf bifurcation.

Laboratory Experiments of Sand Ripples with Bimodal Size Distributions Under Asymmetric Oscillatory Flows

NASA Astrophysics Data System (ADS)

Calantoni, J.; Landry, B. J.

2010-12-01

The dynamics of sand ripples are vital to understanding numerous coastal processes such as sediment transport, wave attenuation, boundary layer development, and seafloor acoustic properties. Though significant laboratory research has been conducted to elucidate oscillatory flow morphodynamics under various constant and transient forcing conditions, the majority of the previous experiments were conducted only for beds with unimodal size distributions of sediment. Recent oscillatory flow experiments as well as past laboratory observations in uniform flows suggest that the presence of heterogeneous size sand compositions may significantly impact ripple morphology, resulting in a variety of observable effects (e.g., sediment sorting, bed armoring, and altered transport rates). Experimental work was conducted in a small oscillatory flow tunnel at the Sediment Dynamics Laboratory at the Naval Research Laboratory, Stennis Space Center. Three different monochromatic oscillatory forcings having velocity asymmetry were used to study sand ripple dynamics over five bimodal and two unimodal sediment beds. The seven different mixtures were composed using two unimodal sands of different colors (blue/white) and median grain diameters (d=0.31 mm / d=0.65 mm) combined into various mixtures by mass (i.e., 0/100; 10/90; 25/75; 50/50; 75/25; 90/10; and 100/0 which denotes mass percentage of blue/white sand, respectively, within each mixture). High-definition video of the sediment bed profile was acquired in conjunction with sediment trap measurements to resolve differences in ripple geometries, migration and evolution rates due to the different sediment mixtures and flow conditions. Observational findings clearly illustrate sediment stratification within ripple crests and the depth of the active mixing layer in addition to supporting sediment sorting in previous research on symmetric oscillatory flows in which the larger grains collect on top of ripple crests and smaller grains in the troughs. Preliminary quantitative results illuminate variations in equilibrium ripple geometry, ripple migration rates, and transition time scales between equilibrium states, all as functions of the sediment size mixture and flow forcing.

Bridging the gap between modules in isolation and as part of networks: A systems framework for elucidating interaction and regulation of signalling modules

NASA Astrophysics Data System (ADS)

Menon, Govind; Krishnan, J.

2016-07-01

While signalling and biochemical modules have been the focus of numerous studies, they are typically studied in isolation, with no examination of the effects of the ambient network. In this paper we formulate and develop a systems framework, rooted in dynamical systems, to understand such effects, by studying the interaction of signalling modules. The modules we consider are (i) basic covalent modification, (ii) monostable switches, (iii) bistable switches, (iv) adaptive modules, and (v) oscillatory modules. We systematically examine the interaction of these modules by analyzing (a) sequential interaction without shared components, (b) sequential interaction with shared components, and (c) oblique interactions. Our studies reveal that the behaviour of a module in isolation may be substantially different from that in a network, and explicitly demonstrate how the behaviour of a given module, the characteristics of the ambient network, and the possibility of shared components can result in new effects. Our global approach illuminates different aspects of the structure and functioning of modules, revealing the importance of dynamical characteristics as well as biochemical features; this provides a methodological platform for investigating the complexity of natural modules shaped by evolution, elucidating the effects of ambient networks on a module in multiple cellular contexts, and highlighting the capabilities and constraints for engineering robust synthetic modules. Overall, such a systems framework provides a platform for bridging the gap between non-linear information processing modules, in isolation and as parts of networks, and a basis for understanding new aspects of natural and engineered cellular networks.

Bridging the gap between modules in isolation and as part of networks: A systems framework for elucidating interaction and regulation of signalling modules.

PubMed

Menon, Govind; Krishnan, J

2016-07-21

While signalling and biochemical modules have been the focus of numerous studies, they are typically studied in isolation, with no examination of the effects of the ambient network. In this paper we formulate and develop a systems framework, rooted in dynamical systems, to understand such effects, by studying the interaction of signalling modules. The modules we consider are (i) basic covalent modification, (ii) monostable switches, (iii) bistable switches, (iv) adaptive modules, and (v) oscillatory modules. We systematically examine the interaction of these modules by analyzing (a) sequential interaction without shared components, (b) sequential interaction with shared components, and (c) oblique interactions. Our studies reveal that the behaviour of a module in isolation may be substantially different from that in a network, and explicitly demonstrate how the behaviour of a given module, the characteristics of the ambient network, and the possibility of shared components can result in new effects. Our global approach illuminates different aspects of the structure and functioning of modules, revealing the importance of dynamical characteristics as well as biochemical features; this provides a methodological platform for investigating the complexity of natural modules shaped by evolution, elucidating the effects of ambient networks on a module in multiple cellular contexts, and highlighting the capabilities and constraints for engineering robust synthetic modules. Overall, such a systems framework provides a platform for bridging the gap between non-linear information processing modules, in isolation and as parts of networks, and a basis for understanding new aspects of natural and engineered cellular networks.

Curved-flow, rolling-flow, and oscillatory pure-yawing wind-tunnel test methods for determination of dynamic stability derivatives

NASA Technical Reports Server (NTRS)

Chambers, J. R.; Grafton, S. B.; Lutze, F. H.

1981-01-01

The test capabilities of the Stability Wind Tunnel of the Virginia Polytechnic Institute and State University are described, and calibrations for curved and rolling flow techniques are given. Oscillatory snaking tests to determine pure yawing derivatives are considered. Representative aerodynamic data obtained for a current fighter configuration using the curved and rolling flow techniques are presented. The application of dynamic derivatives obtained in such tests to the analysis of airplane motions in general, and to high angle of attack flight conditions in particular, is discussed.

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.

Membrane potential dynamics of grid cells

PubMed Central

Domnisoru, Cristina; Kinkhabwala, Amina A.; Tank, David W.

2014-01-01

During navigation, grid cells increase their spike rates in firing fields arranged on a strikingly regular triangular lattice, while their spike timing is often modulated by theta oscillations. Oscillatory interference models of grid cells predict theta amplitude modulations of membrane potential during firing field traversals, while competing attractor network models predict slow depolarizing ramps. Here, using in-vivo whole-cell recordings, we tested these models by directly measuring grid cell intracellular potentials in mice running along linear tracks in virtual reality. Grid cells had large and reproducible ramps of membrane potential depolarization that were the characteristic signature tightly correlated with firing fields. Grid cells also exhibited intracellular theta oscillations that influenced their spike timing. However, the properties of theta amplitude modulations were not consistent with the view that they determine firing field locations. Our results support cellular and network mechanisms in which grid fields are produced by slow ramps, as in attractor models, while theta oscillations control spike timing. PMID:23395984

The role of nonlinear viscoelasticity on the functionality of laminating shortenings

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

Macias-Rodriguez, Braulio A.; Peyronel, Fernanda; Marangoni, Alejandro G.

The rheology of fats is essential for the development of homogeneous and continuous layered structures of doughs. Here, we define laminating shortenings in terms of rheological behavior displayed during linear-to-nonlinear shear deformations, investigated by large amplitude oscillatory shear rheology. Likewise, we associate the rheological behavior of the shortenings with structural length scales elucidated by ultra-small angle x-ray scattering and cryo-electron microscopy. Shortenings exhibited solid-like viscoelastic and viscoelastoplastic behaviors in the linear and nonlinear regimes respectively. In the nonlinear region, laminating shortenings dissipated more viscous energy (larger normalized dynamic viscosities) than a cake bakery shortening. The fat solid-like network of laminatingmore » shortening displayed a three-hierarchy structure and layered crystal aggregates, in comparison to two-hierarchy structure and spherical-like crystal aggregates of a cake shortening. We argue that the observed rheology, correlated to the structural network, is crucial for optimal laminating performance of shortenings.« less

Liposome-Cross-Linked Hybrid Hydrogels for Glutathione-Triggered Delivery of Multiple Cargo Molecules.

PubMed

Liang, Yingkai; Kiick, Kristi L

2016-02-08

Novel, liposome-cross-linked hybrid hydrogels cross-linked by the Michael-type addition of thiols with maleimides were prepared via the use of maleimide-functionalized liposome cross-linkers and thiolated polyethylene glycol (PEG) polymers. Gelation of the materials was confirmed by oscillatory rheology experiments. These hybrid hydrogels are rendered degradable upon exposure to thiol-containing molecules such as glutathione (GSH), via the incorporation of selected thioether succinimide cross-links between the PEG polymers and liposome nanoparticles. Dynamic light scattering (DLS) characterization confirmed that intact liposomes were released upon network degradation. Owing to the hierarchical structure of the network, multiple cargo molecules relevant for chemotherapies, namely doxorubicin (DOX) and cytochrome c, were encapsulated and simultaneously released from the hybrid hydrogels, with differential release profiles that were driven by degradation-mediated release and Fickian diffusion, respectively. This work introduces a facile approach for the development of advanced, hybrid drug delivery vehicles that exhibit novel chemical degradation.

Harnessing functional segregation across brain rhythms as a means to detect EEG oscillatory multiplexing during music listening

NASA Astrophysics Data System (ADS)

Adamos, Dimitrios A.; Laskaris, Nikolaos A.; Micheloyannis, Sifis

2018-06-01

Objective. Music, being a multifaceted stimulus evolving at multiple timescales, modulates brain function in a manifold way that encompasses not only the distinct stages of auditory perception, but also higher cognitive processes like memory and appraisal. Network theory is apparently a promising approach to describe the functional reorganization of brain oscillatory dynamics during music listening. However, the music induced changes have so far been examined within the functional boundaries of isolated brain rhythms. Approach. Using naturalistic music, we detected the functional segregation patterns associated with different cortical rhythms, as these were reflected in the surface electroencephalography (EEG) measurements. The emerged structure was compared across frequency bands to quantify the interplay among rhythms. It was also contrasted against the structure from the rest and noise listening conditions to reveal the specific components stemming from music listening. Our methodology includes an efficient graph-partitioning algorithm, which is further utilized for mining prototypical modular patterns, and a novel algorithmic procedure for identifying ‘switching nodes’ (i.e. recording sites) that consistently change module during music listening. Main results. Our results suggest the multiplex character of the music-induced functional reorganization and particularly indicate the dependence between the networks reconstructed from the δ and β H rhythms. This dependence is further justified within the framework of nested neural oscillations and fits perfectly within the context of recently introduced cortical entrainment to music. Significance. Complying with the contemporary trends towards a multi-scale examination of the brain network organization, our approach specifies the form of neural coordination among rhythms during music listening. Considering its computational efficiency, and in conjunction with the flexibility of in situ electroencephalography, it may lead to novel assistive tools for real-life applications.

Harnessing functional segregation across brain rhythms as a means to detect EEG oscillatory multiplexing during music listening.

PubMed

Adamos, Dimitrios A; Laskaris, Nikolaos A; Micheloyannis, Sifis

2018-06-01

Music, being a multifaceted stimulus evolving at multiple timescales, modulates brain function in a manifold way that encompasses not only the distinct stages of auditory perception, but also higher cognitive processes like memory and appraisal. Network theory is apparently a promising approach to describe the functional reorganization of brain oscillatory dynamics during music listening. However, the music induced changes have so far been examined within the functional boundaries of isolated brain rhythms. Using naturalistic music, we detected the functional segregation patterns associated with different cortical rhythms, as these were reflected in the surface electroencephalography (EEG) measurements. The emerged structure was compared across frequency bands to quantify the interplay among rhythms. It was also contrasted against the structure from the rest and noise listening conditions to reveal the specific components stemming from music listening. Our methodology includes an efficient graph-partitioning algorithm, which is further utilized for mining prototypical modular patterns, and a novel algorithmic procedure for identifying 'switching nodes' (i.e. recording sites) that consistently change module during music listening. Our results suggest the multiplex character of the music-induced functional reorganization and particularly indicate the dependence between the networks reconstructed from the δ and β H rhythms. This dependence is further justified within the framework of nested neural oscillations and fits perfectly within the context of recently introduced cortical entrainment to music. Complying with the contemporary trends towards a multi-scale examination of the brain network organization, our approach specifies the form of neural coordination among rhythms during music listening. Considering its computational efficiency, and in conjunction with the flexibility of in situ electroencephalography, it may lead to novel assistive tools for real-life applications.

The role of high-frequency oscillatory activity in reward processing and learning.

PubMed

Marco-Pallarés, Josep; Münte, Thomas F; Rodríguez-Fornells, Antoni

2015-02-01

Oscillatory activity has been proposed as a key mechanism in the integration of brain activity of distant structures. Particularly, high frequency brain oscillatory activity in the beta and gamma range has received increasing interest in the domains of attention and memory. In addition, a number of recent studies have revealed an increase of beta-gamma activity (20-35 Hz) after unexpected or relevant positive reward outcomes. In the present manuscript we review the literature on this phenomenon and we propose that this activity is a brain signature elicited by unexpected positive outcomes in order to transmit a fast motivational value signal to the reward network. In addition, we hypothesize that beta-gamma oscillatory activity indexes the interaction between attentional and emotional systems, and that it directly reflects the appearance of unexpected positive rewards in learning-related contexts. Copyright © 2014 Elsevier Ltd. All rights reserved.

Nonlinear response of dense colloidal suspensions under oscillatory shear: mode-coupling theory and Fourier transform rheology experiments.

PubMed

Brader, J M; Siebenbürger, M; Ballauff, M; Reinheimer, K; Wilhelm, M; Frey, S J; Weysser, F; Fuchs, M

2010-12-01

Using a combination of theory, experiment, and simulation we investigate the nonlinear response of dense colloidal suspensions to large amplitude oscillatory shear flow. The time-dependent stress response is calculated using a recently developed schematic mode-coupling-type theory describing colloidal suspensions under externally applied flow. For finite strain amplitudes the theory generates a nonlinear response, characterized by significant higher harmonic contributions. An important feature of the theory is the prediction of an ideal glass transition at sufficiently strong coupling, which is accompanied by the discontinuous appearance of a dynamic yield stress. For the oscillatory shear flow under consideration we find that the yield stress plays an important role in determining the nonlinearity of the time-dependent stress response. Our theoretical findings are strongly supported by both large amplitude oscillatory experiments (with Fourier transform rheology analysis) on suspensions of thermosensitive core-shell particles dispersed in water and Brownian dynamics simulations performed on a two-dimensional binary hard-disk mixture. In particular, theory predicts nontrivial values of the exponents governing the final decay of the storage and loss moduli as a function of strain amplitude which are in good agreement with both simulation and experiment. A consistent set of parameters in the presented schematic model achieves to jointly describe linear moduli, nonlinear flow curves, and large amplitude oscillatory spectroscopy.

“Cerebellar contribution to visuo-attentional alpha rhythm: insights from weightlessness”

PubMed Central

Cebolla, A. M.; Petieau, M.; Dan, B.; Balazs, L.; McIntyre, J.; Cheron, G.

2016-01-01

Human brain adaptation in weightlessness follows the necessity to reshape the dynamic integration of the neural information acquired in the new environment. This basic aspect was here studied by the electroencephalogram (EEG) dynamics where oscillatory modulations were measured during a visuo-attentional state preceding a visuo-motor docking task. Astronauts in microgravity conducted the experiment in free-floating aboard the International Space Station, before the space flight and afterwards. We observed stronger power decrease (~ERD: event related desynchronization) of the ~10 Hz oscillation from the occipital-parietal (alpha ERD) to the central areas (mu ERD). Inverse source modelling of the stronger alpha ERD revealed a shift from the posterior cingulate cortex (BA31, from the default mode network) on Earth to the precentral cortex (BA4, primary motor cortex) in weightlessness. We also observed significant contribution of the vestibular network (BA40, BA32, and BA39) and cerebellum (lobule V, VI). We suggest that due to the high demands for the continuous readjustment of an appropriate body posture in free-floating, this visuo-attentional state required more contribution from the motor cortex. The cerebellum and the vestibular network involvement in weightlessness might support the correction signals processing necessary for postural stabilization, and the increased demand to integrate incongruent vestibular information. PMID:27883068

Dynamics of Large Systems of Nonlinearly Evolving Units

NASA Astrophysics Data System (ADS)

Lu, Zhixin

The dynamics of large systems of many nonlinearly evolving units is a general research area that has great importance for many areas in science and technology, including biology, computation by artificial neural networks, statistical mechanics, flocking in animal groups, the dynamics of coupled neurons in the brain, and many others. While universal principles and techniques are largely lacking in this broad area of research, there is still one particular phenomenon that seems to be broadly applicable. In particular, this is the idea of emergence, by which is meant macroscopic behaviors that "emerge" from a large system of many "smaller or simpler entities such that...large entities" [i.e., macroscopic behaviors] arise which "exhibit properties the smaller/simpler entities do not exhibit." In this thesis we investigate mechanisms and manifestations of emergence in four dynamical systems consisting many nonlinearly evolving units. These four systems are as follows. (a) We first study the motion of a large ensemble of many noninteracting particles in a slowly changing Hamiltonian system that undergoes a separatrix crossing. In such systems, we find that separatrix-crossing induces a counterintuitive effect. Specifically, numerical simulation of two sets of densely sprinkled initial conditions on two energy curves appears to suggest that the two energy curves, one originally enclosing the other, seemingly interchange their positions. This, however, is topologically forbidden. We resolve this paradox by introducing a numerical simulation method we call "robust" and study its consequences. (b) We next study the collective dynamics of oscillatory pacemaker neurons in Suprachiasmatic Nucleus (SCN), which, through synchrony, govern the circadian rhythm of mammals. We start from a high-dimensional description of the many coupled oscillatory neuronal units within the SCN. This description is based on a forced Kuramoto model. We then reduce the system dimensionality by using the Ott Antonsen Ansatz and obtain a low-dimensional macroscopic description. Using this reduced macroscopic system, we explain the east-west asymmetry of jet-lag recovery and discus the consequences of our findings. (c) Thirdly, we study neuron firing in integrate-and-fire neural networks. We build a discrete-state/discrete-time model with both excitatory and inhibitory neurons and find a phase transition between avalanching dynamics and ceaseless firing dynamics. Power-law firing avalanche size/duration distributions are observed at critical parameter values. Furthermore, in this critical regime we find the same power law exponents as those observed from experiments and previous, more restricted, simulation studies. We also employ a mean-field method and show that inhibitory neurons in this system promote robustness of the criticality (i.e., an enhanced range of system parameter where power-law avalanche statistics applies). (d) Lastly, we study the dynamics of "reservoir computing networks" (RCN's), which is a recurrent neural network (RNN) scheme for machine learning. The advantage of RCN's over traditional RNN's is that the training is done only on the output layer, usually via a simple least-square method. We show that RCN's are very effective for inferring unmeasured state variables of dynamical systems whose system state is only partially measured. Using the examples of the Lorenz system and the Rossler system we demonstrate the potential of an RCN to perform as an universal model-free "observer".

How time delay and network design shape response patterns in biochemical negative feedback systems.

PubMed

Börsch, Anastasiya; Schaber, Jörg

2016-08-24

Negative feedback in combination with time delay can bring about both sustained oscillations and adaptive behaviour in cellular networks. Here, we study which design features of systems with delayed negative feedback shape characteristic response patterns with special emphasis on the role of time delay. To this end, we analyse generic two-dimensional delay differential equations describing the dynamics of biochemical signal-response networks. We investigate the influence of several design features on the stability of the model equilibrium, i.e., presence of auto-inhibition and/or mass conservation and the kind and/or strength of the delayed negative feedback. We show that auto-inhibition and mass conservation have a stabilizing effect, whereas increasing abruptness and decreasing feedback threshold have a de-stabilizing effect on the model equilibrium. Moreover, applying our theoretical analysis to the mammalian p53 system we show that an auto-inhibitory feedback can decouple period and amplitude of an oscillatory response, whereas the delayed feedback can not. Our theoretical framework provides insight into how time delay and design features of biochemical networks act together to elicit specific characteristic response patterns. Such insight is useful for constructing synthetic networks and controlling their behaviour in response to external stimulation.

Persistent nuclear wave packet oscillation coexistent with incoherent vibrational population at excited F centers in KI.

PubMed

Koyama, Takeshi; Takahashi, Youtarou; Nakajima, Makoto; Suemoto, Tohru

2006-06-14

We investigated nuclear wave packet dynamics in the excited state of KI F centers at 10 K using time-resolved luminescence spectroscopy. Observed transient spectrum is divided into oscillatory and non-oscillatory components. The former lasts over 11 ps without appreciable damping and is attributed to the oscillation of the wave packet consisting mainly of the A(1g) mode around the center. The non-oscillatory part rises quickly after photo-excitation exhibiting a cooling of incoherent vibrational population. This behavior suggests the fast energy dissipation due to the dephasing of the bulk phonon modes.

Dynamic behavior of the bray-liebhafsky oscillatory reaction controlled by sulfuric acid and temperature

NASA Astrophysics Data System (ADS)

Pejić, N.; Vujković, M.; Maksimović, J.; Ivanović, A.; Anić, S.; Čupić, Ž.; Kolar-Anić, Lj.

2011-12-01

The non-periodic, periodic and chaotic regimes in the Bray-Liebhafsky (BL) oscillatory reaction observed in a continuously fed well stirred tank reactor (CSTR) under isothermal conditions at various inflow concentrations of the sulfuric acid were experimentally studied. In each series (at any fixed temperature), termination of oscillatory behavior via saddle loop infinite period bifurcation (SNIPER) as well as some kind of the Andronov-Hopf bifurcation is presented. In addition, it was found that an increase of temperature, in different series of experiments resulted in the shift of bifurcation point towards higher values of sulfuric acid concentration.

Adaptive hybrid simulations for multiscale stochastic reaction networks

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

Hepp, Benjamin; Gupta, Ankit; Khammash, Mustafa

2015-01-21

The probability distribution describing the state of a Stochastic Reaction Network (SRN) evolves according to the Chemical Master Equation (CME). It is common to estimate its solution using Monte Carlo methods such as the Stochastic Simulation Algorithm (SSA). In many cases, these simulations can take an impractical amount of computational time. Therefore, many methods have been developed that approximate sample paths of the underlying stochastic process and estimate the solution of the CME. A prominent class of these methods include hybrid methods that partition the set of species and the set of reactions into discrete and continuous subsets. Such amore » partition separates the dynamics into a discrete and a continuous part. Simulating such a stochastic process can be computationally much easier than simulating the exact discrete stochastic process with SSA. Moreover, the quasi-stationary assumption to approximate the dynamics of fast subnetworks can be applied for certain classes of networks. However, as the dynamics of a SRN evolves, these partitions may have to be adapted during the simulation. We develop a hybrid method that approximates the solution of a CME by automatically partitioning the reactions and species sets into discrete and continuous components and applying the quasi-stationary assumption on identifiable fast subnetworks. Our method does not require any user intervention and it adapts to exploit the changing timescale separation between reactions and/or changing magnitudes of copy-numbers of constituent species. We demonstrate the efficiency of the proposed method by considering examples from systems biology and showing that very good approximations to the exact probability distributions can be achieved in significantly less computational time. This is especially the case for systems with oscillatory dynamics, where the system dynamics change considerably throughout the time-period of interest.« less

Adaptive hybrid simulations for multiscale stochastic reaction networks.

PubMed

Hepp, Benjamin; Gupta, Ankit; Khammash, Mustafa

2015-01-21

The probability distribution describing the state of a Stochastic Reaction Network (SRN) evolves according to the Chemical Master Equation (CME). It is common to estimate its solution using Monte Carlo methods such as the Stochastic Simulation Algorithm (SSA). In many cases, these simulations can take an impractical amount of computational time. Therefore, many methods have been developed that approximate sample paths of the underlying stochastic process and estimate the solution of the CME. A prominent class of these methods include hybrid methods that partition the set of species and the set of reactions into discrete and continuous subsets. Such a partition separates the dynamics into a discrete and a continuous part. Simulating such a stochastic process can be computationally much easier than simulating the exact discrete stochastic process with SSA. Moreover, the quasi-stationary assumption to approximate the dynamics of fast subnetworks can be applied for certain classes of networks. However, as the dynamics of a SRN evolves, these partitions may have to be adapted during the simulation. We develop a hybrid method that approximates the solution of a CME by automatically partitioning the reactions and species sets into discrete and continuous components and applying the quasi-stationary assumption on identifiable fast subnetworks. Our method does not require any user intervention and it adapts to exploit the changing timescale separation between reactions and/or changing magnitudes of copy-numbers of constituent species. We demonstrate the efficiency of the proposed method by considering examples from systems biology and showing that very good approximations to the exact probability distributions can be achieved in significantly less computational time. This is especially the case for systems with oscillatory dynamics, where the system dynamics change considerably throughout the time-period of interest.

The role of propriospinal neuronal network in transmitting the alternating muscular activities of flexor and extensor in parkinsonian tremor.

PubMed

Hao, M; He, X; Lan, N

2012-01-01

It has been shown that normal cyclic movement of human arm and resting limb tremor in Parkinson's disease (PD) are associated with the oscillatory neuronal activities in different cerebral networks, which are transmitted to the antagonistic muscles via the same spinal pathway. There are mono-synaptic and multi-synaptic corticospinal pathways for conveying motor commands. This study investigates the plausible role of propriospinal neuronal (PN) network in the C3-C4 levels in multi-synaptic transmission of cortical commands for oscillatory movements. A PN network model is constructed based on known neurophysiological connections, and is hypothesized to achieve the conversion of cortical oscillations into alternating antagonistic muscle bursts. Simulations performed with a virtual arm (VA) model indicate that without the PN network, the alternating bursts of antagonistic muscle EMG could not be reliably generated, whereas with the PN network, the alternating pattern of bursts were naturally displayed in the three pairs of antagonist muscles. Thus, it is suggested that oscillations in the primary motor cortex (M1) of single and double tremor frequencies are processed at the PN network to compute the alternating burst pattern in the flexor and extensor muscles.

EEG Oscillatory States: Universality, Uniqueness and Specificity across Healthy-Normal, Altered and Pathological Brain Conditions

PubMed Central

Fingelkurts, Alexander A.; Fingelkurts, Andrew A.

2014-01-01

For the first time the dynamic repertoires and oscillatory types of local EEG states in 13 diverse conditions (examined over 9 studies) that covered healthy-normal, altered and pathological brain states were quantified within the same methodological and conceptual framework. EEG oscillatory states were assessed by the probability-classification analysis of short-term EEG spectral patterns. The results demonstrated that brain activity consists of a limited repertoire of local EEG states in any of the examined conditions. The size of the state repertoires was associated with changes in cognition and vigilance or neuropsychopathologic conditions. Additionally universal, optional and unique EEG states across 13 diverse conditions were observed. It was demonstrated also that EEG oscillations which constituted EEG states were characteristic for different groups of conditions in accordance to oscillations’ functional significance. The results suggested that (a) there is a limit in the number of local states available to the cortex and many ways in which these local states can rearrange themselves and still produce the same global state and (b) EEG individuality is determined by varying proportions of universal, optional and unique oscillatory states. The results enriched our understanding about dynamic microstructure of EEG-signal. PMID:24505292

Detailed Characterization of Local Field Potential Oscillations and Their Relationship to Spike Timing in the Antennal Lobe of the Moth Manduca sexta

PubMed Central

Daly, Kevin C.; Galán, Roberto F.; Peters, Oakland J.; Staudacher, Erich M.

2011-01-01

The transient oscillatory model of odor identity encoding seeks to explain how odorants with spatially overlapped patterns of input into primary olfactory networks can be discriminated. This model provides several testable predictions about the distributed nature of network oscillations and how they control spike timing. To test these predictions, 16 channel electrode arrays were placed within the antennal lobe (AL) of the moth Manduca sexta. Unitary spiking and multi site local field potential (LFP) recordings were made during spontaneous activity and in response to repeated presentations of an odor panel. We quantified oscillatory frequency, cross correlations between LFP recording sites, and spike–LFP phase relationships. We show that odor-driven AL oscillations in Manduca are frequency modulating (FM) from ∼100 to 30 Hz; this was odorant and stimulus duration dependent. FM oscillatory responses were localized to one or two recording sites suggesting a localized (perhaps glomerular) not distributed source. LFP cross correlations further demonstrated that only a small (r < 0.05) distributed and oscillatory component was present. Cross spectral density analysis demonstrated the frequency of these weakly distributed oscillations was state dependent (spontaneous activity = 25–55 Hz; odor-driven = 55–85 Hz). Surprisingly, vector strength analysis indicated that unitary phase locking of spikes to the LFP was strongest during spontaneous activity and dropped significantly during responses. Application of bicuculline, a GABAA receptor antagonist, significantly lowered the frequency content of odor-driven distributed oscillatory activity. Bicuculline significantly reduced spike phase locking generally, but the ubiquitous pattern of increased phase locking during spontaneous activity persisted. Collectively, these results indicate that oscillations perform poorly as a stimulus-mediated spike synchronizing mechanism for Manduca and hence are incongruent with the transient oscillatory model. PMID:22046161

A ‘reader’ unit of the chemical computer

PubMed Central

Smelov, Pavel S.

2018-01-01

We suggest the main principals and functional units of the parallel chemical computer, namely, (i) a generator (which is a network of coupled oscillators) of oscillatory dynamic modes, (ii) a unit which is able to recognize these modes (a ‘reader’) and (iii) a decision-making unit, which analyses the current mode, compares it with the external signal and sends a command to the mode generator to switch it to the other dynamical regime. Three main methods of the functioning of the reader unit are suggested and tested computationally: (a) the polychronization method, which explores the differences between the phases of the generator oscillators; (b) the amplitude method which detects clusters of the generator and (c) the resonance method which is based on the resonances between the frequencies of the generator modes and the internal frequencies of the damped oscillations of the reader cells. Pro and contra of these methods have been analysed. PMID:29410852

Global dynamics of selective attention and its lapses in primary auditory cortex.

PubMed

Lakatos, Peter; Barczak, Annamaria; Neymotin, Samuel A; McGinnis, Tammy; Ross, Deborah; Javitt, Daniel C; O'Connell, Monica Noelle

2016-12-01

Previous research demonstrated that while selectively attending to relevant aspects of the external world, the brain extracts pertinent information by aligning its neuronal oscillations to key time points of stimuli or their sampling by sensory organs. This alignment mechanism is termed oscillatory entrainment. We investigated the global, long-timescale dynamics of this mechanism in the primary auditory cortex of nonhuman primates, and hypothesized that lapses of entrainment would correspond to lapses of attention. By examining electrophysiological and behavioral measures, we observed that besides the lack of entrainment by external stimuli, attentional lapses were also characterized by high-amplitude alpha oscillations, with alpha frequency structuring of neuronal ensemble and single-unit operations. Entrainment and alpha-oscillation-dominated periods were strongly anticorrelated and fluctuated rhythmically at an ultra-slow rate. Our results indicate that these two distinct brain states represent externally versus internally oriented computational resources engaged by large-scale task-positive and task-negative functional networks.

How noise affects the synchronization properties of recurrent networks of inhibitory neurons.

PubMed

Brunel, Nicolas; Hansel, David

2006-05-01

GABAergic interneurons play a major role in the emergence of various types of synchronous oscillatory patterns of activity in the central nervous system. Motivated by these experimental facts, modeling studies have investigated mechanisms for the emergence of coherent activity in networks of inhibitory neurons. However, most of these studies have focused either when the noise in the network is absent or weak or in the opposite situation when it is strong. Hence, a full picture of how noise affects the dynamics of such systems is still lacking. The aim of this letter is to provide a more comprehensive understanding of the mechanisms by which the asynchronous states in large, fully connected networks of inhibitory neurons are destabilized as a function of the noise level. Three types of single neuron models are considered: the leaky integrate-and-fire (LIF) model, the exponential integrate-and-fire (EIF), model and conductance-based models involving sodium and potassium Hodgkin-Huxley (HH) currents. We show that in all models, the instabilities of the asynchronous state can be classified in two classes. The first one consists of clustering instabilities, which exist in a restricted range of noise. These instabilities lead to synchronous patterns in which the population of neurons is broken into clusters of synchronously firing neurons. The irregularity of the firing patterns of the neurons is weak. The second class of instabilities, termed oscillatory firing rate instabilities, exists at any value of noise. They lead to cluster state at low noise. As the noise is increased, the instability occurs at larger coupling, and the pattern of firing that emerges becomes more irregular. In the regime of high noise and strong coupling, these instabilities lead to stochastic oscillations in which neurons fire in an approximately Poisson way with a common instantaneous probability of firing that oscillates in time.

Source-reconstruction of the sensorimotor network from resting-state macaque electrocorticography.

PubMed

Hindriks, R; Micheli, C; Bosman, C A; Oostenveld, R; Lewis, C; Mantini, D; Fries, P; Deco, G

2018-06-07

The discovery of hemodynamic (BOLD-fMRI) resting-state networks (RSNs) has brought about a fundamental shift in our thinking about the role of intrinsic brain activity. The electrophysiological underpinnings of RSNs remain largely elusive and it has been shown only recently that electric cortical rhythms are organized into the same RSNs as hemodynamic signals. Most electrophysiological studies into RSNs use magnetoencephalography (MEG) or scalp electroencephalography (EEG), which limits the spatial resolution with which electrophysiological RSNs can be observed. Due to their close proximity to the cortical surface, electrocorticographic (ECoG) recordings can potentially provide a more detailed picture of the functional organization of resting-state cortical rhythms, albeit at the expense of spatial coverage. In this study we propose using source-space spatial independent component analysis (spatial ICA) for identifying generators of resting-state cortical rhythms as recorded with ECoG and for reconstructing their functional connectivity. Network structure is assessed by two kinds of connectivity measures: instantaneous correlations between band-limited amplitude envelopes and oscillatory phase-locking. By simulating rhythmic cortical generators, we find that the reconstruction of oscillatory phase-locking is more challenging than that of amplitude correlations, particularly for low signal-to-noise levels. Specifically, phase-lags can both be over- and underestimated, which troubles the interpretation of lag-based connectivity measures. We illustrate the methodology on somatosensory beta rhythms recorded from a macaque monkey using ECoG. The methodology decomposes the resting-state sensorimotor network into three cortical generators, distributed across primary somatosensory and primary and higher-order motor areas. The generators display significant and reproducible amplitude correlations and phase-locking values with non-zero lags. Our findings illustrate the level of spatial detail attainable with source-projected ECoG and motivates wider use of the methodology for studying resting-state as well as event-related cortical dynamics in macaque and human. Copyright © 2018. Published by Elsevier Inc.

Spatiotemporal dynamics of oscillatory cellular patterns in three-dimensional directional solidification.

PubMed

Bergeon, N; Tourret, D; Chen, L; Debierre, J-M; Guérin, R; Ramirez, A; Billia, B; Karma, A; Trivedi, R

2013-05-31

We report results of directional solidification experiments conducted on board the International Space Station and quantitative phase-field modeling of those experiments. The experiments image for the first time in situ the spatially extended dynamics of three-dimensional cellular array patterns formed under microgravity conditions where fluid flow is suppressed. Experiments and phase-field simulations reveal the existence of oscillatory breathing modes with time periods of several 10's of minutes. Oscillating cells are usually noncoherent due to array disorder, with the exception of small areas where the array structure is regular and stable.

An integrative model of auditory phantom perception: tinnitus as a unified percept of interacting separable subnetworks.

PubMed

De Ridder, Dirk; Vanneste, Sven; Weisz, Nathan; Londero, Alain; Schlee, Winnie; Elgoyhen, Ana Belen; Langguth, Berthold

2014-07-01

Tinnitus is a considered to be an auditory phantom phenomenon, a persistent conscious percept of a salient memory trace, externally attributed, in the absence of a sound source. It is perceived as a phenomenological unified coherent percept, binding multiple separable clinical characteristics, such as its loudness, the sidedness, the type (pure tone, noise), the associated distress and so on. A theoretical pathophysiological framework capable of explaining all these aspects in one model is highly needed. The model must incorporate both the deafferentation based neurophysiological models and the dysfunctional noise canceling model, and propose a 'tinnitus core' subnetwork. The tinnitus core can be defined as the minimal set of brain areas that needs to be jointly activated (=subnetwork) for tinnitus to be consciously perceived, devoid of its affective components. The brain areas involved in the other separable characteristics of tinnitus can be retrieved by studies on spontaneous resting state magnetic and electrical activity in people with tinnitus, evaluated for the specific aspect investigated and controlled for other factors. By combining these functional imaging studies with neuromodulation techniques some of the correlations are turned into causal relationships. Thereof, a heuristic pathophysiological framework is constructed, integrating the tinnitus perceptual core with the other tinnitus related aspects. This phenomenological unified percept of tinnitus can be considered an emergent property of multiple, parallel, dynamically changing and partially overlapping subnetworks, each with a specific spontaneous oscillatory pattern and functional connectivity signature. Communication between these different subnetworks is proposed to occur at hubs, brain areas that are involved in multiple subnetworks simultaneously. These hubs can take part in each separable subnetwork at different frequencies. Communication between the subnetworks is proposed to occur at discrete oscillatory frequencies. As such, the brain uses multiple nonspecific networks in parallel, each with their own oscillatory signature, that adapt to the context to construct a unified percept possibly by synchronized activation integrated at hubs at discrete oscillatory frequencies. Copyright © 2013 Elsevier Ltd. All rights reserved.

Oscillatory signatures of crossmodal congruence effects: An EEG investigation employing a visuotactile pattern matching paradigm.

PubMed

Göschl, Florian; Friese, Uwe; Daume, Jonathan; König, Peter; Engel, Andreas K

2015-08-01

Coherent percepts emerge from the accurate combination of inputs from the different sensory systems. There is an ongoing debate about the neurophysiological mechanisms of crossmodal interactions in the brain, and it has been proposed that transient synchronization of neurons might be of central importance. Oscillatory activity in lower frequency ranges (<30Hz) has been implicated in mediating long-range communication as typically studied in multisensory research. In the current study, we recorded high-density electroencephalograms while human participants were engaged in a visuotactile pattern matching paradigm and analyzed oscillatory power in the theta- (4-7Hz), alpha- (8-13Hz) and beta-bands (13-30Hz). Employing the same physical stimuli, separate tasks of the experiment either required the detection of predefined targets in visual and tactile modalities or the explicit evaluation of crossmodal stimulus congruence. Analysis of the behavioral data showed benefits for congruent visuotactile stimulus combinations. Differences in oscillatory dynamics related to crossmodal congruence within the two tasks were observed in the beta-band for crossmodal target detection, as well as in the theta-band for congruence evaluation. Contrasting ongoing activity preceding visuotactile stimulation between the two tasks revealed differences in the alpha- and beta-bands. Source reconstruction of between-task differences showed prominent involvement of premotor cortex, supplementary motor area, somatosensory association cortex and the supramarginal gyrus. These areas not only exhibited more involvement in the pre-stimulus interval for target detection compared to congruence evaluation, but were also crucially involved in post-stimulus differences related to crossmodal stimulus congruence within the detection task. These results add to the increasing evidence that low frequency oscillations are functionally relevant for integration in distributed brain networks, as demonstrated for crossmodal interactions in visuotactile pattern matching in the current study. Copyright © 2015 Elsevier Inc. All rights reserved.

Analysis of Wind Tunnel Longitudinal Static and Oscillatory Data of the F-16XL Aircraft

NASA Technical Reports Server (NTRS)

Klein, Vladislav; Murphy, Patrick C.; Curry, Timothy J.; Brandon, Jay M.

1997-01-01

Static and oscillatory wind tunnel data are presented for a 10-percent-scale model of an F-16XL aircraft. Static data include the effect of angle of attack, sideslip angle, and control surface deflections on aerodynamic coefficients. Dynamic data from small-amplitude oscillatory tests are presented at nominal values of angle of attack between 20 and 60 degrees. Model oscillations were performed at five frequencies from 0.6 to 2.9 Hz and one amplitude of 5 degrees. A simple harmonic analysis of the oscillatory data provided Fourier coefficients associated with the in-phase and out-of-phase components of the aerodynamic coefficients. A strong dependence of the oscillatory data on frequency led to the development of models with unsteady terms in the form of indicial functions. Two models expressing the variation of the in-phase and out-of-phase components with angle of attack and frequency were proposed and their parameters estimated from measured data.

A neurocomputational model of figure-ground discrimination and target tracking.

PubMed

Sun, H; Liu, L; Guo, A

1999-01-01

A neurocomputational model is presented for figureground discrimination and target tracking. In the model, the elementary motion detectors of the correlation type, the computational modules of saccadic and smooth pursuit eye movement, an oscillatory neural-network motion perception module and a selective attention module are involved. It is shown that through the oscillatory amplitude and frequency encoding, and selective synchronization of phase oscillators, the figure and the ground can be successfully discriminated from each other. The receptive fields developed by hidden units of the networks were surprisingly similar to the actual receptive fields and columnar organization found in the primate visual cortex. It is suggested that equivalent mechanisms may exist in the primate visual cortex to discriminate figure-ground in both temporal and spatial domains.

The relative phases of basal ganglia activities dynamically shape effective connectivity in Parkinson's disease.

PubMed

Cagnan, Hayriye; Duff, Eugene Paul; Brown, Peter

2015-06-01

Optimal phase alignment between oscillatory neural circuits is hypothesized to optimize information flow and enhance system performance. This theory is known as communication-through-coherence. The basal ganglia motor circuit exhibits exaggerated oscillatory and coherent activity patterns in Parkinson's disease. Such activity patterns are linked to compromised motor system performance as evinced by bradykinesia, rigidity and tremor, suggesting that network function might actually deteriorate once a certain level of net synchrony is exceeded in the motor circuit. Here, we characterize the processes underscoring excessive synchronization and its termination. To this end, we analysed local field potential recordings from the subthalamic nucleus and globus pallidus of five patients with Parkinson's disease (four male and one female, aged 37-64 years). We observed that certain phase alignments between subthalamic nucleus and globus pallidus amplified local neural synchrony in the beta frequency band while others either suppressed it or did not induce any significant change with respect to surrogates. The increase in local beta synchrony directly correlated with how long the two nuclei locked to beta-amplifying phase alignments. Crucially, administration of the dopamine prodrug, levodopa, reduced the frequency and duration of periods during which subthalamic and pallidal populations were phase-locked to beta-amplifying alignments. Conversely ON dopamine, the total duration over which subthalamic and pallidal populations were aligned to phases that left beta-amplitude unchanged with respect to surrogates increased. Thus dopaminergic input shifted circuit dynamics from persistent periods of locking to amplifying phase alignments, associated with compromised motoric function, to more dynamic phase alignment and improved motoric function. This effect of dopamine on local circuit resonance suggests means by which novel electrical interventions might prevent resonance-related pathological circuit interactions. © The Author (2015). Published by Oxford University Press on behalf of the Guarantors of Brain.

Theoretical analysis of oscillatory terms in lattice heat-current time correlation functions and their contributions to thermal conductivity

NASA Astrophysics Data System (ADS)

Pereverzev, Andrey; Sewell, Tommy

2018-03-01

Lattice heat-current time correlation functions for insulators and semiconductors obtained using molecular dynamics (MD) simulations exhibit features of both pure exponential decay and oscillatory-exponential decay. For some materials the oscillatory terms contribute significantly to the lattice heat conductivity calculated from the correlation functions. However, the origin of the oscillatory terms is not well understood, and their contribution to the heat conductivity is accounted for by fitting them to empirical functions. Here, a translationally invariant expression for the heat current in terms of creation and annihilation operators is derived. By using this full phonon-picture definition of the heat current and applying the relaxation-time approximation we explain, at least in part, the origin of the oscillatory terms in the lattice heat-current correlation function. We discuss the relationship between the crystal Hamiltonian and the magnitude of the oscillatory terms. A solvable one-dimensional model is used to illustrate the potential importance of terms that are omitted in the commonly used phonon-picture expression for the heat current. While the derivations are fully quantum mechanical, classical-limit expressions are provided that enable direct contact with classical quantities obtainable from MD.

Multiple Independent Oscillatory Networks in the Degenerating Retina

PubMed Central

Euler, Thomas; Schubert, Timm

2015-01-01

During neuronal degenerative diseases, microcircuits undergo severe structural alterations, leading to remodeling of synaptic connectivity. This can be particularly well observed in the retina, where photoreceptor degeneration triggers rewiring of connections in the retina’s first synaptic layer (e.g., Strettoi et al., 2003; Haq et al., 2014), while the synaptic organization of inner retinal circuits appears to be little affected (O’Brien et al., 2014; Figures 1A,B). Remodeling of (outer) retinal circuits and diminishing light-driven activity due to the loss of functional photoreceptors lead to spontaneous activity that can be observed at different retinal levels (Figure 1C), including the retinal ganglion cells, which display rhythmic spiking activity in the degenerative retina (Margolis et al., 2008; Stasheff, 2008; Menzler and Zeck, 2011; Stasheff et al., 2011). Two networks have been suggested to drive the oscillatory activity in the degenerating retina: a network of remnant cone photoreceptors, rod bipolar cells (RBCs) and horizontal cells in the outer retina (Haq et al., 2014), and the AII amacrine cell-cone bipolar cell network in the inner retina (Borowska et al., 2011). Notably, spontaneous rhythmic activity in the inner retinal network can be triggered in the absence of synaptic remodeling in the outer retina, for example, in the healthy retina after photo-bleaching (Menzler et al., 2014). In addition, the two networks show remarkable differences in their dominant oscillation frequency range as well as in the types and numbers of involved cells (Menzler and Zeck, 2011; Haq et al., 2014). Taken together this suggests that the two networks are self-sustained and can be active independently from each other. However, it is not known if and how they modulate each other. In this mini review, we will discuss: (i) commonalities and differences between these two oscillatory networks as well as possible interaction pathways; (ii) how multiple self-sustained networks may hamper visual restoration strategies employing, for example, microelectronic implants, optogenetics or stem cells, and briefly; and (iii) how the finding of diverse (independent) networks in the degenerative retina may relate to other parts of the neurodegenerative central nervous system. PMID:26617491

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.

Using dynamics to identify network topology

NASA Astrophysics Data System (ADS)

Rahi, Sahand Jamal; Tsaneva-Atanasova, Krasimira

2013-03-01

To elucidate the topology of a signaling pathway, generally, experimentalists manipulate a cell's molecular architecture, for example, by knocking out genes. Molecular biology techniques, though, are not only invasive and labor-intensive, they have also often been eluded by the complexity of biological networks, e.g., in the case of the gonadotropin-releasing hormone (GnRH) system. Inspired by the rapidly accumulating examples of oscillatory signaling in biology, we explored whether such dynamical stimuli can be used to discriminate different topologies of adaptive pathways, which are ubiquitous in biology. Responses to static inputs are nearly indistinguishable given strong measurement noise. Sine function stimuli, widely used in physics, are difficult to implement in standard microfluidics or optogenetics set-ups and do not simplify the mathematical analysis because of the nonlinearities in these systems. With periodic on-off pulses, which can be easily produced, however, simple adaptive circuit motifs and detailed models from the literature robustly reveal distinct output characteristics, which manifest in how the period of maximal output varies with pulse width. Our calculations provide a framework for using existing methods to discover difficult to reveal mechanisms. Furthermore, our results constrain the possible design principles of the presumed frequency decoders in biological systems where pulsatile signaling has recently been discovered.

Key role of coupling, delay, and noise in resting brain fluctuations

PubMed Central

Deco, Gustavo; Jirsa, Viktor; McIntosh, A. R.; Sporns, Olaf; Kötter, Rolf

2009-01-01

A growing body of neuroimaging research has documented that, in the absence of an explicit task, the brain shows temporally coherent activity. This so-called “resting state” activity or, more explicitly, the default-mode network, has been associated with daydreaming, free association, stream of consciousness, or inner rehearsal in humans, but similar patterns have also been found under anesthesia and in monkeys. Spatiotemporal activity patterns in the default-mode network are both complex and consistent, which raises the question whether they are the expression of an interesting cognitive architecture or the consequence of intrinsic network constraints. In numerical simulation, we studied the dynamics of a simplified cortical network using 38 noise-driven (Wilson–Cowan) oscillators, which in isolation remain just below their oscillatory threshold. Time delay coupling based on lengths and strengths of primate corticocortical pathways leads to the emergence of 2 sets of 40-Hz oscillators. The sets showed synchronization that was anticorrelated at <0.1 Hz across the sets in line with a wide range of recent experimental observations. Systematic variation of conduction velocity, coupling strength, and noise level indicate a high sensitivity of emerging synchrony as well as simulated blood flow blood oxygen level-dependent (BOLD) on the underlying parameter values. Optimal sensitivity was observed around conduction velocities of 1–2 m/s, with very weak coupling between oscillators. An additional finding was that the optimal noise level had a characteristic scale, indicating the presence of stochastic resonance, which allows the network dynamics to respond with high sensitivity to changes in diffuse feedback activity. PMID:19497858

Interplay between non-NMDA and NMDA receptor activation during oscillatory wave propagation: Analyses of caffeine-induced oscillations in the visual cortex of rats.

PubMed

Yoshimura, Hiroshi; Sugai, Tokio; Kato, Nobuo; Tominaga, Takashi; Tominaga, Yoko; Hasegawa, Takahiro; Yao, Chenjuan; Akamatsu, Tetsuya

2016-07-01

Generation and propagation of oscillatory activities in cortical networks are important features of the brain. However, many issues related to oscillatory phenomena are unclear. We previously reported neocortical oscillation following caffeine treatment of rat brain slices. Input to the primary visual cortex (Oc1) generates N-methyl-d-aspartate (NMDA) receptor-dependent oscillations, and we proposed that the oscillatory signals originate in the secondary visual cortex (Oc2). Because non-NMDA and NMDA receptors cooperate in synaptic transmission, non-NMDA receptors may also play an important role in oscillatory activities. Here we investigated how non-NMDA receptor activities contribute to NMDA receptor-dependent oscillations by using optical recording methods. After induction of stable oscillations with caffeine application, blockade of NMDA receptors abolished the late stable oscillatory phase, but elicited 'hidden' non-NMDA receptor-dependent oscillation during the early depolarizing phase. An interesting finding is that the origin of the non-NMDA receptor-dependent oscillation moved from the Oc1, during the early phase, toward the origin of the NMDA receptor-dependent oscillation that is fixed in the Oc2. In addition, the frequency of the non-NMDA receptor-dependent oscillation was higher than that of the NMDA receptor-dependent oscillation. Thus, in one course of spatiotemporal oscillatory activities, the relative balance in receptor activities between non-NMDA and NMDA receptors gradually changes, and this may be due to the different kinetics of the two receptor types. These results suggest that interplay between the two receptor types in the areas of Oc1 and Oc2 may play an important role in oscillatory signal communication. Copyright © 2016 Elsevier Ltd. All rights reserved.

EEG neural oscillatory dynamics reveal semantic and response conflict at difference levels of conflict awareness

PubMed Central

Jiang, Jun; Zhang, Qinglin; Van Gaal, Simon

2015-01-01

Although previous work has shown that conflict can be detected in the absence of awareness, it is unknown how different sources of conflict (i.e., semantic, response) are processed in the human brain and whether these processes are differently modulated by conflict awareness. To explore this issue, we extracted oscillatory power dynamics from electroencephalographic (EEG) data recorded while human participants performed a modified version of the Stroop task. Crucially, in this task conflict awareness was manipulated by masking a conflict-inducing color word preceding a color patch target. We isolated semantic from response conflict by introducing four color words/patches, of which two were matched to the same response. We observed that both semantic as well as response conflict were associated with mid-frontal theta-band and parietal alpha-band power modulations, irrespective of the level of conflict awareness (high vs. low), although awareness of conflict increased these conflict-related power dynamics. These results show that both semantic and response conflict can be processed in the human brain and suggest that the neural oscillatory mechanisms in EEG reflect mainly “domain general” conflict processing mechanisms, instead of conflict source specific effects. PMID:26169473

EEG neural oscillatory dynamics reveal semantic and response conflict at difference levels of conflict awareness.

PubMed

Jiang, Jun; Zhang, Qinglin; Van Gaal, Simon

2015-07-14

Although previous work has shown that conflict can be detected in the absence of awareness, it is unknown how different sources of conflict (i.e., semantic, response) are processed in the human brain and whether these processes are differently modulated by conflict awareness. To explore this issue, we extracted oscillatory power dynamics from electroencephalographic (EEG) data recorded while human participants performed a modified version of the Stroop task. Crucially, in this task conflict awareness was manipulated by masking a conflict-inducing color word preceding a color patch target. We isolated semantic from response conflict by introducing four color words/patches, of which two were matched to the same response. We observed that both semantic as well as response conflict were associated with mid-frontal theta-band and parietal alpha-band power modulations, irrespective of the level of conflict awareness (high vs. low), although awareness of conflict increased these conflict-related power dynamics. These results show that both semantic and response conflict can be processed in the human brain and suggest that the neural oscillatory mechanisms in EEG reflect mainly "domain general" conflict processing mechanisms, instead of conflict source specific effects.

Oscillatory dynamics of investment and capacity utilization

NASA Astrophysics Data System (ADS)

Greenblatt, R. E.

2017-01-01

Capitalist economic systems display a wide variety of oscillatory phenomena whose underlying causes are often not well understood. In this paper, I consider a very simple model of the reciprocal interaction between investment, capacity utilization, and their time derivatives. The model, which gives rise periodic oscillations, predicts qualitatively the phase relations between these variables. These predictions are observed to be consistent in a statistical sense with econometric data from the US economy.

Control of Cavity Resonance Using Oscillatory Blowing

NASA Technical Reports Server (NTRS)

Scarfe, Alison Lamp; Chokani, Ndaona

2000-01-01

The near-zero net mass oscillatory blowing control of a subsonic cavity flow has been experimentally investigated. An actuator was designed and fabricated to provide both steady and oscillatory blowing over a range of blowing amplitudes and forcing frequencies. The blowing was applied just upstream of the cavity front Wall through interchangeable plate configurations These configurations enabled the effects of hole size, hole shape, and blowing angle to be examined. A significant finding is that in terms of the blowing amplitude, the near zero net mass oscillatory blowing is much more effective than steady blowing; momentum coefficients Lip two orders of magnitude smaller than those required for steady blowing are sufficient to accomplish the same control of cavity resonance. The detailed measurements obtained in the experiment include fluctuating pressure data within the cavity wall, and hot-wire measurements of the cavity shear layer. Spectral and wavelet analysis techniques are applied to understand the dynamics and mechanisms of the cavity flow with control. The oscillatory blowing, is effective in enhancing the mixing in the cavity shear layer and thus modifying the feedback loop associated with the cavity resonance. The nonlinear interactions in the cavity flow are no longer driven by the resonant cavity modes but by the forcing associated with the oscillatory blowing. The oscillatory blowing does not suppress the mode switching behavior of the cavity flow, but the amplitude modulation is reduced.

Parametric resonance in the early Universe—a fitting analysis

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

Figueroa, Daniel G.; Torrentí, Francisco, E-mail: daniel.figueroa@cern.ch, E-mail: f.torrenti@csic.es

Particle production via parametric resonance in the early Universe, is a non-perturbative, non-linear and out-of-equilibrium phenomenon. Although it is a well studied topic, whenever a new scenario exhibits parametric resonance, a full re-analysis is normally required. To avoid this tedious task, many works present often only a simplified linear treatment of the problem. In order to surpass this circumstance in the future, we provide a fitting analysis of parametric resonance through all its relevant stages: initial linear growth, non-linear evolution, and relaxation towards equilibrium. Using lattice simulations in an expanding grid in 3+1 dimensions, we parametrize the dynamics' outcome scanningmore » over the relevant ingredients: role of the oscillatory field, particle coupling strength, initial conditions, and background expansion rate. We emphasize the inaccuracy of the linear calculation of the decay time of the oscillatory field, and propose a more appropriate definition of this scale based on the subsequent non-linear dynamics. We provide simple fits to the relevant time scales and particle energy fractions at each stage. Our fits can be applied to post-inflationary preheating scenarios, where the oscillatory field is the inflaton, or to spectator-field scenarios, where the oscillatory field can be e.g. a curvaton, or the Standard Model Higgs.« less

Phenotypic Plasticity and Cell Fate Decisions in Cancer: Insights from Dynamical Systems Theory.

PubMed

Jia, Dongya; Jolly, Mohit Kumar; Kulkarni, Prakash; Levine, Herbert

2017-06-22

Waddington's epigenetic landscape, a famous metaphor in developmental biology, depicts how a stem cell progresses from an undifferentiated phenotype to a differentiated one. The concept of "landscape" in the context of dynamical systems theory represents a high-dimensional space, in which each cell phenotype is considered as an "attractor" that is determined by interactions between multiple molecular players, and is buffered against environmental fluctuations. In addition, biological noise is thought to play an important role during these cell-fate decisions and in fact controls transitions between different phenotypes. Here, we discuss the phenotypic transitions in cancer from a dynamical systems perspective and invoke the concept of "cancer attractors"-hidden stable states of the underlying regulatory network that are not occupied by normal cells. Phenotypic transitions in cancer occur at varying levels depending on the context. Using epithelial-to-mesenchymal transition (EMT), cancer stem-like properties, metabolic reprogramming and the emergence of therapy resistance as examples, we illustrate how phenotypic plasticity in cancer cells enables them to acquire hybrid phenotypes (such as hybrid epithelial/mesenchymal and hybrid metabolic phenotypes) that tend to be more aggressive and notoriously resilient to therapies such as chemotherapy and androgen-deprivation therapy. Furthermore, we highlight multiple factors that may give rise to phenotypic plasticity in cancer cells, such as (a) multi-stability or oscillatory behaviors governed by underlying regulatory networks involved in cell-fate decisions in cancer cells, and (b) network rewiring due to conformational dynamics of intrinsically disordered proteins (IDPs) that are highly enriched in cancer cells. We conclude by discussing why a therapeutic approach that promotes "recanalization", i.e., the exit from "cancer attractors" and re-entry into "normal attractors", is more likely to succeed rather than a conventional approach that targets individual molecules/pathways.

The Dynamics of a Periodically Forced Cortical Microcircuit, With an Application to Schizophrenia

NASA Astrophysics Data System (ADS)

Vierling-Claassen, Dorea; Kopell, Nancy

2009-01-01

Synchronous neural activity in the brain in the gamma and beta frequency bands (50-70 Hz)is thought to be important for sensory processing and is altered in schizophrenia. In a previous study, gamma/beta click-train auditory stimuli were used to probe cortical oscillatory activity in control and schizophrenic subjects. We found that control subjects exhibited preferential 40 Hz responses to both 20 and 40 Hz stimulations, while schizophrenic subjects had enhanced 20 Hz responses to the same stimuli [D. Vierling-Claassen, P. Siekmeier, S. Stufflebeam, and N. Kopell, J. Neurophysiol., 99 (2008), p. 2656]. High-dimensional computational network models constructed previously, which were based on evidence of altered inhibition in schizophrenia, numerically generated the entrainment behaviors observed experimentally. However, questions regarding the dynamic origin of model behaviors remained. It was not clear that the 20 Hz response to 40 Hz drive in the schizophrenic network was robust to parameter changes, which would be necessary for the predicted mechanism to explain data from a heterogeneous subject population. In the schizophrenic network we observed 30 Hz drive responses with a frequency component below 30 Hz, for which no analogue appeared in experimental data, and wondered if these were dynamically distinct from the modeled 20 Hz response to 40 Hz drive. We also wished to explore the role of background noise in model behavior. To address these questions, we consider a system of two mutually coupled oscillators representative of neural cells, driven periodically in the gamma/beta frequency band. We show that there is a one-parameter family of discontinuous discrete maps, whose dynamics clarifies issues of robustness, classifies entrainment patterns, and provides insight into the role of excitatory noise.

Timing Embryo Segmentation: Dynamics and Regulatory Mechanisms of the Vertebrate Segmentation Clock

PubMed Central

Resende, Tatiana P.; Andrade, Raquel P.; Palmeirim, Isabel

2014-01-01

All vertebrate species present a segmented body, easily observed in the vertebrate column and its associated components, which provides a high degree of motility to the adult body and efficient protection of the internal organs. The sequential formation of the segmented precursors of the vertebral column during embryonic development, the somites, is governed by an oscillating genetic network, the somitogenesis molecular clock. Herein, we provide an overview of the molecular clock operating during somite formation and its underlying molecular regulatory mechanisms. Human congenital vertebral malformations have been associated with perturbations in these oscillatory mechanisms. Thus, a better comprehension of the molecular mechanisms regulating somite formation is required in order to fully understand the origin of human skeletal malformations. PMID:24895605

Efficient “Communication through Coherence” Requires Oscillations Structured to Minimize Interference between Signals

PubMed Central

Akam, Thomas E.; Kullmann, Dimitri M.

2012-01-01

The ‘communication through coherence’ (CTC) hypothesis proposes that selective communication among neural networks is achieved by coherence between firing rate oscillation in a sending region and gain modulation in a receiving region. Although this hypothesis has stimulated extensive work, it remains unclear whether the mechanism can in principle allow reliable and selective information transfer. Here we use a simple mathematical model to investigate how accurately coherent gain modulation can filter a population-coded target signal from task-irrelevant distracting inputs. We show that selective communication can indeed be achieved, although the structure of oscillatory activity in the target and distracting networks must satisfy certain previously unrecognized constraints. Firstly, the target input must be differentiated from distractors by the amplitude, phase or frequency of its oscillatory modulation. When distracting inputs oscillate incoherently in the same frequency band as the target, communication accuracy is severely degraded because of varying overlap between the firing rate oscillations of distracting inputs and the gain modulation in the receiving region. Secondly, the oscillatory modulation of the target input must be strong in order to achieve a high signal-to-noise ratio relative to stochastic spiking of individual neurons. Thus, whilst providing a quantitative demonstration of the power of coherent oscillatory gain modulation to flexibly control information flow, our results identify constraints imposed by the need to avoid interference between signals, and reveal a likely organizing principle for the structure of neural oscillations in the brain. PMID:23144603

Methods for parameter identification in oscillatory networks and application to cortical and thalamic 600 Hz activity.

PubMed

Leistritz, L; Suesse, T; Haueisen, J; Hilgenfeld, B; Witte, H

2006-01-01

Directed information transfer in the human brain occurs presumably by oscillations. As of yet, most approaches for the analysis of these oscillations are based on time-frequency or coherence analysis. The present work concerns the modeling of cortical 600 Hz oscillations, localized within the Brodmann Areas 3b and 1 after stimulation of the nervus medianus, by means of coupled differential equations. This approach leads to the so-called parameter identification problem, where based on a given data set, a set of unknown parameters of a system of ordinary differential equations is determined by special optimization procedures. Some suitable algorithms for this task are presented in this paper. Finally an oscillatory network model is optimally fitted to the data taken from ten volunteers.

Dynamic Imaging of Coherent Sources Reveals Different Network Connectivity Underlying the Generation and Perpetuation of Epileptic Seizures

PubMed Central

Anwar, Abdul Rauf; Deuschl, Günther; Stephani, Ulrich; Raethjen, Jan; Siniatchkin, Michael

2013-01-01

The concept of focal epilepsies includes a seizure origin in brain regions with hyper synchronous activity (epileptogenic zone and seizure onset zone) and a complex epileptic network of different brain areas involved in the generation, propagation, and modulation of seizures. The purpose of this work was to study functional and effective connectivity between regions involved in networks of epileptic seizures. The beginning and middle part of focal seizures from ictal surface EEG data were analyzed using dynamic imaging of coherent sources (DICS), an inverse solution in the frequency domain which describes neuronal networks and coherences of oscillatory brain activities. The information flow (effective connectivity) between coherent sources was investigated using the renormalized partial directed coherence (RPDC) method. In 8/11 patients, the first and second source of epileptic activity as found by DICS were concordant with the operative resection site; these patients became seizure free after epilepsy surgery. In the remaining 3 patients, the results of DICS / RPDC calculations and the resection site were discordant; these patients had a poorer post-operative outcome. The first sources as found by DICS were located predominantly in cortical structures; subsequent sources included some subcortical structures: thalamus, Nucl. Subthalamicus and cerebellum. DICS seems to be a powerful tool to define the seizure onset zone and the epileptic networks involved. Seizure generation seems to be related to the propagation of epileptic activity from the primary source in the seizure onset zone, and maintenance of seizures is attributed to the perpetuation of epileptic activity between nodes in the epileptic network. Despite of these promising results, this proof of principle study needs further confirmation prior to the use of the described methods in the clinical praxis. PMID:24194931

Shaping Neuronal Network Activity by Presynaptic Mechanisms

PubMed Central

Ashery, Uri

2015-01-01

Neuronal microcircuits generate oscillatory activity, which has been linked to basic functions such as sleep, learning and sensorimotor gating. Although synaptic release processes are well known for their ability to shape the interaction between neurons in microcircuits, most computational models do not simulate the synaptic transmission process directly and hence cannot explain how changes in synaptic parameters alter neuronal network activity. In this paper, we present a novel neuronal network model that incorporates presynaptic release mechanisms, such as vesicle pool dynamics and calcium-dependent release probability, to model the spontaneous activity of neuronal networks. The model, which is based on modified leaky integrate-and-fire neurons, generates spontaneous network activity patterns, which are similar to experimental data and robust under changes in the model's primary gain parameters such as excitatory postsynaptic potential and connectivity ratio. Furthermore, it reliably recreates experimental findings and provides mechanistic explanations for data obtained from microelectrode array recordings, such as network burst termination and the effects of pharmacological and genetic manipulations. The model demonstrates how elevated asynchronous release, but not spontaneous release, synchronizes neuronal network activity and reveals that asynchronous release enhances utilization of the recycling vesicle pool to induce the network effect. The model further predicts a positive correlation between vesicle priming at the single-neuron level and burst frequency at the network level; this prediction is supported by experimental findings. Thus, the model is utilized to reveal how synaptic release processes at the neuronal level govern activity patterns and synchronization at the network level. PMID:26372048

Dynamics of Mechanical Signal Transmission through Prestressed Stress Fibers

PubMed Central

Hwang, Yongyun; Barakat, Abdul I.

2012-01-01

Transmission of mechanical stimuli through the actin cytoskeleton has been proposed as a mechanism for rapid long-distance mechanotransduction in cells; however, a quantitative understanding of the dynamics of this transmission and the physical factors governing it remains lacking. Two key features of the actin cytoskeleton are its viscoelastic nature and the presence of prestress due to actomyosin motor activity. We develop a model of mechanical signal transmission through prestressed viscoelastic actin stress fibers that directly connect the cell surface to the nucleus. The analysis considers both temporally stationary and oscillatory mechanical signals and accounts for cytosolic drag on the stress fibers. To elucidate the physical parameters that govern mechanical signal transmission, we initially focus on the highly simplified case of a single stress fiber. The results demonstrate that the dynamics of mechanical signal transmission depend on whether the applied force leads to transverse or axial motion of the stress fiber. For transverse motion, mechanical signal transmission is dominated by prestress while fiber elasticity has a negligible effect. Conversely, signal transmission for axial motion is mediated uniquely by elasticity due to the absence of a prestress restoring force. Mechanical signal transmission is significantly delayed by stress fiber material viscosity, while cytosolic damping becomes important only for longer stress fibers. Only transverse motion yields the rapid and long-distance mechanical signal transmission dynamics observed experimentally. For simple networks of stress fibers, mechanical signals are transmitted rapidly to the nucleus when the fibers are oriented largely orthogonal to the applied force, whereas the presence of fibers parallel to the applied force slows down mechanical signal transmission significantly. The present results suggest that cytoskeletal prestress mediates rapid mechanical signal transmission and allows temporally oscillatory signals in the physiological frequency range to travel a long distance without significant decay due to material viscosity and/or cytosolic drag. PMID:22514731

Independent Oscillatory Patterns Determine Performance Fluctuations in Children with Attention Deficit/Hyperactivity Disorder

ERIC Educational Resources Information Center

Yordanova, Juliana; Albrecht, Bjorn; Uebel, Henrik; Kirov, Roumen; Banaschewski, Tobias; Rothenberger, Aribert; Kolev, Vasil

2011-01-01

The maintenance of stable goal-directed behaviour is a hallmark of conscious executive control in humans. Notably, both correct and error human actions may have a subconscious activation-based determination. One possible source of subconscious interference may be the default mode network that, in contrast to attentional network, manifests…

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.

Abnormal-induced theta activity supports early directed-attention network deficits in progressive MCI.

PubMed

Deiber, Marie-Pierre; Ibañez, Vicente; Missonnier, Pascal; Herrmann, François; Fazio-Costa, Lara; Gold, Gabriel; Giannakopoulos, Panteleimon

2009-09-01

The electroencephalography (EEG) theta frequency band reacts to memory and selective attention paradigms. Global theta oscillatory activity includes a posterior phase-locked component related to stimulus processing and a frontal-induced component modulated by directed attention. To investigate the presence of early deficits in the directed attention-related network in elderly individuals with mild cognitive impairment (MCI), time-frequency analysis at baseline was used to assess global and induced theta oscillatory activity (4-6Hz) during n-back working memory tasks in 29 individuals with MCI and 24 elderly controls (EC). At 1-year follow-up, 13 MCI patients were still stable and 16 had progressed. Baseline task performance was similar in stable and progressive MCI cases. Induced theta activity at baseline was significantly reduced in progressive MCI as compared to EC and stable MCI in all n-back tasks, which were similar in terms of directed attention requirements. While performance is maintained, the decrease of induced theta activity suggests early deficits in the directed-attention network in progressive MCI, whereas this network is functionally preserved in stable MCI.

Decoding Network Structure in On-Chip Integrated Flow Cells with Synchronization of Electrochemical Oscillators

NASA Astrophysics Data System (ADS)

Jia, Yanxin; Kiss, István Z.

2017-04-01

The analysis of network interactions among dynamical units and the impact of the coupling on self-organized structures is a challenging task with implications in many biological and engineered systems. We explore the coupling topology that arises through the potential drops in a flow channel in a lab-on-chip device that accommodates chemical reactions on electrode arrays. The networks are revealed by analysis of the synchronization patterns with the use of an oscillatory chemical reaction (nickel electrodissolution) and are further confirmed by direct decoding using phase model analysis. In dual electrode configuration, a variety coupling schemes, (uni- or bidirectional positive or negative) were identified depending on the relative placement of the reference and counter electrodes (e.g., placed at the same or the opposite ends of the flow channel). With three electrodes, the network consists of a superposition of a localized (upstream) and global (all-to-all) coupling. With six electrodes, the unique, position dependent coupling topology resulted spatially organized partial synchronization such that there was a synchrony gradient along the quasi-one-dimensional spatial coordinate. The networked, electrode potential (current) spike generating electrochemical reactions hold potential for construction of an in-situ information processing unit to be used in electrochemical devices in sensors and batteries.

Complexity Measures in Magnetoencephalography: Measuring "Disorder" in Schizophrenia

PubMed Central

Brookes, Matthew J.; Hall, Emma L.; Robson, Siân E.; Price, Darren; Palaniyappan, Lena; Liddle, Elizabeth B.; Liddle, Peter F.; Robinson, Stephen E.; Morris, Peter G.

2015-01-01

This paper details a methodology which, when applied to magnetoencephalography (MEG) data, is capable of measuring the spatio-temporal dynamics of ‘disorder’ in the human brain. Our method, which is based upon signal entropy, shows that spatially separate brain regions (or networks) generate temporally independent entropy time-courses. These time-courses are modulated by cognitive tasks, with an increase in local neural processing characterised by localised and transient increases in entropy in the neural signal. We explore the relationship between entropy and the more established time-frequency decomposition methods, which elucidate the temporal evolution of neural oscillations. We observe a direct but complex relationship between entropy and oscillatory amplitude, which suggests that these metrics are complementary. Finally, we provide a demonstration of the clinical utility of our method, using it to shed light on aberrant neurophysiological processing in schizophrenia. We demonstrate significantly increased task induced entropy change in patients (compared to controls) in multiple brain regions, including a cingulo-insula network, bilateral insula cortices and a right fronto-parietal network. These findings demonstrate potential clinical utility for our method and support a recent hypothesis that schizophrenia can be characterised by abnormalities in the salience network (a well characterised distributed network comprising bilateral insula and cingulate cortices). PMID:25886553

Dynamics of viscous liquid bridges inside microchannels subject to external oscillatory flow

NASA Astrophysics Data System (ADS)

Ahmadlouydarab, Majid; Azaiez, Jalel; Chen, Zhangxin

2015-02-01

We report on two-dimensional simulations of liquid bridges' dynamics inside microchannels of uniform wettability and subject to an external oscillatory flow rate. The oscillatory flow results in a zero net flow rate and its effects are compared to those of a stationary system. To handle the three phase contact lines motion, Cahn-Hilliard diffuse-interface formulation was used and the flow equations were solved using the finite element method with adaptively refined unstructured grids. The results indicate that the liquid bridge responds in three different ways depending on the substrate wettability properties and the frequency of the oscillatory flow. In particular below a critical frequency, the liquid bridge will rupture when the channel walls are philic or detach from the surface when they are phobic. However, at high frequencies, the liquid bridge shows a perpetual periodic oscillatory motion for both philic and phobic surfaces. Furthermore, an increase in the frequency of the flow velocity results in stabilization effects and a behavior approaching that of the stationary system where no rupture or detachment can be observed. This stable behavior is the direct result of less deformation of the liquid bridge due to the fast flow direction change and motion of contact lines on the solid substrate. Moreover, it was found that the flow velocity is out of phase with the footprint and throat lengths and that the latter two also show a phase difference. These differences were explained in terms of the motion of the two contact lines on the solid substrates and the deformation of the two fluid-fluid interfaces.

Dynamics of viscous liquid bridges inside microchannels subject to external oscillatory flow.

PubMed

Ahmadlouydarab, Majid; Azaiez, Jalel; Chen, Zhangxin

2015-02-01

We report on two-dimensional simulations of liquid bridges' dynamics inside microchannels of uniform wettability and subject to an external oscillatory flow rate. The oscillatory flow results in a zero net flow rate and its effects are compared to those of a stationary system. To handle the three phase contact lines motion, Cahn-Hilliard diffuse-interface formulation was used and the flow equations were solved using the finite element method with adaptively refined unstructured grids. The results indicate that the liquid bridge responds in three different ways depending on the substrate wettability properties and the frequency of the oscillatory flow. In particular below a critical frequency, the liquid bridge will rupture when the channel walls are philic or detach from the surface when they are phobic. However, at high frequencies, the liquid bridge shows a perpetual periodic oscillatory motion for both philic and phobic surfaces. Furthermore, an increase in the frequency of the flow velocity results in stabilization effects and a behavior approaching that of the stationary system where no rupture or detachment can be observed. This stable behavior is the direct result of less deformation of the liquid bridge due to the fast flow direction change and motion of contact lines on the solid substrate. Moreover, it was found that the flow velocity is out of phase with the footprint and throat lengths and that the latter two also show a phase difference. These differences were explained in terms of the motion of the two contact lines on the solid substrates and the deformation of the two fluid-fluid interfaces.

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

PubMed

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

2013-06-01

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

Frequency-band signatures of visual responses to naturalistic input in ferret primary visual cortex during free viewing.

PubMed

Sellers, Kristin K; Bennett, Davis V; Fröhlich, Flavio

2015-02-19

Neuronal firing responses in visual cortex reflect the statistics of visual input and emerge from the interaction with endogenous network dynamics. Artificial visual stimuli presented to animals in which the network dynamics were constrained by anesthetic agents or trained behavioral tasks have provided fundamental understanding of how individual neurons in primary visual cortex respond to input. In contrast, very little is known about the mesoscale network dynamics and their relationship to microscopic spiking activity in the awake animal during free viewing of naturalistic visual input. To address this gap in knowledge, we recorded local field potential (LFP) and multiunit activity (MUA) simultaneously in all layers of primary visual cortex (V1) of awake, freely viewing ferrets presented with naturalistic visual input (nature movie clips). We found that naturalistic visual stimuli modulated the entire oscillation spectrum; low frequency oscillations were mostly suppressed whereas higher frequency oscillations were enhanced. In average across all cortical layers, stimulus-induced change in delta and alpha power negatively correlated with the MUA responses, whereas sensory-evoked increases in gamma power positively correlated with MUA responses. The time-course of the band-limited power in these frequency bands provided evidence for a model in which naturalistic visual input switched V1 between two distinct, endogenously present activity states defined by the power of low (delta, alpha) and high (gamma) frequency oscillatory activity. Therefore, the two mesoscale activity states delineated in this study may define the degree of engagement of the circuit with the processing of sensory input. Copyright © 2014 Elsevier B.V. All rights reserved.

Coordinated Speed Oscillations in Schooling Killifish Enrich Social Communication

NASA Astrophysics Data System (ADS)

Swain, Daniel T.; Couzin, Iain D.; Leonard, Naomi Ehrich

2015-10-01

We examine the spatial dynamics of individuals in small schools of banded killifish ( Fundulus diaphanus) that exhibit rhythmic, oscillating speed, typically with sustained, coordinated, out-of-phase speed oscillations as they move around a shallow water tank. We show that the relative motion among the fish yields a periodically time-varying network of social interactions that enriches visually driven social communication. The oscillations lead to the regular making and breaking of occlusions, which we term "switching." We show that the rate of convergence to consensus (biologically, the capacity for individuals in groups to achieve effective coordinated motion) governed by the switching outperforms static alternatives, and performs as well as the less practical case of every fish sensing every other fish. We show further that the oscillations in speed yield oscillations in relative bearing between fish over a range that includes the angles previously predicted to be optimal for a fish to detect changes in heading and speed of its neighbors. To investigate systematically, we derive and analyze a dynamic model of interacting agents that move with oscillatory speed. We show that coordinated circular motion of the school leads to systematic cycling of spatial ordering of agents and possibilities for enriched spatial density of measurements of the external environment. Our results highlight the potential benefits of dynamic communication topologies in collective animal behavior, and suggest new, useful control laws for the distributed coordination of mobile robotic networks.

Coherent quantum dynamics launched by incoherent relaxation in a quantum circuit simulator of a light-harvesting complex

NASA Astrophysics Data System (ADS)

Chin, A. W.; Mangaud, E.; Atabek, O.; Desouter-Lecomte, M.

2018-06-01

Engineering and harnessing coherent excitonic transport in organic nanostructures has recently been suggested as a promising way towards improving manmade light-harvesting materials. However, realizing and testing the dissipative system-environment models underlying these proposals is presently very challenging in supramolecular materials. A promising alternative is to use simpler and highly tunable "quantum simulators" built from programmable qubits, as recently achieved in a superconducting circuit by Potočnik et al. [A. Potočnik et al., Nat. Commun. 9, 904 (2018), 10.1038/s41467-018-03312-x]. We simulate the real-time dynamics of an exciton coupled to a quantum bath as it moves through a network based on the quantum circuit of Potočnik et al. Using the numerically exact hierarchical equations of motion to capture the open quantum system dynamics, we find that an ultrafast but completely incoherent relaxation from a high-lying "bright" exciton into a doublet of closely spaced "dark" excitons can spontaneously generate electronic coherences and oscillatory real-space motion across the network (quantum beats). Importantly, we show that this behavior also survives when the environmental noise is classically stochastic (effectively high temperature), as in present experiments. These predictions highlight the possibilities of designing matched electronic and spectral noise structures for robust coherence generation that do not require coherent excitation or cold environments.

Time delay and long-range connection induced synchronization transitions in Newman-Watts small-world neuronal networks.

PubMed

Qian, Yu

2014-01-01

The synchronization transitions in Newman-Watts small-world neuronal networks (SWNNs) induced by time delay τ and long-range connection (LRC) probability P have been investigated by synchronization parameter and space-time plots. Four distinct parameter regions, that is, asynchronous region, transition region, synchronous region, and oscillatory region have been discovered at certain LRC probability P = 1.0 as time delay is increased. Interestingly, desynchronization is observed in oscillatory region. More importantly, we consider the spatiotemporal patterns obtained in delayed Newman-Watts SWNNs are the competition results between long-range drivings (LRDs) and neighboring interactions. In addition, for moderate time delay, the synchronization of neuronal network can be enhanced remarkably by increasing LRC probability. Furthermore, lag synchronization has been found between weak synchronization and complete synchronization as LRC probability P is a little less than 1.0. Finally, the two necessary conditions, moderate time delay and large numbers of LRCs, are exposed explicitly for synchronization in delayed Newman-Watts SWNNs.

Time Delay and Long-Range Connection Induced Synchronization Transitions in Newman-Watts Small-World Neuronal Networks

PubMed Central

Qian, Yu

2014-01-01

The synchronization transitions in Newman-Watts small-world neuronal networks (SWNNs) induced by time delay and long-range connection (LRC) probability have been investigated by synchronization parameter and space-time plots. Four distinct parameter regions, that is, asynchronous region, transition region, synchronous region, and oscillatory region have been discovered at certain LRC probability as time delay is increased. Interestingly, desynchronization is observed in oscillatory region. More importantly, we consider the spatiotemporal patterns obtained in delayed Newman-Watts SWNNs are the competition results between long-range drivings (LRDs) and neighboring interactions. In addition, for moderate time delay, the synchronization of neuronal network can be enhanced remarkably by increasing LRC probability. Furthermore, lag synchronization has been found between weak synchronization and complete synchronization as LRC probability is a little less than 1.0. Finally, the two necessary conditions, moderate time delay and large numbers of LRCs, are exposed explicitly for synchronization in delayed Newman-Watts SWNNs. PMID:24810595

A unified 3D default space consciousness model combining neurological and physiological processes that underlie conscious experience

PubMed Central

Jerath, Ravinder; Crawford, Molly W.; Barnes, Vernon A.

2015-01-01

The Global Workspace Theory and Information Integration Theory are two of the most currently accepted consciousness models; however, these models do not address many aspects of conscious experience. We compare these models to our previously proposed consciousness model in which the thalamus fills-in processed sensory information from corticothalamic feedback loops within a proposed 3D default space, resulting in the recreation of the internal and external worlds within the mind. This 3D default space is composed of all cells of the body, which communicate via gap junctions and electrical potentials to create this unified space. We use 3D illustrations to explain how both visual and non-visual sensory information may be filled-in within this dynamic space, creating a unified seamless conscious experience. This neural sensory memory space is likely generated by baseline neural oscillatory activity from the default mode network, other salient networks, brainstem, and reticular activating system. PMID:26379573

iTBS-Induced LTP-Like Plasticity Parallels Oscillatory Activity Changes in the Primary Sensory and Motor Areas of Macaque Monkeys

PubMed Central

Papazachariadis, Odysseas; Dante, Vittorio; Verschure, Paul F. M. J.; Del Giudice, Paolo; Ferraina, Stefano

2014-01-01

Recently, neuromodulation techniques based on the use of repetitive transcranial magnetic stimulation (rTMS) have been proposed as a non-invasive and efficient method to induce in vivo long-term potentiation (LTP)-like aftereffects. However, the exact impact of rTMS-induced perturbations on the dynamics of neuronal population activity is not well understood. Here, in two monkeys, we examine changes in the oscillatory activity of the sensorimotor cortex following an intermittent theta burst stimulation (iTBS) protocol. We first probed iTBS modulatory effects by testing the iTBS-induced facilitation of somatosensory evoked potentials (SEP). Then, we examined the frequency information of the electrocorticographic signal, obtained using a custom-made miniaturised multi-electrode array for electrocorticography, after real or sham iTBS. We observed that iTBS induced facilitation of SEPs and influenced spectral components of the signal, in both animals. The latter effect was more prominent on the θ band (4–8 Hz) and the high γ band (55–90 Hz), de-potentiated and potentiated respectively. We additionally found that the multi-electrode array uniformity of β (13–26 Hz) and high γ bands were also afflicted by iTBS. Our study suggests that enhanced cortical excitability promoted by iTBS parallels a dynamic reorganisation of the interested neural network. The effect in the γ band suggests a transient local modulation, possibly at the level of synaptic strength in interneurons. The effect in the θ band suggests the disruption of temporal coordination on larger spatial scales. PMID:25383621

iTBS-induced LTP-like plasticity parallels oscillatory activity changes in the primary sensory and motor areas of macaque monkeys.

PubMed

Papazachariadis, Odysseas; Dante, Vittorio; Verschure, Paul F M J; Del Giudice, Paolo; Ferraina, Stefano

2014-01-01

Recently, neuromodulation techniques based on the use of repetitive transcranial magnetic stimulation (rTMS) have been proposed as a non-invasive and efficient method to induce in vivo long-term potentiation (LTP)-like aftereffects. However, the exact impact of rTMS-induced perturbations on the dynamics of neuronal population activity is not well understood. Here, in two monkeys, we examine changes in the oscillatory activity of the sensorimotor cortex following an intermittent theta burst stimulation (iTBS) protocol. We first probed iTBS modulatory effects by testing the iTBS-induced facilitation of somatosensory evoked potentials (SEP). Then, we examined the frequency information of the electrocorticographic signal, obtained using a custom-made miniaturised multi-electrode array for electrocorticography, after real or sham iTBS. We observed that iTBS induced facilitation of SEPs and influenced spectral components of the signal, in both animals. The latter effect was more prominent on the θ band (4-8 Hz) and the high γ band (55-90 Hz), de-potentiated and potentiated respectively. We additionally found that the multi-electrode array uniformity of β (13-26 Hz) and high γ bands were also afflicted by iTBS. Our study suggests that enhanced cortical excitability promoted by iTBS parallels a dynamic reorganisation of the interested neural network. The effect in the γ band suggests a transient local modulation, possibly at the level of synaptic strength in interneurons. The effect in the θ band suggests the disruption of temporal coordination on larger spatial scales.

Actin cytoskeleton of chemotactic amoebae operates close to the onset of oscillations

PubMed Central

Westendorf, Christian; Negrete, Jose; Bae, Albert J.; Sandmann, Rabea; Bodenschatz, Eberhard; Beta, Carsten

2013-01-01

The rapid reorganization of the actin cytoskeleton in response to external stimuli is an essential property of many motile eukaryotic cells. Here, we report evidence that the actin machinery of chemotactic Dictyostelium cells operates close to an oscillatory instability. When averaging the actin response of many cells to a short pulse of the chemoattractant cAMP, we observed a transient accumulation of cortical actin reminiscent of a damped oscillation. At the single-cell level, however, the response dynamics ranged from short, strongly damped responses to slowly decaying, weakly damped oscillations. Furthermore, in a small subpopulation, we observed self-sustained oscillations in the cortical F-actin concentration. To substantiate that an oscillatory mechanism governs the actin dynamics in these cells, we systematically exposed a large number of cells to periodic pulse trains of different frequencies. Our results indicate a resonance peak at a stimulation period of around 20 s. We propose a delayed feedback model that explains our experimental findings based on a time-delay in the regulatory network of the actin system. To test the model, we performed stimulation experiments with cells that express GFP-tagged fusion proteins of Coronin and actin-interacting protein 1, as well as knockout mutants that lack Coronin and actin-interacting protein 1. These actin-binding proteins enhance the disassembly of actin filaments and thus allow us to estimate the delay time in the regulatory feedback loop. Based on this independent estimate, our model predicts an intrinsic period of 20 s, which agrees with the resonance observed in our periodic stimulation experiments. PMID:23431176

Self-Induced Switchings between Multiple Space-Time Patterns on Complex Networks of Excitable Units

NASA Astrophysics Data System (ADS)

Ansmann, Gerrit; Lehnertz, Klaus; Feudel, Ulrike

2016-01-01

We report on self-induced switchings between multiple distinct space-time patterns in the dynamics of a spatially extended excitable system. These switchings between low-amplitude oscillations, nonlinear waves, and extreme events strongly resemble a random process, although the system is deterministic. We show that a chaotic saddle—which contains all the patterns as well as channel-like structures that mediate the transitions between them—is the backbone of such a pattern-switching dynamics. Our analyses indicate that essential ingredients for the observed phenomena are that the system behaves like an inhomogeneous oscillatory medium that is capable of self-generating spatially localized excitations and that is dominated by short-range connections but also features long-range connections. With our findings, we present an alternative to the well-known ways to obtain self-induced pattern switching, namely, noise-induced attractor hopping, heteroclinic orbits, and adaptation to an external signal. This alternative way can be expected to improve our understanding of pattern switchings in spatially extended natural dynamical systems like the brain and the heart.

Dynamic oscillatory processes governing cued orienting and allocation of auditory attention

PubMed Central

Ahveninen, Jyrki; Huang, Samantha; Belliveau, John W.; Chang, Wei-Tang; Hämäläinen, Matti

2013-01-01

In everyday listening situations, we need to constantly switch between alternative sound sources and engage attention according to cues that match our goals and expectations. The exact neuronal bases of these processes are poorly understood. We investigated oscillatory brain networks controlling auditory attention using cortically constrained fMRI-weighted magnetoencephalography/ electroencephalography (MEG/EEG) source estimates. During consecutive trials, subjects were instructed to shift attention based on a cue, presented in the ear where a target was likely to follow. To promote audiospatial attention effects, the targets were embedded in streams of dichotically presented standard tones. Occasionally, an unexpected novel sound occurred opposite to the cued ear, to trigger involuntary orienting. According to our cortical power correlation analyses, increased frontoparietal/temporal 30–100 Hz gamma activity at 200–1400 ms after cued orienting predicted fast and accurate discrimination of subsequent targets. This sustained correlation effect, possibly reflecting voluntary engagement of attention after the initial cue-driven orienting, spread from the temporoparietal junction, anterior insula, and inferior frontal (IFC) cortices to the right frontal eye fields. Engagement of attention to one ear resulted in a significantly stronger increase of 7.5–15 Hz alpha in the ipsilateral than contralateral parieto-occipital cortices 200–600 ms after the cue onset, possibly reflecting crossmodal modulation of the dorsal visual pathway during audiospatial attention. Comparisons of cortical power patterns also revealed significant increases of sustained right medial frontal cortex theta power, right dorsolateral prefrontal cortex and anterior insula/IFC beta power, and medial parietal cortex and posterior cingulate cortex gamma activity after cued vs. novelty-triggered orienting (600–1400 ms). Our results reveal sustained oscillatory patterns associated with voluntary engagement of auditory spatial attention, with the frontoparietal and temporal gamma increases being best predictors of subsequent behavioral performance. PMID:23915050

Dynamics of a population of oscillatory and excitable elements.

PubMed

O'Keeffe, Kevin P; Strogatz, Steven H

2016-06-01

We analyze a variant of a model proposed by Kuramoto, Shinomoto, and Sakaguchi for a large population of coupled oscillatory and excitable elements. Using the Ott-Antonsen ansatz, we reduce the behavior of the population to a two-dimensional dynamical system with three parameters. We present the stability diagram and calculate several of its bifurcation curves analytically, for both excitatory and inhibitory coupling. Our main result is that when the coupling function is broad, the system can display bistability between steady states of constant high and low activity, whereas when the coupling function is narrow and inhibitory, one of the states in the bistable regime can show persistent pulsations in activity.

Reliable binary cell-fate decisions based on oscillations

NASA Astrophysics Data System (ADS)

Pfeuty, B.; Kaneko, K.

2014-02-01

Biological systems have often to perform binary decisions under highly dynamic and noisy environments, such as during cell-fate determination. These decisions can be implemented by two main bifurcation mechanisms based on the transitions from either monostability or oscillation to bistability. We compare these two mechanisms by using stochastic models with time-varying fields and by establishing asymptotic formulas for the choice probabilities. Different scaling laws for decision sensitivity with respect to noise strength and signal timescale are obtained, supporting a role for oscillatory dynamics in performing noise-robust and temporally tunable binary decision-making. This result provides a rationale for recent experimental evidences showing that oscillatory expression of proteins often precedes binary cell-fate decisions.

Shuttle rocket booster computational fluid dynamics

NASA Technical Reports Server (NTRS)

Chung, T. J.; Park, O. Y.

1988-01-01

Additional results and a revised and improved computer program listing from the shuttle rocket booster computational fluid dynamics formulations are presented. Numerical calculations for the flame zone of solid propellants are carried out using the Galerkin finite elements, with perturbations expanded to the zeroth, first, and second orders. The results indicate that amplification of oscillatory motions does indeed prevail in high frequency regions. For the second order system, the trend is similar to the first order system for low frequencies, but instabilities may appear at frequencies lower than those of the first order system. The most significant effect of the second order system is that the admittance is extremely oscillatory between moderately high frequency ranges.

One central oscillatory drive is compatible with experimental motor unit behaviour in essential and Parkinsonian tremor

NASA Astrophysics Data System (ADS)

Dideriksen, Jakob L.; Gallego, Juan A.; Holobar, Ales; Rocon, Eduardo; Pons, Jose L.; Farina, Dario

2015-08-01

Objective. Pathological tremors are symptomatic to several neurological disorders that are difficult to differentiate and the way by which central oscillatory networks entrain tremorogenic contractions is unknown. We considered the alternative hypotheses that tremor arises from one oscillator (at the tremor frequency) or, as suggested by recent findings from the superimposition of two separate inputs (at the tremor frequency and twice that frequency). Approach. Assuming one central oscillatory network we estimated analytically the relative amplitude of the harmonics of the tremor frequency in the motor neuron output for different temporal behaviors of the oscillator. Next, we analyzed the bias in the relative harmonics amplitude introduced by superimposing oscillations at twice the tremor frequency. These findings were validated using experimental measurements of wrist angular velocity and surface electromyography (EMG) from 22 patients (11 essential tremor, 11 Parkinson’s disease). The ensemble motor unit action potential trains identified from the EMG represented the neural drive to the muscles. Main results. The analytical results showed that the relative power of the tremor harmonics in the analytical models of the neural drive was determined by the variability and duration of the tremor bursts and the presence of the second oscillator biased this power towards higher values. The experimental findings accurately matched the analytical model assuming one oscillator, indicating a negligible functional role of secondary oscillatory inputs. Furthermore, a significant difference in the relative power of harmonics in the neural drive was found across the patient groups, suggesting a diagnostic value of this measure (classification accuracy: 86%). This diagnostic power decreased substantially when estimated from limb acceleration or the EMG. Signficance. The results indicate that the neural drive in pathological tremor is compatible with one central network providing neural oscillations at the tremor frequency. Moreover, the regularity of this neural oscillation varies across tremor pathologies, making the relative amplitude of tremor harmonics a potential biomarker for diagnostic use.

One central oscillatory drive is compatible with experimental motor unit behaviour in essential and Parkinsonian tremor.

PubMed

Dideriksen, Jakob L; Gallego, Juan A; Holobar, Ales; Rocon, Eduardo; Pons, Jose L; Farina, Dario

2015-08-01

Pathological tremors are symptomatic to several neurological disorders that are difficult to differentiate and the way by which central oscillatory networks entrain tremorogenic contractions is unknown. We considered the alternative hypotheses that tremor arises from one oscillator (at the tremor frequency) or, as suggested by recent findings from the superimposition of two separate inputs (at the tremor frequency and twice that frequency). Assuming one central oscillatory network we estimated analytically the relative amplitude of the harmonics of the tremor frequency in the motor neuron output for different temporal behaviors of the oscillator. Next, we analyzed the bias in the relative harmonics amplitude introduced by superimposing oscillations at twice the tremor frequency. These findings were validated using experimental measurements of wrist angular velocity and surface electromyography (EMG) from 22 patients (11 essential tremor, 11 Parkinson's disease). The ensemble motor unit action potential trains identified from the EMG represented the neural drive to the muscles. The analytical results showed that the relative power of the tremor harmonics in the analytical models of the neural drive was determined by the variability and duration of the tremor bursts and the presence of the second oscillator biased this power towards higher values. The experimental findings accurately matched the analytical model assuming one oscillator, indicating a negligible functional role of secondary oscillatory inputs. Furthermore, a significant difference in the relative power of harmonics in the neural drive was found across the patient groups, suggesting a diagnostic value of this measure (classification accuracy: 86%). This diagnostic power decreased substantially when estimated from limb acceleration or the EMG. SIGNFICANCE: The results indicate that the neural drive in pathological tremor is compatible with one central network providing neural oscillations at the tremor frequency. Moreover, the regularity of this neural oscillation varies across tremor pathologies, making the relative amplitude of tremor harmonics a potential biomarker for diagnostic use.

Efficient Transmission of Subthreshold Signals in Complex Networks of Spiking Neurons

PubMed Central

Torres, Joaquin J.; Elices, Irene; Marro, J.

2015-01-01

We investigate the efficient transmission and processing of weak, subthreshold signals in a realistic neural medium in the presence of different levels of the underlying noise. Assuming Hebbian weights for maximal synaptic conductances—that naturally balances the network with excitatory and inhibitory synapses—and considering short-term synaptic plasticity affecting such conductances, we found different dynamic phases in the system. This includes a memory phase where population of neurons remain synchronized, an oscillatory phase where transitions between different synchronized populations of neurons appears and an asynchronous or noisy phase. When a weak stimulus input is applied to each neuron, increasing the level of noise in the medium we found an efficient transmission of such stimuli around the transition and critical points separating different phases for well-defined different levels of stochasticity in the system. We proved that this intriguing phenomenon is quite robust, as it occurs in different situations including several types of synaptic plasticity, different type and number of stored patterns and diverse network topologies, namely, diluted networks and complex topologies such as scale-free and small-world networks. We conclude that the robustness of the phenomenon in different realistic scenarios, including spiking neurons, short-term synaptic plasticity and complex networks topologies, make very likely that it could also occur in actual neural systems as recent psycho-physical experiments suggest. PMID:25799449

Dynamics of Propofol-Induced Loss of Consciousness Across Primate Neocortex.

PubMed

Ishizawa, Yumiko; Ahmed, Omar J; Patel, Shaun R; Gale, John T; Sierra-Mercado, Demetrio; Brown, Emery N; Eskandar, Emad N

2016-07-20

The precise neural mechanisms underlying transitions between consciousness and anesthetic-induced unconsciousness remain unclear. Here, we studied intracortical neuronal dynamics leading to propofol-induced unconsciousness by recording single-neuron activity and local field potentials directly in the functionally interconnecting somatosensory (S1) and frontal ventral premotor (PMv) network during a gradual behavioral transition from full alertness to loss of consciousness (LOC) and on through a deeper anesthetic level. Macaque monkeys were trained for a behavioral task designed to determine the trial-by-trial alertness and neuronal response to tactile and auditory stimulation. We show that disruption of coherent beta oscillations between S1 and PMv preceded, but did not coincide with, the LOC. LOC appeared to correspond to pronounced but brief gamma-/high-beta-band oscillations (lasting ∼3 min) in PMv, followed by a gamma peak in S1. We also demonstrate that the slow oscillations appeared after LOC in S1 and then in PMv after a delay, together suggesting that neuronal dynamics are very different across S1 versus PMv during LOC. Finally, neurons in both S1 and PMv transition from responding to bimodal (tactile and auditory) stimulation before LOC to only tactile modality during unconsciousness, consistent with an inhibition of multisensory integration in this network. Our results show that propofol-induced LOC is accompanied by spatiotemporally distinct oscillatory neuronal dynamics across the somatosensory and premotor network and suggest that a transitional state from wakefulness to unconsciousness is not a continuous process, but rather a series of discrete neural changes. How information is processed by the brain during awake and anesthetized states and, crucially, during the transition is not clearly understood. We demonstrate that neuronal dynamics are very different within an interconnecting cortical network (primary somatosensory and frontal premotor area) during the loss of consciousness (LOC) induced by propofol in nonhuman primates. Coherent beta oscillations between these regions are disrupted before LOC. Pronounced but brief gamma-band oscillations appear to correspond to LOC. In addition, neurons in both of these cortices transition from responding to both tactile and auditory stimulation before LOC to only tactile modality during unconsciousness. We demonstrate that propofol-induced LOC is accompanied by spatiotemporally distinctive neuronal dynamics in this network with concurrent changes in multisensory processing. Copyright © 2016 the authors 0270-6474/16/367718-09$15.00/0.

Regional gas transport in the heterogeneous lung during oscillatory ventilation

PubMed Central

Herrmann, Jacob; Tawhai, Merryn H.

2016-01-01

Regional ventilation in the injured lung is heterogeneous and frequency dependent, making it difficult to predict how an oscillatory flow waveform at a specified frequency will be distributed throughout the periphery. To predict the impact of mechanical heterogeneity on regional ventilation distribution and gas transport, we developed a computational model of distributed gas flow and CO2 elimination during oscillatory ventilation from 0.1 to 30 Hz. The model consists of a three-dimensional airway network of a canine lung, with heterogeneous parenchymal tissues to mimic effects of gravity and injury. Model CO2 elimination during single frequency oscillation was validated against previously published experimental data (Venegas JG, Hales CA, Strieder DJ, J Appl Physiol 60: 1025–1030, 1986). Simulations of gas transport demonstrated a critical transition in flow distribution at the resonant frequency, where the reactive components of mechanical impedance due to airway inertia and parenchymal elastance were equal. For frequencies above resonance, the distribution of ventilation became spatially clustered and frequency dependent. These results highlight the importance of oscillatory frequency in managing the regional distribution of ventilation and gas exchange in the heterogeneous lung. PMID:27763872

Broadband Electrophysiological Dynamics Contribute to Global Resting-State fMRI Signal.

PubMed

Wen, Haiguang; Liu, Zhongming

2016-06-01

Spontaneous activity observed with resting-state fMRI is used widely to uncover the brain's intrinsic functional networks in health and disease. Although many networks appear modular and specific, global and nonspecific fMRI fluctuations also exist and both pose a challenge and present an opportunity for characterizing and understanding brain networks. Here, we used a multimodal approach to investigate the neural correlates to the global fMRI signal in the resting state. Like fMRI, resting-state power fluctuations of broadband and arrhythmic, or scale-free, macaque electrocorticography and human magnetoencephalography activity were correlated globally. The power fluctuations of scale-free human electroencephalography (EEG) were coupled with the global component of simultaneously acquired resting-state fMRI, with the global hemodynamic change lagging the broadband spectral change of EEG by ∼5 s. The levels of global and nonspecific fluctuation and synchronization in scale-free population activity also varied across and depended on arousal states. Together, these results suggest that the neural origin of global resting-state fMRI activity is the broadband power fluctuation in scale-free population activity observable with macroscopic electrical or magnetic recordings. Moreover, the global fluctuation in neurophysiological and hemodynamic activity is likely modulated through diffuse neuromodulation pathways that govern arousal states and vigilance levels. This study provides new insights into the neural origin of resting-state fMRI. Results demonstrate that the broadband power fluctuation of scale-free electrophysiology is globally synchronized and directly coupled with the global component of spontaneous fMRI signals, in contrast to modularly synchronized fluctuations in oscillatory neural activity. These findings lead to a new hypothesis that scale-free and oscillatory neural processes account for global and modular patterns of functional connectivity observed with resting-state fMRI, respectively. Copyright © 2016 the authors 0270-6474/16/366030-11$15.00/0.

Independent oscillatory patterns determine performance fluctuations in children with attention deficit/hyperactivity disorder.

PubMed

Yordanova, Juliana; Albrecht, Björn; Uebel, Henrik; Kirov, Roumen; Banaschewski, Tobias; Rothenberger, Aribert; Kolev, Vasil

2011-06-01

The maintenance of stable goal-directed behaviour is a hallmark of conscious executive control in humans. Notably, both correct and error human actions may have a subconscious activation-based determination. One possible source of subconscious interference may be the default mode network that, in contrast to attentional network, manifests intrinsic oscillations at very low (<0.1 Hz) frequencies. In the present study, we analyse the time dynamics of performance accuracy to search for multisecond periodic fluctuations of error occurrence. Attentional lapses in attention deficit/hyperactivity disorder are proposed to originate from interferences from intrinsically oscillating networks. Identifying periodic error fluctuations with a frequency<0.1 Hz in patients with attention deficit/hyperactivity disorder would provide a behavioural evidence for such interferences. Performance was monitored during a visual flanker task in 92 children (7- to 16-year olds), 47 with attention deficit/hyperactivity disorder, combined type and 45 healthy controls. Using an original approach, the time distribution of error occurrence was analysed in the frequency and time-frequency domains in order to detect rhythmic periodicity. Major results demonstrate that in both patients and controls, error behaviour was characterized by multisecond rhythmic fluctuations with a period of ∼12 s, appearing with a delay after transition to task. Only in attention deficit/hyperactivity disorder, was there an additional 'pathological' oscillation of error generation, which determined periodic drops of performance accuracy each 20-30 s. Thus, in patients, periodic error fluctuations were modulated by two independent oscillatory patterns. The findings demonstrate that: (i) attentive behaviour of children is determined by multisecond regularities; and (ii) a unique additional periodicity guides performance fluctuations in patients. These observations may re-conceptualize the understanding of attentive behaviour beyond the executive top-down control and may reveal new origins of psychopathological behaviours in attention deficit/hyperactivity disorder.

Elastic constants and dynamics in nematic liquid crystals

NASA Astrophysics Data System (ADS)

Humpert, Anja; Allen, Michael P.

2015-09-01

In this paper, we present molecular dynamics calculations of the Frank elastic constants, and associated time correlation functions, in nematic liquid crystals. We study two variants of the Gay-Berne potential, and use system sizes of half a million molecules, significantly larger than in previous studies of elastic behaviour. Equilibrium orientational fluctuations in reciprocal (k-) space were calculated, to determine the elastic constants by fitting at low |k|; our results indicate that small system size may be a source of inaccuracy in previous work. Furthermore, the dynamics of the Gay-Berne nematic were studied by calculating time correlation functions of components of the order tensor, together with associated components of the velocity field, for a set of wave vectors k. Confirming our earlier work, we found exponential decay for splay and twist correlations, and oscillatory exponential decay for the bend correlation. In this work, we confirm similar behaviour for the corresponding velocity components. In all cases, the decay rates, and oscillation frequencies, were found to be accurately proportional to k2 for small k, as predicted by the equations of nematodynamics. However, the observation of oscillatory bend fluctuations, and corresponding oscillatory shear flow decay, is in contradiction to the usual assumptions appearing in the literature, and in standard texts. We discuss the advantages and drawbacks of using large systems in these calculations.

Beta and gamma oscillatory activities associated with olfactory memory tasks: different rhythms for different functional networks?

PubMed Central

Martin, Claire; Ravel, Nadine

2014-01-01

Olfactory processing in behaving animals, even at early stages, is inextricable from top down influences associated with odor perception. The anatomy of the olfactory network (olfactory bulb, piriform, and entorhinal cortices) and its unique direct access to the limbic system makes it particularly attractive to study how sensory processing could be modulated by learning and memory. Moreover, olfactory structures have been early reported to exhibit oscillatory population activities easy to capture through local field potential recordings. An attractive hypothesis is that neuronal oscillations would serve to “bind” distant structures to reach a unified and coherent perception. In relation to this hypothesis, we will assess the functional relevance of different types of oscillatory activity observed in the olfactory system of behaving animals. This review will focus primarily on two types of oscillatory activities: beta (15–40 Hz) and gamma (60–100 Hz). While gamma oscillations are dominant in the olfactory system in the absence of odorant, both beta and gamma rhythms have been reported to be modulated depending on the nature of the olfactory task. Studies from the authors of the present review and other groups brought evidence for a link between these oscillations and behavioral changes induced by olfactory learning. However, differences in studies led to divergent interpretations concerning the respective role of these oscillations in olfactory processing. Based on a critical reexamination of those data, we propose hypotheses on the functional involvement of beta and gamma oscillations for odor perception and memory. PMID:25002840

Disturbed temporal dynamics of brain synchronization in vision loss.

PubMed

Bola, Michał; Gall, Carolin; Sabel, Bernhard A

2015-06-01

Damage along the visual pathway prevents bottom-up visual input from reaching further processing stages and consequently leads to loss of vision. But perception is not a simple bottom-up process - rather it emerges from activity of widespread cortical networks which coordinate visual processing in space and time. Here we set out to study how vision loss affects activity of brain visual networks and how networks' activity is related to perception. Specifically, we focused on studying temporal patterns of brain activity. To this end, resting-state eyes-closed EEG was recorded from partially blind patients suffering from chronic retina and/or optic-nerve damage (n = 19) and healthy controls (n = 13). Amplitude (power) of oscillatory activity and phase locking value (PLV) were used as measures of local and distant synchronization, respectively. Synchronization time series were created for the low- (7-9 Hz) and high-alpha band (11-13 Hz) and analyzed with three measures of temporal patterns: (i) length of synchronized-/desynchronized-periods, (ii) Higuchi Fractal Dimension (HFD), and (iii) Detrended Fluctuation Analysis (DFA). We revealed that patients exhibit less complex, more random and noise-like temporal dynamics of high-alpha band activity. More random temporal patterns were associated with worse performance in static (r = -.54, p = .017) and kinetic perimetry (r = .47, p = .041). We conclude that disturbed temporal patterns of neural synchronization in vision loss patients indicate disrupted communication within brain visual networks caused by prolonged deafferentation. We propose that because the state of brain networks is essential for normal perception, impaired brain synchronization in patients with vision loss might aggravate the functional consequences of reduced visual input. Copyright © 2015 Elsevier Ltd. All rights reserved.

Pluripotency, Differentiation, and Reprogramming: A Gene Expression Dynamics Model with Epigenetic Feedback Regulation

PubMed Central

Miyamoto, Tadashi; Furusawa, Chikara; Kaneko, Kunihiko

2015-01-01

Embryonic stem cells exhibit pluripotency: they can differentiate into all types of somatic cells. Pluripotent genes such as Oct4 and Nanog are activated in the pluripotent state, and their expression decreases during cell differentiation. Inversely, expression of differentiation genes such as Gata6 and Gata4 is promoted during differentiation. The gene regulatory network controlling the expression of these genes has been described, and slower-scale epigenetic modifications have been uncovered. Although the differentiation of pluripotent stem cells is normally irreversible, reprogramming of cells can be experimentally manipulated to regain pluripotency via overexpression of certain genes. Despite these experimental advances, the dynamics and mechanisms of differentiation and reprogramming are not yet fully understood. Based on recent experimental findings, we constructed a simple gene regulatory network including pluripotent and differentiation genes, and we demonstrated the existence of pluripotent and differentiated states from the resultant dynamical-systems model. Two differentiation mechanisms, interaction-induced switching from an expression oscillatory state and noise-assisted transition between bistable stationary states, were tested in the model. The former was found to be relevant to the differentiation process. We also introduced variables representing epigenetic modifications, which controlled the threshold for gene expression. By assuming positive feedback between expression levels and the epigenetic variables, we observed differentiation in expression dynamics. Additionally, with numerical reprogramming experiments for differentiated cells, we showed that pluripotency was recovered in cells by imposing overexpression of two pluripotent genes and external factors to control expression of differentiation genes. Interestingly, these factors were consistent with the four Yamanaka factors, Oct4, Sox2, Klf4, and Myc, which were necessary for the establishment of induced pluripotent stem cells. These results, based on a gene regulatory network and expression dynamics, contribute to our wider understanding of pluripotency, differentiation, and reprogramming of cells, and they provide a fresh viewpoint on robustness and control during development. PMID:26308610

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.

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 for respiratory entrainment of local field potential activity in human piriform cortex, amygdala, and hippocampus. These effects diminished when breathing was diverted to the mouth, highlighting the importance of nasal airflow for generating respiratory oscillations. Finally, behavioral data in healthy subjects suggest that breathing phase systematically influences cognitive tasks related to amygdala and hippocampal functions. PMID:27927961

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 of local field potential activity in human piriform cortex, amygdala, and hippocampus. These effects diminished when breathing was diverted to the mouth, highlighting the importance of nasal airflow for generating respiratory oscillations. Finally, behavioral data in healthy subjects suggest that breathing phase systematically influences cognitive tasks related to amygdala and hippocampal functions. Copyright © 2016 the authors 0270-6474/16/3612448-20$15.00/0.

The Functional Role of Neural Oscillations in Non-Verbal Emotional Communication

PubMed Central

Symons, Ashley E.; El-Deredy, Wael; Schwartze, Michael; Kotz, Sonja A.

2016-01-01

Effective interpersonal communication depends on the ability to perceive and interpret nonverbal emotional expressions from multiple sensory modalities. Current theoretical models propose that visual and auditory emotion perception involves a network of brain regions including the primary sensory cortices, the superior temporal sulcus (STS), and orbitofrontal cortex (OFC). However, relatively little is known about how the dynamic interplay between these regions gives rise to the perception of emotions. In recent years, there has been increasing recognition of the importance of neural oscillations in mediating neural communication within and between functional neural networks. Here we review studies investigating changes in oscillatory activity during the perception of visual, auditory, and audiovisual emotional expressions, and aim to characterize the functional role of neural oscillations in nonverbal emotion perception. Findings from the reviewed literature suggest that theta band oscillations most consistently differentiate between emotional and neutral expressions. While early theta synchronization appears to reflect the initial encoding of emotionally salient sensory information, later fronto-central theta synchronization may reflect the further integration of sensory information with internal representations. Additionally, gamma synchronization reflects facilitated sensory binding of emotional expressions within regions such as the OFC, STS, and, potentially, the amygdala. However, the evidence is more ambiguous when it comes to the role of oscillations within the alpha and beta frequencies, which vary as a function of modality (or modalities), presence or absence of predictive information, and attentional or task demands. Thus, the synchronization of neural oscillations within specific frequency bands mediates the rapid detection, integration, and evaluation of emotional expressions. Moreover, the functional coupling of oscillatory activity across multiples frequency bands supports a predictive coding model of multisensory emotion perception in which emotional facial and body expressions facilitate the processing of emotional vocalizations. PMID:27252638

Auditory processing assessment suggests that Wistar audiogenic rat neural networks are prone to entrainment.

PubMed

Pinto, Hyorrana Priscila Pereira; Carvalho, Vinícius Rezende; Medeiros, Daniel de Castro; Almeida, Ana Flávia Santos; Mendes, Eduardo Mazoni Andrade Marçal; Moraes, Márcio Flávio Dutra

2017-04-07

Epilepsy is a neurological disease related to the occurrence of pathological oscillatory activity, but the basic physiological mechanisms of seizure remain to be understood. Our working hypothesis is that specific sensory processing circuits may present abnormally enhanced predisposition for coordinated firing in the dysfunctional brain. Such facilitated entrainment could share a similar mechanistic process as those expediting the propagation of epileptiform activity throughout the brain. To test this hypothesis, we employed the Wistar audiogenic rat (WAR) reflex animal model, which is characterized by having seizures triggered reliably by sound. Sound stimulation was modulated in amplitude to produce an auditory steady-state-evoked response (ASSR; -53.71Hz) that covers bottom-up and top-down processing in a time scale compatible with the dynamics of the epileptic condition. Data from inferior colliculus (IC) c-Fos immunohistochemistry and electrographic recordings were gathered for both the control Wistar group and WARs. Under 85-dB SLP auditory stimulation, compared to controls, the WARs presented higher number of Fos-positive cells (at IC and auditory temporal lobe) and a significant increase in ASSR-normalized energy. Similarly, the 110-dB SLP sound stimulation also statistically increased ASSR-normalized energy during ictal and post-ictal periods. However, at the transition from the physiological to pathological state (pre-ictal period), the WAR ASSR analysis demonstrated a decline in normalized energy and a significant increase in circular variance values compared to that of controls. These results indicate an enhanced coordinated firing state for WARs, except immediately before seizure onset (suggesting pre-ictal neuronal desynchronization with external sensory drive). These results suggest a competing myriad of interferences among different networks that after seizure onset converge to a massive oscillatory circuit. Copyright © 2017 IBRO. Published by Elsevier Ltd. All rights reserved.

The Functional Role of Neural Oscillations in Non-Verbal Emotional Communication.

PubMed

Symons, Ashley E; El-Deredy, Wael; Schwartze, Michael; Kotz, Sonja A

2016-01-01

Effective interpersonal communication depends on the ability to perceive and interpret nonverbal emotional expressions from multiple sensory modalities. Current theoretical models propose that visual and auditory emotion perception involves a network of brain regions including the primary sensory cortices, the superior temporal sulcus (STS), and orbitofrontal cortex (OFC). However, relatively little is known about how the dynamic interplay between these regions gives rise to the perception of emotions. In recent years, there has been increasing recognition of the importance of neural oscillations in mediating neural communication within and between functional neural networks. Here we review studies investigating changes in oscillatory activity during the perception of visual, auditory, and audiovisual emotional expressions, and aim to characterize the functional role of neural oscillations in nonverbal emotion perception. Findings from the reviewed literature suggest that theta band oscillations most consistently differentiate between emotional and neutral expressions. While early theta synchronization appears to reflect the initial encoding of emotionally salient sensory information, later fronto-central theta synchronization may reflect the further integration of sensory information with internal representations. Additionally, gamma synchronization reflects facilitated sensory binding of emotional expressions within regions such as the OFC, STS, and, potentially, the amygdala. However, the evidence is more ambiguous when it comes to the role of oscillations within the alpha and beta frequencies, which vary as a function of modality (or modalities), presence or absence of predictive information, and attentional or task demands. Thus, the synchronization of neural oscillations within specific frequency bands mediates the rapid detection, integration, and evaluation of emotional expressions. Moreover, the functional coupling of oscillatory activity across multiples frequency bands supports a predictive coding model of multisensory emotion perception in which emotional facial and body expressions facilitate the processing of emotional vocalizations.

The visual cognitive network, but not the visual sensory network, is affected in amnestic mild cognitive impairment: a study of brain oscillatory responses.

PubMed

Yener, Görsev G; Emek-Savaş, Derya Durusu; Güntekin, Bahar; Başar, Erol

2014-10-17

Mild Cognitive Impairment (MCI) is considered in many as prodromal stage of Alzheimer's disease (AD). Event-related oscillations (ERO) reflect cognitive responses of brain whereas sensory-evoked oscillations (SEO) inform about sensory responses. For this study, we compared visual SEO and ERO responses in MCI to explore brain dynamics (BACKGROUND). Forty-three patients with MCI (mean age=74.0 year) and 41 age- and education-matched healthy-elderly controls (HC) (mean age=71.1 year) participated in the study. The maximum peak-to-peak amplitudes for each subject's averaged delta response (0.5-3.0 Hz) were measured from two conditions (simple visual stimulation and classical visual oddball paradigm target stimulation) (METHOD). Overall, amplitudes of target ERO responses were higher than SEO amplitudes. The preferential location for maximum amplitude values was frontal lobe for ERO and occipital lobe for SEO. The ANOVA for delta responses showed significant results for the group Xparadigm. Post-hoc tests indicated that (1) the difference between groups were significant for target delta responses, but not for SEO, (2) ERO elicited higher responses for HC than MCI patients, and (3) females had higher target ERO than males and this difference was pronounced in the control group (RESULTS). Overall, cognitive responses display almost double the amplitudes of sensory responses over frontal regions. The topography of oscillatory responses differs depending on stimuli: visualsensory responses are highest over occipitals and -cognitive responses over frontal regions. A group effect is observed in MCI indicating that visual sensory and cognitive circuits behave differently indicating preserved visual sensory responses, but decreased cognitive responses (CONCLUSION). Copyright © 2014 Elsevier B.V. All rights reserved.

Growth-rate-dependent dynamics of a bacterial genetic oscillator

NASA Astrophysics Data System (ADS)

Osella, Matteo; Lagomarsino, Marco Cosentino

2013-01-01

Gene networks exhibiting oscillatory dynamics are widespread in biology. The minimal regulatory designs giving rise to oscillations have been implemented synthetically and studied by mathematical modeling. However, most of the available analyses generally neglect the coupling of regulatory circuits with the cellular “chassis” in which the circuits are embedded. For example, the intracellular macromolecular composition of fast-growing bacteria changes with growth rate. As a consequence, important parameters of gene expression, such as ribosome concentration or cell volume, are growth-rate dependent, ultimately coupling the dynamics of genetic circuits with cell physiology. This work addresses the effects of growth rate on the dynamics of a paradigmatic example of genetic oscillator, the repressilator. Making use of empirical growth-rate dependencies of parameters in bacteria, we show that the repressilator dynamics can switch between oscillations and convergence to a fixed point depending on the cellular state of growth, and thus on the nutrients it is fed. The physical support of the circuit (type of plasmid or gene positions on the chromosome) also plays an important role in determining the oscillation stability and the growth-rate dependence of period and amplitude. This analysis has potential application in the field of synthetic biology, and suggests that the coupling between endogenous genetic oscillators and cell physiology can have substantial consequences for their functionality.

Neuronal networks with NMDARs and lateral inhibition implement winner-takes-all

PubMed Central

Shoemaker, Patrick A.

2015-01-01

A neural circuit that relies on the electrical properties of NMDA synaptic receptors is shown by numerical and theoretical analysis to be capable of realizing the winner-takes-all function, a powerful computational primitive that is often attributed to biological nervous systems. This biophysically-plausible model employs global lateral inhibition in a simple feedback arrangement. As its inputs increase, high-gain and then bi- or multi-stable equilibrium states may be assumed in which there is significant depolarization of a single neuron and hyperpolarization or very weak depolarization of other neurons in the network. The state of the winning neuron conveys analog information about its input. The winner-takes-all characteristic depends on the nonmonotonic current-voltage relation of NMDA receptor ion channels, as well as neural thresholding, and the gain and nature of the inhibitory feedback. Dynamical regimes vary with input strength. Fixed points may become unstable as the network enters a winner-takes-all regime, which can lead to entrained oscillations. Under some conditions, oscillatory behavior can be interpreted as winner-takes-all in nature. Stable winner-takes-all behavior is typically recovered as inputs increase further, but with still larger inputs, the winner-takes-all characteristic is ultimately lost. Network stability may be enhanced by biologically plausible mechanisms. PMID:25741276

Analysis and Synthesis of Adaptive Neural Elements and Assembles

DTIC Science & Technology

1992-02-17

effects of neuromodulators on electrically activity. Based on the simulations it appears that there are potentially novel mechanisms with which modulatory...and Byrne, J.H. A learning rule based on empirically-derived activity-dependent neuromodulation supports operant conditioning in a small network...dependent neuromodulation can support operant conditioning in a small oscillatory network". 2. Society for Neuroscience Short Course on Neural

Effect of inhibitory feedback on correlated firing of spiking neural network.

PubMed

Xie, Jinli; Wang, Zhijie

2013-08-01

Understanding the properties and mechanisms that generate different forms of correlation is critical for determining their role in cortical processing. Researches on retina, visual cortex, sensory cortex, and computational model have suggested that fast correlation with high temporal precision appears consistent with common input, and correlation on a slow time scale likely involves feedback. Based on feedback spiking neural network model, we investigate the role of inhibitory feedback in shaping correlations on a time scale of 100 ms. Notably, the relationship between the correlation coefficient and inhibitory feedback strength is non-monotonic. Further, computational simulations show how firing rate and oscillatory activity form the basis of the mechanisms underlying this relationship. When the mean firing rate holds unvaried, the correlation coefficient increases monotonically with inhibitory feedback, but the correlation coefficient keeps decreasing when the network has no oscillatory activity. Our findings reveal that two opposing effects of the inhibitory feedback on the firing activity of the network contribute to the non-monotonic relationship between the correlation coefficient and the strength of the inhibitory feedback. The inhibitory feedback affects the correlated firing activity by modulating the intensity and regularity of the spike trains. Finally, the non-monotonic relationship is replicated with varying transmission delay and different spatial network structure, demonstrating the universality of the results.

Frequency and phase synchronization in large groups: Low dimensional description of synchronized clapping, firefly flashing, and cricket chirping

NASA Astrophysics Data System (ADS)

Ott, Edward; Antonsen, Thomas M.

2017-05-01

A common observation is that large groups of oscillatory biological units often have the ability to synchronize. A paradigmatic model of such behavior is provided by the Kuramoto model, which achieves synchronization through coupling of the phase dynamics of individual oscillators, while each oscillator maintains a different constant inherent natural frequency. Here we consider the biologically likely possibility that the oscillatory units may be capable of enhancing their synchronization ability by adaptive frequency dynamics. We propose a simple augmentation of the Kuramoto model which does this. We also show that, by the use of a previously developed technique [Ott and Antonsen, Chaos 18, 037113 (2008)], it is possible to reduce the resulting dynamics to a lower dimensional system for the macroscopic evolution of the oscillator ensemble. By employing this reduction, we investigate the dynamics of our system, finding a characteristic hysteretic behavior and enhancement of the quality of the achieved synchronization.

Explaining electric conductivity using the particle-in-a-box model: quantum superposition is the key

NASA Astrophysics Data System (ADS)

Sivanesan, Umaseh; Tsang, Kin; Izmaylov, Artur F.

2017-12-01

Most of the textbooks explaining electric conductivity in the context of quantum mechanics provide either incomplete or semi-classical explanations that are not connected with the elementary concepts of quantum mechanics. We illustrate the conduction phenomena using the simplest model system in quantum dynamics, a particle in a box (PIB). To induce the particle dynamics, a linear potential tilting the bottom of the box is introduced, which is equivalent to imposing a constant electric field for a charged particle. Although the PIB model represents a closed system that cannot have a flow of electrons through the system, we consider the oscillatory dynamics of the particle probability density as the analogue of the electric current. Relating the amplitude and other parameters of the particle oscillatory dynamics with the gap between the ground and excited states of the PIB model allows us to demonstrate one of the most basic dependencies of electric conductivity on the valence-conduction band gap of the material.

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

Wilson, Mark A.; Baljon, Arlette R. C.

The response of associating polymers with oscillatory shear is studied through large-scale simulations. A hybrid molecular dynamics (MD), Monte Carlo (MC) algorithm is employed. Polymer chains are modeled as a coarse-grained bead-spring system. Functionalized end groups, at both ends of the polymer chains, can form reversible bonds according to MC rules. Stress-strain curves show nonlinearities indicated by a non-ellipsoidal shape. We consider two types of nonlinearities. Type I occurs at a strain amplitude much larger than one, type II at a frequency at which the elastic storage modulus dominates the viscous loss modulus. In this last case, the network topologymore » resembles that of the system at rest. The reversible bonds are broken and chains stretch when the system moves away from the zero-strain position. For type I, the chains relax and the number of reversible bonds peaks when the system is near an extreme of the motion. During the movement to the other extreme of the cycle, first a stress overshoot occurs, then a yield accompanied by shear-banding. Lastly, the network restructures. Interestingly, the system periodically restores bonds between the same associating groups. Even though major restructuring occurs, the system remembers previous network topologies.« less

EEG functional connectivity, axon delays and white matter disease.

PubMed

Nunez, Paul L; Srinivasan, Ramesh; Fields, R Douglas

2015-01-01

Both structural and functional brain connectivities are closely linked to white matter disease. We discuss several such links of potential interest to neurologists, neurosurgeons, radiologists, and non-clinical neuroscientists. Treatment of brains as genuine complex systems suggests major emphasis on the multi-scale nature of brain connectivity and dynamic behavior. Cross-scale interactions of local, regional, and global networks are apparently responsible for much of EEG's oscillatory behaviors. Finite axon propagation speed, often assumed to be infinite in local network models, is central to our conceptual framework. Myelin controls axon speed, and the synchrony of impulse traffic between distant cortical regions appears to be critical for optimal mental performance and learning. Several experiments suggest that axon conduction speed is plastic, thereby altering the regional and global white matter connections that facilitate binding of remote local networks. Combined EEG and high resolution EEG can provide distinct multi-scale estimates of functional connectivity in both healthy and diseased brains with measures like frequency and phase spectra, covariance, and coherence. White matter disease may profoundly disrupt normal EEG coherence patterns, but currently these kinds of studies are rare in scientific labs and essentially missing from clinical environments. Copyright © 2014 International Federation of Clinical Neurophysiology. All rights reserved.

Unified thalamic model generates multiple distinct oscillations with state-dependent entrainment by stimulation

PubMed Central

2017-01-01

The thalamus plays a critical role in the genesis of thalamocortical oscillations, yet the underlying mechanisms remain elusive. To understand whether the isolated thalamus can generate multiple distinct oscillations, we developed a biophysical thalamic model to test the hypothesis that generation of and transition between distinct thalamic oscillations can be explained as a function of neuromodulation by acetylcholine (ACh) and norepinephrine (NE) and afferent synaptic excitation. Indeed, the model exhibited four distinct thalamic rhythms (delta, sleep spindle, alpha and gamma oscillations) that span the physiological states corresponding to different arousal levels from deep sleep to focused attention. Our simulation results indicate that generation of these distinct thalamic oscillations is a result of both intrinsic oscillatory cellular properties and specific network connectivity patterns. We then systematically varied the ACh/NE and input levels to generate a complete map of the different oscillatory states and their transitions. Lastly, we applied periodic stimulation to the thalamic network and found that entrainment of thalamic oscillations is highly state-dependent. Our results support the hypothesis that ACh/NE modulation and afferent excitation define thalamic oscillatory states and their response to brain stimulation. Our model proposes a broader and more central role of the thalamus in the genesis of multiple distinct thalamo-cortical rhythms than previously assumed. PMID:29073146

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

Chow, Colin M.; Yu, Hongyi; Jones, Aaron M.

In monolayer semiconductor transition metal dichalcogenides, the exciton–phonon interaction strongly affects the photocarrier dynamics. Here, we report on an unusual oscillatory enhancement of the neutral exciton photoluminescence with the excitation laser frequency in monolayer MoSe 2. The frequency of oscillation matches that of the M-point longitudinal acoustic phonon, LA(M), suggesting the significance of zone-edge acoustic phonons and hence the deformation potential in exciton-phonon coupling in MoSe 2. Moreover, oscillatory behavior is observed in the steady-state emission linewidth and in time-resolved PLE data, which reveals variation with excitation energy in the exciton lifetime. These results clearly expose the key role playedmore » by phonons in the exciton formation and relaxation dynamics of two-dimensional van der Waals semiconductors.« less

Curved-flow, rolling-flow, and oscillatory pure-yawing wind-tunnel test methods for determination of dynamic stability derivatives

NASA Technical Reports Server (NTRS)

Chambers, J. R.; Grafton, S. B.; Lutze, F. H.

1981-01-01

Dynamic stability derivatives are evaluated on the basis of rolling-flow, curved-flow and snaking tests. Attention is given to the hardware associated with curved-flow, rolling-flow and oscillatory pure-yawing wind-tunnel tests. It is found that the snaking technique, when combined with linear- and forced-oscillation methods, yields an important method for evaluating beta derivatives for current configurations at high angles of attack. Since the rolling flow model is fixed during testing, forced oscillations may be imparted to the model, permitting the measurement of damping and cross-derivatives. These results, when coupled with basic rolling-flow or rotary-balance data, yield a highly accurate mathematical model for studies of incipient spin and spin entry.

Optical intensity dynamics in a five-emitter semiconductor array laser

NASA Astrophysics Data System (ADS)

Williams, Matthew O.; Kutz, J. Nathan

2009-06-01

The intensity dynamics of a five-emitter laser array subject to a linearly decreasing injection current are examined numerically. We have matched the results of the numerical model to an experimental AlGaAs quantum-dot array laser and have achieved the same robust oscillatory power output with a nearly π phase shift between emitters that was observed in experiments. Due to the linearly decreasing injection current, the output power of the waveguide decreases as a function of waveguide number. For injection currents ranging from 380 to 500 mA, the oscillatory behavior persists with only a slight change in phase difference. However, the fundamental frequency of oscillation increases with injection current, and higher harmonics as well as some fine structures are produced.

Oscillatory Dynamics of One-Dimensional Homogeneous Granular Chains

NASA Astrophysics Data System (ADS)

Starosvetsky, Yuli; Jayaprakash, K. R.; Hasan, Md. Arif; Vakakis, Alexander F.

The acoustics of the homogeneous granular chains has been studied extensively both numerically and experimentally in the references cited in the previous chapters. This chapter focuses on the oscillatory behavior of finite dimensional homogeneous granular chains. It is well known that normal vibration modes are the building blocks of the vibrations of linear systems due to the applicability of the principle of superposition. One the other hand, nonlinear theory is deprived of such a general superposition principle (although special cases of nonlinear superpositions do exist), but nonlinear normal modes ‒ NNMs still play an important role in the forced and resonance dynamics of these systems. In their basic definition [1], NNMs were defined as time-periodic nonlinear oscillations of discrete or continuous dynamical systems where all coordinates (degrees-of-freedom) oscillate in-unison with the same frequency; further extensions of this definition have been considered to account for NNMs of systems with internal resonances [2]...

Stabilization of dynamics of oscillatory systems by nonautonomous perturbation.

PubMed

Lucas, Maxime; Newman, Julian; Stefanovska, Aneta

2018-04-01

Synchronization and stability under periodic oscillatory driving are well understood, but little is known about the effects of aperiodic driving, despite its abundance in nature. Here, we consider oscillators subject to driving with slowly varying frequency, and investigate both short-term and long-term stability properties. For a phase oscillator, we find that, counterintuitively, such variation is guaranteed to enlarge the Arnold tongue in parameter space. Using analytical and numerical methods that provide information on time-variable dynamical properties, we find that the growth of the Arnold tongue is specifically due to the growth of a region of intermittent synchronization where trajectories alternate between short-term stability and short-term neutral stability, giving rise to stability on average. We also present examples of higher-dimensional nonlinear oscillators where a similar stabilization phenomenon is numerically observed. Our findings help support the case that in general, deterministic nonautonomous perturbation is a very good candidate for stabilizing complex dynamics.

Stabilization of dynamics of oscillatory systems by nonautonomous perturbation

NASA Astrophysics Data System (ADS)

Lucas, Maxime; Newman, Julian; Stefanovska, Aneta

2018-04-01

Synchronization and stability under periodic oscillatory driving are well understood, but little is known about the effects of aperiodic driving, despite its abundance in nature. Here, we consider oscillators subject to driving with slowly varying frequency, and investigate both short-term and long-term stability properties. For a phase oscillator, we find that, counterintuitively, such variation is guaranteed to enlarge the Arnold tongue in parameter space. Using analytical and numerical methods that provide information on time-variable dynamical properties, we find that the growth of the Arnold tongue is specifically due to the growth of a region of intermittent synchronization where trajectories alternate between short-term stability and short-term neutral stability, giving rise to stability on average. We also present examples of higher-dimensional nonlinear oscillators where a similar stabilization phenomenon is numerically observed. Our findings help support the case that in general, deterministic nonautonomous perturbation is a very good candidate for stabilizing complex dynamics.

Dynamical current-induced ferromagnetic and antiferromagnetic resonances

NASA Astrophysics Data System (ADS)

Guimarães, F. S. M.; Lounis, S.; Costa, A. T.; Muniz, R. B.

2015-12-01

We demonstrate that ferromagnetic and antiferromagnetic excitations can be triggered by the dynamical spin accumulations induced by the bulk and surface contributions of the spin Hall effect. Due to the spin-orbit interaction, a time-dependent spin density is generated by an oscillatory electric field applied parallel to the atomic planes of Fe/W(110) multilayers. For symmetric trilayers of Fe/W/Fe in which the Fe layers are ferromagnetically coupled, we demonstrate that only the collective out-of-phase precession mode is excited, while the uniform (in-phase) mode remains silent. When they are antiferromagnetically coupled, the oscillatory electric field sets the Fe magnetizations into elliptical precession motions with opposite angular velocities. The manipulation of different collective spin-wave dynamical modes through the engineering of the multilayers and their thicknesses may be used to develop ultrafast spintronics devices. Our work provides a general framework that probes the realistic responses of materials in the time or frequency domain.

Visualization of Notch signaling oscillation in cells and tissues.

PubMed

Shimojo, Hiromi; Harima, Yukiko; Kageyama, Ryoichiro

2014-01-01

The Notch signaling effectors Hes1 and Hes7 exhibit oscillatory expression with a period of about 2-3 h during embryogenesis. Hes1 oscillation is important for proliferation and differentiation of neural stem cells, whereas Hes7 oscillation regulates periodic formation of somites. Continuous expression of Hes1 and Hes7 inhibits these developmental processes. Thus, expression dynamics are very important for gene functions, but it is difficult to distinguish between oscillatory and persistent expression by conventional methods such as in situ hybridization and immunostaining. Here, we describe time-lapse imaging methods using destabilized luciferase reporters and a highly sensitive cooled charge-coupled device camera, which can monitor dynamic gene expression. Furthermore, the expression of two genes can be examined simultaneously by a dual reporter system using two-color luciferase reporters. Time-lapse imaging analyses reveal how dynamically gene expression changes in many biological events.

An Inverse Neural Controller Based on the Applicability Domain of RBF Network Models

PubMed Central

Alexandridis, Alex; Stogiannos, Marios; Papaioannou, Nikolaos; Zois, Elias; Sarimveis, Haralambos

2018-01-01

This paper presents a novel methodology of generic nature for controlling nonlinear systems, using inverse radial basis function neural network models, which may combine diverse data originating from various sources. The algorithm starts by applying the particle swarm optimization-based non-symmetric variant of the fuzzy means (PSO-NSFM) algorithm so that an approximation of the inverse system dynamics is obtained. PSO-NSFM offers models of high accuracy combined with small network structures. Next, the applicability domain concept is suitably tailored and embedded into the proposed control structure in order to ensure that extrapolation is avoided in the controller predictions. Finally, an error correction term, estimating the error produced by the unmodeled dynamics and/or unmeasured external disturbances, is included to the control scheme to increase robustness. The resulting controller guarantees bounded input-bounded state (BIBS) stability for the closed loop system when the open loop system is BIBS stable. The proposed methodology is evaluated on two different control problems, namely, the control of an experimental armature-controlled direct current (DC) motor and the stabilization of a highly nonlinear simulated inverted pendulum. For each one of these problems, appropriate case studies are tested, in which a conventional neural controller employing inverse models and a PID controller are also applied. The results reveal the ability of the proposed control scheme to handle and manipulate diverse data through a data fusion approach and illustrate the superiority of the method in terms of faster and less oscillatory responses. PMID:29361781

Light-driven dynamic Archimedes spirals and periodic oscillatory patterns of topological solitons in anisotropic soft matter

DOE PAGES

Martinez, Angel; Smalyukh, Ivan I.

2015-02-12

Oscillatory and excitable systems very commonly exhibit formation of dynamic non-equilibrium patterns. For example, rotating spiral patterns are observed in biological, chemical, and physical systems ranging from organization of slime mold cells to Belousov-Zhabotinsky reactions, and to crystal growth from nuclei with screw dislocations. Here we describe spontaneous formation of spiral waves and a large variety of other dynamic patterns in anisotropic soft matter driven by low-intensity light. The unstructured ambient or microscope light illumination of thin liquid crystal films in contact with a self-assembled azobenzene monolayer causes spontaneous formation, rich spatial organization, and dynamics of twisted domains and topologicalmore » solitons accompanied by the dynamic patterning of azobenzene group orientations within the monolayer. Linearly polarized incident light interacts with the twisted liquid crystalline domains, mimicking their dynamics and yielding patterns in the polarization state of transmitted light, which can be transformed to similar dynamic patterns in its intensity and interference color. This shows that the delicate light-soft-matter interaction can yield complex self-patterning of both. Finally, we uncover underpinning physical mechanisms and discuss potential uses.« less

Dysfunction of sensory oscillations in Autism Spectrum Disorder

PubMed Central

Simon, David M.; Wallace, Mark T.

2016-01-01

Autism Spectrum Disorder (ASD) is a highly prevalent developmental disability characterized by deficits in social communication and interaction, restricted interests, and repetitive behaviors. Recently, anomalous sensory and perceptual function has gained an increased level of recognition as an important feature of ASD. A specific impairment in the ability to integrate information across brain networks has been proposed to contribute to these disruptions. A crucial mechanism for these integrative processes is the rhythmic synchronization of neuronal excitability across neural populations; collectively known as oscillations. In ASD there is believed to be a deficit in the ability to efficiently couple functional neural networks using these oscillations. This review discusses evidence for disruptions in oscillatory synchronization in ASD, and how disturbance of this neural mechanism contributes to alterations in sensory and perceptual function. The review also frames oscillatory data from the perspective of prevailing neurobiologically-inspired theories of ASD. PMID:27451342

Determining the structure-mechanics relationships of dense microtubule networks with confocal microscopy and magnetic tweezers-based microrheology.

PubMed

Yang, Yali; Valentine, Megan T

2013-01-01

The microtubule (MT) cytoskeleton is essential in maintaining the shape, strength, and organization of cells. Its spatiotemporal organization is fundamental for numerous dynamic biological processes, and mechanical stress within the MT cytoskeleton provides an important signaling mechanism in mitosis and neural development. This raises important questions about the relationships between structure and mechanics in complex MT structures. In vitro, reconstituted cytoskeletal networks provide a minimal model of cell mechanics while also providing a testing ground for the fundamental polymer physics of stiff polymer gels. Here, we describe our development and implementation of a broad tool kit to study structure-mechanics relationships in reconstituted MT networks, including protocols for the assembly of entangled and cross-linked MT networks, fluorescence imaging, microstructure characterization, construction and calibration of magnetic tweezers devices, and mechanical data collection and analysis. In particular, we present the design and assembly of three neodymium iron boron (NdFeB)-based magnetic tweezers devices optimized for use with MT networks: (1) high-force magnetic tweezers devices that enable the application of nano-Newton forces and possible meso- to macroscale materials characterization; (2) ring-shaped NdFeB-based magnetic tweezers devices that enable oscillatory microrheology measurements; and (3) portable magnetic tweezers devices that enable direct visualization of microscale deformation in soft materials under applied force. Copyright © 2013 Elsevier Inc. All rights reserved.

In vitro Neurons in Mammalian Cortical Layer 4 Exhibit Intrinsic Oscillatory Activity in the 10- to 50-Hz Frequency Range

NASA Astrophysics Data System (ADS)

Llinas, Rodolfo R.; Grace, Anthony A.; Yarom, Yosef

1991-02-01

We report here the presence of fast subthreshold oscillatory potentials recorded in vitro from neurons within layer 4 of the guinea pig frontal cortex. Two types of oscillatory neurons were recorded: (i) One type exhibited subthreshold oscillations whose frequency increased with membrane depolarization and encompassed a range of 10-45 Hz. Action potentials in this type of neuron demonstrated clear after-hyperpolarizations. (ii) The second type of neuron was characterized by narrow-frequency oscillations near 35-50 Hz. These oscillations often outlasted the initiating depolarizing stimulus. No calcium component could be identified in their action potential. In both types of cell the subthreshold oscillations were tetrodotoxin-sensitive, indicating that the depolarizing phase of the oscillation was generated by a voltage-dependent sodium conductance. The initial depolarizing phase was followed by a potassium conductance responsible for the falling phase of the oscillatory wave. In both types of cell, the subthreshold oscillation could trigger spikes at the oscillatory frequency, if the membrane was sufficiently depolarized. Combining intracellular recordings with Lucifer yellow staining showed that the narrow-frequency oscillatory activity was produced by a sparsely spinous interneuron located in layer 4 of the cortex. This neuron has extensive local axonal collaterals that ramify in layers 3 and 4 such that they may contribute to the columnar synchronization of activity in the 40- to 50-Hz range. Cortical activity in this frequency range has been proposed as the basis for the "conjunctive properties" of central nervous system networks.

Scalability of Asynchronous Networks Is Limited by One-to-One Mapping between Effective Connectivity and Correlations

PubMed Central

van Albada, Sacha Jennifer; Helias, Moritz; Diesmann, Markus

2015-01-01

Network models are routinely downscaled compared to nature in terms of numbers of nodes or edges because of a lack of computational resources, often without explicit mention of the limitations this entails. While reliable methods have long existed to adjust parameters such that the first-order statistics of network dynamics are conserved, here we show that limitations already arise if also second-order statistics are to be maintained. The temporal structure of pairwise averaged correlations in the activity of recurrent networks is determined by the effective population-level connectivity. We first show that in general the converse is also true and explicitly mention degenerate cases when this one-to-one relationship does not hold. The one-to-one correspondence between effective connectivity and the temporal structure of pairwise averaged correlations implies that network scalings should preserve the effective connectivity if pairwise averaged correlations are to be held constant. Changes in effective connectivity can even push a network from a linearly stable to an unstable, oscillatory regime and vice versa. On this basis, we derive conditions for the preservation of both mean population-averaged activities and pairwise averaged correlations under a change in numbers of neurons or synapses in the asynchronous regime typical of cortical networks. We find that mean activities and correlation structure can be maintained by an appropriate scaling of the synaptic weights, but only over a range of numbers of synapses that is limited by the variance of external inputs to the network. Our results therefore show that the reducibility of asynchronous networks is fundamentally limited. PMID:26325661

Gelatinisation kinetics of corn and chickpea starches using DSC, RVA, and dynamic rheometry

USDA-ARS?s Scientific Manuscript database

The gelatinisation kinetics (non-isothermal) of corn and chickpea starches at different heating rates were calculated using differential scanning calorimetry (DSC), rapid visco analyser (RVA), and oscillatory dynamic rheometry. The data obtained from the DSC thermogram and the RVA profiles were fitt...

Unzip instabilities: Straight to oscillatory transitions in the cutting of thin polymer sheets

NASA Astrophysics Data System (ADS)

Reis, P. M.; Kumar, A.; Shattuck, M. D.; Roman, B.

2008-06-01

We report an experimental investigation of the cutting of a thin brittle polymer sheet with a blunt tool. It was recently shown that the fracture path becomes oscillatory when the tool is much wider than the sheet thickness. Here we uncover two novel transitions from straight to oscillatory fracture by varying either the tilt angle of the tool or the speed of cutting, respectively. We denote these by angle and speed unzip instabilities and analyze them by quantifying both the dynamics of the crack tip and the final shapes of the fracture paths. Moreover, for the speed unzip instability, the straight crack lip obtained at low speeds exhibits out-of-plane buckling undulations (as opposed to being flat above the instability threshold) suggesting a transition from ductile to brittle fracture.

Stochastic amplification and signaling in enzymatic futile cycles through noise-induced bistability with oscillations

NASA Astrophysics Data System (ADS)

Samoilov, Michael; Plyasunov, Sergey; Arkin, Adam P.

2005-02-01

Stochastic effects in biomolecular systems have now been recognized as a major physiologically and evolutionarily important factor in the development and function of many living organisms. Nevertheless, they are often thought of as providing only moderate refinements to the behaviors otherwise predicted by the classical deterministic system description. In this work we show by using both analytical and numerical investigation that at least in one ubiquitous class of (bio)chemical-reaction mechanisms, enzymatic futile cycles, the external noise may induce a bistable oscillatory (dynamic switching) behavior that is both quantitatively and qualitatively different from what is predicted or possible deterministically. We further demonstrate that the noise required to produce these distinct properties can itself be caused by a set of auxiliary chemical reactions, making it feasible for biological systems of sufficient complexity to generate such behavior internally. This new stochastic dynamics then serves to confer additional functional modalities on the enzymatic futile cycle mechanism that include stochastic amplification and signaling, the characteristics of which could be controlled by both the type and parameters of the driving noise. Hence, such noise-induced phenomena may, among other roles, potentially offer a novel type of control mechanism in pathways that contain these cycles and the like units. In particular, observations of endogenous or externally driven noise-induced dynamics in regulatory networks may thus provide additional insight into their topology, structure, and kinetics. network motif | signal transduction | chemical reaction | synthetic biology | systems biology

A Dynamical Model of Pitch Memory Provides an Improved Basis for Implied Harmony Estimation.

PubMed

Kim, Ji Chul

2017-01-01

Tonal melody can imply vertical harmony through a sequence of tones. Current methods for automatic chord estimation commonly use chroma-based features extracted from audio signals. However, the implied harmony of unaccompanied melodies can be difficult to estimate on the basis of chroma content in the presence of frequent nonchord tones. Here we present a novel approach to automatic chord estimation based on the human perception of pitch sequences. We use cohesion and inhibition between pitches in auditory short-term memory to differentiate chord tones and nonchord tones in tonal melodies. We model short-term pitch memory as a gradient frequency neural network, which is a biologically realistic model of auditory neural processing. The model is a dynamical system consisting of a network of tonotopically tuned nonlinear oscillators driven by audio signals. The oscillators interact with each other through nonlinear resonance and lateral inhibition, and the pattern of oscillatory traces emerging from the interactions is taken as a measure of pitch salience. We test the model with a collection of unaccompanied tonal melodies to evaluate it as a feature extractor for chord estimation. We show that chord tones are selectively enhanced in the response of the model, thereby increasing the accuracy of implied harmony estimation. We also find that, like other existing features for chord estimation, the performance of the model can be improved by using segmented input signals. We discuss possible ways to expand the present model into a full chord estimation system within the dynamical systems framework.

Source Space Estimation of Oscillatory Power and Brain Connectivity in Tinnitus

PubMed Central

Zobay, Oliver; Palmer, Alan R.; Hall, Deborah A.; Sereda, Magdalena; Adjamian, Peyman

2015-01-01

Tinnitus is the perception of an internally generated sound that is postulated to emerge as a result of structural and functional changes in the brain. However, the precise pathophysiology of tinnitus remains unknown. Llinas’ thalamocortical dysrhythmia model suggests that neural deafferentation due to hearing loss causes a dysregulation of coherent activity between thalamus and auditory cortex. This leads to a pathological coupling of theta and gamma oscillatory activity in the resting state, localised to the auditory cortex where normally alpha oscillations should occur. Numerous studies also suggest that tinnitus perception relies on the interplay between auditory and non-auditory brain areas. According to the Global Brain Model, a network of global fronto—parietal—cingulate areas is important in the generation and maintenance of the conscious perception of tinnitus. Thus, the distress experienced by many individuals with tinnitus is related to the top—down influence of this global network on auditory areas. In this magnetoencephalographic study, we compare resting-state oscillatory activity of tinnitus participants and normal-hearing controls to examine effects on spectral power as well as functional and effective connectivity. The analysis is based on beamformer source projection and an atlas-based region-of-interest approach. We find increased functional connectivity within the auditory cortices in the alpha band. A significant increase is also found for the effective connectivity from a global brain network to the auditory cortices in the alpha and beta bands. We do not find evidence of effects on spectral power. Overall, our results provide only limited support for the thalamocortical dysrhythmia and Global Brain models of tinnitus. PMID:25799178

Assessment of UVA-Riboflavin Corneal Cross-Linking Using Small Amplitude Oscillatory Shear Measurements.

PubMed

Aslanides, Ioannis M; Dessi, Claudia; Georgoudis, Panagiotis; Charalambidis, Georgios; Vlassopoulos, Dimitris; Coutsolelos, Athanassios G; Kymionis, George; Mukherjee, Achyut; Kitsopoulos, Theofanis N

2016-04-01

The effect of ultraviolet (UV)-riboflavin cross-linking (CXL) has been measured primarily using the strip extensometry technique. We propose a simple and reliable methodology for the assessment of CXL treatment by using an established rheologic protocol based on small amplitude oscillatory shear (SAOS) measurements. It provides information on the average cross-link density and the elastic modulus of treated cornea samples. Three fresh postmortem porcine corneas were used to study the feasibility of the technique, one serving as control and two receiving corneal collagen cross-linking treatment. Subsequently, five pairs of fresh postmortem porcine corneas received corneal collagen cross-linking treatment with riboflavin and UVA-irradiation (370 nm; irradiance of 3 mW/cm2) for 30 minutes (Dresden protocol); the contralateral porcine corneas were used as control samples. After the treatment, the linear viscoelastic moduli of the corneal samples were measured using SAOS measurements and the average cross-linking densities extracted. For all cases investigated, the dynamic moduli of the cross-linked corneas were higher compared to those of the corresponding control samples. The increase of the elastic modulus of the treated samples was between 122% and 1750%. The difference was statistically significant for all tested samples (P = 0.018, 2-tailed t-test). We report a simple and accurate methodology for quantifying the effects of cross-linking on porcine corneas treated with the Dresden protocol by means of SAOS measurements in the linear regime. The measured dynamic moduli, elastic and viscous modulus, represent the energy storage and energy dissipation, respectively. Hence, they provide a means to assess the changing physical properties of the cross-linked collagen networks after CXL treatment.

Regional gas transport in the heterogeneous lung during oscillatory ventilation.

PubMed

Herrmann, Jacob; Tawhai, Merryn H; Kaczka, David W

2016-12-01

Regional ventilation in the injured lung is heterogeneous and frequency dependent, making it difficult to predict how an oscillatory flow waveform at a specified frequency will be distributed throughout the periphery. To predict the impact of mechanical heterogeneity on regional ventilation distribution and gas transport, we developed a computational model of distributed gas flow and CO 2 elimination during oscillatory ventilation from 0.1 to 30 Hz. The model consists of a three-dimensional airway network of a canine lung, with heterogeneous parenchymal tissues to mimic effects of gravity and injury. Model CO 2 elimination during single frequency oscillation was validated against previously published experimental data (Venegas JG, Hales CA, Strieder DJ, J Appl Physiol 60: 1025-1030, 1986). Simulations of gas transport demonstrated a critical transition in flow distribution at the resonant frequency, where the reactive components of mechanical impedance due to airway inertia and parenchymal elastance were equal. For frequencies above resonance, the distribution of ventilation became spatially clustered and frequency dependent. These results highlight the importance of oscillatory frequency in managing the regional distribution of ventilation and gas exchange in the heterogeneous lung. Copyright © 2016 the American Physiological Society.

Modality-specific spectral dynamics in response to visual and tactile sequential shape information processing tasks: An MEG study using multivariate pattern classification analysis.

PubMed

Gohel, Bakul; Lee, Peter; Jeong, Yong

2016-08-01

Brain regions that respond to more than one sensory modality are characterized as multisensory regions. Studies on the processing of shape or object information have revealed recruitment of the lateral occipital cortex, posterior parietal cortex, and other regions regardless of input sensory modalities. However, it remains unknown whether such regions show similar (modality-invariant) or different (modality-specific) neural oscillatory dynamics, as recorded using magnetoencephalography (MEG), in response to identical shape information processing tasks delivered to different sensory modalities. Modality-invariant or modality-specific neural oscillatory dynamics indirectly suggest modality-independent or modality-dependent participation of particular brain regions, respectively. Therefore, this study investigated the modality-specificity of neural oscillatory dynamics in the form of spectral power modulation patterns in response to visual and tactile sequential shape-processing tasks that are well-matched in terms of speed and content between the sensory modalities. Task-related changes in spectral power modulation and differences in spectral power modulation between sensory modalities were investigated at source-space (voxel) level, using a multivariate pattern classification (MVPC) approach. Additionally, whole analyses were extended from the voxel level to the independent-component level to take account of signal leakage effects caused by inverse solution. The modality-specific spectral dynamics in multisensory and higher-order brain regions, such as the lateral occipital cortex, posterior parietal cortex, inferior temporal cortex, and other brain regions, showed task-related modulation in response to both sensory modalities. This suggests modality-dependency of such brain regions on the input sensory modality for sequential shape-information processing. Copyright © 2016 Elsevier B.V. All rights reserved.

Periodic bidirectional associative memory neural networks with distributed delays

NASA Astrophysics Data System (ADS)

Chen, Anping; Huang, Lihong; Liu, Zhigang; Cao, Jinde

2006-05-01

Some sufficient conditions are obtained for the existence and global exponential stability of a periodic solution to the general bidirectional associative memory (BAM) neural networks with distributed delays by using the continuation theorem of Mawhin's coincidence degree theory and the Lyapunov functional method and the Young's inequality technique. These results are helpful for designing a globally exponentially stable and periodic oscillatory BAM neural network, and the conditions can be easily verified and be applied in practice. An example is also given to illustrate our results.

In silico determination of the effect of multi-target drugs on calcium dynamics signaling network underlying sea urchin spermatozoa motility.

PubMed

Espinal-Enríquez, Jesús; Darszon, Alberto; Guerrero, Adán; Martínez-Mekler, Gustavo

2014-01-01

The motility of spermatozoa of both Lytechinus pictus and Strongylocentrotus purpuratus sea urchin species is modulated by the egg-derived decapeptide speract via an oscillatory [Ca2+]-dependent signaling pathway. Comprehension of this pathway is hence directly related to the understanding of regulated sperm swimming. Niflumic acid (NFA), a nonsteroidal anti-inflammatory drug alters several ion channels. Though unspecific, NFA profoundly affects how sea urchin sperm respond to speract, increasing the [Ca2+]i oscillation period, amplitude, peak and average level values of the responses in immobilized and swimming cells. A previous logical network model we developed for the [Ca2+] dynamics of speract signaling cascade in sea urchin sperm allows integrated dissection of individual and multiple actions of NFA. Among the channels affected by NFA are: hyperpolarization-activated and cyclic nucleotide gated Na+ channels (HCN), [Ca2+]-dependent Cl- channels (CaCC) and [Ca2+]-dependent K+ channels (CaKC), all present in the sea urchin genome. Here, using our model we investigated the effect of blocking in silico HCN and CaCC channels suggested by experiments. Regarding CaKC channels, arguments can be provided for either their blockage or activation by NFA. Our study yielded two scenarios compliant with experimental observations: i) under CaKC inhibition, this [Ca2+]-dependent K+ channel should be different from the Slo1 channel and ii) under activation of the CaKC channel, another [Ca2+] channel not considered previously in the network is required, such as the pH-dependent CatSper channel. Additionally, our findings predict cause-effect relations resulting from a selective inhibition of those channels. Knowledge of these relations may be of consequence for a variety of electrophysiological studies and have an impact on drug related investigations. Our study contributes to a better grasp of the network dynamics and suggests further experimental work.

In Silico Determination of the Effect of Multi-Target Drugs on Calcium Dynamics Signaling Network Underlying Sea Urchin Spermatozoa Motility

PubMed Central

Espinal-Enríquez, Jesús; Darszon, Alberto; Guerrero, Adán; Martínez-Mekler, Gustavo

2014-01-01

The motility of spermatozoa of both Lytechinus pictus and Strongylocentrotus purpuratus sea urchin species is modulated by the egg-derived decapeptide speract via an oscillatory [Ca2+]-dependent signaling pathway. Comprehension of this pathway is hence directly related to the understanding of regulated sperm swimming. Niflumic acid (NFA), a nonsteroidal anti-inflammatory drug alters several ion channels. Though unspecific, NFA profoundly affects how sea urchin sperm respond to speract, increasing the [Ca2+]i oscillation period, amplitude, peak and average level values of the responses in immobilized and swimming cells. A previous logical network model we developed for the [Ca2+] dynamics of speract signaling cascade in sea urchin sperm allows integrated dissection of individual and multiple actions of NFA. Among the channels affected by NFA are: hyperpolarization-activated and cyclic nucleotide gated Na+ channels (HCN), [Ca2+]-dependent Cl− channels (CaCC) and [Ca2+]-dependent K+ channels (CaKC), all present in the sea urchin genome. Here, using our model we investigated the effect of blocking in silico HCN and CaCC channels suggested by experiments. Regarding CaKC channels, arguments can be provided for either their blockage or activation by NFA. Our study yielded two scenarios compliant with experimental observations: i) under CaKC inhibition, this [Ca2+]-dependent K+ channel should be different from the Slo1 channel and ii) under activation of the CaKC channel, another [Ca2+] channel not considered previously in the network is required, such as the pH-dependent CatSper channel. Additionally, our findings predict cause-effect relations resulting from a selective inhibition of those channels. Knowledge of these relations may be of consequence for a variety of electrophysiological studies and have an impact on drug related investigations. Our study contributes to a better grasp of the network dynamics and suggests further experimental work. PMID:25162222

Modeling gene regulatory network motifs using statecharts

PubMed Central

2012-01-01

Background Gene regulatory networks are widely used by biologists to describe the interactions among genes, proteins and other components at the intra-cellular level. Recently, a great effort has been devoted to give gene regulatory networks a formal semantics based on existing computational frameworks. For this purpose, we consider Statecharts, which are a modular, hierarchical and executable formal model widely used to represent software systems. We use Statecharts for modeling small and recurring patterns of interactions in gene regulatory networks, called motifs. Results We present an improved method for modeling gene regulatory network motifs using Statecharts and we describe the successful modeling of several motifs, including those which could not be modeled or whose models could not be distinguished using the method of a previous proposal. We model motifs in an easy and intuitive way by taking advantage of the visual features of Statecharts. Our modeling approach is able to simulate some interesting temporal properties of gene regulatory network motifs: the delay in the activation and the deactivation of the "output" gene in the coherent type-1 feedforward loop, the pulse in the incoherent type-1 feedforward loop, the bistability nature of double positive and double negative feedback loops, the oscillatory behavior of the negative feedback loop, and the "lock-in" effect of positive autoregulation. Conclusions We present a Statecharts-based approach for the modeling of gene regulatory network motifs in biological systems. The basic motifs used to build more complex networks (that is, simple regulation, reciprocal regulation, feedback loop, feedforward loop, and autoregulation) can be faithfully described and their temporal dynamics can be analyzed. PMID:22536967

Periodic, Quasi-periodic and Chaotic Dynamics in Simple Gene Elements with Time Delays

PubMed Central

Suzuki, Yoko; Lu, Mingyang; Ben-Jacob, Eshel; Onuchic, José N.

2016-01-01

Regulatory gene circuit motifs play crucial roles in performing and maintaining vital cellular functions. Frequently, theoretical studies of gene circuits focus on steady-state behaviors and do not include time delays. In this study, the inclusion of time delays is shown to entirely change the time-dependent dynamics for even the simplest possible circuits with one and two gene elements with self and cross regulations. These elements can give rise to rich behaviors including periodic, quasi-periodic, weak chaotic, strong chaotic and intermittent dynamics. We introduce a special power-spectrum-based method to characterize and discriminate these dynamical modes quantitatively. Our simulation results suggest that, while a single negative feedback loop of either one- or two-gene element can only have periodic dynamics, the elements with two positive/negative feedback loops are the minimalist elements to have chaotic dynamics. These elements typically have one negative feedback loop that generates oscillations, and another unit that allows frequent switches among multiple steady states or between oscillatory and non-oscillatory dynamics. Possible dynamical features of several simple one- and two-gene elements are presented in details. Discussion is presented for possible roles of the chaotic behavior in the robustness of cellular functions and diseases, for example, in the context of cancer. PMID:26876008

Periodic, Quasi-periodic and Chaotic Dynamics in Simple Gene Elements with Time Delays

NASA Astrophysics Data System (ADS)

Suzuki, Yoko; Lu, Mingyang; Ben-Jacob, Eshel; Onuchic, José N.

2016-02-01

Regulatory gene circuit motifs play crucial roles in performing and maintaining vital cellular functions. Frequently, theoretical studies of gene circuits focus on steady-state behaviors and do not include time delays. In this study, the inclusion of time delays is shown to entirely change the time-dependent dynamics for even the simplest possible circuits with one and two gene elements with self and cross regulations. These elements can give rise to rich behaviors including periodic, quasi-periodic, weak chaotic, strong chaotic and intermittent dynamics. We introduce a special power-spectrum-based method to characterize and discriminate these dynamical modes quantitatively. Our simulation results suggest that, while a single negative feedback loop of either one- or two-gene element can only have periodic dynamics, the elements with two positive/negative feedback loops are the minimalist elements to have chaotic dynamics. These elements typically have one negative feedback loop that generates oscillations, and another unit that allows frequent switches among multiple steady states or between oscillatory and non-oscillatory dynamics. Possible dynamical features of several simple one- and two-gene elements are presented in details. Discussion is presented for possible roles of the chaotic behavior in the robustness of cellular functions and diseases, for example, in the context of cancer.

Effects of stochastic time-delayed feedback on a dynamical system modeling a chemical oscillator.

PubMed

González Ochoa, Héctor O; Perales, Gualberto Solís; Epstein, Irving R; Femat, Ricardo

2018-05-01

We examine how stochastic time-delayed negative feedback affects the dynamical behavior of a model oscillatory reaction. We apply constant and stochastic time-delayed negative feedbacks to a point Field-Körös-Noyes photosensitive oscillator and compare their effects. Negative feedback is applied in the form of simulated inhibitory electromagnetic radiation with an intensity proportional to the concentration of oxidized light-sensitive catalyst in the oscillator. We first characterize the system under nondelayed inhibitory feedback; then we explore and compare the effects of constant (deterministic) versus stochastic time-delayed feedback. We find that the oscillatory amplitude, frequency, and waveform are essentially preserved when low-dispersion stochastic delayed feedback is used, whereas small but measurable changes appear when a large dispersion is applied.

Effects of stochastic time-delayed feedback on a dynamical system modeling a chemical oscillator

NASA Astrophysics Data System (ADS)

González Ochoa, Héctor O.; Perales, Gualberto Solís; Epstein, Irving R.; Femat, Ricardo

2018-05-01

We examine how stochastic time-delayed negative feedback affects the dynamical behavior of a model oscillatory reaction. We apply constant and stochastic time-delayed negative feedbacks to a point Field-Körös-Noyes photosensitive oscillator and compare their effects. Negative feedback is applied in the form of simulated inhibitory electromagnetic radiation with an intensity proportional to the concentration of oxidized light-sensitive catalyst in the oscillator. We first characterize the system under nondelayed inhibitory feedback; then we explore and compare the effects of constant (deterministic) versus stochastic time-delayed feedback. We find that the oscillatory amplitude, frequency, and waveform are essentially preserved when low-dispersion stochastic delayed feedback is used, whereas small but measurable changes appear when a large dispersion is applied.

Dynamics of liquid bridges inside microchannels subject to pure oscillatory flows

NASA Astrophysics Data System (ADS)

Ahmadlouydarab, Majid; Azaiez, Jalel; Chen, Zhangxin

2014-11-01

We report on 2D simulations of liquid bridges' dynamics in microchannels of uniform wettability and subject to external oscillatory flows. The flow equations were solved using the Cahn-Hilliard diffuse-interface formulation and the finite element method with unstructured grid. It was found that regardless of the wettability properties of the microchannel walls, there is a critical frequency above which the bridge shows perpetual periodic oscillatory motion. Below that critical frequency, the liquid bridge ruptures when the channel walls are philic and detaches from the surface when they are phobic. This critical frequency depends on the viscosity ratio, oscillation amplitude and geometric aspect ratio of the bridge. It was also found that the flow velocity is out of phase with the footprint/throat lengths and that the latter two show a phase difference. These differences were explained in terms of the motion of the two contact lines on the substrates and the deformation of the fluid-fluid interfaces. To characterize the behavior of the liquid bridge, two quantitative parameters; the liquid bridge-solid interfacial length and the length of the throat of the liquid bridge were used. Variations of the interfacial morphology development of the bridge were analyzed to understand the bridge response.

A systematical rheological study of polysaccharide from Sophora alopecuroides L. seeds.

PubMed

Wu, Yan; Guo, Rui; Cao, Nannan; Sun, Xiangjun; Sui, Zhongquan; Guo, Qingbin

2018-01-15

The rheological properties of polysaccharide (SAP) from Sophora alopecuroides L. seeds were systematically investigated by fitting different models. The steady flow testing indicated that SAP exhibited shear-thinning behaviors, which were enhanced with increasing concentration and decreasing temperature. This was demonstrated quantitatively by Williamson and Arrhenius models. According to the generalized Morris equation, SAP exhibited random coil conformation with the potential to form weak gel-like network. On the other hand, multiple results of dynamic tests confirmed the viscoelastic properties of SAP, showing oscillatory behaviors between a dilute solution and an elastic gel. Furthermore, SAP solutions were thermorheologically stable without remarkable energetic interactions or structural heterogeneity, since their rheological patterns were successfully applied to Time-temperature superposition (TTS) principle, modified Cole-Cole analysis and Cox-Merz rule. Copyright © 2017 Elsevier Ltd. All rights reserved.

Phenotypic Plasticity and Cell Fate Decisions in Cancer: Insights from Dynamical Systems Theory

PubMed Central

Kulkarni, Prakash; Levine, Herbert

2017-01-01

Waddington’s epigenetic landscape, a famous metaphor in developmental biology, depicts how a stem cell progresses from an undifferentiated phenotype to a differentiated one. The concept of “landscape” in the context of dynamical systems theory represents a high-dimensional space, in which each cell phenotype is considered as an “attractor” that is determined by interactions between multiple molecular players, and is buffered against environmental fluctuations. In addition, biological noise is thought to play an important role during these cell-fate decisions and in fact controls transitions between different phenotypes. Here, we discuss the phenotypic transitions in cancer from a dynamical systems perspective and invoke the concept of “cancer attractors”—hidden stable states of the underlying regulatory network that are not occupied by normal cells. Phenotypic transitions in cancer occur at varying levels depending on the context. Using epithelial-to-mesenchymal transition (EMT), cancer stem-like properties, metabolic reprogramming and the emergence of therapy resistance as examples, we illustrate how phenotypic plasticity in cancer cells enables them to acquire hybrid phenotypes (such as hybrid epithelial/mesenchymal and hybrid metabolic phenotypes) that tend to be more aggressive and notoriously resilient to therapies such as chemotherapy and androgen-deprivation therapy. Furthermore, we highlight multiple factors that may give rise to phenotypic plasticity in cancer cells, such as (a) multi-stability or oscillatory behaviors governed by underlying regulatory networks involved in cell-fate decisions in cancer cells, and (b) network rewiring due to conformational dynamics of intrinsically disordered proteins (IDPs) that are highly enriched in cancer cells. We conclude by discussing why a therapeutic approach that promotes “recanalization”, i.e., the exit from “cancer attractors” and re-entry into “normal attractors”, is more likely to succeed rather than a conventional approach that targets individual molecules/pathways. PMID:28640191

Modeling the Inhomogeneous Response of Steady and Transient Flows of Entangled Micellar Solutions

NASA Astrophysics Data System (ADS)

McKinley, Gareth

2008-03-01

Surfactant molecules can self-assemble in solution into long flexible structures known as wormlike micelles. These structures entangle, forming a viscoelastic network similar to those in entangled polymer melts and solutions. However, in contrast to `inert' polymeric networks, wormlike micelles continuously break and reform leading to an additional relaxation mechanism and the name `living polymers'. Observations in both classes of entangled fluids have shown that steady and transient shearing flows of these solutions exhibit spatial inhomogeneities such as `shear-bands' at sufficiently large applied strains. In the present work, we investigate the dynamical response of a class of two-species elastic network models which can capture, in a self-consistent manner, the creation and destruction of elastically-active network segments, as well as diffusive coupling between the microstructural conformations and the local state of stress in regions with large spatial gradients of local deformation. These models incorporate a discrete version of the micellar breakage and reforming dynamics originally proposed by Cates and capture, at least qualitatively, non-affine tube deformation and chain disentanglement. The `flow curves' of stress and apparent shear rate resulting from an assumption of homogeneous deformation is non-monotonic and linear stability analysis shows that the region of non-monotonic response is unstable. Calculation of the full inhomogeneous flow field results in localized shear bands that grow linearly in extent across the gap as the apparent shear rate increases. Time-dependent calculations in step strain, large amplitude oscillatory shear (LAOS) and in start up of steady shear flow show that the velocity profile in the gap and the total stress measured at the bounding surfaces are coupled and evolve in a complex non-monotonic manner as the shear bands develop and propagate.

Temporal self-organization of the cyclin/Cdk network driving the mammalian cell cycle

PubMed Central

Gérard, Claude; Goldbeter, Albert

2009-01-01

We propose an integrated computational model for the network of cyclin-dependent kinases (Cdks) that controls the dynamics of the mammalian cell cycle. The model contains four Cdk modules regulated by reversible phosphorylation, Cdk inhibitors, and protein synthesis or degradation. Growth factors (GFs) trigger the transition from a quiescent, stable steady state to self-sustained oscillations in the Cdk network. These oscillations correspond to the repetitive, transient activation of cyclin D/Cdk4–6 in G1, cyclin E/Cdk2 at the G1/S transition, cyclin A/Cdk2 in S and at the S/G2 transition, and cyclin B/Cdk1 at the G2/M transition. The model accounts for the following major properties of the mammalian cell cycle: (i) repetitive cell cycling in the presence of suprathreshold amounts of GF; (ii) control of cell-cycle progression by the balance between antagonistic effects of the tumor suppressor retinoblastoma protein (pRB) and the transcription factor E2F; and (iii) existence of a restriction point in G1, beyond which completion of the cell cycle becomes independent of GF. The model also accounts for endoreplication. Incorporating the DNA replication checkpoint mediated by kinases ATR and Chk1 slows down the dynamics of the cell cycle without altering its oscillatory nature and leads to better separation of the S and M phases. The model for the mammalian cell cycle shows how the regulatory structure of the Cdk network results in its temporal self-organization, leading to the repetitive, sequential activation of the four Cdk modules that brings about the orderly progression along cell-cycle phases. PMID:20007375

Theory of Tumbling Bodies Entering Planetary Atmospheres with Application to Probe Vehicles and the Australian Tektites

NASA Technical Reports Server (NTRS)

Tobak, Murray; Peterson, Victor L.

1964-01-01

The tumbling motion of aerodynamically stable bodies entering planetary atmospheres is analyzed considering that the tumbling, its arrest, and the subsequent oscillatory motion are governed by the equation for the fifth Painleve' transcendent. Results based on the asymptotic behavior of the transcendent are applied to study (1) the oscillatory behavior of planetary probe vehicles in relation to aerodynamic heating and loads and (2) the dynamic behavior of the Australian tektites on entering the Earth's atmosphere, under the hypothesis that their origin was the Moon.

Large-scale oscillatory calcium waves in the immature cortex.

PubMed

Garaschuk, O; Linn, J; Eilers, J; Konnerth, A

2000-05-01

Two-photon imaging of large neuronal networks in cortical slices of newborn rats revealed synchronized oscillations in intracellular Ca2+ concentration. These spontaneous Ca2+ waves usually started in the posterior cortex and propagated slowly (2.1 mm per second) toward its anterior end. Ca2+ waves were associated with field-potential changes and required activation of AMPA and NMDA receptors. Although GABAA receptors were not involved in wave initiation, the developmental transition of GABAergic transmission from depolarizing to hyperpolarizing (around postnatal day 7) stopped the oscillatory activity. Thus we identified a type of large-scale Ca2+ wave that may regulate long-distance wiring in the immature cortex.

Theta-Modulated Gamma-Band Synchronization Among Activated Regions During a Verb Generation Task

PubMed Central

Doesburg, Sam M.; Vinette, Sarah A.; Cheung, Michael J.; Pang, Elizabeth W.

2012-01-01

Expressive language is complex and involves processing within a distributed network of cortical regions. Functional MRI and magnetoencephalography (MEG) have identified brain areas critical for expressive language, but how these regions communicate across the network remains poorly understood. It is thought that synchronization of oscillations between neural populations, particularly at a gamma rate (>30 Hz), underlies functional integration within cortical networks. Modulation of gamma rhythms by theta-band oscillations (4–8 Hz) has been proposed as a mechanism for the integration of local cell coalitions into large-scale networks underlying cognition and perception. The present study tested the hypothesis that these oscillatory mechanisms of functional integration were present within the expressive language network. We recorded MEG while subjects performed a covert verb generation task. We localized activated cortical regions using beamformer analysis, calculated inter-regional phase locking between activated areas, and measured modulation of inter-regional gamma synchronization by theta phase. The results show task-dependent gamma-band synchronization among regions activated during the performance of the verb generation task, and we provide evidence that these transient and periodic instances of high-frequency connectivity were modulated by the phase of cortical theta oscillations. These findings suggest that oscillatory synchronization and cross-frequency interactions are mechanisms for functional integration among distributed brain areas supporting expressive language processing. PMID:22707946

Modulation of neuronal oscillatory activity in the beta- and gamma-band is associated with current individual anxiety levels.

PubMed

Schneider, Till R; Hipp, Joerg F; Domnick, Claudia; Carl, Christine; Büchel, Christian; Engel, Andreas K

2018-05-26

Human faces are among the most salient visual stimuli and act both as socially and emotionally relevant signals. Faces and especially faces with emotional expression receive prioritized processing in the human brain and activate a distributed network of brain areas reflected, e.g., in enhanced oscillatory neuronal activity. However, an inconsistent picture emerged so far regarding neuronal oscillatory activity across different frequency-bands modulated by emotionally and socially relevant stimuli. The individual level of anxiety among healthy populations might be one explanation for these inconsistent findings. Therefore, we tested the hypothesis whether oscillatory neuronal activity is associated with individual anxiety levels during perception of faces with neutral and fearful facial expressions. We recorded neuronal activity using magnetoencephalography (MEG) in 27 healthy participants and determined their individual state anxiety levels. Images of human faces with neutral and fearful expressions, and physically matched visual control stimuli were presented while participants performed a simple color detection task. Spectral analyses revealed that face processing and in particular processing of fearful faces was characterized by enhanced neuronal activity in the theta- and gamma-band and decreased activity in the beta-band in early visual cortex and the fusiform gyrus (FFG). Moreover, the individuals' state anxiety levels correlated positively with the gamma-band response and negatively with the beta response in the FFG and the amygdala. Our results suggest that oscillatory neuronal activity plays an important role in affective face processing and is dependent on the individual level of state anxiety. Our work provides new insights on the role of oscillatory neuronal activity underlying processing of faces. Copyright © 2018. Published by Elsevier Inc.

Top-down alpha oscillatory network interactions during visuospatial attention orienting.

PubMed

Doesburg, Sam M; Bedo, Nicolas; Ward, Lawrence M

2016-05-15

Neuroimaging and lesion studies indicate that visual attention is controlled by a distributed network of brain areas. The covert control of visuospatial attention has also been associated with retinotopic modulation of alpha-band oscillations within early visual cortex, which are thought to underlie inhibition of ignored areas of visual space. The relation between distributed networks mediating attention control and more focal oscillatory mechanisms, however, remains unclear. The present study evaluated the hypothesis that alpha-band, directed, network interactions within the attention control network are systematically modulated by the locus of visuospatial attention. We localized brain areas involved in visuospatial attention orienting using magnetoencephalographic (MEG) imaging and investigated alpha-band Granger-causal interactions among activated regions using narrow-band transfer entropy. The deployment of attention to one side of visual space was indexed by lateralization of alpha power changes between about 400ms and 700ms post-cue onset. The changes in alpha power were associated, in the same time period, with lateralization of anterior-to-posterior information flow in the alpha-band from various brain areas involved in attention control, including the anterior cingulate cortex, left middle and inferior frontal gyri, left superior temporal gyrus, and right insula, and inferior parietal lobule, to early visual areas. We interpreted these results to indicate that distributed network interactions mediated by alpha oscillations exert top-down influences on early visual cortex to modulate inhibition of processing for ignored areas of visual space. Copyright © 2016. Published by Elsevier Inc.

Synchronization in neural nets

NASA Technical Reports Server (NTRS)

Vidal, Jacques J.; Haggerty, John

1988-01-01

The paper presents an artificial neural network concept (the Synchronizable Oscillator Networks) where the instants of individual firings in the form of point processes constitute the only form of information transmitted between joining neurons. In the model, neurons fire spontaneously and regularly in the absence of perturbation. When interaction is present, the scheduled firings are advanced or delayed by the firing of neighboring neurons. Networks of such neurons become global oscillators which exhibit multiple synchronizing attractors. From arbitrary initial states, energy minimization learning procedures can make the network converge to oscillatory modes that satisfy multi-dimensional constraints. Such networks can directly represent routing and scheduling problems that consist of ordering sequences of events.

Direct observation of forward-scattering oscillations in the H+HD→H2+D reaction

NASA Astrophysics Data System (ADS)

Yuan, Daofu; Yu, Shengrui; Chen, Wentao; Sang, Jiwei; Luo, Chang; Wang, Tao; Xu, Xin; Casavecchia, Piergiorgio; Wang, Xingan; Sun, Zhigang; Zhang, Dong H.; Yang, Xueming

2018-06-01

Accurate measurements of product state-resolved angular distributions are central to fundamental studies of chemical reaction dynamics. Yet, fine quantum-mechanical structures in product angular distributions of a reactive scattering process, such as the fast oscillations in the forward-scattering direction, have never been observed experimentally and the nature of these oscillations has not been fully explored. Here we report the crossed-molecular-beam experimental observation of these fast forward-scattering oscillations in the product angular distribution of the benchmark chemical reaction, H + HD → H2 + D. Clear oscillatory structures are observed for the H2(v' = 0, j' = 1, 3) product states at a collision energy of 1.35 eV, in excellent agreement with the quantum-mechanical dynamics calculations. Our analysis reveals that the oscillatory forward-scattering components are mainly contributed by the total angular momentum J around 28. The partial waves and impact parameters responsible for the forward scatterings are also determined from these observed oscillations, providing crucial dynamics information on the transient reaction process.

Effects of thermal fluctuations and fluid compressibility on hydrodynamic synchronization of microrotors at finite oscillatory Reynolds number: a multiparticle collision dynamics simulation study.

PubMed

Theers, Mario; Winkler, Roland G

2014-08-28

We investigate the emergent dynamical behavior of hydrodynamically coupled microrotors by means of multiparticle collision dynamics (MPC) simulations. The two rotors are confined in a plane and move along circles driven by active forces. Comparing simulations to theoretical results based on linearized hydrodynamics, we demonstrate that time-dependent hydrodynamic interactions lead to synchronization of the rotational motion. Thermal noise implies large fluctuations of the phase-angle difference between the rotors, but synchronization prevails and the ensemble-averaged time dependence of the phase-angle difference agrees well with analytical predictions. Moreover, we demonstrate that compressibility effects lead to longer synchronization times. In addition, the relevance of the inertia terms of the Navier-Stokes equation are discussed, specifically the linear unsteady acceleration term characterized by the oscillatory Reynolds number ReT. We illustrate the continuous breakdown of synchronization with the Reynolds number ReT, in analogy to the continuous breakdown of the scallop theorem with decreasing Reynolds number.

Accelerated and Airy-Bloch oscillations

NASA Astrophysics Data System (ADS)

Longhi, Stefano

2016-09-01

A quantum particle subjected to a constant force undergoes an accelerated motion following a parabolic path, which differs from the classical motion just because of wave packet spreading (quantum diffusion). However, when a periodic potential is added (such as in a crystal) the particle undergoes Bragg scattering and an oscillatory (rather than accelerated) motion is found, corresponding to the famous Bloch oscillations (BOs). Here, we introduce an exactly-solvable quantum Hamiltonian model, corresponding to a generalized Wannier-Stark Hamiltonian Ĥ, in which a quantum particle shows an intermediate dynamical behavior, namely an oscillatory motion superimposed to an accelerated one. Such a novel dynamical behavior is referred to as accelerated BOs. Analytical expressions of the spectrum, improper eigenfunctions and propagator of the generalized Wannier-Stark Hamiltonian Ĥ are derived. Finally, it is shown that acceleration and quantum diffusion in the generalized Wannier-Stark Hamiltonian are prevented for Airy wave packets, which undergo a periodic breathing dynamics that can be referred to as Airy-Bloch oscillations.

Oscillatory dynamics and place field maps reflect hippocampal ensemble processing of sequence and place memory under NMDA receptor control.

PubMed

Cabral, Henrique O; Vinck, Martin; Fouquet, Celine; Pennartz, Cyriel M A; Rondi-Reig, Laure; Battaglia, Francesco P

2014-01-22

Place coding in the hippocampus requires flexible combination of sensory inputs (e.g., environmental and self-motion information) with memory of past events. We show that mouse CA1 hippocampal spatial representations may either be anchored to external landmarks (place memory) or reflect memorized sequences of cell assemblies depending on the behavioral strategy spontaneously selected. These computational modalities correspond to different CA1 dynamical states, as expressed by theta and low- and high-frequency gamma oscillations, when switching from place to sequence memory-based processing. These changes are consistent with a shift from entorhinal to CA3 input dominance on CA1. In mice with a deletion of forebrain NMDA receptors, the ability of place cells to maintain a map based on sequence memory is selectively impaired and oscillatory dynamics are correspondingly altered, suggesting that oscillations contribute to selecting behaviorally appropriate computations in the hippocampus and that NMDA receptors are crucial for this function. Copyright © 2014 Elsevier Inc. All rights reserved.

Dipteran insect flight dynamics. Part 1 Longitudinal motion about hover.

PubMed

Faruque, Imraan; Sean Humbert, J

2010-05-21

This paper presents a reduced-order model of longitudinal hovering flight dynamics for dipteran insects. The quasi-steady wing aerodynamics model is extended by including perturbation states from equilibrium and paired with rigid body equations of motion to create a nonlinear simulation of a Drosophila-like insect. Frequency-based system identification tools are used to identify the transfer functions from biologically inspired control inputs to rigid body states. Stability derivatives and a state space linear system describing the dynamics are also identified. The vehicle control requirements are quantified with respect to traditional human pilot handling qualities specification. The heave dynamics are found to be decoupled from the pitch/fore/aft dynamics. The haltere-on system revealed a stabilized system with a slow (heave) and fast subsidence mode, and a stable oscillatory mode. The haltere-off (bare airframe) system revealed a slow (heave) and fast subsidence mode and an unstable oscillatory mode, a modal structure in agreement with CFD studies. The analysis indicates that passive aerodynamic mechanisms contribute to stability, which may help explain how insects are able to achieve stable locomotion on a very small computational budget. Copyright (c) 2010. Published by Elsevier Ltd.

The situated HKB model: how sensorimotor spatial coupling can alter oscillatory brain dynamics

PubMed Central

Aguilera, Miguel; Bedia, Manuel G.; Santos, Bruno A.; Barandiaran, Xabier E.

2013-01-01

Despite the increase of both dynamic and embodied/situated approaches in cognitive science, there is still little research on how coordination dynamics under a closed sensorimotor loop might induce qualitatively different patterns of neural oscillations compared to those found in isolated systems. We take as a departure point the Haken-Kelso-Bunz (HKB) model, a generic model for dynamic coordination between two oscillatory components, which has proven useful for a vast range of applications in cognitive science and whose dynamical properties are well understood. In order to explore the properties of this model under closed sensorimotor conditions we present what we call the situated HKB model: a robotic model that performs a gradient climbing task and whose “brain” is modeled by the HKB equation. We solve the differential equations that define the agent-environment coupling for increasing values of the agent's sensitivity (sensor gain), finding different behavioral strategies. These results are compared with two different models: a decoupled HKB with no sensory input and a passively-coupled HKB that is also decoupled but receives a structured input generated by a situated agent. We can precisely quantify and qualitatively describe how the properties of the system, when studied in coupled conditions, radically change in a manner that cannot be deduced from the decoupled HKB models alone. We also present the notion of neurodynamic signature as the dynamic pattern that correlates with a specific behavior and we show how only a situated agent can display this signature compared to an agent that simply receives the exact same sensory input. To our knowledge, this is the first analytical solution of the HKB equation in a sensorimotor loop and qualitative and quantitative analytic comparison of spatially coupled vs. decoupled oscillatory controllers. Finally, we discuss the limitations and possible generalization of our model to contemporary neuroscience and philosophy of mind. PMID:23986692

Oscillatory mechanisms of process binding in memory.

PubMed

Klimesch, Wolfgang; Freunberger, Roman; Sauseng, Paul

2010-06-01

A central topic in cognitive neuroscience is the question, which processes underlie large scale communication within and between different neural networks. The basic assumption is that oscillatory phase synchronization plays an important role for process binding--the transient linking of different cognitive processes--which may be considered a special type of large scale communication. We investigate this question for memory processes on the basis of different types of oscillatory synchronization mechanisms. The reviewed findings suggest that theta and alpha phase coupling (and phase reorganization) reflect control processes in two large memory systems, a working memory and a complex knowledge system that comprises semantic long-term memory. It is suggested that alpha phase synchronization may be interpreted in terms of processes that coordinate top-down control (a process guided by expectancy to focus on relevant search areas) and access to memory traces (a process leading to the activation of a memory trace). An analogous interpretation is suggested for theta oscillations and the controlled access to episodic memories. Copyright (c) 2009 Elsevier Ltd. All rights reserved.

Theory on the Dynamics of Oscillatory Loops in the Transcription Factor Networks

PubMed Central

Murugan, Rajamanickam

2014-01-01

We develop a detailed theoretical framework for various types of transcription factor gene oscillators. We further demonstrate that one can build genetic-oscillators which are tunable and robust against perturbations in the critical control parameters by coupling two or more independent Goodwin-Griffith oscillators through either -OR- or -AND- type logic. Most of the coupled oscillators constructed in the literature so far seem to be of -OR- type. When there are transient perturbations in one of the -OR- type coupled-oscillators, then the overall period of the system remains constant (period-buffering) whereas in case of -AND- type coupling the overall period of the system moves towards the perturbed oscillator. Though there is a period-buffering, the amplitudes of oscillators coupled through -OR- type logic are more sensitive to perturbations in the parameters associated with the promoter state dynamics than -AND- type. Further analysis shows that the period of -AND- type coupled dual-feedback oscillators can be tuned without conceding on the amplitudes. Using these results we derive the basic design principles governing the robust and tunable synthetic gene oscillators without compromising on their amplitudes. PMID:25111803

Architecture-Dependent Robustness and Bistability in a Class of Genetic Circuits

PubMed Central

Zhang, Jiajun; Yuan, Zhanjiang; Li, Han-Xiong; Zhou, Tianshou

2010-01-01

Understanding the relationship between genotype and phenotype is a challenge in systems biology. An interesting yet related issue is why a particular circuit topology is present in a cell when the same function can supposedly be obtained from an alternative architecture. Here we analyzed two topologically equivalent genetic circuits of coupled positive and negative feedback loops, named NAT and ALT circuits, respectively. The computational search for the oscillation volume of the entire biologically reasonable parameter region through large-scale random samplings shows that the NAT circuit exhibits a distinctly larger fraction of the oscillatory region than the ALT circuit. Such a global robustness difference between two circuits is supplemented by analyzing local robustness, including robustness to parameter perturbations and to molecular noise. In addition, detailed dynamical analysis shows that the molecular noise of both circuits can induce transient switching of the different mechanism between a stable steady state and a stable limit cycle. Our investigation on robustness and dynamics through examples provides insights into the relationship between network architecture and its function. PMID:20712986

Steady-state visually evoked potential correlates of human body perception.

PubMed

Giabbiconi, Claire-Marie; Jurilj, Verena; Gruber, Thomas; Vocks, Silja

2016-11-01

In cognitive neuroscience, interest in the neuronal basis underlying the processing of human bodies is steadily increasing. Based on functional magnetic resonance imaging studies, it is assumed that the processing of pictures of human bodies is anchored in a network of specialized brain areas comprising the extrastriate and the fusiform body area (EBA, FBA). An alternative to examine the dynamics within these networks is electroencephalography, more specifically so-called steady-state visually evoked potentials (SSVEPs). In SSVEP tasks, a visual stimulus is presented repetitively at a predefined flickering rate and typically elicits a continuous oscillatory brain response at this frequency. This brain response is characterized by an excellent signal-to-noise ratio-a major advantage for source reconstructions. The main goal of present study was to demonstrate the feasibility of this method to study human body perception. To that end, we presented pictures of bodies and contrasted the resulting SSVEPs to two control conditions, i.e., non-objects and pictures of everyday objects (chairs). We found specific SSVEPs amplitude differences between bodies and both control conditions. Source reconstructions localized the SSVEP generators to a network of temporal, occipital and parietal areas. Interestingly, only body perception resulted in activity differences in middle temporal and lateral occipitotemporal areas, most likely reflecting the EBA/FBA.

The many roads to tremor.

PubMed

Brittain, John-Stuart; Brown, Peter

2013-12-01

Tremor represents one of the most prominent examples of aberrant synchronisation within the human motor system, and Essential Tremor (ET) is by far the most common tremor disorder. Yet, even within ET there is considerable variation, and patients may have contrasting amounts of postural and intention tremor. Recently, Pedrosa et al. (2013) challenged tremor circuits in a cohort of patients presenting with ET, by applying low-frequency deep brain stimulation within thalamus. This interventional approach provided strong evidence that distinct (yet possibly overlapping) neural substrates are responsible for postural and intention tremor in ET. Intention tremor, and not postural tremor, was exacerbated by low frequency stimulation, and the effect was localised in the region of the ventrolateral thalamus in such a way as to implicate cerebello-thalamic pathways. These results, taken in conjunction with the contemporary literature, reveal that pathological changes exaggerate oscillatory synchrony in selective components of an extensive and distributed motor network, and that synchronisation within these networks is further regulated according to motor state. Through a combination of pathological and more dynamic physiological factors, activity then spills out into the periphery in the form of tremor. The findings of Pedrosa et al. (2013) are timely as they coincide with an emerging notion that tremor may result through selective dysregulation within a broader tremorgenic network. © 2013.

Activation and synchronization of the oscillatory morphodynamics in multicellular monolayer

PubMed Central

Lin, Shao-Zhen; Li, Bo; Lan, Ganhui; Feng, Xi-Qiao

2017-01-01

Oscillatory morphodynamics provides necessary mechanical cues for many multicellular processes. Owing to their collective nature, these processes require robustly coordinated dynamics of individual cells, which are often separated too distantly to communicate with each other through biomaterial transportation. Although it is known that the mechanical balance generally plays a significant role in the systems’ morphologies, it remains elusive whether and how the mechanical components may contribute to the systems’ collective morphodynamics. Here, we study the collective oscillations in the Drosophila amnioserosa tissue to elucidate the regulatory roles of the mechanical components. We identify that the tensile stress is the key activator that switches the collective oscillations on and off. This regulatory role is shown analytically using the Hopf bifurcation theory. We find that the physical properties of the tissue boundary are directly responsible for synchronizing the oscillatory intensity and polarity of all inner cells and for orchestrating the spatial oscillation patterns inthe tissue. PMID:28716911

Oscillations in the permanganate oxidation of glycine in a stirred flow reactor.

PubMed

Poros, Eszter; Kurin-Csörgei, Krisztina; Szalai, István; Orbán, Miklós

2013-09-19

Oscillatory behavior is reported in the permanganate oxidation of glycine in the presence of Na2HPO4 in a stirred flow reactor. In near-neutral solutions, long-period sustained oscillations were recorded in the potential of a Pt electrode and in the light absorbance measured at λ = 418 and 545 nm, characteristic wavelengths for following the evolution of the intermediate [Mn(IV)] and reagent [MnO4(-) ] during the course of the reaction. No evidence of bistability was found. The chemical and physical backgrounds of the oscillatory phenomenon are discussed. In the oscillatory cycle, the positive feedback is attributed to the autocatalytic formation of a soluble Mn(IV) species, whereas the negative feedback arises from its removal from the solution in the form of solid MnO2. A simple model is suggested that qualitatively simulates the experimental observations in batch runs and the dynamics that appears in the flow system.

Multiple running speed signals in medial entorhinal cortex

PubMed Central

Hinman, James R.; Brandon, Mark P.; Climer, Jason R.; Chapman, G. William; Hasselmo, Michael E.

2016-01-01

Grid cells in medial entorhinal cortex (MEC) can be modeled using oscillatory interference or attractor dynamic mechanisms that perform path integration, a computation requiring information about running direction and speed. The two classes of computational models often use either an oscillatory frequency or a firing rate that increases as a function of running speed. Yet it is currently not known whether these are two manifestations of the same speed signal or dissociable signals with potentially different anatomical substrates. We examined coding of running speed in MEC and identified these two speed signals to be independent of each other within individual neurons. The medial septum (MS) is strongly linked to locomotor behavior and removal of MS input resulted in strengthening of the firing rate speed signal, while decreasing the strength of the oscillatory speed signal. Thus two speed signals are present in MEC that are differentially affected by disrupted MS input. PMID:27427460

SRB combustion dynamics analysis computer program (CDA-1)

NASA Technical Reports Server (NTRS)

Chung, T. J.; Park, O. Y.

1988-01-01

A two-dimensional numerical model is developed for the unsteady oscillatory combustion of the solid propellant flame zone. Variations of pressure with low and high frequency responses across the long flame, such as in the double-base propellants, are accommodated. The formulation is based on a premixed, laminar flame with a one-step overall chemical reaction and the Arrhenius law of decomposition for the gaseous phase with no condensed phase reaction. Numerical calculations are carried out using the Galerkin finite elements, with perturbations expanded to the zeroth, first, and second orders. The numerical results indicate that amplification of oscillatory motions does indeed prevail in high frequency regions. For the second order system, the trend is similar to the first order system for low frequencies, but instabilities may appear at frequencies lower than those of the first order system. The most significant effect of the second order system is that the admittance is extremely oscillatory between moderately high frequency ranges.

Transition to subthreshold activity with the use of phase shifting in a model thalamic network

NASA Astrophysics Data System (ADS)

Thomas, Elizabeth; Grisar, Thierry

1997-05-01

Absence epilepsy involves a state of low frequency synchronous oscillations by the involved neuronal networks. These oscillations may be either above or subthreshold. In this investigation, we studied the methods which could be utilized to transform the threshold activity of neurons in the network to a subthreshold state. A model thalamic network was constructed using the Hodgkin Huxley framework. Subthreshold activity was achieved by the application of stimuli to the network which caused phase shifts in the oscillatory activity of selected neurons in the network. In some instances the stimulus was a periodic pulse train of low frequency to the reticular thalamic neurons of the network while in others, it was a constant hyperpolarizing current applied to the thalamocortical neurons.

Characterizing Feedback Control Mechanisms in Nonlinear Microbial Models of Soil Organic Matter Decomposition by Stability Analysis

NASA Astrophysics Data System (ADS)

Georgiou, K.; Tang, J.; Riley, W. J.; Torn, M. S.

2014-12-01

Soil organic matter (SOM) decomposition is regulated by biotic and abiotic processes. Feedback interactions between such processes may act to dampen oscillatory responses to perturbations from equilibrium. Indeed, although biological oscillations have been observed in small-scale laboratory incubations, the overlying behavior at the plot-scale exhibits a relatively stable response to disturbances in input rates and temperature. Recent studies have demonstrated the ability of microbial models to capture nonlinear feedbacks in SOM decomposition that linear Century-type models are unable to reproduce, such as soil priming in response to increased carbon input. However, these microbial models often exhibit strong oscillatory behavior that is deemed unrealistic. The inherently nonlinear dynamics of SOM decomposition have important implications for global climate-carbon and carbon-concentration feedbacks. It is therefore imperative to represent these dynamics in Earth System Models (ESMs) by introducing sub-models that accurately represent microbial and abiotic processes. In the present study we explore, both analytically and numerically, four microbe-enabled model structures of varying levels of complexity. The most complex model combines microbial physiology, a non-linear mineral sorption isotherm, and enzyme dynamics. Based on detailed stability analysis of the nonlinear dynamics, we calculate the system modes as functions of model parameters. This dependence provides insight into the source of state oscillations. We find that feedback mechanisms that emerge from careful representation of enzyme and mineral interactions, with parameter values in a prescribed range, are critical for both maintaining system stability and capturing realistic responses to disturbances. Corroborating and expanding upon the results of recent studies, we explain the emergence of oscillatory responses and discuss the appropriate microbe-enabled model structure for inclusion in ESMs.

Understanding Epileptiform After-Discharges as Rhythmic Oscillatory Transients.

PubMed

Baier, Gerold; Taylor, Peter N; Wang, Yujiang

2017-01-01

Electro-cortical activity in patients with epilepsy may show abnormal rhythmic transients in response to stimulation. Even when using the same stimulation parameters in the same patient, wide variability in the duration of transient response has been reported. These transients have long been considered important for the mapping of the excitability levels in the epileptic brain but their dynamic mechanism is still not well understood. To investigate the occurrence of abnormal transients dynamically, we use a thalamo-cortical neural population model of epileptic spike-wave activity and study the interaction between slow and fast subsystems. In a reduced version of the thalamo-cortical model, slow wave oscillations arise from a fold of cycles (FoC) bifurcation. This marks the onset of a region of bistability between a high amplitude oscillatory rhythm and the background state. In vicinity of the bistability in parameter space, the model has excitable dynamics, showing prolonged rhythmic transients in response to suprathreshold pulse stimulation. We analyse the state space geometry of the bistable and excitable states, and find that the rhythmic transient arises when the impending FoC bifurcation deforms the state space and creates an area of locally reduced attraction to the fixed point. This area essentially allows trajectories to dwell there before escaping to the stable steady state, thus creating rhythmic transients. In the full thalamo-cortical model, we find a similar FoC bifurcation structure. Based on the analysis, we propose an explanation of why stimulation induced epileptiform activity may vary between trials, and predict how the variability could be related to ongoing oscillatory background activity. We compare our dynamic mechanism with other mechanisms (such as a slow parameter change) to generate excitable transients, and we discuss the proposed excitability mechanism in the context of stimulation responses in the epileptic cortex.

Data based identification and prediction of nonlinear and complex dynamical systems

NASA Astrophysics Data System (ADS)

Wang, Wen-Xu; Lai, Ying-Cheng; Grebogi, Celso

2016-07-01

The problem of reconstructing nonlinear and complex dynamical systems from measured data or time series is central to many scientific disciplines including physical, biological, computer, and social sciences, as well as engineering and economics. The classic approach to phase-space reconstruction through the methodology of delay-coordinate embedding has been practiced for more than three decades, but the paradigm is effective mostly for low-dimensional dynamical systems. Often, the methodology yields only a topological correspondence of the original system. There are situations in various fields of science and engineering where the systems of interest are complex and high dimensional with many interacting components. A complex system typically exhibits a rich variety of collective dynamics, and it is of great interest to be able to detect, classify, understand, predict, and control the dynamics using data that are becoming increasingly accessible due to the advances of modern information technology. To accomplish these goals, especially prediction and control, an accurate reconstruction of the original system is required. Nonlinear and complex systems identification aims at inferring, from data, the mathematical equations that govern the dynamical evolution and the complex interaction patterns, or topology, among the various components of the system. With successful reconstruction of the system equations and the connecting topology, it may be possible to address challenging and significant problems such as identification of causal relations among the interacting components and detection of hidden nodes. The "inverse" problem thus presents a grand challenge, requiring new paradigms beyond the traditional delay-coordinate embedding methodology. The past fifteen years have witnessed rapid development of contemporary complex graph theory with broad applications in interdisciplinary science and engineering. The combination of graph, information, and nonlinear dynamical systems theories with tools from statistical physics, optimization, engineering control, applied mathematics, and scientific computing enables the development of a number of paradigms to address the problem of nonlinear and complex systems reconstruction. In this Review, we describe the recent advances in this forefront and rapidly evolving field, with a focus on compressive sensing based methods. In particular, compressive sensing is a paradigm developed in recent years in applied mathematics, electrical engineering, and nonlinear physics to reconstruct sparse signals using only limited data. It has broad applications ranging from image compression/reconstruction to the analysis of large-scale sensor networks, and it has become a powerful technique to obtain high-fidelity signals for applications where sufficient observations are not available. We will describe in detail how compressive sensing can be exploited to address a diverse array of problems in data based reconstruction of nonlinear and complex networked systems. The problems include identification of chaotic systems and prediction of catastrophic bifurcations, forecasting future attractors of time-varying nonlinear systems, reconstruction of complex networks with oscillatory and evolutionary game dynamics, detection of hidden nodes, identification of chaotic elements in neuronal networks, reconstruction of complex geospatial networks and nodal positioning, and reconstruction of complex spreading networks with binary data.. A number of alternative methods, such as those based on system response to external driving, synchronization, and noise-induced dynamical correlation, will also be discussed. Due to the high relevance of network reconstruction to biological sciences, a special section is devoted to a brief survey of the current methods to infer biological networks. Finally, a number of open problems including control and controllability of complex nonlinear dynamical networks are discussed. The methods outlined in this Review are principled on various concepts in complexity science and engineering such as phase transitions, bifurcations, stabilities, and robustness. The methodologies have the potential to significantly improve our ability to understand a variety of complex dynamical systems ranging from gene regulatory systems to social networks toward the ultimate goal of controlling such systems.

Reducing Traffic Congestions by Introducing CACC-Vehicles on a Multi-Lane Highway Using Agent-Based Approach

NASA Technical Reports Server (NTRS)

Arnaout, Georges M.; Bowling, Shannon R.

2011-01-01

Traffic congestion is an ongoing problem of great interest to researchers from different areas in academia. With the emerging technology for inter-vehicle communication, vehicles have the ability to exchange information with predecessors by wireless communication. In this paper, we present an agent-based model of traffic congestion and examine the impact of having CACC (Cooperative Adaptive Cruise Control) embedded vehicle(s) on a highway system consisting of 4 traffic lanes without overtaking. In our model, CACC vehicles adapt their acceleration/deceleration according to vehicle-to-vehicle inter-communication. We analyze the average speed of the cars, the shockwaves, and the evolution of traffic congestion throughout the lifecycle of the model. The study identifies how CACC vehicles affect the dynamics of traffic flow on a complex network and reduce the oscillatory behavior (stop and go) resulting from the acceleration/deceleration of the vehicles.

A Network Model of Local Field Potential Activity in Essential Tremor and the Impact of Deep Brain Stimulation

PubMed Central

Mace, Michael; Pavese, Nicola; Borisyuk, Roman; Bain, Peter

2017-01-01

Essential tremor (ET), a movement disorder characterised by an uncontrollable shaking of the affected body part, is often professed to be the most common movement disorder, affecting up to one percent of adults over 40 years of age. The precise cause of ET is unknown, however pathological oscillations of a network of a number of brain regions are implicated in leading to the disorder. Deep brain stimulation (DBS) is a clinical therapy used to alleviate the symptoms of a number of movement disorders. DBS involves the surgical implantation of electrodes into specific nuclei in the brain. For ET the targeted region is the ventralis intermedius (Vim) nucleus of the thalamus. Though DBS is effective for treating ET, the mechanism through which the therapeutic effect is obtained is not understood. To elucidate the mechanism underlying the pathological network activity and the effect of DBS on such activity, we take a computational modelling approach combined with electrophysiological data. The pathological brain activity was recorded intra-operatively via implanted DBS electrodes, whilst simultaneously recording muscle activity of the affected limbs. We modelled the network hypothesised to underlie ET using the Wilson-Cowan approach. The modelled network exhibited oscillatory behaviour within the tremor frequency range, as did our electrophysiological data. By applying a DBS-like input we suppressed these oscillations. This study shows that the dynamics of the ET network support oscillations at the tremor frequency and the application of a DBS-like input disrupts this activity, which could be one mechanism underlying the therapeutic benefit. PMID:28068428

Resting-state theta band connectivity and graph analysis in generalized social anxiety disorder.

PubMed

Xing, Mengqi; Tadayonnejad, Reza; MacNamara, Annmarie; Ajilore, Olusola; DiGangi, Julia; Phan, K Luan; Leow, Alex; Klumpp, Heide

2017-01-01

Functional magnetic resonance imaging (fMRI) resting-state studies show generalized social anxiety disorder (gSAD) is associated with disturbances in networks involved in emotion regulation, emotion processing, and perceptual functions, suggesting a network framework is integral to elucidating the pathophysiology of gSAD. However, fMRI does not measure the fast dynamic interconnections of functional networks. Therefore, we examined whole-brain functional connectomics with electroencephalogram (EEG) during resting-state. Resting-state EEG data was recorded for 32 patients with gSAD and 32 demographically-matched healthy controls (HC). Sensor-level connectivity analysis was applied on EEG data by using Weighted Phase Lag Index (WPLI) and graph analysis based on WPLI was used to determine clustering coefficient and characteristic path length to estimate local integration and global segregation of networks. WPLI results showed increased oscillatory midline coherence in the theta frequency band indicating higher connectivity in the gSAD relative to HC group during rest. Additionally, WPLI values positively correlated with state anxiety levels within the gSAD group but not the HC group. Our graph theory based connectomics analysis demonstrated increased clustering coefficient and decreased characteristic path length in theta-based whole brain functional organization in subjects with gSAD compared to HC. Theta-dependent interconnectivity was associated with state anxiety in gSAD and an increase in information processing efficiency in gSAD (compared to controls). Results may represent enhanced baseline self-focused attention, which is consistent with cognitive models of gSAD and fMRI studies implicating emotion dysregulation and disturbances in task negative networks (e.g., default mode network) in gSAD.

Wavelet-based localization of oscillatory sources from magnetoencephalography data.

PubMed

Lina, J M; Chowdhury, R; Lemay, E; Kobayashi, E; Grova, C

2014-08-01

Transient brain oscillatory activities recorded with Eelectroencephalography (EEG) or magnetoencephalography (MEG) are characteristic features in physiological and pathological processes. This study is aimed at describing, evaluating, and illustrating with clinical data a new method for localizing the sources of oscillatory cortical activity recorded by MEG. The method combines time-frequency representation and an entropic regularization technique in a common framework, assuming that brain activity is sparse in time and space. Spatial sparsity relies on the assumption that brain activity is organized among cortical parcels. Sparsity in time is achieved by transposing the inverse problem in the wavelet representation, for both data and sources. We propose an estimator of the wavelet coefficients of the sources based on the maximum entropy on the mean (MEM) principle. The full dynamics of the sources is obtained from the inverse wavelet transform, and principal component analysis of the reconstructed time courses is applied to extract oscillatory components. This methodology is evaluated using realistic simulations of single-trial signals, combining fast and sudden discharges (spike) along with bursts of oscillating activity. The method is finally illustrated with a clinical application using MEG data acquired on a patient with a right orbitofrontal epilepsy.

Application of nonlinear rheology to assess the effect of secondary nanofiller on network structure of hybrid polymer nanocomposites

NASA Astrophysics Data System (ADS)

Kamkar, Milad; Aliabadian, Ehsan; Shayesteh Zeraati, Ali; Sundararaj, Uttandaraman

2018-02-01

Carbon nanotube (CNT)/polymer nanocomposites exhibit excellent electrical properties by forming a percolated network. Adding a secondary filler can significantly affect the CNTs' network, resulting in changing the electrical properties. In this work, we investigated the effect of adding manganese dioxide nanowires (MnO2NWs) as a secondary nanofiller on the CNTs' network structure inside a poly(vinylidene fluoride) (PVDF) matrix. Incorporating MnO2NWs to PVDF/CNT samples produced a better state of dispersion of CNTs, as corroborated by light microscopy and transmission electron microscopy. The steady shear and oscillatory shear flows were employed to obtain a better insight into the nanofiller structure and viscoelastic behavior of the nanocomposites. The transient response under steady shear flow revealed that the stress overshoot of hybrid nanocomposites (two-fillers), PVDF/CNT/MnO2NWs, increased dramatically in comparison to binary nanocomposites (single-filler), PVDF/CNT and PVDF/MnO2NWs. This can be attributed to microstructural changes. Large amplitude oscillatory shear characterization was also performed to further investigate the effect of the secondary nanofiller on the nonlinear viscoelastic behavior of the samples. The nonlinear rheological observations were explained using quantitative nonlinear parameters [strain-stiffening ratio (S) and shear-thickening ratio (T)] and Lissajous-Bowditch plots. Results indicated that a more rigid nanofiller network was formed for the hybrid nanocomposites due to the better dispersion state of CNTs and this led to a more nonlinear viscoelastic behavior.

Locking of correlated neural activity to ongoing oscillations

PubMed Central

Helias, Moritz

2017-01-01

Population-wide oscillations are ubiquitously observed in mesoscopic signals of cortical activity. In these network states a global oscillatory cycle modulates the propensity of neurons to fire. Synchronous activation of neurons has been hypothesized to be a separate channel of signal processing information in the brain. A salient question is therefore if and how oscillations interact with spike synchrony and in how far these channels can be considered separate. Experiments indeed showed that correlated spiking co-modulates with the static firing rate and is also tightly locked to the phase of beta-oscillations. While the dependence of correlations on the mean rate is well understood in feed-forward networks, it remains unclear why and by which mechanisms correlations tightly lock to an oscillatory cycle. We here demonstrate that such correlated activation of pairs of neurons is qualitatively explained by periodically-driven random networks. We identify the mechanisms by which covariances depend on a driving periodic stimulus. Mean-field theory combined with linear response theory yields closed-form expressions for the cyclostationary mean activities and pairwise zero-time-lag covariances of binary recurrent random networks. Two distinct mechanisms cause time-dependent covariances: the modulation of the susceptibility of single neurons (via the external input and network feedback) and the time-varying variances of single unit activities. For some parameters, the effectively inhibitory recurrent feedback leads to resonant covariances even if mean activities show non-resonant behavior. Our analytical results open the question of time-modulated synchronous activity to a quantitative analysis. PMID:28604771

Lasting EEG/MEG Aftereffects of Rhythmic Transcranial Brain Stimulation: Level of Control Over Oscillatory Network Activity

PubMed Central

Veniero, Domenica; Vossen, Alexandra; Gross, Joachim; Thut, Gregor

2015-01-01

A number of rhythmic protocols have emerged for non-invasive brain stimulation (NIBS) in humans, including transcranial alternating current stimulation (tACS), oscillatory transcranial direct current stimulation (otDCS), and repetitive (also called rhythmic) transcranial magnetic stimulation (rTMS). With these techniques, it is possible to match the frequency of the externally applied electromagnetic fields to the intrinsic frequency of oscillatory neural population activity (“frequency-tuning”). Mounting evidence suggests that by this means tACS, otDCS, and rTMS can entrain brain oscillations and promote associated functions in a frequency-specific manner, in particular during (i.e., online to) stimulation. Here, we focus instead on the changes in oscillatory brain activity that persist after the end of stimulation. Understanding such aftereffects in healthy participants is an important step for developing these techniques into potentially useful clinical tools for the treatment of specific patient groups. Reviewing the electrophysiological evidence in healthy participants, we find aftereffects on brain oscillations to be a common outcome following tACS/otDCS and rTMS. However, we did not find a consistent, predictable pattern of aftereffects across studies, which is in contrast to the relative homogeneity of reported online effects. This indicates that aftereffects are partially dissociated from online, frequency-specific (entrainment) effects during tACS/otDCS and rTMS. We outline possible accounts and future directions for a better understanding of the link between online entrainment and offline aftereffects, which will be key for developing more targeted interventions into oscillatory brain activity. PMID:26696834

Synaptic remodeling generates synchronous oscillations in the degenerated outer mouse retina

PubMed Central

Haq, Wadood; Arango-Gonzalez, Blanca; Zrenner, Eberhart; Euler, Thomas; Schubert, Timm

2014-01-01

During neuronal degenerative diseases, neuronal microcircuits undergo severe structural alterations, leading to remodeling of synaptic connectivity. The functional consequences of such remodeling are mostly unknown. For instance, in mutant rd1 mouse retina, a common model for Retinitis Pigmentosa, rod bipolar cells (RBCs) establish contacts with remnant cone photoreceptors (cones) as a consequence of rod photoreceptor cell death and the resulting lack of presynaptic input. To assess the functional connectivity in the remodeled, light-insensitive outer rd1 retina, we recorded spontaneous population activity in retinal wholemounts using Ca2+ imaging and identified the participating cell types. Focusing on cones, RBCs and horizontal cells (HCs), we found that these cell types display spontaneous oscillatory activity and form synchronously active clusters. Overall activity was modulated by GABAergic inhibition from interneurons such as HCs and/or possibly interplexiform cells. Many of the activity clusters comprised both cones and RBCs. Opposite to what is expected from the intact (wild-type) cone-ON bipolar cell pathway, cone and RBC activity was positively correlated and, at least partially, mediated by glutamate transporters expressed on RBCs. Deletion of gap junctional coupling between cones reduced the number of clusters, indicating that electrical cone coupling plays a crucial role for generating the observed synchronized oscillations. In conclusion, degeneration-induced synaptic remodeling of the rd1 retina results in a complex self-sustained outer retinal oscillatory network, that complements (and potentially modulates) the recently described inner retinal oscillatory network consisting of amacrine, bipolar and ganglion cells. PMID:25249942

Enhancing Electrophoretic Display Lifetime: Thiol-Polybutadiene Evaporation Barrier Property Response to Network Microstructure

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

Cook, Caitlyn Christian

An evaporation barrier is required to enhance the lifetime of electrophoretic deposition (EPD) displays. As EPD functions on the basis of reversible deposition and resuspension of colloids suspended in a solvent, evaporation of the solvent ultimately leads to device failure. Incorporation of a thiol-polybutadiene elastomer into EPD displays enabled display lifetime surpassing six months in counting and catalyzed rigid display transition into a flexible package. Final flexible display transition to mass production compels an electronic-ink approach to encapsulate display suspension within an elastomer shell. Final thiol-polybutadiene photosensitive resin network microstructure was idealized to be dense, homogeneous, and expose an elasticmore » response to deformation. Research at hand details an approach to understanding microstructural change within display elastomers. Polybutadiene-based resin properties are modified via polymer chain structure, with and without added aromatic urethane methacrylate difunctionality, and in measuring network response to variation in thiol and initiator concentration. Dynamic mechanical analysis results signify that cross-linked segments within a difunctionalized polybutadiene network were on average eight times more elastically active than that of linked segments within a non-functionalized polybutadiene network. Difunctionalized polybutadiene samples also showed a 2.5 times greater maximum elastic modulus than non-functionalized samples. Hybrid polymer composed of both polybutadiene chains encompassed TE-2000 stiffness and B-1000 elasticity for use in encapsulating display suspension. Later experiments measured kinetic and rheological response due to alteration in dithiol cross-linker chain length via real time Fourier transform infrared spectroscopy and real-time dynamic rheology. Distinct differences were discovered between dithiol resin systems, as maximum thiol conversion achieved in short and long chain length dithiols was 86% and 11%, respectively. Oscillatory real-time rheological experiments confirmed a more uniform network to better dissipate applied shear in short chain length dithiol systems, as long chain length dithiols relayed a steep internal stress build-up due to less cross-links and chain entanglements. Thorough understanding of network formation aids the production of a stronger and impermeable elastomeric barrier for preservation of EPD displays.« less

Imaging of neural oscillations with embedded inferential and group prevalence statistics.

PubMed

Donhauser, Peter W; Florin, Esther; Baillet, Sylvain

2018-02-01

Magnetoencephalography and electroencephalography (MEG, EEG) are essential techniques for studying distributed signal dynamics in the human brain. In particular, the functional role of neural oscillations remains to be clarified. For that reason, imaging methods need to identify distinct brain regions that concurrently generate oscillatory activity, with adequate separation in space and time. Yet, spatial smearing and inhomogeneous signal-to-noise are challenging factors to source reconstruction from external sensor data. The detection of weak sources in the presence of stronger regional activity nearby is a typical complication of MEG/EEG source imaging. We propose a novel, hypothesis-driven source reconstruction approach to address these methodological challenges. The imaging with embedded statistics (iES) method is a subspace scanning technique that constrains the mapping problem to the actual experimental design. A major benefit is that, regardless of signal strength, the contributions from all oscillatory sources, which activity is consistent with the tested hypothesis, are equalized in the statistical maps produced. We present extensive evaluations of iES on group MEG data, for mapping 1) induced oscillations using experimental contrasts, 2) ongoing narrow-band oscillations in the resting-state, 3) co-modulation of brain-wide oscillatory power with a seed region, and 4) co-modulation of oscillatory power with peripheral signals (pupil dilation). Along the way, we demonstrate several advantages of iES over standard source imaging approaches. These include the detection of oscillatory coupling without rejection of zero-phase coupling, and detection of ongoing oscillations in deeper brain regions, where signal-to-noise conditions are unfavorable. We also show that iES provides a separate evaluation of oscillatory synchronization and desynchronization in experimental contrasts, which has important statistical advantages. The flexibility of iES allows it to be adjusted to many experimental questions in systems neuroscience.

Imaging of neural oscillations with embedded inferential and group prevalence statistics

PubMed Central

2018-01-01

Magnetoencephalography and electroencephalography (MEG, EEG) are essential techniques for studying distributed signal dynamics in the human brain. In particular, the functional role of neural oscillations remains to be clarified. For that reason, imaging methods need to identify distinct brain regions that concurrently generate oscillatory activity, with adequate separation in space and time. Yet, spatial smearing and inhomogeneous signal-to-noise are challenging factors to source reconstruction from external sensor data. The detection of weak sources in the presence of stronger regional activity nearby is a typical complication of MEG/EEG source imaging. We propose a novel, hypothesis-driven source reconstruction approach to address these methodological challenges. The imaging with embedded statistics (iES) method is a subspace scanning technique that constrains the mapping problem to the actual experimental design. A major benefit is that, regardless of signal strength, the contributions from all oscillatory sources, which activity is consistent with the tested hypothesis, are equalized in the statistical maps produced. We present extensive evaluations of iES on group MEG data, for mapping 1) induced oscillations using experimental contrasts, 2) ongoing narrow-band oscillations in the resting-state, 3) co-modulation of brain-wide oscillatory power with a seed region, and 4) co-modulation of oscillatory power with peripheral signals (pupil dilation). Along the way, we demonstrate several advantages of iES over standard source imaging approaches. These include the detection of oscillatory coupling without rejection of zero-phase coupling, and detection of ongoing oscillations in deeper brain regions, where signal-to-noise conditions are unfavorable. We also show that iES provides a separate evaluation of oscillatory synchronization and desynchronization in experimental contrasts, which has important statistical advantages. The flexibility of iES allows it to be adjusted to many experimental questions in systems neuroscience. PMID:29408902

Impact of competitive flow on wall shear stress in coronary surgery: computational fluid dynamics of a LIMA-LAD model.

PubMed

Nordgaard, Håvard; Swillens, Abigail; Nordhaug, Dag; Kirkeby-Garstad, Idar; Van Loo, Denis; Vitale, Nicola; Segers, Patrick; Haaverstad, Rune; Lovstakken, Lasse

2010-12-01

Competitive flow from native coronary vessels is considered a major factor in the failure of coronary bypass grafts. However, the pathophysiological effects are not fully understood. Low and oscillatory wall shear stress (WSS) is known to induce endothelial dysfunction and vascular disease, like atherosclerosis and intimal hyperplasia. The aim was to investigate the impact of competitive flow on WSS in mammary artery bypass grafts. Using computational fluid dynamics, WSS was calculated in a left internal mammary artery (LIMA) graft to the left anterior descending artery in a three-dimensional in vivo porcine coronary artery bypass graft model. The following conditions were investigated: high competitive flow (non-significant coronary lesion), partial competitive flow (significant coronary lesion), and no competitive flow (totally occluded coronary vessel). Time-averaged WSS of LIMA at high, partial, and no competitive flow were 0.3-0.6, 0.6-3.0, and 0.9-3.0 Pa, respectively. Further, oscillatory WSS quantified as the oscillatory shear index (OSI) ranged from (maximum OSI = 0.5 equals zero net WSS) 0.15 to 0.35, <0.05, and <0.05, respectively. Thus, high competitive flow resulted in substantial oscillatory and low WSS. Moderate competitive flow resulted in WSS and OSI similar to the no competitive flow condition. Graft flow is highly dependent on the degree of competitive flow. High competitive flow was found to produce unfavourable WSS consistent with endothelial dysfunction and subsequent graft narrowing and failure. Partial competitive flow, however, may be better tolerated as it was found to be similar to the ideal condition of no competitive flow.

Night and day variations of sleep in patients with disorders of consciousness.

PubMed

Wislowska, Malgorzata; Del Giudice, Renata; Lechinger, Julia; Wielek, Tomasz; Heib, Dominik P J; Pitiot, Alain; Pichler, Gerald; Michitsch, Gabriele; Donis, Johann; Schabus, Manuel

2017-03-21

Brain injuries substantially change the entire landscape of oscillatory dynamics and render detection of typical sleep patterns difficult. Yet, sleep is characterized not only by specific EEG waveforms, but also by its circadian organization. In the present study we investigated whether brain dynamics of patients with disorders of consciousness systematically change between day and night. We recorded ~24 h EEG at the bedside of 18 patients diagnosed to be vigilant but unaware (Unresponsive Wakefulness Syndrome) and 17 patients revealing signs of fluctuating consciousness (Minimally Conscious State). The day-to-night changes in (i) spectral power, (ii) sleep-specific oscillatory patterns and (iii) signal complexity were analyzed and compared to 26 healthy control subjects. Surprisingly, the prevalence of sleep spindles and slow waves did not systematically vary between day and night in patients, whereas day-night changes in EEG power spectra and signal complexity were revealed in minimally conscious but not unaware patients.

System Identification Applied to Dynamic CFD Simulation and Wind Tunnel Data

NASA Technical Reports Server (NTRS)

Murphy, Patrick C.; Klein, Vladislav; Frink, Neal T.; Vicroy, Dan D.

2011-01-01

Demanding aerodynamic modeling requirements for military and civilian aircraft have provided impetus for researchers to improve computational and experimental techniques. Model validation is a key component for these research endeavors so this study is an initial effort to extend conventional time history comparisons by comparing model parameter estimates and their standard errors using system identification methods. An aerodynamic model of an aircraft performing one-degree-of-freedom roll oscillatory motion about its body axes is developed. The model includes linear aerodynamics and deficiency function parameters characterizing an unsteady effect. For estimation of unknown parameters two techniques, harmonic analysis and two-step linear regression, were applied to roll-oscillatory wind tunnel data and to computational fluid dynamics (CFD) simulated data. The model used for this study is a highly swept wing unmanned aerial combat vehicle. Differences in response prediction, parameters estimates, and standard errors are compared and discussed

Transient dynamics of a nonlinear magneto-optical rotation

NASA Astrophysics Data System (ADS)

Grewal, Raghwinder Singh; Pustelny, S.; Rybak, A.; Florkowski, M.

2018-04-01

We analyze nonlinear magneto-optical rotation (NMOR) in rubidium vapor subjected to a continuously scanned magnetic field. By varying the magnetic-field sweep rate, a transition from traditionally observed dispersivelike NMOR signals (low sweep rate) to oscillating signals (higher sweep rates) is demonstrated. The transient oscillatory behavior is studied versus light and magnetic-field parameters, revealing a strong dependence of the signals on magnetic sweep rate and light intensity. The experimental results are supported with density-matrix calculations, which enable quantitative analysis of the effect. Fitting of the signals simulated versus different parameters with a theoretically motivated curve reveals the presence of oscillatory and static components in the signals. The components depend differently on the system parameters, which suggests their distinct nature. The investigations provide insight into the dynamics of ground-state coherence generation and enable application of NMOR in detection of transient spin couplings.

Theta oscillations locked to intended actions rhythmically modulate perception.

PubMed

Tomassini, Alice; Ambrogioni, Luca; Medendorp, W Pieter; Maris, Eric

2017-07-07

Ongoing brain oscillations are known to influence perception, and to be reset by exogenous stimulations. Voluntary action is also accompanied by prominent rhythmic activity, and recent behavioral evidence suggests that this might be coupled with perception. Here, we reveal the neurophysiological underpinnings of this sensorimotor coupling in humans. We link the trial-by-trial dynamics of EEG oscillatory activity during movement preparation to the corresponding dynamics in perception, for two unrelated visual and motor tasks. The phase of theta oscillations (~4 Hz) predicts perceptual performance, even >1 s before movement. Moreover, theta oscillations are phase-locked to the onset of the movement. Remarkably, the alignment of theta phase and its perceptual relevance unfold with similar non-monotonic profiles, suggesting their relatedness. The present work shows that perception and movement initiation are automatically synchronized since the early stages of motor planning through neuronal oscillatory activity in the theta range.

Dynamic diseases in neurology and psychiatry

NASA Astrophysics Data System (ADS)

Milton, John; Black, Deborah

1995-03-01

Thirty-two (32) periodic diseases of the nervous system are identified in which symptoms and/or signs recur. In 10/32, the recurrence of a symptom complex is one of the defining features of the illness, whereas in 22/32 oscillatory signs occur in the setting of an ongoing nervous system disorder. We discuss the possibility that these disorders may be dynamic diseases.

Adaptiveness in monotone pseudo-Boolean optimization and stochastic neural computation.

PubMed

Grossi, Giuliano

2009-08-01

Hopfield neural network (HNN) is a nonlinear computational model successfully applied in finding near-optimal solutions of several difficult combinatorial problems. In many cases, the network energy function is obtained through a learning procedure so that its minima are states falling into a proper subspace (feasible region) of the search space. However, because of the network nonlinearity, a number of undesirable local energy minima emerge from the learning procedure, significantly effecting the network performance. In the neural model analyzed here, we combine both a penalty and a stochastic process in order to enhance the performance of a binary HNN. The penalty strategy allows us to gradually lead the search towards states representing feasible solutions, so avoiding oscillatory behaviors or asymptotically instable convergence. Presence of stochastic dynamics potentially prevents the network to fall into shallow local minima of the energy function, i.e., quite far from global optimum. Hence, for a given fixed network topology, the desired final distribution on the states can be reached by carefully modulating such process. The model uses pseudo-Boolean functions both to express problem constraints and cost function; a combination of these two functions is then interpreted as energy of the neural network. A wide variety of NP-hard problems fall in the class of problems that can be solved by the model at hand, particularly those having a monotonic quadratic pseudo-Boolean function as constraint function. That is, functions easily derived by closed algebraic expressions representing the constraint structure and easy (polynomial time) to maximize. We show the asymptotic convergence properties of this model characterizing its state space distribution at thermal equilibrium in terms of Markov chain and give evidence of its ability to find high quality solutions on benchmarks and randomly generated instances of two specific problems taken from the computational graph theory.

Self-sustained asynchronous irregular states and Up-Down states in thalamic, cortical and thalamocortical networks of nonlinear integrate-and-fire neurons.

PubMed

Destexhe, Alain

2009-12-01

Randomly-connected networks of integrate-and-fire (IF) neurons are known to display asynchronous irregular (AI) activity states, which resemble the discharge activity recorded in the cerebral cortex of awake animals. However, it is not clear whether such activity states are specific to simple IF models, or if they also exist in networks where neurons are endowed with complex intrinsic properties similar to electrophysiological measurements. Here, we investigate the occurrence of AI states in networks of nonlinear IF neurons, such as the adaptive exponential IF (Brette-Gerstner-Izhikevich) model. This model can display intrinsic properties such as low-threshold spike (LTS), regular spiking (RS) or fast-spiking (FS). We successively investigate the oscillatory and AI dynamics of thalamic, cortical and thalamocortical networks using such models. AI states can be found in each case, sometimes with surprisingly small network size of the order of a few tens of neurons. We show that the presence of LTS neurons in cortex or in thalamus, explains the robust emergence of AI states for relatively small network sizes. Finally, we investigate the role of spike-frequency adaptation (SFA). In cortical networks with strong SFA in RS cells, the AI state is transient, but when SFA is reduced, AI states can be self-sustained for long times. In thalamocortical networks, AI states are found when the cortex is itself in an AI state, but with strong SFA, the thalamocortical network displays Up and Down state transitions, similar to intracellular recordings during slow-wave sleep or anesthesia. Self-sustained Up and Down states could also be generated by two-layer cortical networks with LTS cells. These models suggest that intrinsic properties such as adaptation and low-threshold bursting activity are crucial for the genesis and control of AI states in thalamocortical networks.

Modulation of Frontoparietal Neurovascular Dynamics in Working Memory

PubMed Central

Ardestani, Allen; Shen, Wei; Darvas, Felix; Toga, Arthur W.; Fuster, Joaquin M.

2016-01-01

Our perception of the world is represented in widespread, overlapping, and interactive neuronal networks of the cerebral cortex. A majority of physiological studies on the subject have focused on oscillatory synchrony as the binding mechanism for representation and transmission of neural information. Little is known, however, about the stability of that synchrony during prolonged cognitive operations that span more than just a few seconds. The present research, in primates, investigated the dynamic patterns of oscillatory synchrony by two complementary recording methods, surface field potentials (SFPs) and near-infrared spectroscopy (NIRS). The signals were first recorded during the resting state to examine intrinsic functional connectivity. The temporal modulation of coactivation was then examined on both signals during performance of working memory ( WM) tasks with long delays (memory retention epochs). In both signals, the peristimulus period exhibited characteristic features in frontal and parietal regions. Examination of SFP signals over delays lasting tens of seconds, however, revealed alternations of synchronization and desynchronization. These alternations occurred within the same frequency bands observed in the peristimulus epoch, without a specific correspondence between any definite cognitive process (e.g., WM) and synchrony within a given frequency band. What emerged instead was a correlation between the degree of SFP signal fragmentation (in time, frequency, and brain space) and the complexity and efficiency of the task being performed. In other words, the incidence and extent of SFP transitions between synchronization and desynchronization—rather than the absolute degree of synchrony—augmented in correct task performance compared with incorrect performance or in a control task without WM demand. An opposite relationship was found in NIRS: increasing task complexity induced more uniform, rather than fragmented, NIRS coactivations. These findings indicate that the particular features of neural oscillations cannot be linearly mapped to cognitive functions. Rather, information and the cognitive operations performed on it are primarily reflected in their modulations over time. The increased complexity and fragmentation of electrical frequencies in WM may reflect the activation of hierarchically diverse cognits (cognitive networks) in that condition. Conversely, the homogeneity in coherence of NIRS responses may reflect the cumulative vascular reactions that accompany that neuroelectrical proliferation of frequencies and the longer time constant of the NIRS signal. These findings are directly relevant to the mechanisms mediating cognitive processes and to physiologically based interpretations of functional brain imaging. PMID:26679214

Characterizing Oscillatory Bursts in Single-Trial EEG Data

NASA Technical Reports Server (NTRS)

Knuth, K. H.; Shah, A. S.; Lakatos, P.; Schroeder, C. E.

2004-01-01

Oscillatory bursts in numerous bands ranging from low (theta) to high frequencies (e.g., gamma) undoubtedly play an important role in cortical dynamics. Largely because of the inadequacy of existing analytic techniques. however, oscillatory bursts and their role in cortical processing remains poorly understood. To study oscillatory bursts effectively one must be able to isolate them and characterize them in the single trial. We describe a series of straightforward analysis techniques that produce useful indices of burst characteristics. First, stimulus-evoked responses are estimated using Differentially Variable Component Analysis (dVCA), and are subtracted from the single-trial. The single-trial characteristics of the evoked responses are stored to identify possible correlations with burst activity. Time-frequency (T-F), or wavelet, analyses are then applied to the single trial residuals. While T-F plots have been used in recent studies to identify and isolate bursts, we go further by fitting each burst in the T-F plot with a two-dimensional Gaussian. This provides a set of burst characteristics, such as, center time. burst duration, center frequency. frequency dispersion. and amplitude, all of which contribute to the accurate characterization of the individual burst. The burst phase can also be estimated. Burst characteristics can be quantified with several standard techniques (e.g.. histogramming and clustering), as well as Bayesian techniques (e.g., blocking) to allow a more parametric description analysis of the characteristics of oscillatory bursts, and the relationships of specific parameters to cortical excitability and stimulus integration.

Dynamics of human subthalamic neuron phase-locking to motor and sensory cortical oscillations during movement.

PubMed

Lipski, Witold J; Wozny, Thomas A; Alhourani, Ahmad; Kondylis, Efstathios D; Turner, Robert S; Crammond, Donald J; Richardson, Robert Mark

2017-09-01

Coupled oscillatory activity recorded between sensorimotor regions of the basal ganglia-thalamocortical loop is thought to reflect information transfer relevant to movement. A neuronal firing-rate model of basal ganglia-thalamocortical circuitry, however, has dominated thinking about basal ganglia function for the past three decades, without knowledge of the relationship between basal ganglia single neuron firing and cortical population activity during movement itself. We recorded activity from 34 subthalamic nucleus (STN) neurons, simultaneously with cortical local field potentials and motor output, in 11 subjects with Parkinson's disease (PD) undergoing awake deep brain stimulator lead placement. STN firing demonstrated phase synchronization to both low- and high-beta-frequency cortical oscillations, and to the amplitude envelope of gamma oscillations, in motor cortex. We found that during movement, the magnitude of this synchronization was dynamically modulated in a phase-frequency-specific manner. Importantly, we found that phase synchronization was not correlated with changes in neuronal firing rate. Furthermore, we found that these relationships were not exclusive to motor cortex, because STN firing also demonstrated phase synchronization to both premotor and sensory cortex. The data indicate that models of basal ganglia function ultimately will need to account for the activity of populations of STN neurons that are bound in distinct functional networks with both motor and sensory cortices and code for movement parameters independent of changes in firing rate. NEW & NOTEWORTHY Current models of basal ganglia-thalamocortical networks do not adequately explain simple motor functions, let alone dysfunction in movement disorders. Our findings provide data that inform models of human basal ganglia function by demonstrating how movement is encoded by networks of subthalamic nucleus (STN) neurons via dynamic phase synchronization with cortex. The data also demonstrate, for the first time in humans, a mechanism through which the premotor and sensory cortices are functionally connected to the STN. Copyright © 2017 the American Physiological Society.

Symmetries of Chimera States

NASA Astrophysics Data System (ADS)

Kemeth, Felix P.; Haugland, Sindre W.; Krischer, Katharina

2018-05-01

Symmetry broken states arise naturally in oscillatory networks. In this Letter, we investigate chaotic attractors in an ensemble of four mean-coupled Stuart-Landau oscillators with two oscillators being synchronized. We report that these states with partially broken symmetry, so-called chimera states, have different setwise symmetries in the incoherent oscillators, and in particular, some are and some are not invariant under a permutation symmetry on average. This allows for a classification of different chimera states in small networks. We conclude our report with a discussion of related states in spatially extended systems, which seem to inherit the symmetry properties of their counterparts in small networks.

Nonlinear dynamics of resonant electrons interacting with coherent Langmuir waves

NASA Astrophysics Data System (ADS)

Tobita, Miwa; Omura, Yoshiharu

2018-03-01

We study the nonlinear dynamics of resonant particles interacting with coherent waves in space plasmas. Magnetospheric plasma waves such as whistler-mode chorus, electromagnetic ion cyclotron waves, and hiss emissions contain coherent wave structures with various discrete frequencies. Although these waves are electromagnetic, their interaction with resonant particles can be approximated by equations of motion for a charged particle in a one-dimensional electrostatic wave. The equations are expressed in the form of nonlinear pendulum equations. We perform test particle simulations of electrons in an electrostatic model with Langmuir waves and a non-oscillatory electric field. We solve equations of motion and study the dynamics of particles with different values of inhomogeneity factor S defined as a ratio of the non-oscillatory electric field intensity to the wave amplitude. The simulation results demonstrate deceleration/acceleration, thermalization, and trapping of particles through resonance with a single wave, two waves, and multiple waves. For two-wave and multiple-wave cases, we describe the wave-particle interaction as either coherent or incoherent based on the probability of nonlinear trapping.

Spatially Localized Chemical Patterns around an A + B → Oscillator Front.

PubMed

Budroni, M A; Lemaigre, L; Escala, D M; Muñuzuri, A P; De Wit, A

2016-02-18

When two gels, each loaded with a different set of reactants A and B of an oscillatory reaction, are brought into contact, reaction-diffusion patterns such as waves or Turing patterns can develop in the reactive contact zone. The initial condition which separates the reactants at the beginning leads to a localization in space of the different dynamical regimes accessible to the chemical oscillator. We study here both numerically and experimentally the composite traveling structures resulting from the interaction between chemical fronts and localized waves in the case in which the reactants of such an A + B → oscillator system are those of the canonical Belousov-Zhabotinsky (BZ) oscillating reaction. A transition between different dynamics is obtained by varying the initial concentration of the organic substrate of the BZ reactants, which is one of the parameters controlling the local excitability. We show that the dynamical regime (excitable or oscillatory) characterizing the BZ oscillator in the initial contact area is the key feature which determines the spatiotemporal evolution of the system. The experimental results are in qualitative agreement with the theoretical predictions.

Direct observation of forward-scattering oscillations in the H+HD→H2+D reaction.

PubMed

Yuan, Daofu; Yu, Shengrui; Chen, Wentao; Sang, Jiwei; Luo, Chang; Wang, Tao; Xu, Xin; Casavecchia, Piergiorgio; Wang, Xingan; Sun, Zhigang; Zhang, Dong H; Yang, Xueming

2018-06-01

Accurate measurements of product state-resolved angular distributions are central to fundamental studies of chemical reaction dynamics. Yet, fine quantum-mechanical structures in product angular distributions of a reactive scattering process, such as the fast oscillations in the forward-scattering direction, have never been observed experimentally and the nature of these oscillations has not been fully explored. Here we report the crossed-molecular-beam experimental observation of these fast forward-scattering oscillations in the product angular distribution of the benchmark chemical reaction, H + HD → H 2  + D. Clear oscillatory structures are observed for the H 2 (v' = 0, j' = 1, 3) product states at a collision energy of 1.35 eV, in excellent agreement with the quantum-mechanical dynamics calculations. Our analysis reveals that the oscillatory forward-scattering components are mainly contributed by the total angular momentum J around 28. The partial waves and impact parameters responsible for the forward scatterings are also determined from these observed oscillations, providing crucial dynamics information on the transient reaction process.

Oscillatory dynamics in rock-paper-scissors games with mutations.

PubMed

Mobilia, Mauro

2010-05-07

We study the oscillatory dynamics in the generic three-species rock-paper-scissors games with mutations. In the mean-field limit, different behaviors are found: (a) for high mutation rate, there is a stable interior fixed point with coexistence of all species; (b) for low mutation rates, there is a region of the parameter space characterized by a limit cycle resulting from a Hopf bifurcation; (c) in the absence of mutations, there is a region where heteroclinic cycles yield oscillations of large amplitude (not robust against noise). After a discussion on the main properties of the mean-field dynamics, we investigate the stochastic version of the model within an individual-based formulation. Demographic fluctuations are therefore naturally accounted and their effects are studied using a diffusion theory complemented by numerical simulations. It is thus shown that persistent erratic oscillations (quasi-cycles) of large amplitude emerge from a noise-induced resonance phenomenon. We also analytically and numerically compute the average escape time necessary to reach a (quasi-)cycle on which the system oscillates at a given amplitude. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

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

Impaired theta phase-resetting underlying auditory N1 suppression in chronic alcoholism.

PubMed

Fuentemilla, Lluis; Marco-Pallarés, Josep; Gual, Antoni; Escera, Carles; Polo, Maria Dolores; Grau, Carles

2009-02-18

It has been suggested that chronic alcoholism may lead to altered neural mechanisms related to inhibitory processes. Here, we studied auditory N1 suppression phenomena (i.e. amplitude reduction with repetitive stimuli) in chronic alcoholic patients as an early-stage information-processing brain function involving inhibition by the analysis of the N1 event-related potential and time-frequency computation (spectral power and phase-resetting). Our results showed enhanced neural theta oscillatory phase-resetting underlying N1 generation in suppressed N1 event-related potential. The present findings suggest that chronic alcoholism alters neural oscillatory synchrony dynamics at very early stages of information processing.

Oscillatory flow in the cochlea visualized by a magnetic resonance imaging technique.

PubMed

Denk, W; Keolian, R M; Ogawa, S; Jelinski, L W

1993-02-15

We report a magnetic resonance imaging technique that directly measures motion of cochlear fluids. It uses oscillating magnetic field gradients phase-locked to an external stimulus to selectively visualize and quantify oscillatory fluid motion. It is not invasive, and it does not require optical line-of-sight access to the inner ear. It permits the detection of displacements far smaller than the spatial resolution. The method is demonstrated on a phantom and on living rats. It is projected to have applications for auditory research, for the visualization of vocal tract dynamics during speech and singing, and for determination of the spatial distribution of mechanical relaxations in materials.

Combined effects of heat and mass transfer to magneto hydrodynamics oscillatory dusty fluid flow in a porous channel

NASA Astrophysics Data System (ADS)

Govindarajan, A.; Vijayalakshmi, R.; Ramamurthy, V.

2018-04-01

The main aim of this article is to study the combined effects of heat and mass transfer to radiative Magneto Hydro Dynamics (MHD) oscillatory optically thin dusty fluid in a saturated porous medium channel. Based on certain assumptions, the momentum, energy, concentration equations are obtained.The governing equations are non-dimensionalised, simplified and solved analytically. The closed analytical form solutions for velocity, temperature, concentration profiles are obtained. Numerical computations are presented graphically to show the salient features of various physical parameters. The shear stress, the rate of heat transfer and the rate of mass transfer are also presented graphically.

Synchrony, waves and ripple in spatially coupled Kuramoto oscillators with Mexican hat connectivity.

PubMed

Heitmann, Stewart; Ermentrout, G Bard

2015-06-01

Spatiotemporal waves of synchronized activity are known to arise in oscillatory neural networks with lateral inhibitory coupling. How such patterns respond to dynamic changes in coupling strength is largely unexplored. The present study uses analysis and simulation to investigate the evolution of wave patterns when the strength of lateral inhibition is varied dynamically. Neural synchronization was modeled by a spatial ring of Kuramoto oscillators with Mexican hat lateral coupling. Broad bands of coexisting stable wave solutions were observed at all levels of inhibition. The stability of these waves was formally analyzed in both the infinite ring and the finite ring. The broad range of multi-stability predicted hysteresis in transitions between neighboring wave solutions when inhibition is slowly varied. Numerical simulation confirmed the predicted transitions when inhibition was ramped down from a high initial value. However, non-wave solutions emerged from the uniform solution when inhibition was ramped upward from zero. These solutions correspond to spatially periodic deviations of phase that we call ripple states. Numerical continuation showed that stable ripple states emerge from synchrony via a supercritical pitchfork bifurcation. The normal form of this bifurcation was derived analytically, and its predictions compared against the numerical results. Ripple states were also found to bifurcate from wave solutions, but these were locally unstable. Simulation also confirmed the existence of hysteresis and ripple states in two spatial dimensions. Our findings show that spatial synchronization patterns can remain structurally stable despite substantial changes in network connectivity.

Detecting event-related changes of multivariate phase coupling in dynamic brain networks.

PubMed

Canolty, Ryan T; Cadieu, Charles F; Koepsell, Kilian; Ganguly, Karunesh; Knight, Robert T; Carmena, Jose M

2012-04-01

Oscillatory phase coupling within large-scale brain networks is a topic of increasing interest within systems, cognitive, and theoretical neuroscience. Evidence shows that brain rhythms play a role in controlling neuronal excitability and response modulation (Haider B, McCormick D. Neuron 62: 171-189, 2009) and regulate the efficacy of communication between cortical regions (Fries P. Trends Cogn Sci 9: 474-480, 2005) and distinct spatiotemporal scales (Canolty RT, Knight RT. Trends Cogn Sci 14: 506-515, 2010). In this view, anatomically connected brain areas form the scaffolding upon which neuronal oscillations rapidly create and dissolve transient functional networks (Lakatos P, Karmos G, Mehta A, Ulbert I, Schroeder C. Science 320: 110-113, 2008). Importantly, testing these hypotheses requires methods designed to accurately reflect dynamic changes in multivariate phase coupling within brain networks. Unfortunately, phase coupling between neurophysiological signals is commonly investigated using suboptimal techniques. Here we describe how a recently developed probabilistic model, phase coupling estimation (PCE; Cadieu C, Koepsell K Neural Comput 44: 3107-3126, 2010), can be used to investigate changes in multivariate phase coupling, and we detail the advantages of this model over the commonly employed phase-locking value (PLV; Lachaux JP, Rodriguez E, Martinerie J, Varela F. Human Brain Map 8: 194-208, 1999). We show that the N-dimensional PCE is a natural generalization of the inherently bivariate PLV. Using simulations, we show that PCE accurately captures both direct and indirect (network mediated) coupling between network elements in situations where PLV produces erroneous results. We present empirical results on recordings from humans and nonhuman primates and show that the PCE-estimated coupling values are different from those using the bivariate PLV. Critically on these empirical recordings, PCE output tends to be sparser than the PLVs, indicating fewer significant interactions and perhaps a more parsimonious description of the data. Finally, the physical interpretation of PCE parameters is straightforward: the PCE parameters correspond to interaction terms in a network of coupled oscillators. Forward modeling of a network of coupled oscillators with parameters estimated by PCE generates synthetic data with statistical characteristics identical to empirical signals. Given these advantages over the PLV, PCE is a useful tool for investigating multivariate phase coupling in distributed brain networks.

Oscillatory Activities in Neurological Disorders of Elderly: Biomarkers to Target for Neuromodulation.

PubMed

Giovanni, Assenza; Capone, Fioravante; di Biase, Lazzaro; Ferreri, Florinda; Florio, Lucia; Guerra, Andrea; Marano, Massimo; Paolucci, Matteo; Ranieri, Federico; Salomone, Gaetano; Tombini, Mario; Thut, Gregor; Di Lazzaro, Vincenzo

2017-01-01

Non-invasive brain stimulation (NIBS) has been under investigation as adjunct treatment of various neurological disorders with variable success. One challenge is the limited knowledge on what would be effective neuronal targets for an intervention, combined with limited knowledge on the neuronal mechanisms of NIBS. Motivated on the one hand by recent evidence that oscillatory activities in neural systems play a role in orchestrating brain functions and dysfunctions, in particular those of neurological disorders specific of elderly patients, and on the other hand that NIBS techniques may be used to interact with these brain oscillations in a controlled way, we here explore the potential of modulating brain oscillations as an effective strategy for clinical NIBS interventions. We first review the evidence for abnormal oscillatory profiles to be associated with a range of neurological disorders of elderly (e.g., Parkinson's disease (PD), Alzheimer's disease (AD), stroke, epilepsy), and for these signals of abnormal network activity to normalize with treatment, and/or to be predictive of disease progression or recovery. We then ask the question to what extent existing NIBS protocols have been tailored to interact with these oscillations and possibly associated dysfunctions. Our review shows that, despite evidence for both reliable neurophysiological markers of specific oscillatory dis-functionalities in neurological disorders and NIBS protocols potentially able to interact with them, there are few applications of NIBS aiming to explore clinical outcomes of this interaction. Our review article aims to point out oscillatory markers of neurological, which are also suitable targets for modification by NIBS, in order to facilitate in future studies the matching of technical application to clinical targets.

Oscillatory Activities in Neurological Disorders of Elderly: Biomarkers to Target for Neuromodulation

PubMed Central

Assenza, Giovanni; Capone, Fioravante; di Biase, Lazzaro; Ferreri, Florinda; Florio, Lucia; Guerra, Andrea; Marano, Massimo; Paolucci, Matteo; Ranieri, Federico; Salomone, Gaetano; Tombini, Mario; Thut, Gregor; Di Lazzaro, Vincenzo

2017-01-01

Non-invasive brain stimulation (NIBS) has been under investigation as adjunct treatment of various neurological disorders with variable success. One challenge is the limited knowledge on what would be effective neuronal targets for an intervention, combined with limited knowledge on the neuronal mechanisms of NIBS. Motivated on the one hand by recent evidence that oscillatory activities in neural systems play a role in orchestrating brain functions and dysfunctions, in particular those of neurological disorders specific of elderly patients, and on the other hand that NIBS techniques may be used to interact with these brain oscillations in a controlled way, we here explore the potential of modulating brain oscillations as an effective strategy for clinical NIBS interventions. We first review the evidence for abnormal oscillatory profiles to be associated with a range of neurological disorders of elderly (e.g., Parkinson’s disease (PD), Alzheimer’s disease (AD), stroke, epilepsy), and for these signals of abnormal network activity to normalize with treatment, and/or to be predictive of disease progression or recovery. We then ask the question to what extent existing NIBS protocols have been tailored to interact with these oscillations and possibly associated dysfunctions. Our review shows that, despite evidence for both reliable neurophysiological markers of specific oscillatory dis-functionalities in neurological disorders and NIBS protocols potentially able to interact with them, there are few applications of NIBS aiming to explore clinical outcomes of this interaction. Our review article aims to point out oscillatory markers of neurological, which are also suitable targets for modification by NIBS, in order to facilitate in future studies the matching of technical application to clinical targets. PMID:28659788

Oscillatory brain activity in spontaneous and induced sleep stages in flies.

PubMed

Yap, Melvyn H W; Grabowska, Martyna J; Rohrscheib, Chelsie; Jeans, Rhiannon; Troup, Michael; Paulk, Angelique C; van Alphen, Bart; Shaw, Paul J; van Swinderen, Bruno

2017-11-28

Sleep is a dynamic process comprising multiple stages, each associated with distinct electrophysiological properties and potentially serving different functions. While these phenomena are well described in vertebrates, it is unclear if invertebrates have distinct sleep stages. We perform local field potential (LFP) recordings on flies spontaneously sleeping, and compare their brain activity to flies induced to sleep using either genetic activation of sleep-promoting circuitry or the GABA A agonist Gaboxadol. We find a transitional sleep stage associated with a 7-10 Hz oscillation in the central brain during spontaneous sleep. Oscillatory activity is also evident when we acutely activate sleep-promoting neurons in the dorsal fan-shaped body (dFB) of Drosophila. In contrast, sleep following Gaboxadol exposure is characterized by low-amplitude LFPs, during which dFB-induced effects are suppressed. Sleep in flies thus appears to involve at least two distinct stages: increased oscillatory activity, particularly during sleep induction, followed by desynchronized or decreased brain activity.

Relationship between the mechanisms of gamma rhythm generation and the magnitude of the macroscopic phase response function in a population of excitatory and inhibitory modified quadratic integrate-and-fire neurons

NASA Astrophysics Data System (ADS)

Akao, Akihiko; Ogawa, Yutaro; Jimbo, Yasuhiko; Ermentrout, G. Bard; Kotani, Kiyoshi

2018-01-01

Gamma oscillations are thought to play an important role in brain function. Interneuron gamma (ING) and pyramidal interneuron gamma (PING) mechanisms have been proposed as generation mechanisms for these oscillations. However, the relation between the generation mechanisms and the dynamical properties of the gamma oscillation are still unclear. Among the dynamical properties of the gamma oscillation, the phase response function (PRF) is important because it encodes the response of the oscillation to inputs. Recently, the PRF for an inhibitory population of modified theta neurons that generate an ING rhythm was computed by the adjoint method applied to the associated Fokker-Planck equation (FPE) for the model. The modified theta model incorporates conductance-based synapses as well as the voltage and current dynamics. Here, we extended this previous work by creating an excitatory-inhibitory (E-I) network using the modified theta model and described the population dynamics with the corresponding FPE. We conducted a bifurcation analysis of the FPE to find parameter regions which generate gamma oscillations. In order to label the oscillatory parameter regions by their generation mechanisms, we defined ING- and PING-type gamma oscillation in a mathematically plausible way based on the driver of the inhibitory population. We labeled the oscillatory parameter regions by these generation mechanisms and derived PRFs via the adjoint method on the FPE in order to investigate the differences in the responses of each type of oscillation to inputs. PRFs for PING and ING mechanisms are derived and compared. We found the amplitude of the PRF for the excitatory population is larger in the PING case than in the ING case. Finally, the E-I population of the modified theta neuron enabled us to analyze the PRFs of PING-type gamma oscillation and the entrainment ability of E and I populations. We found a parameter region in which PRFs of E and I are both purely positive in the case of PING oscillations. The different entrainment abilities of E and I stimulation as governed by the respective PRFs was compared to direct simulations of finite populations of model neurons. We find that it is easier to entrain the gamma rhythm by stimulating the inhibitory population than by stimulating the excitatory population as has been found experimentally.

Bubble Dynamics on a Heated Surface

NASA Technical Reports Server (NTRS)

Kassemi, M.; Rashidnia, N.

1999-01-01

In this work, we study steady and oscillatory thermocapillary and natural convective flows generated by a bubble on a heated solid surface. The interaction between gas and vapor bubbles with the surrounding fluid is of interest for both space and ground-based processing. A combined numerical-experimental approach is adopted here. The temperature field is visualized using Mach-Zehnder and/or Wollaston Prism Interferometry and the flow field is observed by a laser sheet flow visualization technique. A finite element numerical model is developed which solves the transient two-dimensional continuity, momentum, and energy equations and includes the effects of temperature-dependent surface tension and bubble surface deformation. Below the critical Marangoni number, the steady state low-g and 1-g temperature and velocity fields predicted by the finite element model are in excellent agreement with both the visualization experiments in our laboratory and recently published experimental results in the literature. Above the critical Marangoni number, the model predicts an oscillatory flow which is also closely confirmed by experiments. It is shown that the dynamics of the oscillatory flow are directly controlled by the thermal and hydrodynamic interactions brought about by combined natural and thermocapillary convection. Therefore, as numerical simulations show, there are considerable differences between the 1-g and low-g temperature and flow fields at both low and high Marangoni numbers. This has serious implications for both materials processing and fluid management in space.

Transitions between Multiband Oscillatory Patterns Characterize Memory-Guided Perceptual Decisions in Prefrontal Circuits.

PubMed

Wimmer, Klaus; Ramon, Marc; Pasternak, Tatiana; Compte, Albert

2016-01-13

Neuronal activity in the lateral prefrontal cortex (LPFC) reflects the structure and cognitive demands of memory-guided sensory discrimination tasks. However, we still do not know how neuronal activity articulates in network states involved in perceiving, remembering, and comparing sensory information during such tasks. Oscillations in local field potentials (LFPs) provide fingerprints of such network dynamics. Here, we examined LFPs recorded from LPFC of macaques while they compared the directions or the speeds of two moving random-dot patterns, S1 and S2, separated by a delay. LFP activity in the theta, beta, and gamma bands tracked consecutive components of the task. In response to motion stimuli, LFP theta and gamma power increased, and beta power decreased, but showed only weak motion selectivity. In the delay, LFP beta power modulation anticipated the onset of S2 and encoded the task-relevant S1 feature, suggesting network dynamics associated with memory maintenance. After S2 onset the difference between the current stimulus S2 and the remembered S1 was strongly reflected in broadband LFP activity, with an early sensory-related component proportional to stimulus difference and a later choice-related component reflecting the behavioral decision buildup. Our results demonstrate that individual LFP bands reflect both sensory and cognitive processes engaged independently during different stages of the task. This activation pattern suggests that during elementary cognitive tasks, the prefrontal network transitions dynamically between states and that these transitions are characterized by the conjunction of LFP rhythms rather than by single LFP bands. Neurons in the brain communicate through electrical impulses and coordinate this activity in ensembles that pulsate rhythmically, very much like musical instruments in an orchestra. These rhythms change with "brain state," from sleep to waking, but also signal with different oscillation frequencies rapid changes between sensory and cognitive processing. Here, we studied rhythmic electrical activity in the monkey prefrontal cortex, an area implicated in working memory, decision making, and executive control. Monkeys had to identify and remember a visual motion pattern and compare it to a second pattern. We found orderly transitions between rhythmic activity where the same frequency channels were active in all ongoing prefrontal computations. This supports prefrontal circuit dynamics that transitions rapidly between complex rhythmic patterns during structured cognitive tasks. Copyright © 2016 the authors 0270-6474/16/360489-17$15.00/0.

Complex networks with large numbers of labelable attractors

NASA Astrophysics Data System (ADS)

Mi, Yuanyuan; Zhang, Lisheng; Huang, Xiaodong; Qian, Yu; Hu, Gang; Liao, Xuhong

2011-09-01

Information storage in many functional subsystems of the brain is regarded by theoretical neuroscientists to be related to attractors of neural networks. The number of attractors is large and each attractor can be temporarily represented or suppressed easily by corresponding external stimulus. In this letter, we discover that complex networks consisting of excitable nodes have similar fascinating properties of coexistence of large numbers of oscillatory attractors, most of which can be labeled with a few nodes. According to a simple labeling rule, different attractors can be identified and the number of labelable attractors can be predicted from the analysis of network topology. With the cues of the labeling association, these attractors can be conveniently retrieved or suppressed on purpose.

The influence of oscillations on product selectivity during the palladium-catalysed phenylacetylene oxidative carbonylation reaction.

PubMed

Novakovic, Katarina; Grosjean, Christophe; Scott, Stephen K; Whiting, Andrew; Willis, Mark J; Wright, Allen R

2008-02-07

This paper reports on the influence of oscillations on product selectivity as well as the dynamics of product formation during the palladium-catalysed phenylacetylene oxidative carbonylation reaction in a catalytic system (PdI2, KI, Air, NaOAc in methanol). The occurrence of the pH oscillations is related to PdI2 granularity and the initial pH drop after phenylacetylene addition. To achieve pH and reaction exotherm oscillations regulation of the amount of PdI2 is required, ensuring that the initial pH does not fall significantly below 1 after phenylacetylene addition. Experiments in both oscillatory and non-oscillatory pH regimes were performed in an HEL SIMULAR reaction calorimeter with the concentration-time profiles measured using a GC-MS. It is demonstrated that when operating in an oscillatory pH regime product formation may be suppressed until oscillations occur after which there is a steep increase in the formation of Z-2-phenyl-but-2-enedioic acid dimethyl ester. When operating in non-oscillatory pH mode the products are formed steadily over time with the main products being Z-2-phenyl-but-2-enedioic acid dimethyl ester, 2-phenyl-acrylic acid methyl ester and E-3-phenyl-acrylic acid methyl ester.

Attractor Metabolic Networks

PubMed Central

De la Fuente, Ildefonso M.; Cortes, Jesus M.; Pelta, David A.; Veguillas, Juan

2013-01-01

Background The experimental observations and numerical studies with dissipative metabolic networks have shown that cellular enzymatic activity self-organizes spontaneously leading to the emergence of a Systemic Metabolic Structure in the cell, characterized by a set of different enzymatic reactions always locked into active states (metabolic core) while the rest of the catalytic processes are only intermittently active. This global metabolic structure was verified for Escherichia coli, Helicobacter pylori and Saccharomyces cerevisiae, and it seems to be a common key feature to all cellular organisms. In concordance with these observations, the cell can be considered a complex metabolic network which mainly integrates a large ensemble of self-organized multienzymatic complexes interconnected by substrate fluxes and regulatory signals, where multiple autonomous oscillatory and quasi-stationary catalytic patterns simultaneously emerge. The network adjusts the internal metabolic activities to the external change by means of flux plasticity and structural plasticity. Methodology/Principal Findings In order to research the systemic mechanisms involved in the regulation of the cellular enzymatic activity we have studied different catalytic activities of a dissipative metabolic network under different external stimuli. The emergent biochemical data have been analysed using statistical mechanic tools, studying some macroscopic properties such as the global information and the energy of the system. We have also obtained an equivalent Hopfield network using a Boltzmann machine. Our main result shows that the dissipative metabolic network can behave as an attractor metabolic network. Conclusions/Significance We have found that the systemic enzymatic activities are governed by attractors with capacity to store functional metabolic patterns which can be correctly recovered from specific input stimuli. The network attractors regulate the catalytic patterns, modify the efficiency in the connection between the multienzymatic complexes, and stably retain these modifications. Here for the first time, we have introduced the general concept of attractor metabolic network, in which this dynamic behavior is observed. PMID:23554883

Oscillations and patterns in a model of simultaneous CO and C2H2 oxidation and NO(x) reduction in a cross-flow reactor.

PubMed

Hadač, Otto; Kohout, Martin; Havlica, Jaromír; Schreiber, Igor

2015-03-07

A model describing simultaneous catalytic oxidation of CO and C2H2 and reduction of NOx in a cross-flow tubular reactor is explored with the aim of relating spatiotemporal patterns to specific pathways in the mechanism. For that purpose, a detailed mechanism proposed for three-way catalytic converters is split into two subsystems, (i) simultaneous oxidation of CO and C2H2, and (ii) oxidation of CO combined with NOx reduction. The ability of these two subsystems to display mechanism-specific dynamical effects is studied initially by neglecting transport phenomena and applying stoichiometric network and bifurcation analyses. We obtain inlet temperature - inlet oxygen concentration bifurcation diagrams, where each region possessing specific dynamics - oscillatory, bistable and excitable - is associated with a dominant reaction pathway. Next, the spatiotemporal behaviour due to reaction kinetics combined with transport processes is studied. The observed spatiotemporal patterns include phase waves, travelling fronts, pulse waves and spatiotemporal chaos. Although these types of pattern occur generally when the kinetic scheme possesses autocatalysis, we find that some of their properties depend on the underlying dominant reaction pathway. The relation of patterns to specific reaction pathways is discussed.

Effects of delay and noise in a negative feedback regulatory motif

NASA Astrophysics Data System (ADS)

Palassini, Matteo; Dies, Marta

2009-03-01

The small copy number of the molecules involved in gene regulation can induce nontrivial stochastic phenomena such as noise-induced oscillations. An often neglected aspect of regulation dynamics are the delays involved in transcription and translation. Delays introduce analytical and computational complications because the dynamics is non-Markovian. We study the interplay of noise and delays in a negative feedback model of the p53 core regulatory network. Recent experiments have found pronounced oscillations in the concentrations of proteins p53 and Mdm2 in individual cells subjected to DNA damage. Similar oscillations occur in the Hes-1 and NK-kB systems, and in circadian rhythms. Several mechanisms have been proposed to explain this oscillatory behaviour, such as deterministic limit cycles, with and without delay, or noise-induced excursions in excitable models. We consider a generic delayed Master Equation incorporating the activation of Mdm2 by p53 and the Mdm2-promoted degradation of p53. In the deterministic limit and for large delays, the model shows a Hopf bifurcation. Via exact stochastic simulations, we find strong noise-induced oscillations well outside the limit-cycle region. We propose that this may be a generic mechanism for oscillations in gene regulatory systems.

Oscillatory Alpha-Band Suppression Mechanisms during the Rapid Attentional Shifts Required to Perform an Anti-Saccade Task

PubMed Central

Belyusar, Daniel; Snyder, Adam C.; Frey, Hans-Peter; Harwood, Mark R.; Wallman, Josh; Foxe, John J.

2015-01-01

Neuroimaging has demonstrated anatomical overlap between covert and overt attention systems, although behavioral and electrophysiological studies have suggested that the two systems do not rely on entirely identical circuits or mechanisms. In a parallel line of research, topographically-specific modulations of alpha-band power (~8-14Hz) have been consistently correlated with anticipatory states during tasks requiring covert attention shifts. These tasks, however, typically employ cue-target-interval paradigms where attentional processes are examined across relatively protracted periods of time and not at the rapid timescales implicated during overt attention tasks. The anti-saccade task, where one must first covertly attend for a peripheral target, before executing a rapid overt attention shift (i.e. a saccade) to the opposite side of space, is particularly well-suited for examining the rapid dynamics of overt attentional deployments. Here, we asked whether alpha-band oscillatory mechanisms would also be associated with these very rapid overt shifts, potentially representing a common neural mechanism across overt and covert attention systems. High-density electroencephalography in conjunction with infra-red eye-tracking was recorded while participants engaged in both pro- and anti- saccade task blocks. Alpha power, time-locked to saccade onset, showed three distinct phases of significantly lateralized topographic shifts, all occurring within a period of less than one second, closely reflecting the temporal dynamics of anti-saccade performance. Only two such phases were observed during the pro-saccade task. These data point to substantially more rapid temporal dynamics of alpha-band suppressive mechanisms than previously established, and implicate oscillatory alpha-band activity as a common mechanism across both overt and covert attentional deployments. PMID:23041338

Bursting endemic bubbles in an adaptive network

NASA Astrophysics Data System (ADS)

Sherborne, N.; Blyuss, K. B.; Kiss, I. Z.

2018-04-01

The spread of an infectious disease is known to change people's behavior, which in turn affects the spread of disease. Adaptive network models that account for both epidemic and behavioral change have found oscillations, but in an extremely narrow region of the parameter space, which contrasts with intuition and available data. In this paper we propose a simple susceptible-infected-susceptible epidemic model on an adaptive network with time-delayed rewiring, and show that oscillatory solutions are now present in a wide region of the parameter space. Altering the transmission or rewiring rates reveals the presence of an endemic bubble—an enclosed region of the parameter space where oscillations are observed.

Recognition and classification of oscillatory patterns of electric brain activity using artificial neural network approach

NASA Astrophysics Data System (ADS)

Pchelintseva, Svetlana V.; Runnova, Anastasia E.; Musatov, Vyacheslav Yu.; Hramov, Alexander E.

2017-03-01

In the paper we study the problem of recognition type of the observed object, depending on the generated pattern and the registered EEG data. EEG recorded at the time of displaying cube Necker characterizes appropriate state of brain activity. As an image we use bistable image Necker cube. Subject selects the type of cube and interpret it either as aleft cube or as the right cube. To solve the problem of recognition, we use artificial neural networks. In our paper to create a classifier we have considered a multilayer perceptron. We examine the structure of the artificial neural network and define cubes recognition accuracy.

Weak temporal signals can synchronize and accelerate the transition dynamics of biopolymers under tension.

PubMed

Kim, Won Kyu; Hyeon, Changbong; Sung, Wokyung

2012-09-04

In addition to thermal noise, which is essential to promote conformational transitions in biopolymers, the cellular environment is replete with a spectrum of athermal fluctuations that are produced from a plethora of active processes. To understand the effect of athermal noise on biological processes, we studied how a small oscillatory force affects the thermally induced folding and unfolding transition of an RNA hairpin, whose response to constant tension had been investigated extensively in both theory and experiments. Strikingly, our molecular simulations performed under overdamped condition show that even at a high (low) tension that renders the hairpin (un)folding improbable, a weak external oscillatory force at a certain frequency can synchronously enhance the transition dynamics of RNA hairpin and increase the mean transition rate. Furthermore, the RNA dynamics can still discriminate a signal with resonance frequency even when the signal is mixed among other signals with nonresonant frequencies. In fact, our computational demonstration of thermally induced resonance in RNA hairpin dynamics is a direct realization of the phenomena called stochastic resonance and resonant activation. Our study, amenable to experimental tests using optical tweezers, is of great significance to the folding of biopolymers in vivo that are subject to the broad spectrum of cellular noises.

Nanofluidics in cellular tubes under oscillatory extension

NASA Astrophysics Data System (ADS)

Nassoy, P.; Cuvelier, D.; Bruinsma, R.; Brochard-Wyart, F.

2008-10-01

Membrane nanotubes or tethers extruded from cells exhibit dynamic features that are believed to exhibit viscoelastic rheological properties. We have performed typical microrheology experiments on tethers pulled from red blood cells by measuring the force response to small oscillatory extensions or compressions. Our data, supported by a simple theoretical model, show that the force response does not reflect any intrinsic viscoelastic properties of the tethers themselves, but instead is dominated by the drainage of the internal cellular fluid into and out of the oscillating nanoconduit over a frequency-dependent penetration depth. The simplicity of tether rheology suggests its usage as a probe for measuring the local viscosity of the cytosol near the plasma membrane.

Infrasonic Monitoring,

DTIC Science & Technology

1995-08-14

seismic network. At large range, infrasound signals are oscillatory acoustic signals detected as small pressure variations about the ambient value... Infrasound Review and Background Infrasound signals are regular acoustic signals in that they are longitudinal pressure waves albeit at rather low frequency...energy is concentrated at higher frequency than that for higher yield sources. Infrasound can be generated by natural and manmade processes; moreover

The Conundrum of Estrogen Receptor Oscillatory Activity in the Search for an Appropriate Hormone Replacement Therapy

PubMed Central

Della Torre, Sara; Biserni, Andrea; Rando, Gianpaolo; Monteleone, Giuseppina; Ciana, Paolo; Komm, Barry

2011-01-01

By the use of in vivo imaging, we investigated the dynamics of estrogen receptor (ER) activity in intact, ovariectomized, and hormone-replaced estrogen response element-luciferase reporter mice. The study revealed the existence of a long-paced, noncircadian oscillation of ER transcriptional activity. Among the ER-expressing organs, this oscillation was asynchronous and its amplitude and period were tissue dependent. Ovariectomy affected the amplitude but did not suppress ER oscillations, suggesting the presence of tissue endogenous oscillators. Long-term administration of raloxifene, bazedoxifene, combined estrogens alone or with basedoxifene to ovariectomized estrogen response element-luciferase mice showed that each treatment induced a distinct spatiotemporal profile of ER activity, demonstrating that the phasing of ER activity among tissues may be regulated by the chemical nature and the concentration of circulating estrogen. This points to the possibility of a hierarchical organization of the tissue-specific pacemakers. Conceivably, the rhythm of ER transcriptional activity translates locally into the activation of specific gene networks enabling ER to significantly change its physiological activity according to circulating estrogens. In reproductive and nonreproductive organs this hierarchical regulation may provide ER with the signaling plasticity necessary to drive the complex metabolic changes occurring at each female reproductive status. We propose that the tissue-specific oscillatory activity here described is an important component of ER signaling necessary for the full hormone action including the beneficial effects reported for nonreproductive organs. Thus, this mechanism needs to be taken in due consideration to develop novel, more efficacious, and safer hormone replacement therapies. PMID:21505049

The Relationship between Membrane Potential and Calcium Dynamics in Glucose-Stimulated Beta Cell Syncytium in Acute Mouse Pancreas Tissue Slices

PubMed Central

Miller, Evan W.; Slak Rupnik, Marjan

2013-01-01

Oscillatory electrical activity is regarded as a hallmark of the pancreatic beta cell glucose-dependent excitability pattern. Electrophysiologically recorded membrane potential oscillations in beta cells are associated with in-phase oscillatory cytosolic calcium activity ([Ca2+]i) measured with fluorescent probes. Recent high spatial and temporal resolution confocal imaging revealed that glucose stimulation of beta cells in intact islets within acute tissue slices produces a [Ca2+]i change with initial transient phase followed by a plateau phase with highly synchronized [Ca2+]i oscillations. Here, we aimed to correlate the plateau [Ca2+]i oscillations with the oscillations of membrane potential using patch-clamp and for the first time high resolution voltage-sensitive dye based confocal imaging. Our results demonstrated that the glucose-evoked membrane potential oscillations spread over the islet in a wave-like manner, their durations and wave velocities being comparable to the ones for [Ca2+]i oscillations and waves. High temporal resolution simultaneous records of membrane potential and [Ca2+]i confirmed tight but nevertheless limited coupling of the two processes, with membrane depolarization preceding the [Ca2+]i increase. The potassium channel blocker tetraethylammonium increased the velocity at which oscillations advanced over the islet by several-fold while, at the same time, emphasized differences in kinetics of the membrane potential and the [Ca2+]i. The combination of both imaging techniques provides a powerful tool that will help us attain deeper knowledge of the beta cell network. PMID:24324777

Periodic protein adsorption at the gold/biotin aqueous solution interface: evidence of kinetics with time delay

NASA Astrophysics Data System (ADS)

Neff, H.; Laborde, H. M.; Lima, A. M. N.

2016-11-01

An oscillatory molecular adsorption pattern of the protein neutravidin from aqueous solution onto gold, in presence of a pre-deposited self assembled mono-molecular biotin film, is reported. Real time surface Plasmon resonance sensing was utilized for evaluation of the adsorption kinetics. Two different fractions were identified: in the initial phase, protein molecules attach irreversibly onto the Biotin ligands beneath towards the jamming limit, forming a neutravidin-biotin fraction. Afterwards, the growth rate exhibits distinct, albeit damped adsorption-desorption oscillations over an extended time span, assigned to a quasi reversibly bound fraction. These findings agree with, and firstly confirm a previously published model, proposing macro-molecular adsorption with time delay. The non-linear dynamic model is applicable to and also resembles non-damped oscillatory binding features of the hetero-catalytic oxidation of carbon monoxide molecules on platinum in the gas phase. An associated surface residence time can be linked to the dynamics and time scale required for self-organization.

Oscillatory brain dynamics associated with the automatic processing of emotion in words.

PubMed

Wang, Lin; Bastiaansen, Marcel

2014-10-01

This study examines the automaticity of processing the emotional aspects of words, and characterizes the oscillatory brain dynamics that accompany this automatic processing. Participants read emotionally negative, neutral and positive nouns while performing a color detection task in which only perceptual-level analysis was required. Event-related potentials and time frequency representations were computed from the concurrently measured EEG. Negative words elicited a larger P2 and a larger late positivity than positive and neutral words, indicating deeper semantic/evaluative processing of negative words. In addition, sustained alpha power suppressions were found for the emotional compared to neutral words, in the time range from 500 to 1000ms post-stimulus. These results suggest that sustained attention was allocated to the emotional words, whereas the attention allocated to the neutral words was released after an initial analysis. This seems to hold even when the emotional content of the words is task-irrelevant. Copyright © 2014 Elsevier Inc. All rights reserved.

Analysis of Oscillatory Neural Activity in Series Network Models of Parkinson's Disease During Deep Brain Stimulation.

PubMed

Davidson, Clare M; de Paor, Annraoi M; Cagnan, Hayriye; Lowery, Madeleine M

2016-01-01

Parkinson's disease is a progressive, neurodegenerative disorder, characterized by hallmark motor symptoms. It is associated with pathological, oscillatory neural activity in the basal ganglia. Deep brain stimulation (DBS) is often successfully used to treat medically refractive Parkinson's disease. However, the selection of stimulation parameters is based on qualitative assessment of the patient, which can result in a lengthy tuning period and a suboptimal choice of parameters. This study explores fourth-order, control theory-based models of oscillatory activity in the basal ganglia. Describing function analysis is applied to examine possible mechanisms for the generation of oscillations in interacting nuclei and to investigate the suppression of oscillations with high-frequency stimulation. The theoretical results for the suppression of the oscillatory activity obtained using both the fourth-order model, and a previously described second-order model, are optimized to fit clinically recorded local field potential data obtained from Parkinsonian patients with implanted DBS. Close agreement between the power of oscillations recorded for a range of stimulation amplitudes is observed ( R(2)=0.69-0.99 ). The results suggest that the behavior of the system and the suppression of pathological neural oscillations with DBS is well described by the macroscopic models presented. The results also demonstrate that in this instance, a second-order model is sufficient to model the clinical data, without the need for added complexity. Describing the system behavior with computationally efficient models could aid in the identification of optimal stimulation parameters for patients in a clinical environment.

Structural state diagram of concentrated suspensions of jammed soft particles in oscillatory shear flow

NASA Astrophysics Data System (ADS)

Khabaz, Fardin; Cloitre, Michel; Bonnecaze, Roger T.

2018-03-01

In a recent study [Khabaz et al., Phys. Rev. Fluids 2, 093301 (2017), 10.1103/PhysRevFluids.2.093301], we showed that jammed soft particle glasses (SPGs) crystallize and order in steady shear flow. Here we investigate the rheology and microstructures of these suspensions in oscillatory shear flow using particle-dynamics simulations. The microstructures in both types of flows are similar, but their evolutions are very different. In both cases the monodisperse and polydisperse suspensions form crystalline and layered structures, respectively, at high shear rates. The crystals obtained in the oscillatory shear flow show fewer defects compared to those in the steady shear. SPGs remain glassy for maximum oscillatory strains less than about the yield strain of the material. For maximum strains greater than the yield strain, microstructural and rheological transitions occur for SPGs. Polydisperse SPGs rearrange into a layered structure parallel to the flow-vorticity plane for sufficiently high maximum shear rates and maximum strains about 10 times greater than the yield strain. Monodisperse suspensions form a face-centered cubic (FCC) structure when the maximum shear rate is low and hexagonal close-packed (HCP) structure when the maximum shear rate is high. In steady shear, the transition from a glassy state to a layered one for polydisperse suspensions included a significant induction strain before the transformation. In oscillatory shear, the transformation begins to occur immediately and with different microstructural changes. A state diagram for suspensions in large amplitude oscillatory shear flow is found to be in close but not exact agreement with the state diagram for steady shear flow. For more modest amplitudes of around one to five times the yield strain, there is a transition from a glassy structure to FCC and HCP crystals, at low and high frequencies, respectively, for monodisperse suspensions. At moderate frequencies, the transition is from glassy to HCP via an intermediate FCC phase.

Nonlinear oscillatory rheology and structure of wormlike micellar solutions and colloidal suspensions

NASA Astrophysics Data System (ADS)

Gurnon, Amanda Kate

The complex, nonlinear flow behavior of soft materials transcends industrial applications, smart material design and non-equilibrium thermodynamics. A long-standing, fundamental challenge in soft-matter science is establishing a quantitative connection between the deformation field, local microstructure and macroscopic dynamic flow properties i.e., the rheology. Soft materials are widely used in consumer products and industrial processes including energy recovery, surfactants for personal healthcare (e.g. soap and shampoo), coatings, plastics, drug delivery, medical devices and therapeutics. Oftentimes, these materials are processed by, used during, or exposed to non-equilibrium conditions for which the transient response of the complex fluid is critical. As such, designing new dynamic experiments is imperative to testing these materials and further developing micromechanical models to predict their transient response. Two of the most common classes of these soft materials stand as the focus of the present research; they are: solutions of polymer-like micelles (PLM or also known as wormlike micelles, WLM) and concentrated colloidal suspensions. In addition to their varied applications these two different classes of soft materials are also governed by different physics. In contrast, to the shear thinning behavior of the WLMs at high shear rates, the near hard-sphere colloidal suspensions are known to display increases, sometimes quite substantial, in viscosity (known as shear thickening). The stress response of these complex fluids derive from the shear-induced microstructure, thus measurements of the microstructure under flow are critical for understanding the mechanisms underlying the complex, nonlinear rheology of these complex fluids. A popular micromechanical model is reframed from its original derivation for predicting steady shear rheology of polymers and WLMs to be applicable to weakly nonlinear oscillatory shear flow. The validity, utility and limits of this constitutive model are tested by comparison with experiments on model WLM solutions. Further comparisons to the nonlinear oscillatory shear responses measured from colloidal suspensions establishes this analysis as a promising, quantitative method for understanding the underlying mechanisms responsible for the nonlinear dynamic response of complex fluids. A new experimental technique is developed to measure the microstructure of complex fluids during steady and transient shear flow using small-angle neutron scattering (SANS). The Flow-SANS experimental method is now available to the broader user communities at the NIST Center for Neutron Research, Gaithersburg, MD and the Institut Laue-Langevin, Grenoble, France. Using this new method, a model shear banding WLM solution is interrogated under steady and oscillatory shear. For the first time, the flow-SANS methods identify new metastable states for shear banding WLM solutions, thus establishing the method as capable of probing new states not accessible using traditional steady or linear oscillatory shear methods. The flow-induced three-dimensional microstructure of a colloidal suspension under steady and dynamic oscillatory shear is also measured using these rheo- and flow-SANS methods. A new structure state is identified in the shear thickening regime that proves critical for defining the "hydrocluster" microstructure state of the suspension that is responsible for shear thickening. For both the suspensions and the WLM solutions, stress-SANS rules with the measured microstructures define the individual stress components arising separately from conservative and hydrodynamic forces and these are compared with the macroscopic rheology. Analysis of these results defines the crucial length- and time-scales of the transient microstructure response. The novel dynamic microstructural measurements presented in this dissertation provide new insights into the complexities of shear thickening and shear banding flow phenomena, which are effects observed more broadly across many different types of soft materials. Consequently, the microstructure-rheology property relationships developed for these two classes of complex fluids will aid in the testing and advancement of micromechanical constitutive model development, smart material design, industrial processing and fundamental non-equilibrium thermodynamic research of a broad range of soft materials.

Dynamic adjustments of cognitive control: oscillatory correlates of the conflict adaptation effect.

PubMed

Pastötter, Bernhard; Dreisbach, Gesine; Bäuml, Karl-Heinz T

2013-12-01

It is a prominent idea that cognitive control mediates conflict adaptation, in that response conflict in a previous trial triggers control adjustments that reduce conflict in a current trial. In the present EEG study, we investigated the dynamics of cognitive control in a response-priming task by examining the effects of previous trial conflict on intertrial and current trial oscillatory brain activities, both on the electrode and the source level. Behavioral results showed conflict adaptation effects for RTs and response accuracy. Physiological results showed sustained intertrial effects in left parietal theta power, originating in the left inferior parietal cortex, and midcentral beta power, originating in the left and right (pre)motor cortex. Moreover, physiological analysis revealed a current trial conflict adaptation effect in midfrontal theta power, originating in the ACC. Correlational analyses showed that intertrial effects predicted conflict-induced midfrontal theta power in currently incongruent trials. In addition, conflict adaptation effects in midfrontal theta power and RTs were positively related. Together, these findings point to a dynamic cognitive control system that, as a function of previous trial type, up- and down-regulates attention and preparatory motor activities in anticipation of the next trial.

Steady dynein forces induce flutter instability and propagating waves in mathematical models of flagella

PubMed Central

Dutcher, S. K.

2016-01-01

Cilia and flagella are highly conserved organelles that beat rhythmically with propulsive, oscillatory waveforms. The mechanism that produces these autonomous oscillations remains a mystery. It is widely believed that dynein activity must be dynamically regulated (switched on and off, or modulated) on opposite sides of the axoneme to produce oscillations. A variety of regulation mechanisms have been proposed based on feedback from mechanical deformation to dynein force. In this paper, we show that a much simpler interaction between dynein and the passive components of the axoneme can produce coordinated, propulsive oscillations. Steady, distributed axial forces, acting in opposite directions on coupled beams in viscous fluid, lead to dynamic structural instability and oscillatory, wave-like motion. This ‘flutter’ instability is a dynamic analogue to the well-known static instability, buckling. Flutter also occurs in slender beams subjected to tangential axial loads, in aircraft wings exposed to steady air flow and in flexible pipes conveying fluid. By analysis of the flagellar equations of motion and simulation of structural models of flagella, we demonstrate that dynein does not need to switch direction or inactivate to produce autonomous, propulsive oscillations, but must simply pull steadily above a critical threshold force. PMID:27798276

Oscillatory vapour shielding of liquid metal walls in nuclear fusion devices.

PubMed

van Eden, G G; Kvon, V; van de Sanden, M C M; Morgan, T W

2017-08-04

Providing an efficacious plasma facing surface between the extreme plasma heat exhaust and the structural materials of nuclear fusion devices is a major challenge on the road to electricity production by fusion power plants. The performance of solid plasma facing surfaces may become critically reduced over time due to progressing damage accumulation. Liquid metals, however, are now gaining interest in solving the challenge of extreme heat flux hitting the reactor walls. A key advantage of liquid metals is the use of vapour shielding to reduce the plasma exhaust. Here we demonstrate that this phenomenon is oscillatory by nature. The dynamics of a Sn vapour cloud are investigated by exposing liquid Sn targets to H and He plasmas at heat fluxes greater than 5 MW m -2 . The observations indicate the presence of a dynamic equilibrium between the plasma and liquid target ruled by recombinatory processes in the plasma, leading to an approximately stable surface temperature.Vapour shielding is one of the interesting mechanisms for reducing the heat load to plasma facing components in fusion reactors. Here the authors report on the observation of a dynamic equilibrium between the plasma and the divertor liquid Sn surface leading to an overall stable surface temperature.

Synchronous Motions Across the Instrumental Climate Record

NASA Astrophysics Data System (ADS)

Carl, Peter

The Earth's climate system bears a rich variety of feedback mechanisms that may give rise to complex, evolving modal structures under internal and external control. Various types of synchronization may be identified in the system's motion when looking at representative time series of the instrumental period through the glasses of an advanced technique of sparse data approximation, the Matching Pursuit (MP) approach. To disentangle the emerging network of oscillatory modes to the degree that climate dynamics turns out to be separable, a large dictionary of "Gaussian logons," i.e. frequency modulated (FM) Gabor atoms, is applied. Though the extracted modes make up linear decompositions, this flexible analyzing signal matches highly nonlinear waveforms. Univariate analyses over the period 1870-1997 are presented of a set of customary time series in annual resolution, comprising global and regional climate, central European synoptic systems, German precipitation, and runoff of the Elbe river near Dresden. All the evidence from this first-generation MP-FM study, obtained in subsequent multivariate syntheses, points to dynamically excited regimes of an organized yet complex climate system under permanent change—perhaps a (pre)chaotic one at centennial timescales, suggesting a "chaos control" perspective on global climate dynamics and change. Findings and conclusions include, among others, internal structure of reconstructed insolation, the episodic nature of global warming as reflected in multidecadal temperature modes, their swarm of "interdomain" companions across the whole system that unveils an unknown regime character of interannual climate dynamics, and the apparent onset early in the 1990s of the present thermal stagnation.

Reorganization of the human central nervous system.

PubMed

Schalow, G; Zäch, G A

2000-10-01

The key strategies on which the discovery of the functional organization of the central nervous system (CNS) under physiologic and pathophysiologic conditions have been based included (1) our measurements of phase and frequency coordination between the firings of alpha- and gamma-motoneurons and secondary muscle spindle afferents in the human spinal cord, (2) knowledge on CNS reorganization derived upon the improvement of the functions of the lesioned CNS in our patients in the short-term memory and the long-term memory (reorganization), and (3) the dynamic pattern approach for re-learning rhythmic coordinated behavior. The theory of self-organization and pattern formation in nonequilibrium systems is explicitly related to our measurements of the natural firing patterns of sets of identified single neurons in the human spinal premotor network and re-learned coordinated movements following spinal cord and brain lesions. Therapy induced cell proliferation, and maybe, neurogenesis seem to contribute to the host of structural changes during the process of re-learning of the lesioned CNS. So far, coordinated functions like movements could substantially be improved in every of the more than 100 patients with a CNS lesion by applying coordination dynamic therapy. As suggested by the data of our patients on re-learning, the human CNS seems to have a second integrative strategy for learning, re-learning, storing and recalling, which makes an essential contribution of the functional plasticity following a CNS lesion. A method has been developed by us for the simultaneous recording with wire electrodes of extracellular action potentials from single human afferent and efferent nerve fibres of undamaged sacral nerve roots. A classification scheme of the nerve fibres in the human peripheral nervous system (PNS) could be set up in which the individual classes of nerve fibres are characterized by group conduction velocities and group nerve fibre diameters. Natural impulse patterns of several identified single afferent and efferent nerve fibres (motoneuron axons) were extracted from multi-unit impulse patterns, and human CNS functions could be analyzed under physiologic and pathophysiologic conditions. With our discovery of premotor spinal oscillators it became possible to judge upon CNS neuronal network organization based on the firing patterns of these spinal oscillators and their driving afferents. Since motoneurons fire occasionally for low activation and oscillatory for high activation, the coherent organization of subnetworks to generate macroscopic function is very complex and for the time being, may be best described by the theory of coordination dynamics. Since oscillatory firing has also been observed by us in single motor unit firing patterns measured electromyographically, it seems possible to follow up therapeutic intervention in patients with spinal cord and brain lesions not only based on the activity levels and phases of motor programs during locomotion but also based on the physiologic and pathophysiologic firing patterns and recruitment of spinal oscillators. The improvement of the coordination dynamics of the CNS can be partly measured directly by rhythmicity upon the patient performing rhythmic movements coordinated up to milliseconds. Since rhythmic dynamic, coordinated, stereotyped movements are mainly located in the spinal cord and only little supraspinal drive is necessary to initiate, maintain, and terminate them, rhythmic, dynamic, coordinated movements were used in therapy to enforce reorganization of the lesioned CNS by improving the self-organization and relative coordination of spinal oscillators (and their interactions with occasionally firing motoneurons) which became pathologic in their firing following CNS lesion. Paraparetic, tetraparetic spinal cord and brain-lesioned patients re-learned running and other movements by an oscillator formation and coordination dynamic therapy. Our development in neurorehabilitation is in accordance with those of theoretical and computational neurosciences which deal with the self-organization of neuronal networks. In particular, jumping on a springboard 'in-phase' and in 'anti-phase' to re-learn phase relations of oscillator coupling can be understood in the framework of the Haken-Kelso-Bunz coordination dynamic model. By introducing broken symmetry, intention, learning and spasticity in the landscape of the potential function of the integrated CNS activity, the change in self-organization becomes understandable. Movement patterns re-learned by oscillator formation and coordination dynamic therapy evolve from reorganization and regeneration of the lesioned CNS by cooperative and competitive interplay between intrinsic coordination dynamics, extrinsic therapy related inputs with physiologic re-afferent input, including intention, motivation, supervised learning, interpersonal coordination, and genetic constraints including neurogenesis. (ABSTRACT TRUNCATED)

Resource Paper: Molecular Excited State Relaxation Processes.

ERIC Educational Resources Information Center

Rhodes, William

1979-01-01

Develops the concept of oscillatory v dissipative limits as it applies to electronic excited state processes in molecular systems. Main emphasis is placed on the radiative and nonradiative dynamics of the excited state of a molecule prepared by interaction with light or some other excitation source. (BT)

Lifespan Differences in Cortical Dynamics of Auditory Perception

ERIC Educational Resources Information Center

Muller, Viktor; Gruber, Walter; Klimesch, Wolfgang; Lindenberger, Ulman

2009-01-01

Using electroencephalographic recordings (EEG), we assessed differences in oscillatory cortical activity during auditory-oddball performance between children aged 9-13 years, younger adults, and older adults. From childhood to old age, phase synchronization increased within and between electrodes, whereas whole power and evoked power decreased. We…

Oscillatory/Chaotic Thermocapillary Flow Induced by Radiant Heating

NASA Technical Reports Server (NTRS)

DeWitt, Kenneth J.

1998-01-01

There is a continuing need to understand the fluid physics occurring under low gravity conditions in processes such as crystal growth, materials processing, and the movement of bubbles or droplets. The fluid flow in such situations is often caused by a gradient in interfacial tension. If a temperature gradient is created due to a heat source, the resulting flow is called thermocapillary flow, a special case of Marangoni Convection. In this study, an experimental investigation was conducted using silicone oil in cylindrical containers with a laser heat source at the free surface. It was desired to determine the conditions under which steady, axisymmetrical thermocapillary flow becomes unstable and oscillatory three-dimensional flow states develop. The critical Marangoni number for each observed oscillatory state was measured as a function of the container aspect ratio and the dynamic Bond number, a measure of buoyant force versus ii thermocapillary force. Various oscillatory modes were observed during three- dimensional convection, and chaotic flow was reached in one test condition. The critical Marangoni numbers are compared with those measured in previous studies, and the power spectra and phase trajectories of the instantaneous surface temperature distributions are used to characterize the routes of transitions to the chaotic flow state. Results show that only superharmonic modes appear in the routes to chaos while infinite number of subharmonic modes occur in flow transitions for pure Rayleigh convection.

Designing attractive models via automated identification of chaotic and oscillatory dynamical regimes.

PubMed

Silk, Daniel; Kirk, Paul D W; Barnes, Chris P; Toni, Tina; Rose, Anna; Moon, Simon; Dallman, Margaret J; Stumpf, Michael P H

2011-10-04

Chaos and oscillations continue to capture the interest of both the scientific and public domains. Yet despite the importance of these qualitative features, most attempts at constructing mathematical models of such phenomena have taken an indirect, quantitative approach, for example, by fitting models to a finite number of data points. Here we develop a qualitative inference framework that allows us to both reverse-engineer and design systems exhibiting these and other dynamical behaviours by directly specifying the desired characteristics of the underlying dynamical attractor. This change in perspective from quantitative to qualitative dynamics, provides fundamental and new insights into the properties of dynamical systems.

Oscillatory motor network activity during rest and movement: an fNIRS study

PubMed Central

Bajaj, Sahil; Drake, Daniel; Butler, Andrew J.; Dhamala, Mukesh

2014-01-01

Coherent network oscillations (<0.1 Hz) linking distributed brain regions are commonly observed in the brain during both rest and task conditions. What oscillatory network exists and how network oscillations change in connectivity strength, frequency and direction when going from rest to explicit task are topics of recent inquiry. Here, we study network oscillations within the sensorimotor regions of able-bodied individuals using hemodynamic activity as measured by functional near-infrared spectroscopy (fNIRS). Using spectral interdependency methods, we examined how the supplementary motor area (SMA), the left premotor cortex (LPMC) and the left primary motor cortex (LM1) are bound as a network during extended resting state (RS) and between-tasks resting state (btRS), and how the activity of the network changes as participants execute left, right, and bilateral hand (LH, RH, and BH) finger movements. We found: (i) power, coherence and Granger causality (GC) spectra had significant peaks within the frequency band (0.01–0.04 Hz) during RS whereas the peaks shifted to a bit higher frequency range (0.04–0.08 Hz) during btRS and finger movement tasks, (ii) there was significant bidirectional connectivity between all the nodes during RS and unidirectional connectivity from the LM1 to SMA and LM1 to LPMC during btRS, and (iii) the connections from SMA to LM1 and from LPMC to LM1 were significantly modulated in LH, RH, and BH finger movements relative to btRS. The unidirectional connectivity from SMA to LM1 just before the actual task changed to the bidirectional connectivity during LH and BH finger movement. The uni-directionality could be associated with movement suppression and the bi-directionality with preparation, sensorimotor update and controlled execution. These results underscore that fNIRS is an effective tool for monitoring spectral signatures of brain activity, which may serve as an important precursor before monitoring the recovery progress following brain injury. PMID:24550793

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

PubMed

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

2017-02-01

Oscillatory activity occurs in cortical and hippocampal networks with specific frequency ranges thought to be critical to working memory, attention, differentiation of neuronal precursors, and memory trace replay. Synchronized activity within relatively large neuronal populations is influenced by firing and bursting frequency within individual cells, and the latter is modulated by changes in intrinsic membrane excitability and synaptic transmission. Published work suggests that dopamine, a potent modulator of learning and memory, acts on dopamine receptor 1-like dopamine receptors to influence the phosphorylation and trafficking of glutamate receptor subunits, along with long-term potentiation of excitatory synaptic transmission in striatum and prefrontal cortex. Prior studies also suggest that dopamine can influence voltage gated ion channel function and membrane excitability in these regions. Fewer studies have examined dopamine's effect on related endpoints in hippocampus, or potential consequences in terms of network burst dynamics. In this study, we record action potential activity using a microelectrode array system to examine the ability of dopamine to modulate baseline and glutamate-stimulated bursting activity in an in vitro network of cultured murine hippocampal neurons. We show that dopamine stimulates a dopamine type-1 receptor-dependent increase in number of overall bursts within minutes of its application. Notably, however, at the concentration used herein, dopamine did not increase the overall synchrony of bursts between electrodes. Although the number of bursts normalizes by 40 min, bursting in response to a subsequent glutamate challenge is enhanced by dopamine pretreatment. Dopamine-dependent potentiation of glutamate-stimulated bursting was not observed when the two modulators were administered concurrently. In parallel, pretreatment of murine hippocampal cultures with dopamine stimulated lasting increases in the phosphorylation of the glutamate receptor subunit GluA1 at serine 845. This effect is consistent with the possibility that enhanced membrane insertion of GluAs may contribute to a more slowly evolving dopamine-dependent potentiation of glutamate-stimulated bursting. Together, these results are consistent with the possibility that dopamine can influence hippocampal bursting by at least two temporally distinct mechanisms, contributing to an emerging appreciation of dopamine-dependent effects on network activity in the hippocampus. © 2016 International Society for Neurochemistry.

Fast entrainment of human electroencephalogram to a theta-band photic flicker during successful memory encoding.

PubMed

Sato, Naoyuki

2013-01-01

Theta band power (4-8 Hz) in the scalp electroencephalogram (EEG) is thought to be stronger during memory encoding for subsequently remembered items than for forgotten items. According to simultaneous EEG-functional magnetic resonance imaging (fMRI) measurements, the memory-dependent EEG theta is associated with multiple regions of the brain. This suggests that the multiple regions cooperate with EEG theta synchronization during successful memory encoding. However, a question still remains: What kind of neural dynamic organizes such a memory-dependent global network? In this study, the modulation of the EEG theta entrainment property during successful encoding was hypothesized to lead to EEG theta synchronization among a distributed network. Then, a transient response of EEG theta to a theta-band photic flicker with a short duration was evaluated during memory encoding. In the results, flicker-induced EEG power increased and decreased with a time constant of several hundred milliseconds following the onset and the offset of the flicker, respectively. Importantly, the offset response of EEG power was found to be significantly decreased during successful encoding. Moreover, the offset response of the phase locking index was also found to associate with memory performance. According to computational simulations, the results are interpreted as a smaller time constant (i.e., faster response) of a driven harmonic oscillator rather than a change in the spontaneous oscillatory input. This suggests that the fast response of EEG theta forms a global EEG theta network among memory-related regions during successful encoding, and it contributes to a flexible formation of the network along the time course.

Self-Organisation and Intermittent Coherent Oscillations in the EXTRAP T2 Reversed Field Pinch

NASA Astrophysics Data System (ADS)

Cecconello, M.; Malmberg, J.-A.; Sallander, E.; Drake, J. R.

Many reversed-field pinch (RFP) experiments exhibit a coherent oscillatory behaviour that is characteristic of discrete dynamo events and is associated with intermittent current profile self-organisation phenomena. However, in the vast majority of the discharges in the resistive shell RFP experiment EXTRAP T2, the dynamo activity does not show global, coherent oscillatory behaviour. The internally resonant tearing modes are phase-aligned and wall-locked resulting in a large localised magnetic perturbation. Equilibrium and plasma parameters have a level of high frequency fluctuations but the average values are quasi-steady. For some discharges, however, the equilibrium parameters exhibit the oscillatory behaviour characteristic of the discrete dynamo events. For these discharges, the trend observed in the tearing mode spectra, associated with the onset of the discrete relaxation event behaviour, is a relative higher amplitude of m = 0 mode activity and relative lower amplitude of the m = 1 mode activity compared with their average values. Global plasma parameters and model profile calculations for sample discharges representing the two types of relaxation dynamics are presented.

Analytical study of the critical behavior of the nonlinear pendulum

NASA Astrophysics Data System (ADS)

Lima, F. M. S.

2010-11-01

The dynamics of a simple pendulum consisting of a small bob and a massless rigid rod has three possible regimes depending on its total energy E: Oscillatory (when E is not enough for the pendulum to reach the top position), "perpetual ascent" when E is exactly the energy needed to reach the top, and nonoscillatory for greater energies. In the latter regime, the pendulum rotates periodically without velocity inversions. In contrast to the oscillatory regime, for which an exact analytic solution is known, the other two regimes are usually studied by solving the equation of motion numerically. By applying conservation of energy, I derive exact analytical solutions to both the perpetual ascent and nonoscillatory regimes and an exact expression for the pendulum period in the nonoscillatory regime. Based on Cromer's approximation for the large-angle pendulum period, I find a simple approximate expression for the decrease of the period with the initial velocity in the nonoscillatory regime, valid near the critical velocity. This expression is used to study the critical slowing down, which is observed near the transition between the oscillatory and nonoscillatory regimes.

Design of Tunable Oscillatory Dynamics in a Synthetic NF-κB Signaling Circuit.

PubMed

Zhang, Zhi-Bo; Wang, Qiu-Yue; Ke, Yu-Xi; Liu, Shi-Yu; Ju, Jian-Qi; Lim, Wendell A; Tang, Chao; Wei, Ping

2017-11-22

Although oscillatory circuits are prevalent in transcriptional regulation, it is unclear how a circuit's structure and the specific parameters that describe its components determine the shape of its oscillations. Here, we engineer a minimal, inducible human nuclear factor κB (NF-κB)-based system that is composed of NF-κB (RelA) and degradable inhibitor of NF-κB (IκBα), into the yeast, Saccharomyces cerevisiae. We define an oscillation's waveform quantitatively as a function of signal amplitude, rest time, rise time, and decay time; by systematically tuning RelA concentration, the strength of negative feedback, and the degradation rate of IκBα, we demonstrate that peak shape and frequency of oscillations can be controlled in vivo and predicted mathematically. In addition, we show that nested negative feedback loops can be employed to specifically tune the frequency of oscillations while leaving their peak shape unchanged. In total, this work establishes design principles that enable function-guided design of oscillatory signaling controllers in diverse synthetic biology applications. Copyright © 2017 Elsevier Inc. All rights reserved.

Dynamics of Oscillating and Rotating Liquid Drop using Electrostatic Levitator

NASA Astrophysics Data System (ADS)

Matsumoto, Satoshi; Awazu, Shigeru; Abe, Yutaka; Watanabe, Tadashi; Nishinari, Katsuhiro; Yoda, Shinichi

2006-11-01

In order to understand the nonlinear behavior of liquid drop with oscillatory and/or rotational motions, an experimental study was performed. The electrostatic levitator was employed to achieve liquid drop formation on ground. A liquid drop with about 3 mm in diameter was levitated. The oscillation of mode n=2 along the vertical axis was induced by an external electrostatic force. The oscillatory motions were observed to clarify the nonlinearities of oscillatory behavior. A relationship between amplitude and frequency shift was made clear and the effect of frequency shift on amplitude agreed well with the theory. The frequency shift became larger with increasing the amplitude of oscillation. To confirm the nonlinear effects, we modeled the oscillation by employing the mass-spring-damper system included the nonlinear term. The result indicates that the large-amplitude oscillation includes the effect of nonlinear oscillation. The sound pressure was imposed to rotate the liquid drop along a vertical axis by using a pair of acoustic transducers. The drop transited to the two lobed shape due to centrifugal force when nondimensional angular velocity exceeded to 0.58.

Simulation study of 2D spectrum of molecular aggregates coupled to correlated vibrations

NASA Astrophysics Data System (ADS)

Abramavicius, Darius; Butkus, Vytautas; Valkunas, Leonas; Mukamel, Shaul

2011-03-01

Oscillatory dynamics of two-dimensional (2D) spectra of photosynthetic pigment-protein complexes raise the questions of how to disentangle various origins of these oscillations, which may include quantum beats, quantum transport, or molecular vibrations. We study the effects of correlated overdamped fluctuations and under-damped vibrations on the 2D spectra of Fenna-Matthews-Olson (FMO) aggregate, which has well-resolved exciton resonances, and a circular porphyrin aggregate (P6), whose absorption shows vibrational progression. We use a generic exciton Hamiltonian coupled to a bath, characterized by a spectral density. Fluctuations have smooth, while vibtations have δ -type spectral densities. We show how various scenarios of correlated molecular fluctuations lead to some highly oscillatory crosspeaks. Molecular vibrations cause progression of diagonal peaks in the 2D spectrum and make their corresponding cross-peaks highly oscillatory. We, thus, demonstrate that bath fluctuations and molecular vibrations of realistic molecular aggregates are highly entangled in 2D spectroscopy. DA acknowledges grant VP1-3.1-SMM-07-V, SM - the grants CHE0745892 (NSF), DRPA BAA-10-40 QUBE.

Molecular Dynamics Simulations of Laser Powered Carbon Nanotube Gears

NASA Technical Reports Server (NTRS)

Srivastava, Deepak; Globus, Al; Han, Jie; Chancellor, Marisa K. (Technical Monitor)

1997-01-01

Dynamics of laser powered carbon nanotube gears is investigated by molecular dynamics simulations with Brenner's hydrocarbon potential. We find that when the frequency of the laser electric field is much less than the intrinsic frequency of the carbon nanotube, the tube exhibits an oscillatory pendulam behavior. However, a unidirectional rotation of the gear with oscillating frequency is observed under conditions of resonance between the laser field and intrinsic gear frequencies. The operating conditions for stable rotations of the nanotube gears, powered by laser electric fields are explored, in these simulations.

The network of causal interactions for beta oscillations in the pedunculopontine nucleus, primary motor cortex, and subthalamic nucleus of walking parkinsonian rats.

PubMed

Li, Min; Zhou, Ming; Wen, Peng; Wang, Qiang; Yang, Yong; Xiao, Hu; Xie, Zhengyuan; Li, Xing; Wang, Ning; Wang, Jinyan; Luo, Fei; Chang, Jingyu; Zhang, Wangming

2016-08-01

Oscillatory activity has been well-studied in many structures within cortico-basal ganglia circuits, but it is not well understood within the pedunculopontine nucleus (PPN), which was recently introduced as a potential target for the treatment of gait and postural impairments in advanced stages of Parkinson's disease (PD). To investigate oscillatory activity in the PPN and its relationship with oscillatory activity in cortico-basal ganglia circuits, we simultaneously recorded local field potentials in the PPN, primary motor cortex (M1), and subthalamic nucleus (STN) of 6-hydroxydopamine (6-OHDA)-induced hemiparkinsonian rats during resting and walking. After analysis of power spectral density, coherence, and partial Granger causality, three major findings emerged: 1) after 6-OHDA lesions, beta band oscillations were enhanced in all three regions during walking; 2) the direction of information flow for beta oscillations among the three structures was STN→M1, STN→PPN, and PPN→M1; 3) after the treatment of levodopa, beta activity in the three regions was reduced significantly and the flow of beta band was also abrogated. Our results suggest that beta activity in the PPN is transmitted from the basal ganglia and probably comes from the STN, and the STN plays a dominant role in the network of causal interactions for beta activity. Thus, the STN may be a potential source of aberrant beta band oscillations in PD. Levodopa can inhibit beta activity in the PPN of parkinsonian rats but cannot relieve parkinsonian patients' axial symptoms clinically. Therefore, beta oscillations may not be the major cause of axial symptoms. Copyright © 2016 Elsevier Inc. All rights reserved.

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

PubMed

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

2012-12-01

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

Cortico-cortical evoked potentials for sites of early versus late seizure spread in stereoelectroencephalography.

PubMed

Lega, Bradley; Dionisio, Sasha; Flanigan, Patrick; Bingaman, William; Najm, Imad; Nair, Dileep; Gonzalez-Martinez, Jorge

2015-09-01

Cortico-cortical evoked potentials offer the possibility of understanding connectivity within seizure networks to improve diagnosis and more accurately identify candidates for seizure surgery. We sought to determine if cortico-cortical evoked potentials and post-stimulation oscillatory changes differ for sites of EARLY versus LATE ictal spread. 37 patients undergoing stereoelectroencephalography were tested using a cortico-cortical evoked potential paradigm. All electrodes were classified according to the speed of ictal spread. EARLY spread sites were matched to a LATE spread site equidistant from the onset zone. Root-mean-square was used to quantify evoked responses and post-stimulation gamma band power and coherence were extracted and compared. Sites of EARLY spread exhibited significantly greater evoked responses after stimulation across all patients (t(36)=2.973, p=0.004). Stimulation elicited enhanced gamma band activity at EARLY spread sites (t(36)=2.61, p=0.03, FDR corrected); this gamma band oscillation was highly coherent with the onset zone. Cortico-cortical evoked potentials and post-stimulation changes in gamma band activity differ between sites of EARLY versus LATE ictal spread. The oscillatory changes can help visualize connectivity within the seizure network. Copyright © 2015 Elsevier B.V. All rights reserved.

Embedding memories in colloidal gels though oscillatory shear

NASA Astrophysics Data System (ADS)

Schwen, Eric; Ramaswamay, Meera; Jan, Linda; Cheng, Chieh-Min; Cohen, Itai

While gels are ubiquitous in applications from food products to filtration, their mechanical properties are usually determined by self-assembly. We use oscillatory shear to train colloidal gels, embedding memories of the training protocol in rheological responses such as the yield strain and the gel network structures. When our gels undergo shear, the particles are forced to rearrange until they organize into structures that can locally undergo reversible shear cycles. We utilize a high-speed confocal microscope and a shear cell to image a colloidal gel while simultaneously straining the gel and measuring its shear stresses. By comparing stroboscopic images of the gel, we quantify the decrease in particle rearrangement as the gel develops reversible structures. We analyze and construct a model for the rates at which different regions in the gel approach reversible configurations. Through characterizing the gel network, we determine the structural origins of these shear training memories in gels. These results may allow us to use shear training protocols to produce gels with controllable yield strains and to better understand changes in the microstructure and rheology of gels that undergo repeated shear through mixing or flowing. This research was supported in part by NSF CBET 1509308 and Xerox Corporation.

Parametric Sensitivity Analysis of Oscillatory Delay Systems with an Application to Gene Regulation.

PubMed

Ingalls, Brian; Mincheva, Maya; Roussel, Marc R

2017-07-01

A parametric sensitivity analysis for periodic solutions of delay-differential equations is developed. Because phase shifts cause the sensitivity coefficients of a periodic orbit to diverge, we focus on sensitivities of the extrema, from which amplitude sensitivities are computed, and of the period. Delay-differential equations are often used to model gene expression networks. In these models, the parametric sensitivities of a particular genotype define the local geometry of the evolutionary landscape. Thus, sensitivities can be used to investigate directions of gradual evolutionary change. An oscillatory protein synthesis model whose properties are modulated by RNA interference is used as an example. This model consists of a set of coupled delay-differential equations involving three delays. Sensitivity analyses are carried out at several operating points. Comments on the evolutionary implications of the results are offered.

The role of flow in the morphodynamics of embryonic heart

NASA Astrophysics Data System (ADS)

Gharib, Morteza

2017-11-01

Nature has shown us that some hearts do not require valves to achieve unidirectional flow. In its earliest stages, the vertebrate heart consists of a primitive tube that drives blood through a simple vascular network nourishing tissues and other developing organ systems. We have shown that in the case of the embryonic zebrafish heart, an elastic wave resonance mechanism based on impedance mismatches at the boundaries of the heart tube is the likely mechanism responsible for the valveless pumping behavior. When functioning normally, mature heart valves prevent intracardiac retrograde blood flow; before valves develop there is considerable regurgitation, resulting in oscillatory flow between the atrium and ventricle. We show that reversing flows are particularly strong stimuli to endothelial cells and that heart valves form as a developmental response to oscillatory blood flow through the maturing heart.

Missile Motion Sensitivity to Dynamic Stability Derivatives

DTIC Science & Technology

1980-09-01

to Lifting-Surface/Body Interference." AFFDL- TR-71-5, April 1972. 5. Williams, John E. and Vukelich, Steven R. "The USAF Stability and Control...and Laberge , J. G. "Direct and Cross-Coupling Subsonic Moment Derivatives Due to Oscillatory Pitching and Yawing of an Aircraft- Like Model of

Fizz-Ball Fizzics

ERIC Educational Resources Information Center

Moinester, Murray; Gerland, Lars; Liger-Belair, Gerard; Ocherashvili, Aharon

2012-01-01

We describe the fluid dynamics principles governing the up-down oscillatory cycling of a bubble-covered, low-density, low-mass ball of material (referred to henceforth as a "fizz-ball") immersed inside a glass of bubbling (super-saturated) carbonated liquid. The bubbles serve to desaturate the liquid of excess CO[subscript 2]. The fizz-ball acts…

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

Lee, Jonghun; Jiang, Zhang; Wang, Jin

Using high resolution in situ small angle x-ray scattering in conjunction with oscillatory shear on highly monodisperse silica suspensions, we demonstrate that an order-to-disorder transition leads to a dynamic shear thickening in a lower stress regime than the standard steady shear thickening. We show that the order-to-disorder transition is controlled by strain, which is distinguishably different from steady shear thickening which is a stress related phenomenon. The appearance of this two-step shear thinning and thickening transition is also influenced by particle size, monodispersity and measurement conditions (i.e. oscillatory shear vs. steady shear). Our results show definitively that the order-to-disorder transitionmore » induced thickening is completely unrelated to the mechanism that drives the steady shear thickening.« less

Unraveling the Role of Order-to-Disorder Transition in Shear Thickening Suspensions

NASA Astrophysics Data System (ADS)

Lee, Jonghun; Jiang, Zhang; Wang, Jin; Sandy, Alec R.; Narayanan, Suresh; Lin, Xiao-Min

2018-01-01

Using high-resolution in situ small angle x-ray scattering in conjunction with oscillatory shear on highly monodisperse silica suspensions, we demonstrate that an order-to-disorder transition leads to a dynamic shear thickening in a lower stress regime than the standard steady shear thickening. We show that the order-to-disorder transition is controlled by strain, which is distinguishably different from steady shear thickening, which is a stress-related phenomenon. The appearance of this two-step shear thinning and thickening transition is also influenced by the particle size, monodispersity, and measurement conditions (i.e., oscillatory shear versus steady shear). Our results show definitively that the order-to-disorder transition-induced thickening is completely unrelated to the mechanism that drives steady shear thickening.

Mechanical Rectification of Oscillatory Motion for High Torque Microactuators

NASA Astrophysics Data System (ADS)

You, Liang; Tabib-Azar, Massood

2004-03-01

High-torque and scalable rotational micromotors were designed, microfabricated using a 3 mask LPCVD polysilicon process, and characterized. Oscillatory motions generated by comb-drive actuators were rectified by a rotor with fins. The actuator periodically deforms the fins generating forces with tangential and normal components in the rotor. Tangential forces generate rotation. In comparison to the electrostatic side-drive micromotor (torque pN-m), the measured torques for these micromotors were much larger and reached 4.5 µN-m at 200Vpp applied to the comb-drive at 1 KHz. Both the comb-drive and the finned rotor are second-order resonant structures that, when coupled, result in interesting dynamic that manifests itself as different excitation (forward, reverse, stepping, and chaotic) modes of the rotor.

Phase slips in oscillatory hair bundles.

PubMed

Roongthumskul, Yuttana; Shlomovitz, Roie; Bruinsma, Robijn; Bozovic, Dolores

2013-04-05

Hair cells of the inner ear contain an active amplifier that allows them to detect extremely weak signals. As one of the manifestations of an active process, spontaneous oscillations arise in fluid immersed hair bundles of in vitro preparations of selected auditory and vestibular organs. We measure the phase-locking dynamics of oscillatory bundles exposed to low-amplitude sinusoidal signals, a transition that can be described by a saddle-node bifurcation on an invariant circle. The transition is characterized by the occurrence of phase slips, at a rate that is dependent on the amplitude and detuning of the applied drive. The resultant staircase structure in the phase of the oscillation can be described by the stochastic Adler equation, which reproduces the statistics of phase slip production.

Multi-Dimensional High Order Essentially Non-Oscillatory Finite Difference Methods in Generalized Coordinates

NASA Technical Reports Server (NTRS)

Shu, Chi-Wang

1998-01-01

This project is about the development of high order, non-oscillatory type schemes for computational fluid dynamics. Algorithm analysis, implementation, and applications are performed. Collaborations with NASA scientists have been carried out to ensure that the research is relevant to NASA objectives. The combination of ENO finite difference method with spectral method in two space dimension is considered, jointly with Cai [3]. The resulting scheme behaves nicely for the two dimensional test problems with or without shocks. Jointly with Cai and Gottlieb, we have also considered one-sided filters for spectral approximations to discontinuous functions [2]. We proved theoretically the existence of filters to recover spectral accuracy up to the discontinuity. We also constructed such filters for practical calculations.

Bianchi IX dynamics in bouncing cosmologies: homoclinic chaos and the BKL conjecture

NASA Astrophysics Data System (ADS)

Maier, Rodrigo; Damião Soares, Ivano; Valentino Tonini, Eduardo

2015-12-01

We examine the dynamics of a Bianchi IX model with three scale factors on a 4-dim Lorentzian brane embedded in a 5-dim conformally flat empty bulk with a timelike extra dimension. The matter content is a pressureless perfect fluid restricted to the brane, with the embedding consistently satisfying the Gauss-Codazzi equations. The 4-dim Einstein equations on the brane reduce to a 6-dim Hamiltonian dynamical system with additional terms (due to the bulk-brane interaction) that avoid the singularity and implement nonsingular bounces in the model. We examine the complex Bianchi IX dynamics in its approach to the neighborhood of the bounce which replaces the cosmological singularity of general relativity. The phase space of the model presents (i) two critical points (a saddle-center-center and a center-center-center) in a finite region of phase space, (ii) two asymptotic de Sitter critical points at infinity, one acting as an attractor to late-time acceleration and (iii) a 2-dim invariant plane, which together organize the dynamics of the phase space. The saddle-center-center engenders in the phase space the topology of stable and unstable 4-dim cylinders R × S 3, where R is a saddle direction and S 3 is the center manifold of unstable periodic orbits, the latter being the nonlinear extension of the center-center sector. By a proper canonical transformation the degrees of freedom of the dynamics are separated into one degree connected with the expansion/contraction of the scales of the model, and two rotational degrees of freedom associated with the center manifold S 3. The typical dynamical flow is thus an oscillatory mode about the orbits of the invariant plane. The stable and unstable cylinders are spanned by oscillatory orbits about the separatrix towards the bounce, leading to the homoclinic transversal intersection of the cylinders, as shown numerically in two distinct simulations. The homoclinic intersection manifold has the topology of R × S 2 consisting of homoclinic orbits biasymptotic to the center manifold S 3. This behavior defines a chaotic saddle associated with S 3, indicating that the intersection points of the cylinders have the nature of a Cantor set with compact support S 2. This is an invariant signature of chaos in the model. We discuss the connection between these properties of the dynamics, namely the oscillatory approach to the bounce together with its chaotic behavior, and analogous features present in the BKL conjecture in general relativity.

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

Optimal Information Processing in Biochemical Networks

NASA Astrophysics Data System (ADS)

Wiggins, Chris

2012-02-01

A variety of experimental results over the past decades provide examples of near-optimal information processing in biological networks, including in biochemical and transcriptional regulatory networks. Computing information-theoretic quantities requires first choosing or computing the joint probability distribution describing multiple nodes in such a network --- for example, representing the probability distribution of finding an integer copy number of each of two interacting reactants or gene products while respecting the `intrinsic' small copy number noise constraining information transmission at the scale of the cell. I'll given an overview of some recent analytic and numerical work facilitating calculation of such joint distributions and the associated information, which in turn makes possible numerical optimization of information flow in models of noisy regulatory and biochemical networks. Illustrating cases include quantification of form-function relations, ideal design of regulatory cascades, and response to oscillatory driving.

Inhibition Potentiates the Synchronizing Action of Electrical Synapses

PubMed Central

Pfeuty, Benjamin; Golomb, David; Mato, Germán; Hansel, David

2007-01-01

In vivo and in vitro experimental studies have found that blocking electrical interactions connecting GABAergic interneurons reduces oscillatory activity in the γ range in cortex. However, recent theoretical works have shown that the ability of electrical synapses to promote or impede synchrony, when alone, depends on their location on the dendritic tree of the neurons, the intrinsic properties of the neurons and the connectivity of the network. The goal of the present paper is to show that this versatility in the synchronizing ability of electrical synapses is greatly reduced when the neurons also interact via inhibition. To this end, we study a model network comprising two-compartment conductance-based neurons interacting with both types of synapses. We investigate the effect of electrical synapses on the dynamical state of the network as a function of the strength of the inhibition. We find that for weak inhibition, electrical synapses reinforce inhibition-generated synchrony only if they promote synchrony when they are alone. In contrast, when inhibition is sufficiently strong, electrical synapses improve synchrony even if when acting alone they would stabilize asynchronous firing. We clarify the mechanism underlying this cooperative interplay between electrical and inhibitory synapses. We show that it is relevant in two physiologically observed regimes: spike-to-spike synchrony, where neurons fire at almost every cycle of the population oscillations, and stochastic synchrony, where neurons fire irregularly and at a rate which is substantially lower than the frequency of the global population rhythm. PMID:18946530

Phase-locking and bistability in neuronal networks with synaptic depression

NASA Astrophysics Data System (ADS)

Akcay, Zeynep; Huang, Xinxian; Nadim, Farzan; Bose, Amitabha

2018-02-01

We consider a recurrent network of two oscillatory neurons that are coupled with inhibitory synapses. We use the phase response curves of the neurons and the properties of short-term synaptic depression to define Poincaré maps for the activity of the network. The fixed points of these maps correspond to phase-locked modes of the network. Using these maps, we analyze the conditions that allow short-term synaptic depression to lead to the existence of bistable phase-locked, periodic solutions. We show that bistability arises when either the phase response curve of the neuron or the short-term depression profile changes steeply enough. The results apply to any Type I oscillator and we illustrate our findings using the Quadratic Integrate-and-Fire and Morris-Lecar neuron models.

Sleep Neurophysiological Dynamics Through the Lens of Multitaper Spectral Analysis

PubMed Central

Prerau, Michael J.; Brown, Ritchie E.; Bianchi, Matt T.; Ellenbogen, Jeffrey M.; Purdon, Patrick L.

2016-01-01

During sleep, cortical and subcortical structures within the brain engage in highly structured oscillatory dynamics that can be observed in the electroencephalogram (EEG). The ability to accurately describe changes in sleep state from these oscillations has thus been a major goal of sleep medicine. While numerous studies over the past 50 years have shown sleep to be a continuous, multifocal, dynamic process, long-standing clinical practice categorizes sleep EEG into discrete stages through visual inspection of 30-s epochs. By representing sleep as a coarsely discretized progression of stages, vital neurophysiological information on the dynamic interplay between sleep and arousal is lost. However, by using principled time-frequency spectral analysis methods, the rich dynamics of the sleep EEG are immediately visible—elegantly depicted and quantified at time scales ranging from a full night down to individual microevents. In this paper, we review the neurophysiology of sleep through this lens of dynamic spectral analysis. We begin by reviewing spectral estimation techniques traditionally used in sleep EEG analysis and introduce multitaper spectral analysis, a method that makes EEG spectral estimates clearer and more accurate than traditional approaches. Through the lens of the multitaper spectrogram, we review the oscillations and mechanisms underlying the traditional sleep stages. In doing so, we will demonstrate how multitaper spectral analysis makes the oscillatory structure of traditional sleep states instantaneously visible, closely paralleling the traditional hypnogram, but with a richness of information that suggests novel insights into the neural mechanisms of sleep, as well as novel clinical and research applications. PMID:27927806

Low-dimensional spike rate models derived from networks of adaptive integrate-and-fire neurons: Comparison and implementation.

PubMed

Augustin, Moritz; Ladenbauer, Josef; Baumann, Fabian; Obermayer, Klaus

2017-06-01

The spiking activity of single neurons can be well described by a nonlinear integrate-and-fire model that includes somatic adaptation. When exposed to fluctuating inputs sparsely coupled populations of these model neurons exhibit stochastic collective dynamics that can be effectively characterized using the Fokker-Planck equation. This approach, however, leads to a model with an infinite-dimensional state space and non-standard boundary conditions. Here we derive from that description four simple models for the spike rate dynamics in terms of low-dimensional ordinary differential equations using two different reduction techniques: one uses the spectral decomposition of the Fokker-Planck operator, the other is based on a cascade of two linear filters and a nonlinearity, which are determined from the Fokker-Planck equation and semi-analytically approximated. We evaluate the reduced models for a wide range of biologically plausible input statistics and find that both approximation approaches lead to spike rate models that accurately reproduce the spiking behavior of the underlying adaptive integrate-and-fire population. Particularly the cascade-based models are overall most accurate and robust, especially in the sensitive region of rapidly changing input. For the mean-driven regime, when input fluctuations are not too strong and fast, however, the best performing model is based on the spectral decomposition. The low-dimensional models also well reproduce stable oscillatory spike rate dynamics that are generated either by recurrent synaptic excitation and neuronal adaptation or through delayed inhibitory synaptic feedback. The computational demands of the reduced models are very low but the implementation complexity differs between the different model variants. Therefore we have made available implementations that allow to numerically integrate the low-dimensional spike rate models as well as the Fokker-Planck partial differential equation in efficient ways for arbitrary model parametrizations as open source software. The derived spike rate descriptions retain a direct link to the properties of single neurons, allow for convenient mathematical analyses of network states, and are well suited for application in neural mass/mean-field based brain network models.

Low-dimensional spike rate models derived from networks of adaptive integrate-and-fire neurons: Comparison and implementation

PubMed Central

Baumann, Fabian; Obermayer, Klaus

2017-01-01

The spiking activity of single neurons can be well described by a nonlinear integrate-and-fire model that includes somatic adaptation. When exposed to fluctuating inputs sparsely coupled populations of these model neurons exhibit stochastic collective dynamics that can be effectively characterized using the Fokker-Planck equation. This approach, however, leads to a model with an infinite-dimensional state space and non-standard boundary conditions. Here we derive from that description four simple models for the spike rate dynamics in terms of low-dimensional ordinary differential equations using two different reduction techniques: one uses the spectral decomposition of the Fokker-Planck operator, the other is based on a cascade of two linear filters and a nonlinearity, which are determined from the Fokker-Planck equation and semi-analytically approximated. We evaluate the reduced models for a wide range of biologically plausible input statistics and find that both approximation approaches lead to spike rate models that accurately reproduce the spiking behavior of the underlying adaptive integrate-and-fire population. Particularly the cascade-based models are overall most accurate and robust, especially in the sensitive region of rapidly changing input. For the mean-driven regime, when input fluctuations are not too strong and fast, however, the best performing model is based on the spectral decomposition. The low-dimensional models also well reproduce stable oscillatory spike rate dynamics that are generated either by recurrent synaptic excitation and neuronal adaptation or through delayed inhibitory synaptic feedback. The computational demands of the reduced models are very low but the implementation complexity differs between the different model variants. Therefore we have made available implementations that allow to numerically integrate the low-dimensional spike rate models as well as the Fokker-Planck partial differential equation in efficient ways for arbitrary model parametrizations as open source software. The derived spike rate descriptions retain a direct link to the properties of single neurons, allow for convenient mathematical analyses of network states, and are well suited for application in neural mass/mean-field based brain network models. PMID:28644841

Functional network inference of the suprachiasmatic nucleus

PubMed Central

Abel, John H.; Meeker, Kirsten; Granados-Fuentes, Daniel; St. John, Peter C.; Wang, Thomas J.; Bales, Benjamin B.; Doyle, Francis J.; Herzog, Erik D.; Petzold, Linda R.

2016-01-01

In the mammalian suprachiasmatic nucleus (SCN), noisy cellular oscillators communicate within a neuronal network to generate precise system-wide circadian rhythms. Although the intracellular genetic oscillator and intercellular biochemical coupling mechanisms have been examined previously, the network topology driving synchronization of the SCN has not been elucidated. This network has been particularly challenging to probe, due to its oscillatory components and slow coupling timescale. In this work, we investigated the SCN network at a single-cell resolution through a chemically induced desynchronization. We then inferred functional connections in the SCN by applying the maximal information coefficient statistic to bioluminescence reporter data from individual neurons while they resynchronized their circadian cycling. Our results demonstrate that the functional network of circadian cells associated with resynchronization has small-world characteristics, with a node degree distribution that is exponential. We show that hubs of this small-world network are preferentially located in the central SCN, with sparsely connected shells surrounding these cores. Finally, we used two computational models of circadian neurons to validate our predictions of network structure. PMID:27044085

State and Spectral Properties of Chloride Oscillations in Pollen

PubMed Central

Zonia, Laura; Feijó, José A.

2003-01-01

Pollen tube growth is a dynamic system expressing a number of oscillating circuits. Our recent work identified a new circuit, oscillatory efflux of Cl− anion from the pollen tube apex. Cl− efflux is the first ion signal found to be coupled in phase with growth oscillations. Functional analyses indicate an active role for Cl− flux in pollen tube growth. In this report the dynamical properties of Cl− efflux are examined. Phase space analysis demonstrates that the system trajectory converges on a limit cycle. Fourier analysis reveals that two harmonic frequencies characterize normal growth. Cl− efflux is inhibited by the channel blocker DIDS, is stimulated by hypoosmotic treatment, and is antagonized by the signal encoded in inositol 3,4,5,6-tetrakisphosphate. These perturbations induce transitions of the limit cycle to new metastable states or cause system collapse to a static attractor centered near the origin. These perturbations also transform the spectral profile, inducing subharmonic frequencies, transitions to period doubling and tripling, superharmonic resonance, and chaos. These results indicate that Cl− signals in pollen tubes display features that are characteristic of active oscillators that carry frequency-encoded information. A reaction network of the Cl− oscillator coupled to two nonlinear feedback circuits that may drive pollen tube growth oscillations is considered. PMID:12547818

Impact of time delays on oscillatory dynamics of interlinked positive and negative feedback loops

NASA Astrophysics Data System (ADS)

Huang, Bo; Tian, Xinyu; Liu, Feng; Wang, Wei

2016-11-01

Interlinking a positive feedback loop (PFL) with a negative feedback loop (NFL) constitutes a typical motif in genetic networks, performing various functions in cell signaling. How time delay in feedback regulation affects the dynamics of such systems still remains unclear. Here, we investigate three systems of interlinked PFL and NFL with time delays: a synthetic genetic oscillator, a three-node circuit, and a simplified single-node model. The stability of steady states and the routes to oscillation in the single-node model are analyzed in detail. The amplitude and period of oscillations vary with a pointwise periodicity over a range of time delay. Larger-amplitude oscillations can be induced when the PFL has an appropriately long delay, in comparison with the PFL with no delay or short delay; this conclusion holds true for all the three systems. We unravel the underlying mechanism for the above effects via analytical derivation under a limiting condition. We also develop a stochastic algorithm for simulating a single reaction with two delays and show that robust oscillations can be maintained by the PFL with a properly long delay in the single-node system. This work presents an effective method for constructing robust large-amplitude oscillators and interprets why similar circuit architectures are engaged in timekeeping systems such as circadian clocks.

Cellular Interrogation: Exploiting Cell-to-Cell Variability to Discriminate Regulatory Mechanisms in Oscillatory Signalling.

PubMed

Estrada, Javier; Andrew, Natalie; Gibson, Daniel; Chang, Frederick; Gnad, Florian; Gunawardena, Jeremy

2016-07-01

The molecular complexity within a cell may be seen as an evolutionary response to the external complexity of the cell's environment. This suggests that the external environment may be harnessed to interrogate the cell's internal molecular architecture. Cells, however, are not only nonlinear and non-stationary, but also exhibit heterogeneous responses within a clonal, isogenic population. In effect, each cell undertakes its own experiment. Here, we develop a method of cellular interrogation using programmable microfluidic devices which exploits the additional information present in cell-to-cell variation, without requiring model parameters to be fitted to data. We focussed on Ca2+ signalling in response to hormone stimulation, which exhibits oscillatory spiking in many cell types and chose eight models of Ca2+ signalling networks which exhibit similar behaviour in simulation. We developed a nonlinear frequency analysis for non-stationary responses, which could classify models into groups under parameter variation, but found that this question alone was unable to distinguish critical feedback loops. We further developed a nonlinear amplitude analysis and found that the combination of both questions ruled out six of the models as inconsistent with the experimentally-observed dynamics and heterogeneity. The two models that survived the double interrogation were mathematically different but schematically identical and yielded the same unexpected predictions that we confirmed experimentally. Further analysis showed that subtle mathematical details can markedly influence non-stationary responses under parameter variation, emphasising the difficulty of finding a "correct" model. By developing questions for the pathway being studied, and designing more versatile microfluidics, cellular interrogation holds promise as a systematic strategy that can complement direct intervention by genetics or pharmacology.

Synchronization, TIGoRS, and Information Flow in Complex Systems: Dispositional Cellular Automata.

PubMed

Sulis, William H

2016-04-01

Synchronization has a long history in physics where it refers to the phase matching of two identical oscillators. This notion has been extensively studied in physics as well as in biology, where it has been applied to such widely varying phenomena as the flashing of fireflies and firing of neurons in the brain. Human behavior, however, may be recurrent but it is not oscillatory even though many physiological systems do exhibit oscillatory tendencies. Moreover, much of human behaviour is collaborative and cooperative, where the individual behaviours may be distinct yet contemporaneous (if not simultaneous) and taken collectively express some functionality. In the context of behaviour, the important aspect is the repeated co-occurrence in time of behaviours that facilitate the propagation of information or of functionality, regardless of whether or not these behaviours are similar or identical. An example of this weaker notion of synchronization is transient induced global response synchronization (TIGoRS). Previous work has shown that TIGoRS is a ubiquitous phenomenon among complex systems, enabling them to stably parse environmental transients into salient units to which they stably respond. This leads to the notion of Sulis machines, which emergently generate a primitive linguistic structure through their dynamics. This article reviews the notion of TIGoRS and its expression in several complex systems models including tempered neural networks, driven cellular automata and cocktail party automata. The emergent linguistics of Sulis machines are discussed. A new class of complex systems model, the dispositional cellular automaton is introduced. A new metric for TIGoRS, the excess synchronization, is introduced and applied to the study of TIGoRS in dispositional cellular automata. It is shown that these automata exhibit a nonlinear synchronization response to certain perturbing transients.

Origin of long-lived oscillations in 2D-spectra of a quantum vibronic model: Electronic versus vibrational coherence

NASA Astrophysics Data System (ADS)

Plenio, M. B.; Almeida, J.; Huelga, S. F.

2013-12-01

We demonstrate that the coupling of excitonic and vibrational motion in biological complexes can provide mechanisms to explain the long-lived oscillations that have been obtained in nonlinear spectroscopic signals of different photosynthetic pigment protein complexes and we discuss the contributions of excitonic versus purely vibrational components to these oscillatory features. Considering a dimer model coupled to a structured spectral density we exemplify the fundamental aspects of the electron-phonon dynamics, and by analyzing separately the different contributions to the nonlinear signal, we show that for realistic parameter regimes purely electronic coherence is of the same order as purely vibrational coherence in the electronic ground state. Moreover, we demonstrate how the latter relies upon the excitonic interaction to manifest. These results link recently proposed microscopic, non-equilibrium mechanisms to support long lived coherence at ambient temperatures with actual experimental observations of oscillatory behaviour using 2D photon echo techniques to corroborate the fundamental importance of the interplay of electronic and vibrational degrees of freedom in the dynamics of light harvesting aggregates.

Division site selection in Escherichia coli involves dynamic redistribution of Min proteins within coiled structures that extend between the two cell poles

NASA Astrophysics Data System (ADS)

Shih, Yu-Ling; Le, Trung; Rothfield, Lawrence

2003-06-01

The MinCDE proteins of Escherichia coli are required for proper placement of the division septum at midcell. The site selection process requires the rapid oscillatory redistribution of the proteins from pole to pole. We report that the three Min proteins are organized into extended membrane-associated coiled structures that wind around the cell between the two poles. The pole-to-pole oscillation of the proteins reflects oscillatory changes in their distribution within the coiled structure. We also report that the E. coli MreB protein, which is required for maintaining the rod shape of the cell, also forms extended coiled structures, which are similar to the MreB structures that have previously been reported in Bacillus subtilis. The MreB and MinCDE coiled arrays do not appear identical. The results suggest that at least two functionally distinct cytoskeletal-like elements are present in E. coli and that structures of this type can undergo dynamic changes that play important roles in division site placement and possibly other aspects of the life of the cell.

Monocyte recruitment to endothelial cells in response to oscillatory shear stress

PubMed Central

Hsiai, Tzung K.; Cho, Sung K.; Wong, Pak K.; Ing, Mike; Salazar, Adler; Sevanian, Alex; Navab, Mohamad; Demer, Linda L.; Ho, Chih-Ming

2014-01-01

Leukocyte recruitment to endothelial cells is a critical event in inflammatory responses. The spatial, temporal gradients of shear stress, topology, and outcome of cellular interactions that underlie these responses have so far been inferred from static imaging of tissue sections or studies of statically cultured cells. In this report, we developed micro-electromechanical systems (MEMS) sensors, comparable to a single endothelial cell (EC) in size, to link real-time shear stress with monocyte/EC binding kinetics in a complex flow environment, simulating the moving and unsteady separation point at the arterial bifurcation with high spatial and temporal resolution. In response to oscillatory shear stress (τ) at ± 2.6 dyn/cm2 at a time-averaged shear stress (τave) = 0 and 0.5 Hz, individual monocytes displayed unique to-and-fro trajectories undergoing rolling, binding, and dissociation with other monocyte, followed by solid adhesion on EC. Our study quantified individual monocyte/EC binding kinetics in terms of displacement and velocity profiles. Oscillatory flow induces up-regulation of adhesion molecules and cytokines to mediate monocyte/EC interactions over a dynamic range of shear stress ± 2.6 dyn/cm2 (P= 0.50, n= 10).—Hsiai, T. K., Cho, S. K., Wong, P. K., Ing, M., Salazar, A., Sevanian, A., Navab, M., Demer, L. L., Ho, C.-M. Monocyte recruitment to endothelial cells in response to oscillatory shear stress. FASEB J. 17, 1648–1657 (2003) PMID:12958171

[Recent results in research on oscillatory chemical reactions].

PubMed

Poros, Eszter; Kurin-Csörgei, Krisztina

2014-01-01

The mechanisms of the complicated periodical phenomenas in the nature (e.g. hearth beat, sleep cycle, circadian rhythms, etc) could be understood with using the laws of nonlinear chemical systems. In this article the newest result in the research of the subfield of nonlinear chemical dynamics aimed at constructing oscillatory chemical reactions, which are novel either in composition or in configuration, are presented. In the introductory part the concept of chemical periodicity is defined, then the forms as it can appear in time and space and the methods of their study are discussed. Detailed description of the experimental work that has resulted in two significant discoveries is provided. A method was developed to design pH-oscillators which are capable of operating under close conditions. The batch pH-oscillators are more convenient to use in some proposed applications than the equivalent CSTR variant. A redox oscillator that is new in composition was found. The permanganate oxidation of some amino acids was shown to take place according to oscillatory kinetics in a narrow range of the experimental parameters. The KMnO4 - glycine - Na2HPO4 system represents the first example in the family of manganese based oscillators where amino acids is involved. In the conclusion formal analogies between the simple chemical and some more complicated biological oscillatory phenomena are mentioned and the possibility of modeling periodic processes with the use of information gained from the studies of chemical oscillations is pointed out.

Alpha phase determines successful lexical decision in noise.

PubMed

Strauß, Antje; Henry, Molly J; Scharinger, Mathias; Obleser, Jonas

2015-02-18

Psychophysical target detection has been shown to be modulated by slow oscillatory brain phase. However, thus far, only low-level sensory stimuli have been used as targets. The current human electroencephalography (EEG) study examined the influence of neural oscillatory phase on a lexical-decision task performed for stimuli embedded in noise. Neural phase angles were compared for correct versus incorrect lexical decisions using a phase bifurcation index (BI), which quantifies differences in mean phase angles and phase concentrations between correct and incorrect trials. Neural phase angles in the alpha frequency range (8-12 Hz) over right anterior sensors were approximately antiphase in a prestimulus time window, and thus successfully distinguished between correct and incorrect lexical decisions. Moreover, alpha-band oscillations were again approximately antiphase across participants for correct versus incorrect trials during a later peristimulus time window (∼500 ms) at left-central electrodes. Strikingly, lexical decision accuracy was not predicted by either event-related potentials (ERPs) or oscillatory power measures. We suggest that correct lexical decisions depend both on successful sensory processing, which is made possible by the alignment of stimulus onset with an optimal alpha phase, as well as integration and weighting of decisional information, which is coupled to alpha phase immediately following the critical manipulation that differentiated words from pseudowords. The current study constitutes a first step toward characterizing the role of dynamic oscillatory brain states for higher cognitive functions, such as spoken word recognition. Copyright © 2015 the authors 0270-6474/15/353256-07$15.00/0.

Linear viscoelasticity and thermorheological simplicity of n-hexadecane fluids under oscillatory shear via non-equilibrium molecular dynamics simulations.

PubMed

Tseng, Huan-Chang; Wu, Jiann-Shing; Chang, Rong-Yeu

2010-04-28

A small amplitude oscillatory shear flows with the classic characteristic of a phase shift when using non-equilibrium molecular dynamics simulations for n-hexadecane fluids. In a suitable range of strain amplitude, the fluid possesses significant linear viscoelastic behavior. Non-linear viscoelastic behavior of strain thinning, which means the dynamic modulus monotonously decreased with increasing strain amplitudes, was found at extreme strain amplitudes. Under isobaric conditions, different temperatures strongly affected the range of linear viscoelasticity and the slope of strain thinning. The fluid's phase states, containing solid-, liquid-, and gel-like states, can be distinguished through a criterion of the viscoelastic spectrum. As a result, a particular condition for the viscoelastic behavior of n-hexadecane molecules approaching that of the Rouse chain was obtained. Besides, more importantly, evidence of thermorheologically simple materials was presented in which the relaxation modulus obeys the time-temperature superposition principle. Therefore, using shift factors from the time-temperature superposition principle, the estimated Arrhenius flow activation energy was in good agreement with related experimental values. Furthermore, one relaxation modulus master curve well exhibited both transition and terminal zones. Especially regarding non-equilibrium thermodynamic states, variations in the density, with respect to frequencies, were revealed.

Dynamic response of Hovercraft lift fans

NASA Astrophysics Data System (ADS)

Moran, D. D.

1981-08-01

Hovercraft lift fans are subjected to varying back pressure due to wave action and craft motions when these vehicles are operating in a seaway. The oscillatory back pressure causes the fans to perform dynamically, exhibiting a hysteresis type of response and a corresponding degradation in mean performance. Since Hovercraft motions are influenced by variations in lift fan pressure and discharge, it is important to understand completely the nature of the dynamic performance of lift fans in order to completely solve the Hovercraft seakeeping problem. The present study was performed to determine and classify the instabilities encountered in a centrifugal fan operating against time-varying back pressure. A model-scale experiment was developed in which the fan discharge was directed into a flow-measuring device, terminating in a rotating valve which produced an oscillatory back pressure superimposed upon a mean aerodynamic resistance. Pressure and local velocity were measured as functions of time at several locations in the fan volute. The measurements permitted the identification of rotating (or propagating) stall in the impeller. One cell and two cell configurations were classified and the transient condition connecting these two configurations was observed. The mechanisms which lead to rotating stall in a centrifugal compressor are presented and discussed with specific reference to Hovercraft applications.

Particle and Blood Cell Dynamics in Oscillatory Flows Final Report

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

Juan M. Restrepo

2008-09-01

Our aim has been to uncover fundamental aspects of the suspension and dislodgement of particles in wall-bounded oscillatory flows, in flows characterized by Reynolds numbers en- compassing the situation found in rivers and near shores (and perhaps in some industrial processes). Our research tools are computational and our coverage of parameter space fairly broad. Computational means circumvent many complications that make the measurement of the dynamics of particles in a laboratory setting an impractical task, especially on the broad range of parameter space we plan to report upon. The impact of this work on the geophysical problem of sedimentation ismore » boosted considerably by the fact that the proposed calculations can be considered ab-initio, in the sense that little to no modeling is done in generating dynamics of the particles and of the moving fluid: we use a three-dimensional Navier Stokes solver along with straightforward boundry conditions. Hence, to the extent that Navier Stokes is a model for an ideal incompressible isotropic Newtonian fluid, the calculations yield benchmark values for such things as the drag, buoyancy, and lift of particles, in a highly controlled environment. Our approach will be to make measurements of the lift, drag, and buoyancy of particles, by considering progressively more complex physical configurations and physics.« less

Computational Fluid Dynamics Modeling of Submerged Objects Under Unidirectional and Oscillatory Flows.

NASA Astrophysics Data System (ADS)

Fytanidis, D. K.; Wu, H.; Landry, B. J.; Garcia, M. H.

2017-12-01

Abandoned Unexploded Ordnances (UXOs) from wartime events, accidents, training or other military activities can be found in coastal environments. While the interest for these hazardous submerged objects is increased, there are still existing knowledge gaps regarding the mechanisms of incipient motion and flow behavior around UXOs lying on the seafloor. Numerical modeling of flow around near bed placed UXOs is conducted for unidirectional and oscillatory flow conditions using Computational Fluid Dynamics techniques. The Reynolds-Averaged Navier-Stokes (RANS) approach is used to simulate the complex turbulent flow field around UXOs. The numerical results are compared with two-dimensional Particle Image Velocimetry measurements from experiments conducted in unidirectional and oscillatory flow facilities within the Ven Te Chow Hydrosystems Laboratory to evaluate the accuracy of the applied RANS-based solver. Realistic boundary conditions are imposed in the numerical models to mimic the experimental conditions in the laboratory facilities. The comparison between the numerical results and the experimental data agrees well. In addition, the effect of the angle of attack on the forces that UXOs experience is examined. Numerical results suggest that the orientation of UXOs with respect to the mean flow is an important parameter for incipient motion under critical flow conditions which is in agreement with prior laboratory experimental results regarding the identification of critical flow conditions for the initiation of motion of UXOs. Finally, an extensive parametric analysis is conducted to evaluate the effect of the maximum current velocity and wave characteristics (maximum velocity and period) on the flow forces and the mean flow pattern around the objects.

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.

Coordinated prefrontal-hippocampal activity and navigation strategy-related prefrontal firing during spatial memory formation.

PubMed

Negrón-Oyarzo, Ignacio; Espinosa, Nelson; Aguilar, Marcelo; Fuenzalida, Marco; Aboitiz, Francisco; Fuentealba, Pablo

2018-06-18

Learning the location of relevant places in the environment is crucial for survival. Such capacity is supported by a distributed network comprising the prefrontal cortex and hippocampus, yet it is not fully understood how these structures cooperate during spatial reference memory formation. Hence, we examined neural activity in the prefrontal-hippocampal circuit in mice during acquisition of spatial reference memory. We found that interregional oscillatory coupling increased with learning, specifically in the slow-gamma frequency (20 to 40 Hz) band during spatial navigation. In addition, mice used both spatial and nonspatial strategies to navigate and solve the task, yet prefrontal neuronal spiking and oscillatory phase coupling were selectively enhanced in the spatial navigation strategy. Lastly, a representation of the behavioral goal emerged in prefrontal spiking patterns exclusively in the spatial navigation strategy. These results suggest that reference memory formation is supported by enhanced cortical connectivity and evolving prefrontal spiking representations of behavioral goals.

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.

Understanding the Geometry of Connected Fracture Flow with Multiperiod Oscillatory Hydraulic Tests.

PubMed

Sayler, Claire; Cardiff, Michael; Fort, Michael D

2018-03-01

An understanding of the spatial and hydraulic properties of fast preferential flow pathways in the subsurface is necessary in applications ranging from contaminant fate and transport modeling to design of energy extraction systems. One method for the characterization of fracture properties over interwellbore scales is Multiperiod Oscillatory Hydraulic (MOH) testing, in which the aquifer response to oscillatory pressure stimulations is observed. MOH tests were conducted on isolated intervals of wells in siliciclastic and carbonate aquifers in southern Wisconsin. The goal was to characterize the spatial properties of discrete fractures over interwellbore scales. MOH tests were conducted on two discrete fractured intervals intersecting two boreholes at one field site, and a nest of three piezometers at another field site. Fracture diffusivity estimates were obtained using analytical solutions that relate diffusivity to observed phase lag and amplitude decay. In addition, MOH tests were used to investigate the spatial extent of flow using different conceptual models of fracture geometry. Results indicated that fracture geometry at both field sites can be approximated by permeable two-dimensional fracture planes, oriented near-horizontally at one site, and near-vertically at the other. The technique used on MOH field data to characterize fracture geometry shows promise in revealing fracture network characteristics important to groundwater flow and transport. © 2017, National Ground Water Association.

Inhibitory interneuron circuits at cortical and spinal levels are associated with individual differences in corticomuscular coherence during isometric voluntary contraction

PubMed Central

Matsuya, Ryosuke; Ushiyama, Junichi; Ushiba, Junichi

2017-01-01

Corticomuscular coherence (CMC) is an oscillatory synchronization of 15–35 Hz (β-band) between electroencephalogram (EEG) of the sensorimotor cortex and electromyogram of contracting muscles. Although we reported that the magnitude of CMC varies among individuals, the physiological mechanisms underlying this variation are still unclear. Here, we aimed to investigate the associations between CMC and intracortical inhibition (ICI) in the primary motor cortex (M1)/recurrent inhibition (RI) in the spinal cord, which probably affect oscillatory neural activities. Firstly, we quantified ICI from changes in motor-evoked potentials induced by paired-pulse transcranial magnetic stimulation in M1 during tonic isometric voluntary contraction of the first dorsal interosseous. ICI showed a significant, negative correlation with the strength of EEG β-oscillation, but not with the magnitude of CMC across individuals. Next, we quantified RI from changes in H-reflexes induced by paired-pulse electrical nerve stimulation to the posterior tibial nerve during isometric contraction of the soleus muscle. We observed a significant, positive correlation between RI and peak CMC across individuals. These results suggest that the local inhibitory interneuron networks in cortical and spinal levels are associated with the oscillatory activity in corticospinal loop. PMID:28290507

A model of economic growth with physical and human capital: The role of time delays.

PubMed

Gori, Luca; Guerrini, Luca; Sodini, Mauro

2016-09-01

This article aims at analysing a two-sector economic growth model with discrete delays. The focus is on the dynamic properties of the emerging system. In particular, this study concentrates on the stability properties of the stationary solution, characterised by analytical results and geometrical techniques (stability crossing curves), and the conditions under which oscillatory dynamics emerge (through Hopf bifurcations). In addition, this article proposes some numerical simulations to illustrate the behaviour of the system when the stationary equilibrium is unstable.

Quantum dynamics of relativistic bosons through nonminimal vector square potentials

NASA Astrophysics Data System (ADS)

de Oliveira, Luiz P.

2016-09-01

The dynamics of relativistic bosons (scalar and vectorial) through nonminimal vector square (well and barrier) potentials is studied in the Duffin-Kemmer-Petiau (DKP) formalism. We show that the problem can be mapped in effective Schrödinger equations for a component of the DKP spinor. An oscillatory transmission coefficient is found and there is total reflection. Additionally, the energy spectrum of bound states is obtained and reveals the Schiff-Snyder-Weinberg effect, for specific conditions the potential lodges bound states of particles and antiparticles.

Flexive and Propulsive Dynamics of Elastica at Low Reynolds Number

NASA Astrophysics Data System (ADS)

Wiggins, Chris H.; Goldstein, Raymond E.

1998-04-01

A stiff one-armed swimmer in glycerine goes nowhere. However, if its arm is elastic, the swimmer can go on its way. Quantifying this observation, we study a hyperdiffusion equation for the shape of the elastica in a viscous fluid, find solutions for impulsive or oscillatory forcing, and elucidate relevant aspects of propulsion. These results have application in a variety of physical and biological contexts, from dynamic experiments measuring biopolymer bending moduli to instabilities of twisted elastic filaments.

Spontaneous mode switching in coupled oscillators competing for constant amounts of resources

NASA Astrophysics Data System (ADS)

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

2010-03-01

We propose a widely applicable scheme of coupling that models competitions among dynamical systems for fixed amounts of resources. Two oscillators coupled in this way synchronize in antiphase. Three oscillators coupled circularly show a number of oscillation modes such as rotation and partially in-phase synchronization. Intriguingly, simple oscillators in the model also produce complex behavior such as spontaneous switching among different modes. The dynamics reproduces well the spatiotemporal oscillatory behavior of a true slime mold Physarum, which is capable of computational optimization.

Oscillatory behavior of the domain wall dynamics in a curved cylindrical magnetic nanowire

NASA Astrophysics Data System (ADS)

Moreno, R.; Carvalho-Santos, V. L.; Espejo, A. P.; Laroze, D.; Chubykalo-Fesenko, O.; Altbir, D.

2017-11-01

Understanding the domain wall dynamics is an important issue in modern magnetism. Here we present results of domain wall displacement in curved cylindrical nanowires at a constant magnetic field. We show that the average velocity of a transverse domain wall increases with curvature. Contrary to what is observed in stripes, in a curved wire the transverse domain wall oscillates along and rotates around the nanowire with the same frequency. These results open the possibility of new oscillation-based applications.

Unraveling the Role of Order-to-Disorder Transition in Shear Thickening Suspensions

DOE PAGES

Lee, Jonghun; Jiang, Zhang; Wang, Jin; ...

2018-01-09

Using high resolution in situ small angle x-ray scattering in conjunction with oscillatory shear on highly monodisperse silica suspensions, we demonstrate that an order-to-disorder transition leads to a dynamic shear thickening in a lower stress regime than the standard steady shear thickening. We show that the order-to-disorder transition is controlled by strain, which is distinguishably different from steady shear thickening which is a stress related phenomenon. The appearance of this two-step shear thinning and thickening transition is also influenced by particle size, monodispersity and measurement conditions (i.e. oscillatory shear vs. steady shear). Our results show definitively that the order-to-disorder transitionmore » induced thickening is completely unrelated to the mechanism that drives the steady shear thickening.« less

Experimental observation of phase-flip transitions in the brain

NASA Astrophysics Data System (ADS)

Dotson, Nicholas M.; Gray, Charles M.

2016-10-01

The phase-flip transition has been demonstrated in a host of coupled nonlinear oscillator models, many pertaining directly to understanding neural dynamics. However, there is little evidence that this phenomenon occurs in the brain. Using simultaneous microelectrode recordings in the nonhuman primate cerebral cortex, we demonstrate the presence of phase-flip transitions between oscillatory narrow-band local field potential signals separated by several centimeters. Specifically, we show that sharp transitions between in-phase and antiphase synchronization are accompanied by a jump in synchronization frequency. These findings are significant for two reasons. First, they validate predictions made by model systems. Second, they have potentially far reaching implications for our understanding of the mechanisms underlying corticocortical communication, which are thought to rely on narrow-band oscillatory synchronization with specific relative phase relationships.

Vortex-induced vibration (VIV) effects of a drilling riser due to vessel motion

NASA Astrophysics Data System (ADS)

Joseph, R. S.; Wang, J.; Ong, M. C.; Jakobsen, J. B.

2017-12-01

A marine riser undergoes oscillatory motion in water due to the vessel motions, known as global dynamic response. This to-and-fro motion of the riser will generate an equivalent flow that can cause Vortex-Induced Vibrations (VIVs), even in the absence of the ocean current. In the present work, full-scale measurement data of a drilling riser operating in the Gulf of Mexico are analysed. The VIV occurrences for the riser are identified from the data and the possible excitation sources are discussed. The oscillatory flow due to vessel motion is compared with the ocean current and its possibility to excite VIV is analysed. The full-scale data analysis provides an insight into the vessel motion-induced VIV of marine risers in the actual field environment.

Human brain networks function in connectome-specific harmonic waves.

PubMed

Atasoy, Selen; Donnelly, Isaac; Pearson, Joel

2016-01-21

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

Short desynchronization episodes prevail in synchronous dynamics of human brain rhythms.

PubMed

Ahn, Sungwoo; Rubchinsky, Leonid L

2013-03-01

Neural synchronization is believed to be critical for many brain functions. It frequently exhibits temporal variability, but it is not known if this variability has a specific temporal patterning. This study explores these synchronization/desynchronization patterns. We employ recently developed techniques to analyze the fine temporal structure of phase-locking to study the temporal patterning of synchrony of the human brain rhythms. We study neural oscillations recorded by electroencephalograms in α and β frequency bands in healthy human subjects at rest and during the execution of a task. While the phase-locking strength depends on many factors, dynamics of synchrony has a very specific temporal pattern: synchronous states are interrupted by frequent, but short desynchronization episodes. The probability for a desynchronization episode to occur decreased with its duration. The transition matrix between synchronized and desynchronized states has eigenvalues close to 0 and 1 where eigenvalue 1 has multiplicity 1, and therefore if the stationary distribution between these states is perturbed, the system converges back to the stationary distribution very fast. The qualitative similarity of this patterning across different subjects, brain states and electrode locations suggests that this may be a general type of dynamics for the brain. Earlier studies indicate that not all oscillatory networks have this kind of patterning of synchronization/desynchronization dynamics. Thus, the observed prevalence of short (but potentially frequent) desynchronization events (length of one cycle of oscillations) may have important functional implications for the brain. Numerous short desynchronizations (as opposed to infrequent, but long desynchronizations) may allow for a quick and efficient formation and break-up of functionally significant neuronal assemblies.

Short desynchronization episodes prevail in synchronous dynamics of human brain rhythms

NASA Astrophysics Data System (ADS)

Ahn, Sungwoo; Rubchinsky, Leonid L.

2013-03-01

Neural synchronization is believed to be critical for many brain functions. It frequently exhibits temporal variability, but it is not known if this variability has a specific temporal patterning. This study explores these synchronization/desynchronization patterns. We employ recently developed techniques to analyze the fine temporal structure of phase-locking to study the temporal patterning of synchrony of the human brain rhythms. We study neural oscillations recorded by electroencephalograms in α and β frequency bands in healthy human subjects at rest and during the execution of a task. While the phase-locking strength depends on many factors, dynamics of synchrony has a very specific temporal pattern: synchronous states are interrupted by frequent, but short desynchronization episodes. The probability for a desynchronization episode to occur decreased with its duration. The transition matrix between synchronized and desynchronized states has eigenvalues close to 0 and 1 where eigenvalue 1 has multiplicity 1, and therefore if the stationary distribution between these states is perturbed, the system converges back to the stationary distribution very fast. The qualitative similarity of this patterning across different subjects, brain states and electrode locations suggests that this may be a general type of dynamics for the brain. Earlier studies indicate that not all oscillatory networks have this kind of patterning of synchronization/desynchronization dynamics. Thus, the observed prevalence of short (but potentially frequent) desynchronization events (length of one cycle of oscillations) may have important functional implications for the brain. Numerous short desynchronizations (as opposed to infrequent, but long desynchronizations) may allow for a quick and efficient formation and break-up of functionally significant neuronal assemblies.

Mechanisms of Zero-Lag Synchronization in Cortical Motifs

PubMed Central

Gollo, Leonardo L.; Mirasso, Claudio; Sporns, Olaf; Breakspear, Michael

2014-01-01

Zero-lag synchronization between distant cortical areas has been observed in a diversity of experimental data sets and between many different regions of the brain. Several computational mechanisms have been proposed to account for such isochronous synchronization in the presence of long conduction delays: Of these, the phenomenon of “dynamical relaying” – a mechanism that relies on a specific network motif – has proven to be the most robust with respect to parameter mismatch and system noise. Surprisingly, despite a contrary belief in the community, the common driving motif is an unreliable means of establishing zero-lag synchrony. Although dynamical relaying has been validated in empirical and computational studies, the deeper dynamical mechanisms and comparison to dynamics on other motifs is lacking. By systematically comparing synchronization on a variety of small motifs, we establish that the presence of a single reciprocally connected pair – a “resonance pair” – plays a crucial role in disambiguating those motifs that foster zero-lag synchrony in the presence of conduction delays (such as dynamical relaying) from those that do not (such as the common driving triad). Remarkably, minor structural changes to the common driving motif that incorporate a reciprocal pair recover robust zero-lag synchrony. The findings are observed in computational models of spiking neurons, populations of spiking neurons and neural mass models, and arise whether the oscillatory systems are periodic, chaotic, noise-free or driven by stochastic inputs. The influence of the resonance pair is also robust to parameter mismatch and asymmetrical time delays amongst the elements of the motif. We call this manner of facilitating zero-lag synchrony resonance-induced synchronization, outline the conditions for its occurrence, and propose that it may be a general mechanism to promote zero-lag synchrony in the brain. PMID:24763382

Bistable flapping of flexible flyers in oscillatory flow

NASA Astrophysics Data System (ADS)

Huang, Yangyang; Kanso, Eva

2016-11-01

Biological and bio-inspired flyers move by shape actuation. The direct control of shape variables for locomotory purposes is well studied. Less is known about indirect shape actuation via the fluid medium. Here, we consider a flexible Λ-flyer in oscillatory flow that is free to flap and rotate around its fixed apex. We study its motion in the context of the inviscid vortex sheet model. We first analyze symmetric flapping about the vertical axis of gravity. We find that there is a finite value of the flexibility that maximizes both the flapping amplitude and elastic energy storage. Our results show that rather than resonance, the flyer relies on fluidic effects to optimize these two quantities. We then perturb the flyer away from the vertical and analyze its stability. Four distinct types of rolling behavior are identified: mono-stable, bistable, bistable oscillatory rotations and chaotic dynamics. We categorize these types of behavior in terms of the flyer's and flow parameters. In particular, the transition from mono-stable to bistable behavior occurs at a constant value of the product of the flow amplitude and acceleration. This product can be interpreted as the ratio of fluidic drag to gravity, confirming the fluid role in this transition.

Modelling Quasi-Periodic Pulsations in Solar and Stellar Flares

NASA Astrophysics Data System (ADS)

McLaughlin, J. A.; Nakariakov, V. M.; Dominique, M.; Jelínek, P.; Takasao, S.

2018-02-01

Solar flare emission is detected in all EM bands and variations in flux density of solar energetic particles. Often the EM radiation generated in solar and stellar flares shows a pronounced oscillatory pattern, with characteristic periods ranging from a fraction of a second to several minutes. These oscillations are referred to as quasi-periodic pulsations (QPPs), to emphasise that they often contain apparent amplitude and period modulation. We review the current understanding of quasi-periodic pulsations in solar and stellar flares. In particular, we focus on the possible physical mechanisms, with an emphasis on the underlying physics that generates the resultant range of periodicities. These physical mechanisms include MHD oscillations, self-oscillatory mechanisms, oscillatory reconnection/reconnection reversal, wave-driven reconnection, two loop coalescence, MHD flow over-stability, the equivalent LCR-contour mechanism, and thermal-dynamical cycles. We also provide a histogram of all QPP events published in the literature at this time. The occurrence of QPPs puts additional constraints on the interpretation and understanding of the fundamental processes operating in flares, e.g. magnetic energy liberation and particle acceleration. Therefore, a full understanding of QPPs is essential in order to work towards an integrated model of solar and stellar flares.

GABA-mediated changes in inter-hemispheric beta frequency activity in early-stage Parkinson’s disease

PubMed Central

Hall, S.D.; Prokic, E.J.; McAllister, C.J.; Ronnqvist, K.C.; Williams, A.C.; Yamawaki, N.; Witton, C.; Woodhall, G.L.; Stanford, I.M.

2014-01-01

In Parkinson’s disease (PD), elevated beta (15–35 Hz) power in subcortical motor networks is widely believed to promote aspects of PD symptomatology, moreover, a reduction in beta power and coherence accompanies symptomatic improvement following effective treatment with l-DOPA. Previous studies have reported symptomatic improvements that correlate with changes in cortical network activity following GABAA receptor modulation. In this study we have used whole-head magnetoencephalography to characterize neuronal network activity, at rest and during visually cued finger abductions, in unilaterally symptomatic PD and age-matched control participants. Recordings were then repeated following administration of sub-sedative doses of the hypnotic drug zolpidem (0.05 mg/kg), which binds to the benzodiazepine site of the GABAA receptor. A beamforming based ‘virtual electrode’ approach was used to reconstruct oscillatory power in the primary motor cortex (M1), contralateral and ipsilateral to symptom presentation in PD patients or dominant hand in control participants. In PD patients, contralateral M1 showed significantly greater beta power than ipsilateral M1. Following zolpidem administration contralateral beta power was significantly reduced while ipsilateral beta power was significantly increased resulting in a hemispheric power ratio that approached parity. Furthermore, there was highly significant correlation between hemispheric beta power ratio and Unified Parkinson’s Disease Rating Scale (UPDRS). The changes in contralateral and ipsilateral beta power were reflected in pre-movement beta desynchronization and the late post-movement beta rebound. However, the absolute level of movement-related beta desynchronization was not altered. These results show that low-dose zolpidem not only reduces contralateral beta but also increases ipsilateral beta, while rebalancing the dynamic range of M1 network oscillations between the two hemispheres. These changes appear to underlie the symptomatic improvements afforded by low-dose zolpidem. PMID:25261686

The Computational Fluid Dynamics Rupture Challenge 2013—Phase I: prediction of rupture status in intracranial aneurysms.

PubMed

Janiga, G; Berg, P; Sugiyama, S; Kono, K; Steinman, D A

2015-03-01

Rupture risk assessment for intracranial aneurysms remains challenging, and risk factors, including wall shear stress, are discussed controversially. The primary purpose of the presented challenge was to determine how consistently aneurysm rupture status and rupture site could be identified on the basis of computational fluid dynamics. Two geometrically similar MCA aneurysms were selected, 1 ruptured, 1 unruptured. Participating computational fluid dynamics groups were blinded as to which case was ruptured. Participants were provided with digitally segmented lumen geometries and, for this phase of the challenge, were free to choose their own flow rates, blood rheologies, and so forth. Participants were asked to report which case had ruptured and the likely site of rupture. In parallel, lumen geometries were provided to a group of neurosurgeons for their predictions of rupture status and site. Of 26 participating computational fluid dynamics groups, 21 (81%) correctly identified the ruptured case. Although the known rupture site was associated with low and oscillatory wall shear stress, most groups identified other sites, some of which also experienced low and oscillatory shear. Of the 43 participating neurosurgeons, 39 (91%) identified the ruptured case. None correctly identified the rupture site. Geometric or hemodynamic considerations favor identification of rupture status; however, retrospective identification of the rupture site remains a challenge for both engineers and clinicians. A more precise understanding of the hemodynamic factors involved in aneurysm wall pathology is likely required for computational fluid dynamics to add value to current clinical decision-making regarding rupture risk. © 2015 by American Journal of Neuroradiology.

Horizons of cybernetical physics

PubMed Central

2017-01-01

The subject and main areas of a new research field—cybernetical physics—are discussed. A brief history of cybernetical physics is outlined. The main areas of activity in cybernetical physics are briefly surveyed, such as control of oscillatory and chaotic behaviour, control of resonance and synchronization, control in thermodynamics, control of distributed systems and networks, quantum control. This article is part of the themed issue ‘Horizons of cybernetical physics’. PMID:28115620

Environmental factors linked to depression vulnerability are associated with altered cerebellar resting-state synchronization.

PubMed

Córdova-Palomera, Aldo; Tornador, Cristian; Falcón, Carles; Bargalló, Nuria; Brambilla, Paolo; Crespo-Facorro, Benedicto; Deco, Gustavo; Fañanás, Lourdes

2016-11-28

Hosting nearly eighty percent of all human neurons, the cerebellum is functionally connected to large regions of the brain. Accumulating data suggest that some cerebellar resting-state alterations may constitute a key candidate mechanism for depressive psychopathology. While there is some evidence linking cerebellar function and depression, two topics remain largely unexplored. First, the genetic or environmental roots of this putative association have not been elicited. Secondly, while different mathematical representations of resting-state fMRI patterns can embed diverse information of relevance for health and disease, many of them have not been studied in detail regarding the cerebellum and depression. Here, high-resolution fMRI scans were examined to estimate functional connectivity patterns across twenty-six cerebellar regions in a sample of 48 identical twins (24 pairs) informative for depression liability. A network-based statistic approach was employed to analyze cerebellar functional networks built using three methods: the conventional approach of filtered BOLD fMRI time-series, and two analytic components of this oscillatory activity (amplitude envelope and instantaneous phase). The findings indicate that some environmental factors may lead to depression vulnerability through alterations of the neural oscillatory activity of the cerebellum during resting-state. These effects may be observed particularly when exploring the amplitude envelope of fMRI oscillations.

Observation of oscillatory surface reactions of riboflavin, trolox, and singlet oxygen using single carbon nanotube fluorescence spectroscopy.

PubMed

Sen, Fatih; Boghossian, Ardemis A; Sen, Selda; Ulissi, Zachary W; Zhang, Jingqing; Strano, Michael S

2012-12-21

Single-molecule fluorescent microscopy allows semiconducting single-walled carbon nanotubes (SWCNTs) to detect the adsorption and desorption of single adsorbate molecules as a stochastic modulation of emission intensity. In this study, we identify and assign the signature of the complex decomposition and reaction pathways of riboflavin in the presence of the free radical scavenger Trolox using DNA-wrapped SWCNT sensors dispersed onto an aminopropyltriethoxysilane (APTES) coated surface. SWCNT emission is quenched by riboflavin-induced reactive oxygen species (ROS), but increases upon the adsorption of Trolox, which functions as a reductive brightening agent. Riboflavin has two parallel reaction pathways, a Trolox oxidizer and a photosensitizer for singlet oxygen and superoxide generation. The resulting reaction network can be detected in real time in the vicinity of a single SWCNT and can be completely described using elementary reactions and kinetic rate constants measured independently. The reaction mechanism results in an oscillatory fluorescence response from each SWCNT, allowing for the simultaneous detection of multiple reactants. A series-parallel kinetic model is shown to describe the critical points of these oscillations, with partition coefficients on the order of 10(-6)-10(-4) for the reactive oxygen and excited state species. These results highlight the potential for SWCNTs to characterize complex reaction networks at the nanometer scale.

Weak synchronization and large-scale collective oscillation in dense bacterial suspensions

NASA Astrophysics Data System (ADS)

Chen, Chong; Liu, Song; Shi, Xia-Qing; Chaté, Hugues; Wu, Yilin

2017-01-01

Collective oscillatory behaviour is ubiquitous in nature, having a vital role in many biological processes from embryogenesis and organ development to pace-making in neuron networks. Elucidating the mechanisms that give rise to synchronization is essential to the understanding of biological self-organization. Collective oscillations in biological multicellular systems often arise from long-range coupling mediated by diffusive chemicals, by electrochemical mechanisms, or by biomechanical interaction between cells and their physical environment. In these examples, the phase of some oscillatory intracellular degree of freedom is synchronized. Here, in contrast, we report the discovery of a weak synchronization mechanism that does not require long-range coupling or inherent oscillation of individual cells. We find that millions of motile cells in dense bacterial suspensions can self-organize into highly robust collective oscillatory motion, while individual cells move in an erratic manner, without obvious periodic motion but with frequent, abrupt and random directional changes. So erratic are individual trajectories that uncovering the collective oscillations of our micrometre-sized cells requires individual velocities to be averaged over tens or hundreds of micrometres. On such large scales, the oscillations appear to be in phase and the mean position of cells typically describes a regular elliptic trajectory. We found that the phase of the oscillations is organized into a centimetre-scale travelling wave. We present a model of noisy self-propelled particles with strictly local interactions that accounts faithfully for our observations, suggesting that self-organized collective oscillatory motion results from spontaneous chiral and rotational symmetry breaking. These findings reveal a previously unseen type of long-range order in active matter systems (those in which energy is spent locally to produce non-random motion). This mechanism of collective oscillation may inspire new strategies to control the self-organization of active matter and swarming robots.

Weak synchronization and large-scale collective oscillation in dense bacterial suspensions.

PubMed

Chen, Chong; Liu, Song; Shi, Xia-Qing; Chaté, Hugues; Wu, Yilin

2017-02-09

Collective oscillatory behaviour is ubiquitous in nature, having a vital role in many biological processes from embryogenesis and organ development to pace-making in neuron networks. Elucidating the mechanisms that give rise to synchronization is essential to the understanding of biological self-organization. Collective oscillations in biological multicellular systems often arise from long-range coupling mediated by diffusive chemicals, by electrochemical mechanisms, or by biomechanical interaction between cells and their physical environment. In these examples, the phase of some oscillatory intracellular degree of freedom is synchronized. Here, in contrast, we report the discovery of a weak synchronization mechanism that does not require long-range coupling or inherent oscillation of individual cells. We find that millions of motile cells in dense bacterial suspensions can self-organize into highly robust collective oscillatory motion, while individual cells move in an erratic manner, without obvious periodic motion but with frequent, abrupt and random directional changes. So erratic are individual trajectories that uncovering the collective oscillations of our micrometre-sized cells requires individual velocities to be averaged over tens or hundreds of micrometres. On such large scales, the oscillations appear to be in phase and the mean position of cells typically describes a regular elliptic trajectory. We found that the phase of the oscillations is organized into a centimetre-scale travelling wave. We present a model of noisy self-propelled particles with strictly local interactions that accounts faithfully for our observations, suggesting that self-organized collective oscillatory motion results from spontaneous chiral and rotational symmetry breaking. These findings reveal a previously unseen type of long-range order in active matter systems (those in which energy is spent locally to produce non-random motion). This mechanism of collective oscillation may inspire new strategies to control the self-organization of active matter and swarming robots.

Why don't you like me? Midfrontal theta power in response to unexpected peer rejection feedback.

PubMed

van der Molen, M J W; Dekkers, L M S; Westenberg, P M; van der Veen, F M; van der Molen, M W

2017-02-01

Social connectedness theory posits that the brain processes social rejection as a threat to survival. Recent electrophysiological evidence suggests that midfrontal theta (4-8Hz) oscillations in the EEG provide a window on the processing of social rejection. Here we examined midfrontal theta dynamics (power and inter-trial phase synchrony) during the processing of social evaluative feedback. We employed the Social Judgment paradigm in which 56 undergraduate women (mean age=19.67 years) were asked to communicate their expectancies about being liked vs. disliked by unknown peers. Expectancies were followed by feedback indicating social acceptance vs. rejection. Results revealed a significant increase in EEG theta power to unexpected social rejection feedback. This EEG theta response could be source-localized to brain regions typically reported during activation of the saliency network (i.e., dorsal anterior cingulate cortex, insula, inferior frontal gyrus, frontal pole, and the supplementary motor area). Theta phase dynamics mimicked the behavior of the time-domain averaged feedback-related negativity (FRN) by showing stronger phase synchrony for feedback that was unexpected vs. expected. Theta phase, however, differed from the FRN by also displaying stronger phase synchrony in response to rejection vs. acceptance feedback. Together, this study highlights distinct roles for midfrontal theta power and phase synchrony in response to social evaluative feedback. Our findings contribute to the literature by showing that midfrontal theta oscillatory power is sensitive to social rejection but only when peer rejection is unexpected, and this theta response is governed by a widely distributed neural network implicated in saliency detection and conflict monitoring. Copyright © 2016 Elsevier Inc. All rights reserved.

A 1.26 μW Cytomimetic IC Emulating Complex Nonlinear Mammalian Cell Cycle Dynamics: Synthesis, Simulation and Proof-of-Concept Measured Results.

PubMed

Houssein, Alexandros; Papadimitriou, Konstantinos I; Drakakis, Emmanuel M

2015-08-01

Cytomimetic circuits represent a novel, ultra low-power, continuous-time, continuous-value class of circuits, capable of mapping on silicon cellular and molecular dynamics modelled by means of nonlinear ordinary differential equations (ODEs). Such monolithic circuits are in principle able to emulate on chip, single or multiple cell operations in a highly parallel fashion. Cytomimetic topologies can be synthesized by adopting the Nonlinear Bernoulli Cell Formalism (NBCF), a mathematical framework that exploits the striking similarities between the equations describing weakly-inverted Metal-Oxide Semiconductor (MOS) devices and coupled nonlinear ODEs, typically appearing in models of naturally encountered biochemical systems. The NBCF maps biological state variables onto strictly positive subthreshold MOS circuit currents. This paper presents the synthesis, the simulation and proof-of-concept chip results corresponding to the emulation of a complex cellular network mechanism, the skeleton model for the network of Cyclin-dependent Kinases (CdKs) driving the mammalian cell cycle. This five variable nonlinear biological model, when appropriate model parameter values are assigned, can exhibit multiple oscillatory behaviors, varying from simple periodic oscillations, to complex oscillations such as quasi-periodicity and chaos. The validity of our approach is verified by simulated results with realistic process parameters from the commercially available AMS 0.35 μm technology and by chip measurements. The fabricated chip occupies an area of 2.27 mm2 and consumes a power of 1.26 μW from a power supply of 3 V. The presented cytomimetic topology follows closely the behavior of its biological counterpart, exhibiting similar time-dependent solutions of the Cdk complexes, the transcription factors and the proteins.

A Statistical-Dynamical Approach to Intraseasonal Prediction of Tropical Cyclogenesis in the Western North Pacific

DTIC Science & Technology

2009-03-01

state of the climate system...information about the current or forecasted state of the climate system. Collocated with FNMOD, is the Air Force’s 14th Weather Squadron (14WS; formerly...relationships between the LSEFs and TC formations can be skillful regardless of the oscillatory state of the climate system. D.