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.

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.

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.

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.

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

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

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.

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.

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.

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

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.

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.

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.

Automatic network coupling analysis for dynamical systems based on detailed kinetic models.

PubMed

Lebiedz, Dirk; Kammerer, Julia; Brandt-Pollmann, Ulrich

2005-10-01

We introduce a numerical complexity reduction method for the automatic identification and analysis of dynamic network decompositions in (bio)chemical kinetics based on error-controlled computation of a minimal model dimension represented by the number of (locally) active dynamical modes. Our algorithm exploits a generalized sensitivity analysis along state trajectories and subsequent singular value decomposition of sensitivity matrices for the identification of these dominant dynamical modes. It allows for a dynamic coupling analysis of (bio)chemical species in kinetic models that can be exploited for the piecewise computation of a minimal model on small time intervals and offers valuable functional insight into highly nonlinear reaction mechanisms and network dynamics. We present results for the identification of network decompositions in a simple oscillatory chemical reaction, time scale separation based model reduction in a Michaelis-Menten enzyme system and network decomposition of a detailed model for the oscillatory peroxidase-oxidase enzyme system.

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.

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

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.

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.

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

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

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

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

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

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.

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.

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…

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.

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

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

Identifying stochastic oscillations in single-cell live imaging time series using Gaussian processes

PubMed Central

Manning, Cerys; Rattray, Magnus

2017-01-01

Multiple biological processes are driven by oscillatory gene expression at different time scales. Pulsatile dynamics are thought to be widespread, and single-cell live imaging of gene expression has lead to a surge of dynamic, possibly oscillatory, data for different gene networks. However, the regulation of gene expression at the level of an individual cell involves reactions between finite numbers of molecules, and this can result in inherent randomness in expression dynamics, which blurs the boundaries between aperiodic fluctuations and noisy oscillators. This underlies a new challenge to the experimentalist because neither intuition nor pre-existing methods work well for identifying oscillatory activity in noisy biological time series. Thus, there is an acute need for an objective statistical method for classifying whether an experimentally derived noisy time series is periodic. Here, we present a new data analysis method that combines mechanistic stochastic modelling with the powerful methods of non-parametric regression with Gaussian processes. Our method can distinguish oscillatory gene expression from random fluctuations of non-oscillatory expression in single-cell time series, despite peak-to-peak variability in period and amplitude of single-cell oscillations. We show that our method outperforms the Lomb-Scargle periodogram in successfully classifying cells as oscillatory or non-oscillatory in data simulated from a simple genetic oscillator model and in experimental data. Analysis of bioluminescent live-cell imaging shows a significantly greater number of oscillatory cells when luciferase is driven by a Hes1 promoter (10/19), which has previously been reported to oscillate, than the constitutive MoMuLV 5’ LTR (MMLV) promoter (0/25). The method can be applied to data from any gene network to both quantify the proportion of oscillating cells within a population and to measure the period and quality of oscillations. It is publicly available as a MATLAB package. PMID:28493880

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.

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.

Mean Field Analysis of Stochastic Neural Network Models with Synaptic Depression

NASA Astrophysics Data System (ADS)

Yasuhiko Igarashi,; Masafumi Oizumi,; Masato Okada,

2010-08-01

We investigated the effects of synaptic depression on the macroscopic behavior of stochastic neural networks. Dynamical mean field equations were derived for such networks by taking the average of two stochastic variables: a firing-state variable and a synaptic variable. In these equations, the average product of thesevariables is decoupled as the product of their averages because the two stochastic variables are independent. We proved the independence of these two stochastic variables assuming that the synaptic weight Jij is of the order of 1/N with respect to the number of neurons N. Using these equations, we derived macroscopic steady-state equations for a network with uniform connections and for a ring attractor network with Mexican hat type connectivity and investigated the stability of the steady-state solutions. An oscillatory uniform state was observed in the network with uniform connections owing to a Hopf instability. For the ring network, high-frequency perturbations were shown not to affect system stability. Two mechanisms destabilize the inhomogeneous steady state, leading to two oscillatory states. A Turing instability leads to a rotating bump state, while a Hopf instability leads to an oscillatory bump state, which was previously unreported. Various oscillatory states take place in a network with synaptic depression depending on the strength of the interneuron connections.

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

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

Restoration of rhythmicity in diffusively coupled dynamical networks.

PubMed

Zou, Wei; Senthilkumar, D V; Nagao, Raphael; Kiss, István Z; Tang, Yang; Koseska, Aneta; Duan, Jinqiao; Kurths, Jürgen

2015-07-15

Oscillatory behaviour is essential for proper functioning of various physical and biological processes. However, diffusive coupling is capable of suppressing intrinsic oscillations due to the manifestation of the phenomena of amplitude and oscillation deaths. Here we present a scheme to revoke these quenching states in diffusively coupled dynamical networks, and demonstrate the approach in experiments with an oscillatory chemical reaction. By introducing a simple feedback factor in the diffusive coupling, we show that the stable (in)homogeneous steady states can be effectively destabilized to restore dynamic behaviours of coupled systems. Even a feeble deviation from the normal diffusive coupling drastically shrinks the death regions in the parameter space. The generality of our method is corroborated in diverse non-linear systems of diffusively coupled paradigmatic models with various death scenarios. Our study provides a general framework to strengthen the robustness of dynamic activity in diffusively coupled dynamical networks.

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.

Cross-modal integration of lexical-semantic features during word processing: evidence from oscillatory dynamics during EEG.

PubMed

van Ackeren, Markus J; Rueschemeyer, Shirley-Ann

2014-01-01

In recent years, numerous studies have provided converging evidence that word meaning is partially stored in modality-specific cortical networks. However, little is known about the mechanisms supporting the integration of this distributed semantic content into coherent conceptual representations. In the current study we aimed to address this issue by using EEG to look at the spatial and temporal dynamics of feature integration during word comprehension. Specifically, participants were presented with two modality-specific features (i.e., visual or auditory features such as silver and loud) and asked to verify whether these two features were compatible with a subsequently presented target word (e.g., WHISTLE). Each pair of features described properties from either the same modality (e.g., silver, tiny  =  visual features) or different modalities (e.g., silver, loud  =  visual, auditory). Behavioral and EEG data were collected. The results show that verifying features that are putatively represented in the same modality-specific network is faster than verifying features across modalities. At the neural level, integrating features across modalities induces sustained oscillatory activity around the theta range (4-6 Hz) in left anterior temporal lobe (ATL), a putative hub for integrating distributed semantic content. In addition, enhanced long-range network interactions in the theta range were seen between left ATL and a widespread cortical network. These results suggest that oscillatory dynamics in the theta range could be involved in integrating multimodal semantic content by creating transient functional networks linking distributed modality-specific networks and multimodal semantic hubs such as left ATL.

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

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.

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.

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.

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

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.

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.

Distinct collective states due to trade-off between attractive and repulsive couplings

NASA Astrophysics Data System (ADS)

Sathiyadevi, K.; Chandrasekar, V. K.; Senthilkumar, D. V.; Lakshmanan, M.

2018-03-01

We investigate the effect of repulsive coupling together with an attractive coupling in a network of nonlocally coupled oscillators. To understand the complex interaction between these two couplings we introduce a control parameter in the repulsive coupling which plays a crucial role in inducing distinct complex collective patterns. In particular, we show the emergence of various cluster chimera death states through a dynamically distinct transition route, namely the oscillatory cluster state and coherent oscillation death state as a function of the repulsive coupling in the presence of the attractive coupling. In the oscillatory cluster state, the oscillators in the network are grouped into two distinct dynamical states of homogeneous and inhomogeneous oscillatory states. Further, the network of coupled oscillators follow the same transition route in the entire coupling range. Depending upon distinct coupling ranges, the system displays different number of clusters in the death state and oscillatory state. We also observe that the number of coherent domains in the oscillatory cluster state exponentially decreases with increase in coupling range and obeys a power-law decay. Additionally, we show analytical stability for observed solitary state, synchronized state, and incoherent oscillation death state.

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.

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.

Optimal Phase Oscillatory Network

NASA Astrophysics Data System (ADS)

Follmann, Rosangela

2013-03-01

Important topics as preventive detection of epidemics, collective self-organization, information flow and systemic robustness in clusters are typical examples of processes that can be studied in the context of the theory of complex networks. It is an emerging theory in a field, which has recently attracted much interest, involving the synchronization of dynamical systems associated to nodes, or vertices, of the network. Studies have shown that synchronization in oscillatory networks depends not only on the individual dynamics of each element, but also on the combination of the topology of the connections as well as on the properties of the interactions of these elements. Moreover, the response of the network to small damages, caused at strategic points, can enhance the global performance of the whole network. In this presentation we explore an optimal phase oscillatory network altered by an additional term in the coupling function. The application to associative-memory network shows improvement on the correct information retrieval as well as increase of the storage capacity. The inclusion of some small deviations on the nodes, when solutions are attracted to a false state, results in additional enhancement of the performance of the associative-memory network. Supported by FAPESP - Sao Paulo Research Foundation, grant number 2012/12555-4

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.

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.

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

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

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.

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

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.

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

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

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

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.

Rhythmic Ganglion Cell Activity in Bleached and Blind Adult Mouse Retinas

PubMed Central

Menzler, Jacob; Channappa, Lakshmi; Zeck, Guenther

2014-01-01

In retinitis pigmentosa – a degenerative disease which often leads to incurable blindness- the loss of photoreceptors deprives the retina from a continuous excitatory input, the so-called dark current. In rodent models of this disease this deprivation leads to oscillatory electrical activity in the remaining circuitry, which is reflected in the rhythmic spiking of retinal ganglion cells (RGCs). It remained unclear, however, if the rhythmic RGC activity is attributed to circuit alterations occurring during photoreceptor degeneration or if rhythmic activity is an intrinsic property of healthy retinal circuitry which is masked by the photoreceptor’s dark current. Here we tested these hypotheses by inducing and analysing oscillatory activity in adult healthy (C57/Bl6) and blind mouse retinas (rd10 and rd1). Rhythmic RGC activity in healthy retinas was detected upon partial photoreceptor bleaching using an extracellular high-density multi-transistor-array. The mean fundamental spiking frequency in bleached retinas was 4.3 Hz; close to the RGC rhythm detected in blind rd10 mouse retinas (6.5 Hz). Crosscorrelation analysis of neighbouring wild-type and rd10 RGCs (separation distance <200 µm) reveals synchrony among homologous RGC types and a constant phase shift (∼70 msec) among heterologous cell types (ON versus OFF). The rhythmic RGC spiking in these retinas is driven by a network of presynaptic neurons. The inhibition of glutamatergic ganglion cell input or the inhibition of gap junctional coupling abolished the rhythmic pattern. In rd10 and rd1 retinas the presynaptic network leads to local field potentials, whereas in bleached retinas additional pharmacological disinhibition is required to achieve detectable field potentials. Our results demonstrate that photoreceptor bleaching unmasks oscillatory activity in healthy retinas which shares many features with the functional phenotype detected in rd10 retinas. The quantitative physiological differences advance the understanding of the degeneration process and may guide future rescue strategies. PMID:25153888

Rhythmic ganglion cell activity in bleached and blind adult mouse retinas.

PubMed

Menzler, Jacob; Channappa, Lakshmi; Zeck, Guenther

2014-01-01

In retinitis pigmentosa--a degenerative disease which often leads to incurable blindness--the loss of photoreceptors deprives the retina from a continuous excitatory input, the so-called dark current. In rodent models of this disease this deprivation leads to oscillatory electrical activity in the remaining circuitry, which is reflected in the rhythmic spiking of retinal ganglion cells (RGCs). It remained unclear, however, if the rhythmic RGC activity is attributed to circuit alterations occurring during photoreceptor degeneration or if rhythmic activity is an intrinsic property of healthy retinal circuitry which is masked by the photoreceptor's dark current. Here we tested these hypotheses by inducing and analysing oscillatory activity in adult healthy (C57/Bl6) and blind mouse retinas (rd10 and rd1). Rhythmic RGC activity in healthy retinas was detected upon partial photoreceptor bleaching using an extracellular high-density multi-transistor-array. The mean fundamental spiking frequency in bleached retinas was 4.3 Hz; close to the RGC rhythm detected in blind rd10 mouse retinas (6.5 Hz). Crosscorrelation analysis of neighbouring wild-type and rd10 RGCs (separation distance <200 µm) reveals synchrony among homologous RGC types and a constant phase shift (∼70 msec) among heterologous cell types (ON versus OFF). The rhythmic RGC spiking in these retinas is driven by a network of presynaptic neurons. The inhibition of glutamatergic ganglion cell input or the inhibition of gap junctional coupling abolished the rhythmic pattern. In rd10 and rd1 retinas the presynaptic network leads to local field potentials, whereas in bleached retinas additional pharmacological disinhibition is required to achieve detectable field potentials. Our results demonstrate that photoreceptor bleaching unmasks oscillatory activity in healthy retinas which shares many features with the functional phenotype detected in rd10 retinas. The quantitative physiological differences advance the understanding of the degeneration process and may guide future rescue strategies.

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.

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.

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.

The anterior and posterior pedunculopontine tegmental nucleus are involved in behavior and neuronal activity of the cuneiform and entopeduncular nuclei.

PubMed

Jin, X; Schwabe, K; Krauss, J K; Alam, M

2016-05-13

Loss of cholinergic neurons in the mesencephalic locomotor region, comprising the pedunculopontine nucleus (PPN) and the cuneiform nucleus (CnF), is related to gait disturbances in late stage Parkinson's disease (PD). We investigate the effect of anterior or posterior cholinergic lesions of the PPN on gait-related motor behavior, and on neuronal network activity of the PPN area and basal ganglia (BG) motor loop in rats. Anterior PPN lesions, posterior PPN lesions or sham lesions were induced by stereotaxic microinjection of the cholinergic toxin AF64-A or vehicle in male Sprague-Dawley rats. First, locomotor activity (open field), postural disturbances (Rotarod) and gait asymmetry (treadmill test) were assessed. Thereafter, single-unit and oscillatory activities were measured in the non-lesioned area of the PPN, the CnF and the entopeduncular nucleus (EPN), the BG output region, with microelectrodes under urethane anesthesia. Additionally, ECoG was recorded in the motor cortex. Injection of AF64-A into the anterior and posterior PPN decreased cholinergic cell counts as compared to naive controls (P<0.001) but also destroyed non-cholinergic cells. Only anterior PPN lesions decreased the front limb swing time of gait in the treadmill test, while not affecting other gait-related parameters tested. Main electrophysiological findings were that anterior PPN lesions increased the firing activity in the CnF (P<0.001). Further, lesions of either PPN region decreased the coherence of alpha (8-12 Hz) band between CnF and motor cortex (MCx), and increased the beta (12-30 Hz) oscillatory synchronization between EPN and the MCx. Lesions of the PPN in rats had complex effects on oscillatory neuronal activity of the CnF and the BG network, which may contribute to the understanding of the pathophysiology of gait disturbance in PD. Copyright © 2016 IBRO. Published by Elsevier Ltd. All rights reserved.

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.

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

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.

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.

Modulation of Beta-Band Activity in the Subgenual Anterior Cingulate Cortex during Emotional Empathy in Treatment-Resistant Depression.

PubMed

Merkl, Angela; Neumann, Wolf-Julian; Huebl, Julius; Aust, Sabine; Horn, Andreas; Krauss, Joachim K; Dziobek, Isabel; Kuhn, Jens; Schneider, Gerd-Helge; Bajbouj, Malek; Kühn, Andrea A

2016-06-01

Deep brain stimulation (DBS) is a promising approach in treatment-resistant depression (TRD). TRD is associated with problems in interpersonal relationships, which might be linked to impaired empathy. Here, we investigate the influence of DBS in the subgenual anterior cingulate cortex (sgACC) on empathy in patients with TRD and explore the pattern of oscillatory sgACC activity during performance of the multifaceted empathy test. We recorded local field potential activity directly from sgACC via DBS electrodes in patients. Based on previous behavioral findings, we expected disrupted empathy networks. Patients showed increased empathic involvement ratings toward negative stimuli as compared with healthy subjects that were significantly reduced after 6 months of DBS. Stimulus-related oscillatory activity pattern revealed a broad desynchronization in the beta (14-35 Hz) band that was significantly larger during patients' reported emotional empathy for negative stimuli than when patients reported to have no empathy. Beta desynchronization for empathic involvement correlated with self-reported severity of depression. Our results indicate a "negativity bias" in patients that can be reduced by DBS. Moreover, direct recordings show activation of the sgACC area during emotional processing and propose that changes in beta-band oscillatory activity in the sgACC might index empathic involvement of negative emotion in TRD. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

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.

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

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.

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.

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.

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

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.

Large-scale cortical correlation structure of spontaneous oscillatory activity

PubMed Central

Hipp, Joerg F.; Hawellek, David J.; Corbetta, Maurizio; Siegel, Markus; Engel, Andreas K.

2013-01-01

Little is known about the brain-wide correlation of electrophysiological signals. Here we show that spontaneous oscillatory neuronal activity exhibits frequency-specific spatial correlation structure in the human brain. We developed an analysis approach that discounts spurious correlation of signal power caused by the limited spatial resolution of electrophysiological measures. We applied this approach to source estimates of spontaneous neuronal activity reconstructed from magnetoencephalography (MEG). Overall, correlation of power across cortical regions was strongest in the alpha to beta frequency range (8–32 Hz) and correlation patterns depended on the underlying oscillation frequency. Global hubs resided in the medial temporal lobe in the theta frequency range (4–6 Hz), in lateral parietal areas in the alpha to beta frequency range (8–23 Hz), and in sensorimotor areas for higher frequencies (32–45 Hz). Our data suggest that interactions in various large-scale cortical networks may be reflected in frequency specific power-envelope correlations. PMID:22561454

Human gamma-frequency oscillations associated with attention and memory.

PubMed

Jensen, Ole; Kaiser, Jochen; Lachaux, Jean-Philippe

2007-07-01

Both theoretical and experimental animal work supports the hypothesis that transient oscillatory synchronization of neuronal assemblies at gamma frequencies (30-100 Hz) is closely associated with sensory processing. Recent data from recordings in animals and humans have suggested that gamma-frequency activity also has an important role in attention and both working and long-term memory. The involvement of gamma-band synchronization in various cognitive paradigms in humans is currently being investigated using intracranial and high-density electro- and magnetoencephalography recordings. Here, we discuss recent findings demonstrating human gamma-frequency activity associated with attention and memory in both sensory and non-sensory areas. Because oscillatory gamma-frequency activity has an important role in neuronal communication and synaptic plasticity, it could provide a key for understanding neuronal processing in both local and distributed cortical networks engaged in complex cognitive functions. 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).

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.

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.

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.

Speed and segmentation control mechanisms characterized in rhythmically-active circuits created from spinal neurons produced from genetically-tagged embryonic stem cells

PubMed Central

Sternfeld, Matthew J; Hinckley, Christopher A; Moore, Niall J; Pankratz, Matthew T; Hilde, Kathryn L; Driscoll, Shawn P; Hayashi, Marito; Amin, Neal D; Bonanomi, Dario; Gifford, Wesley D; Sharma, Kamal; Goulding, Martyn; Pfaff, Samuel L

2017-01-01

Flexible neural networks, such as the interconnected spinal neurons that control distinct motor actions, can switch their activity to produce different behaviors. Both excitatory (E) and inhibitory (I) spinal neurons are necessary for motor behavior, but the influence of recruiting different ratios of E-to-I cells remains unclear. We constructed synthetic microphysical neural networks, called circuitoids, using precise combinations of spinal neuron subtypes derived from mouse stem cells. Circuitoids of purified excitatory interneurons were sufficient to generate oscillatory bursts with properties similar to in vivo central pattern generators. Inhibitory V1 neurons provided dual layers of regulation within excitatory rhythmogenic networks - they increased the rhythmic burst frequency of excitatory V3 neurons, and segmented excitatory motor neuron activity into sub-networks. Accordingly, the speed and pattern of spinal circuits that underlie complex motor behaviors may be regulated by quantitatively gating the intra-network cellular activity ratio of E-to-I neurons. DOI: http://dx.doi.org/10.7554/eLife.21540.001 PMID:28195039

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

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

Synchronicity and Rhythmicity of Purkinje Cell Firing during Generalized Spike-and-Wave Discharges in a Natural Mouse Model of Absence Epilepsy

PubMed Central

Kros, Lieke; Lindeman, Sander; Eelkman Rooda, Oscar H. J.; Murugesan, Pavithra; Bina, Lorenzo; Bosman, Laurens W. J.; De Zeeuw, Chris I.; Hoebeek, Freek E.

2017-01-01

Absence epilepsy is characterized by the occurrence of generalized spike and wave discharges (GSWDs) in electrocorticographical (ECoG) recordings representing oscillatory activity in thalamocortical networks. The oscillatory nature of GSWDs has been shown to be reflected in the simple spike activity of cerebellar Purkinje cells and in the activity of their target neurons in the cerebellar nuclei, but it is unclear to what extent complex spike activity is implicated in generalized epilepsy. Purkinje cell complex spike firing is elicited by climbing fiber activation and reflects action potential firing in the inferior olive. Here, we investigated to what extent modulation of complex spike firing is reflected in the temporal patterns of seizures. Extracellular single-unit recordings in awake, head-restrained homozygous tottering mice, which suffer from a mutation in the voltage-gated CaV2.1 calcium channel, revealed that a substantial proportion of Purkinje cells (26%) showed increased complex spike activity and rhythmicity during GSWDs. Moreover, Purkinje cells, recorded either electrophysiologically or by using Ca2+-imaging, showed a significant increase in complex spike synchronicity for both adjacent and remote Purkinje cells during ictal events. These seizure-related changes in firing frequency, rhythmicity and synchronicity were most prominent in the lateral cerebellum, a region known to receive cerebral input via the inferior olive. These data indicate profound and widespread changes in olivary firing that are most likely induced by seizure-related activity changes in the thalamocortical network, thereby highlighting the possibility that olivary neurons can compensate for pathological brain-state changes by dampening oscillations. PMID:29163057

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.

Using Dual Regression to Investigate Network Shape and Amplitude in Functional Connectivity Analyses

PubMed Central

Nickerson, Lisa D.; Smith, Stephen M.; Öngür, Döst; Beckmann, Christian F.

2017-01-01

Independent Component Analysis (ICA) is one of the most popular techniques for the analysis of resting state FMRI data because it has several advantageous properties when compared with other techniques. Most notably, in contrast to a conventional seed-based correlation analysis, it is model-free and multivariate, thus switching the focus from evaluating the functional connectivity of single brain regions identified a priori to evaluating brain connectivity in terms of all brain resting state networks (RSNs) that simultaneously engage in oscillatory activity. Furthermore, typical seed-based analysis characterizes RSNs in terms of spatially distributed patterns of correlation (typically by means of simple Pearson's coefficients) and thereby confounds together amplitude information of oscillatory activity and noise. ICA and other regression techniques, on the other hand, retain magnitude information and therefore can be sensitive to both changes in the spatially distributed nature of correlations (differences in the spatial pattern or “shape”) as well as the amplitude of the network activity. Furthermore, motion can mimic amplitude effects so it is crucial to use a technique that retains such information to ensure that connectivity differences are accurately localized. In this work, we investigate the dual regression approach that is frequently applied with group ICA to assess group differences in resting state functional connectivity of brain networks. We show how ignoring amplitude effects and how excessive motion corrupts connectivity maps and results in spurious connectivity differences. We also show how to implement the dual regression to retain amplitude information and how to use dual regression outputs to identify potential motion effects. Two key findings are that using a technique that retains magnitude information, e.g., dual regression, and using strict motion criteria are crucial for controlling both network amplitude and motion-related amplitude effects, respectively, in resting state connectivity analyses. We illustrate these concepts using realistic simulated resting state FMRI data and in vivo data acquired in healthy subjects and patients with bipolar disorder and schizophrenia. PMID:28348512

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

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

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

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.

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.

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

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

A biophysical model of the cortex-basal ganglia-thalamus network in the 6-OHDA lesioned rat model of Parkinson's disease.

PubMed

Kumaravelu, Karthik; Brocker, David T; Grill, Warren M

2016-04-01

Electrical stimulation of sub-cortical brain regions (the basal ganglia), known as deep brain stimulation (DBS), is an effective treatment for Parkinson's disease (PD). Chronic high frequency (HF) DBS in the subthalamic nucleus (STN) or globus pallidus interna (GPi) reduces motor symptoms including bradykinesia and tremor in patients with PD, but the therapeutic mechanisms of DBS are not fully understood. We developed a biophysical network model comprising of the closed loop cortical-basal ganglia-thalamus circuit representing the healthy and parkinsonian rat brain. The network properties of the model were validated by comparing responses evoked in basal ganglia (BG) nuclei by cortical (CTX) stimulation to published experimental results. A key emergent property of the model was generation of low-frequency network oscillations. Consistent with their putative pathological role, low-frequency oscillations in model BG neurons were exaggerated in the parkinsonian state compared to the healthy condition. We used the model to quantify the effectiveness of STN DBS at different frequencies in suppressing low-frequency oscillatory activity in GPi. Frequencies less than 40 Hz were ineffective, low-frequency oscillatory power decreased gradually for frequencies between 50 Hz and 130 Hz, and saturated at frequencies higher than 150 Hz. HF STN DBS suppressed pathological oscillations in GPe/GPi both by exciting and inhibiting the firing in GPe/GPi neurons, and the number of GPe/GPi neurons influenced was greater for HF stimulation than low-frequency stimulation. Similar to the frequency dependent suppression of pathological oscillations, STN DBS also normalized the abnormal GPi spiking activity evoked by CTX stimulation in a frequency dependent fashion with HF being the most effective. Therefore, therapeutic HF STN DBS effectively suppresses pathological activity by influencing the activity of a greater proportion of neurons in the output nucleus of the BG.

Opto-current-clamp actuation of cortical neurons using a strategically designed channelrhodopsin.

PubMed

Wen, Lei; Wang, Hongxia; Tanimoto, Saki; Egawa, Ryo; Matsuzaka, Yoshiya; Mushiake, Hajime; Ishizuka, Toru; Yawo, Hiromu

2010-09-23

Optogenetic manipulation of a neuronal network enables one to reveal how high-order functions emerge in the central nervous system. One of the Chlamydomonas rhodopsins, channelrhodopsin-1 (ChR1), has several advantages over channelrhodopsin-2 (ChR2) in terms of the photocurrent kinetics. Improved temporal resolution would be expected by the optogenetics using the ChR1 variants with enhanced photocurrents. The photocurrent retardation of ChR1 was overcome by exchanging the sixth helix domain with its counterpart in ChR2 producing Channelrhodopsin-green receiver (ChRGR) with further reform of the molecule. When the ChRGR photocurrent was measured from the expressing HEK293 cells under whole-cell patch clamp, it was preferentially activated by green light and has fast kinetics with minimal desensitization. With its kinetic advantages the use of ChRGR would enable one to inject a current into a neuron by the time course as predicted by the intensity of the shedding light (opto-current clamp). The ChRGR was also expressed in the motor cortical neurons of a mouse using Sindbis pseudovirion vectors. When an oscillatory LED light signal was applied sweeping through frequencies, it robustly evoked action potentials synchronized to the oscillatory light at 5-10 Hz in layer 5 pyramidal cells in the cortical slice. The ChRGR-expressing neurons were also driven in vivo with monitoring local field potentials (LFPs) and the time-frequency energy distribution of the light-evoked response was investigated using wavelet analysis. The oscillatory light enhanced both the in-phase and out-phase responses of LFP at the preferential frequencies of 5-10 Hz. The spread of activity was evidenced by the fact that there were many c-Fos-immunoreactive neurons that were negative for ChRGR in a region of the motor cortex. The opto-current-clamp study suggests that the depolarization of a small number of neurons wakes up the motor cortical network over some critical point to the activated state.

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.

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

The brain's resting-state activity is shaped by synchronized cross-frequency coupling of neural oscillations

PubMed Central

Florin, Esther; Baillet, Sylvain

2015-01-01

Functional imaging of the resting brain consistently reveals broad motifs of correlated blood oxygen level dependent (BOLD) activity that engage cerebral regions from distinct functional systems. Yet, the neurophysiological processes underlying these organized, large-scale fluctuations remain to be uncovered. Using magnetoencephalography (MEG) imaging during rest in 12 healthy subjects we analyse the resting state networks and their underlying neurophysiology. We first demonstrate non-invasively that cortical occurrences of high-frequency oscillatory activity are conditioned to the phase of slower spontaneous fluctuations in neural ensembles. We further show that resting-state networks emerge from synchronized phase-amplitude coupling across the brain. Overall, these findings suggest a unified principle of local-to-global neural signaling for long-range brain communication. PMID:25680519

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.

Cardiac and respiratory patterns synchronize between persons during choir singing.

PubMed

Müller, Viktor; Lindenberger, Ulman

2011-01-01

Dyadic and collective activities requiring temporally coordinated action are likely to be associated with cardiac and respiratory patterns that synchronize within and between people. However, the extent and functional significance of cardiac and respiratory between-person couplings have not been investigated thus far. Here, we report interpersonal oscillatory couplings among eleven singers and one conductor engaged in choir singing. We find that: (a) phase synchronization both in respiration and heart rate variability increase significantly during singing relative to a rest condition; (b) phase synchronization is higher when singing in unison than when singing pieces with multiple voice parts; (c) directed coupling measures are consistent with the presence of causal effects of the conductor on the singers at high modulation frequencies; (d) the different voices of the choir are reflected in network analyses of cardiac and respiratory activity based on graph theory. Our results suggest that oscillatory coupling of cardiac and respiratory patterns provide a physiological basis for interpersonal action coordination.

Cardiac and Respiratory Patterns Synchronize between Persons during Choir Singing

PubMed Central

Müller, Viktor; Lindenberger, Ulman

2011-01-01

Dyadic and collective activities requiring temporally coordinated action are likely to be associated with cardiac and respiratory patterns that synchronize within and between people. However, the extent and functional significance of cardiac and respiratory between-person couplings have not been investigated thus far. Here, we report interpersonal oscillatory couplings among eleven singers and one conductor engaged in choir singing. We find that: (a) phase synchronization both in respiration and heart rate variability increase significantly during singing relative to a rest condition; (b) phase synchronization is higher when singing in unison than when singing pieces with multiple voice parts; (c) directed coupling measures are consistent with the presence of causal effects of the conductor on the singers at high modulation frequencies; (d) the different voices of the choir are reflected in network analyses of cardiac and respiratory activity based on graph theory. Our results suggest that oscillatory coupling of cardiac and respiratory patterns provide a physiological basis for interpersonal action coordination. PMID:21957466

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

PubMed

Oliva, Carolina A; Inestrosa, Nibaldo C

2015-07-01

During early and late postnatal developments, the establishment of functional neuronal connectivity depends on molecules like Wnt that help the recently formed synapses to establish and consolidate their new cellular interactions. However, unlike other molecules, whether Wnt can modulate the firing properties of cells is unknown. Here, for the first time we explore the physiological effect of the canonical and non-canonical Wnt pathways on a circuit that is currently generating oscillatory activity, the entorhinal cortex-hippocampal circuit. Our results indicate that Wnt pathways have strong influence in the circuital and cellular properties depending on the Wnt protein isoforms, concentration, and type of neuronal circuit. Antibodies against canonical and non-canonical ligands, as well as WASP-1 and sFRP-2, demonstrate that constitutive release of Wnts contributes to the maintenance of the network and intrinsic properties of the circuit. Furthermore, we found that the excess of Wnt3a or the permanent intracellular activation of the pathway with BIO-6 accelerates the period of the oscillation by disrupting the oscillatory units (Up states) in short units, presumably by affecting the synaptic mechanisms that couples neurons into the oscillatory cycle, but without affecting the spike generation. Instead, low doses of Wnt5a increase the period of the oscillation in EC by incorporating new cells into the network activity, probably modifying firing activity in other places of the circuit. Moreover, we found that Wnt signaling operates under different principles in the hippocampus. Using pyrvinium pamoate, a Wnt/β-catenin dependent pathway inhibitor, we demonstrated that this pathway is essential to keep the firing activity in the circuit CA3, and in less degree of CA1 circuit. However, CA1 circuit possesses homeostatic mechanisms to up-regulate the firing activity when it has been suppressed in CA3, and to down-modulate the cellular excitability when exacerbated circuital activity has dominated. In summary, the amount of Wnt that is being released can exert a fine tuning of the physiological output, modulating firing activity, improving reliability of communication between neurons, and maintaining a continuous self-regulatory cycle of synaptic structure-function that can be present during all postnatal life. Copyright © 2015 Elsevier Inc. All rights reserved.

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.

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.

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.

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.

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

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.

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

Psychoacoustic Tinnitus Loudness and Tinnitus-Related Distress Show Different Associations with Oscillatory Brain Activity

PubMed Central

Balkenhol, Tobias; Wallhäusser-Franke, Elisabeth; Delb, Wolfgang

2013-01-01

Background The phantom auditory perception of subjective tinnitus is associated with aberrant brain activity as evidenced by magneto- and electroencephalographic studies. We tested the hypotheses (1) that psychoacoustically measured tinnitus loudness is related to gamma oscillatory band power, and (2) that tinnitus loudness and tinnitus-related distress are related to distinct brain activity patterns as suggested by the distinction between loudness and distress experienced by tinnitus patients. Furthermore, we explored (3) how hearing impairment, minimum masking level, and (4) psychological comorbidities are related to spontaneous oscillatory brain activity in tinnitus patients. Methods and Findings Resting state oscillatory brain activity recorded electroencephalographically from 46 male tinnitus patients showed a positive correlation between gamma band oscillations and psychoacoustic tinnitus loudness determined with the reconstructed tinnitus sound, but not with the other psychoacoustic loudness measures that were used. Tinnitus-related distress did also correlate with delta band activity, but at electrode positions different from those associated with tinnitus loudness. Furthermore, highly distressed tinnitus patients exhibited a higher level of theta band activity. Moreover, mean hearing loss between 0.125 kHz and 16 kHz was associated with a decrease in gamma activity, whereas minimum masking levels correlated positively with delta band power. In contrast, psychological comorbidities did not express significant correlations with oscillatory brain activity. Conclusion Different clinically relevant tinnitus characteristics show distinctive associations with spontaneous brain oscillatory power. Results support hypothesis (1), but exclusively for the tinnitus loudness derived from matching to the reconstructed tinnitus sound. This suggests to preferably use the reconstructed tinnitus spectrum to determine psychoacoustic tinnitus loudness. Results also support hypothesis (2). Moreover, hearing loss and minimum masking level correlate with oscillatory power in distinctive frequency bands. The lack of an association between psychological comorbidities and oscillatory power may be attributed to the overall low level of mental health problems in the present sample. PMID:23326394

Mild traumatic brain injury: graph-model characterization of brain networks for episodic memory.

PubMed

Tsirka, Vasso; Simos, Panagiotis G; Vakis, Antonios; Kanatsouli, Kassiani; Vourkas, Michael; Erimaki, Sofia; Pachou, Ellie; Stam, Cornelis Jan; Micheloyannis, Sifis

2011-02-01

Episodic memory is among the cognitive functions that can be affected in the acute phase following mild traumatic brain injury (MTBI). The present study used EEG recordings to evaluate global synchronization and network organization of rhythmic activity during the encoding and recognition phases of an episodic memory task varying in stimulus type (kaleidoscope images, pictures, words, and pseudowords). Synchronization of oscillatory activity was assessed using a linear and nonlinear connectivity estimator and network analyses were performed using algorithms derived from graph theory. Twenty five MTBI patients (tested within days post-injury) and healthy volunteers were closely matched on demographic variables, verbal ability, psychological status variables, as well as on overall task performance. Patients demonstrated sub-optimal network organization, as reflected by changes in graph parameters in the theta and alpha bands during both encoding and recognition. There were no group differences in spectral energy during task performance or on network parameters during a control condition (rest). Evidence of less optimally organized functional networks during memory tasks was more prominent for pictorial than for verbal stimuli. Copyright © 2010 Elsevier B.V. All rights reserved.

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.

Impaired brainstem and thalamic high-frequency oscillatory EEG activity in migraine between attacks.

PubMed

Porcaro, Camillo; Di Lorenzo, Giorgio; Seri, Stefano; Pierelli, Francesco; Tecchio, Franca; Coppola, Gianluca

2017-09-01

Introduction We investigated whether interictal thalamic dysfunction in migraine without aura (MO) patients is a primary determinant or the expression of its functional disconnection from proximal or distal areas along the somatosensory pathway. Methods Twenty MO patients and twenty healthy volunteers (HVs) underwent an electroencephalographic (EEG) recording during electrical stimulation of the median nerve at the wrist. We used the functional source separation algorithm to extract four functionally constrained nodes (brainstem, thalamus, primary sensory radial, and primary sensory motor tangential parietal sources) along the somatosensory pathway. Two digital filters (1-400 Hz and 450-750 Hz) were applied in order to extract low- (LFO) and high- frequency (HFO) oscillatory activity from the broadband signal. Results Compared to HVs, patients presented significantly lower brainstem (BS) and thalamic (Th) HFO activation bilaterally. No difference between the two cortical HFO as well as in LFO peak activations between the two groups was seen. The age of onset of the headache was positively correlated with HFO power in the right brainstem and thalamus. Conclusions This study provides evidence for complex dysfunction of brainstem and thalamocortical networks under the control of genetic factors that might act by modulating the severity of migraine phenotype.

Aberrant Modulation of Brain Oscillatory Activity and Attentional Impairment in Attention-Deficit/Hyperactivity Disorder.

PubMed

Lenartowicz, Agatha; Mazaheri, Ali; Jensen, Ole; Loo, Sandra K

2018-01-01

Electroencephalography and magnetoencephalography are noninvasive neuroimaging techniques that have been used extensively to study various resting-state and cognitive processes in the brain. The purpose of this review is to highlight a number of recent studies that have investigated the alpha band (8-12 Hz) oscillatory activity present in magnetoencephalography and electroencephalography, to provide new insights into the maladaptive network activity underlying attentional impairments in attention-deficit/hyperactivity disorder (ADHD). Studies reviewed demonstrate that event-related decrease in alpha is attenuated during visual selective attention, primarily in ADHD inattentive type, and is often significantly associated with accuracy and reaction time during task performance. Furthermore, aberrant modulation of alpha activity has been reported across development and may have abnormal or atypical lateralization patterns in ADHD. Modulations in the alpha band thus represent a robust, relatively unexplored putative biomarker of attentional impairment and a strong prospect for future studies aimed at examining underlying neural mechanisms and treatment response among individuals with ADHD. Potential limitations of its use as a diagnostic biomarker and directions for future research are discussed. Copyright © 2017 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Neuronal plasticity and thalamocortical sleep and waking oscillations

PubMed Central

Timofeev, Igor

2011-01-01

Throughout life, thalamocortical (TC) network alternates between activated states (wake or rapid eye movement sleep) and slow oscillatory state dominating slow-wave sleep. The patterns of neuronal firing are different during these distinct states. I propose that due to relatively regular firing, the activated states preset some steady state synaptic plasticity and that the silent periods of slow-wave sleep contribute to a release from this steady state synaptic plasticity. In this respect, I discuss how states of vigilance affect short-, mid-, and long-term synaptic plasticity, intrinsic neuronal plasticity, as well as homeostatic plasticity. Finally, I suggest that slow oscillation is intrinsic property of cortical network and brain homeostatic mechanisms are tuned to use all forms of plasticity to bring cortical network to the state of slow oscillation. However, prolonged and profound shift from this homeostatic balance could lead to development of paroxysmal hyperexcitability and seizures as in the case of brain trauma. PMID:21854960

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.

Oscillatory serotonin function in depression.

PubMed

Salomon, Ronald M; Cowan, Ronald L

2013-11-01

Oscillations in brain activities with periods of minutes to hours may be critical for normal mood behaviors. Ultradian (faster than circadian) rhythms of mood behaviors and associated central nervous system activities are altered in depression. Recent data suggest that ultradian rhythms in serotonin (5HT) function also change in depression. In two separate studies, 5HT metabolites in cerebrospinal fluid (CSF) were measured every 10 min for 24 h before and after chronic antidepressant treatment. Antidepressant treatments were associated with enhanced ultradian amplitudes of CSF metabolite levels. Another study used resting-state functional magnetic resonance imaging (fMRI) to measure amplitudes of dorsal raphé activation cycles following sham or active dietary depletions of the 5HT precursor (tryptophan). During depletion, amplitudes of dorsal raphé activation cycles increased with rapid 6 s periods (about 0.18 Hz) while functional connectivity weakened between dorsal raphé and thalamus at slower periods of 20 s (0.05 Hz). A third approach studied MDMA (ecstasy, 3,4-methylenedioxy-N-methylamphetamine) users because of their chronically diminished 5HT function compared with non-MDMA polysubstance users (Karageorgiou et al., 2009). Compared with a non-MDMA using cohort, MDMA users showed diminished fMRI intra-regional coherence in motor regions along with altered functional connectivity, again suggesting effects of altered 5HT oscillatory function. These data support a hypothesis that qualities of ultradian oscillations in 5HT function may critically influence moods and behaviors. Dysfunctional 5HT rhythms in depression may be a common endpoint and biomarker for depression, linking dysfunction of slow brain network oscillators to 5HT mechanisms affected by commonly available treatments. 5HT oscillatory dysfunction may define illness subtypes and predict responses to serotonergic agents. Further studies of 5HT oscillations in depression are indicated. Copyright © 2013 Wiley Periodicals, Inc.

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

Emergence of β-Band Oscillations in the Aged Rat Amygdala during Discrimination Learning and Decision Making Tasks

PubMed Central

Samson, Rachel D.; Duarte, Leroy; Venkatesh, Anu

2017-01-01

Abstract Older adults tend to use strategies that differ from those used by young adults to solve decision-making tasks. MRI experiments suggest that altered strategy use during aging can be accompanied by a change in extent of activation of a given brain region, inter-hemispheric bilateralization or added brain structures. It has been suggested that these changes reflect compensation for less effective networks to enable optimal performance. One way that communication can be influenced within and between brain networks is through oscillatory events that help structure and synchronize incoming and outgoing information. It is unknown how aging impacts local oscillatory activity within the basolateral complex of the amygdala (BLA). The present study recorded local field potentials (LFPs) and single units in old and young rats during the performance of tasks that involve discrimination learning and probabilistic decision making. We found task- and age-specific increases in power selectively within the β range (15–30 Hz). The increased β power occurred after lever presses, as old animals reached the goal location. Periods of high-power β developed over training days in the aged rats, and was greatest in early trials of a session. β Power was also greater after pressing for the large reward option. These data suggest that aging of BLA networks results in strengthened synchrony of β oscillations when older animals are learning or deciding between rewards of different size. Whether this increased synchrony reflects the neural basis of a compensatory strategy change of old animals in reward-based decision-making tasks, remains to be verified. PMID:29034315

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.

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.

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

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).

Development and function of human cerebral cortex neural networks from pluripotent stem cells in vitro

PubMed Central

Kirwan, Peter; Turner-Bridger, Benita; Peter, Manuel; Momoh, Ayiba; Arambepola, Devika; Robinson, Hugh P. C.; Livesey, Frederick J.

2015-01-01

A key aspect of nervous system development, including that of the cerebral cortex, is the formation of higher-order neural networks. Developing neural networks undergo several phases with distinct activity patterns in vivo, which are thought to prune and fine-tune network connectivity. We report here that human pluripotent stem cell (hPSC)-derived cerebral cortex neurons form large-scale networks that reflect those found in the developing cerebral cortex in vivo. Synchronised oscillatory networks develop in a highly stereotyped pattern over several weeks in culture. An initial phase of increasing frequency of oscillations is followed by a phase of decreasing frequency, before giving rise to non-synchronous, ordered activity patterns. hPSC-derived cortical neural networks are excitatory, driven by activation of AMPA- and NMDA-type glutamate receptors, and can undergo NMDA-receptor-mediated plasticity. Investigating single neuron connectivity within PSC-derived cultures, using rabies-based trans-synaptic tracing, we found two broad classes of neuronal connectivity: most neurons have small numbers (<10) of presynaptic inputs, whereas a small set of hub-like neurons have large numbers of synaptic connections (>40). These data demonstrate that the formation of hPSC-derived cortical networks mimics in vivo cortical network development and function, demonstrating the utility of in vitro systems for mechanistic studies of human forebrain neural network biology. PMID:26395144

Development and function of human cerebral cortex neural networks from pluripotent stem cells in vitro.

PubMed

Kirwan, Peter; Turner-Bridger, Benita; Peter, Manuel; Momoh, Ayiba; Arambepola, Devika; Robinson, Hugh P C; Livesey, Frederick J

2015-09-15

A key aspect of nervous system development, including that of the cerebral cortex, is the formation of higher-order neural networks. Developing neural networks undergo several phases with distinct activity patterns in vivo, which are thought to prune and fine-tune network connectivity. We report here that human pluripotent stem cell (hPSC)-derived cerebral cortex neurons form large-scale networks that reflect those found in the developing cerebral cortex in vivo. Synchronised oscillatory networks develop in a highly stereotyped pattern over several weeks in culture. An initial phase of increasing frequency of oscillations is followed by a phase of decreasing frequency, before giving rise to non-synchronous, ordered activity patterns. hPSC-derived cortical neural networks are excitatory, driven by activation of AMPA- and NMDA-type glutamate receptors, and can undergo NMDA-receptor-mediated plasticity. Investigating single neuron connectivity within PSC-derived cultures, using rabies-based trans-synaptic tracing, we found two broad classes of neuronal connectivity: most neurons have small numbers (<10) of presynaptic inputs, whereas a small set of hub-like neurons have large numbers of synaptic connections (>40). These data demonstrate that the formation of hPSC-derived cortical networks mimics in vivo cortical network development and function, demonstrating the utility of in vitro systems for mechanistic studies of human forebrain neural network biology. © 2015. Published by The Company of Biologists Ltd.

Experience-dependent emergence of beta and gamma band oscillations in the primary visual cortex during the critical period

PubMed Central

Chen, Guang; Rasch, Malte J.; Wang, Ran; Zhang, Xiao-hui

2015-01-01

Neural oscillatory activities have been shown to play important roles in neural information processing and the shaping of circuit connections during development. However, it remains unknown whether and how specific neural oscillations emerge during a postnatal critical period (CP), in which neuronal connections are most substantially modified by neural activity and experience. By recording local field potentials (LFPs) and single unit activity in developing primary visual cortex (V1) of head-fixed awake mice, we here demonstrate an emergence of characteristic oscillatory activities during the CP. From the pre-CP to CP, the peak frequency of spontaneous fast oscillatory activities shifts from the beta band (15–35 Hz) to the gamma band (40–70 Hz), accompanied by a decrease of cross-frequency coupling (CFC) and broadband spike-field coherence (SFC). Moreover, visual stimulation induced a large increase of beta-band activity but a reduction of gamma-band activity specifically from the CP onwards. Dark rearing of animals from the birth delayed this emergence of oscillatory activities during the CP, suggesting its dependence on early visual experience. These findings suggest that the characteristic neuronal oscillatory activities emerged specifically during the CP may represent as neural activity trait markers for the experience-dependent maturation of developing visual cortical circuits. PMID:26648548

Understanding action language modulates oscillatory mu and beta rhythms in the same way as observing actions.

PubMed

Moreno, Iván; de Vega, Manuel; León, Inmaculada

2013-08-01

The mu rhythms (8-13 Hz) and the beta rhythms (15 up to 30 Hz) of the EEG are observed in the central electrodes (C3, Cz and C4) in resting states, and become suppressed when participants perform a manual action or when they observe another's action. This has led researchers to consider that these rhythms are electrophysiological markers of the motor neuron activity in humans. This study tested whether the comprehension of action language, unlike abstract language, modulates mu and low beta rhythms (15-20 Hz) in a similar way as the observation of real actions. The log-ratios were calculated for each oscillatory band between each condition and baseline resting periods. The results indicated that both action language and action videos caused mu and beta suppression (negative log-ratios), whereas abstract language did not, confirming the hypothesis that understanding action language activates motor networks in the brain. In other words, the resonance of motor areas associated with action language is compatible with the embodiment approach to linguistic meaning. Copyright © 2013 Elsevier Inc. All rights reserved.

Synchronization Dynamics of Coupled Chemical Oscillators

NASA Astrophysics Data System (ADS)

Tompkins, Nathan

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

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.

Brain reflections: A circuit-based framework for understanding information processing and cognitive control.

PubMed

Gratton, Gabriele

2018-03-01

Here, I propose a view of the architecture of the human information processing system, and of how it can be adapted to changing task demands (which is the hallmark of cognitive control). This view is informed by an interpretation of brain activity as reflecting the excitability level of neural representations, encoding not only stimuli and temporal contexts, but also action plans and task goals. The proposed cognitive architecture includes three types of circuits: open circuits, involved in feed-forward processing such as that connecting stimuli with responses and characterized by brief, transient brain activity; and two types of closed circuits, positive feedback circuits (characterized by sustained, high-frequency oscillatory activity), which help select and maintain representations, and negative feedback circuits (characterized by brief, low-frequency oscillatory bursts), which are instead associated with changes in representations. Feed-forward activity is primarily responsible for the spread of activation along the information processing system. Oscillatory activity, instead, controls this spread. Sustained oscillatory activity due to both local cortical circuits (gamma) and longer corticothalamic circuits (alpha and beta) allows for the selection of individuated representations. Through the interaction of these circuits, it also allows for the preservation of representations across different temporal spans (sensory and working memory) and their spread across the brain. In contrast, brief bursts of oscillatory activity, generated by novel and/or conflicting information, lead to the interruption of sustained oscillatory activity and promote the generation of new representations. I discuss how this framework can account for a number of psychological and behavioral phenomena. © 2017 Society for Psychophysiological Research.

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.

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

PubMed

Ekstrom, Arne D; Watrous, Andrew J

2014-01-15

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

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

PubMed Central

Ekstrom, Arne D.; Watrous, Andrew J.

2014-01-01

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

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.

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.

Brain oscillatory subsequent memory effects differ in power and long-range synchronization between semantic and survival processing.

PubMed

Fellner, Marie-Christin; Bäuml, Karl-Heinz T; Hanslmayr, Simon

2013-10-01

Memory crucially depends on the way information is processed during encoding. Differences in processes during encoding not only lead to differences in memory performance but also rely on different brain networks. Although these assumptions are corroborated by several previous fMRI and ERP studies, little is known about how brain oscillations dissociate between different memory encoding tasks. The present study therefore compared encoding related brain oscillatory activity elicited by two very efficient encoding tasks: a typical deep semantic item feature judgment task and a more elaborative survival encoding task. Subjects were asked to judge words either for survival relevance or for animacy, as indicated by a cue presented prior to the item. This allowed dissociating pre-item activity from item-related activity for both tasks. Replicating prior studies, survival processing led to higher recognition performance than semantic processing. Successful encoding in the semantic condition was reflected by a strong decrease in alpha and beta power, whereas successful encoding in the survival condition was related to increased alpha and beta long-range phase synchrony. Moreover, a pre-item subsequent memory effect in theta power was found which did not vary with encoding condition. These results show that measures of local synchrony (power) and global long range-synchrony (phase synchronization) dissociate between memory encoding processes. Whereas semantic encoding was reflected in decreases in local synchrony, increases in global long range synchrony were related to elaborative survival encoding, presumably reflecting the involvement of a more widespread cortical network in this task. Copyright © 2013 Elsevier Inc. All rights reserved.

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.

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.

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

NASA Astrophysics Data System (ADS)

Wang, DeLiang; Terman, David

1995-01-01

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

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.

Oscillatory Correlates of Visual Consciousness

PubMed Central

Gallotto, Stefano; Sack, Alexander T.; Schuhmann, Teresa; de Graaf, Tom A.

2017-01-01

Conscious experiences are linked to activity in our brain: the neural correlates of consciousness (NCC). Empirical research on these NCCs covers a wide range of brain activity signals, measures, and methodologies. In this paper, we focus on spontaneous brain oscillations; rhythmic fluctuations of neuronal (population) activity which can be characterized by a range of parameters, such as frequency, amplitude (power), and phase. We provide an overview of oscillatory measures that appear to correlate with conscious perception. We also discuss how increasingly sophisticated techniques allow us to study the causal role of oscillatory activity in conscious perception (i.e., ‘entrainment’). This review of oscillatory correlates of consciousness suggests that, for example, activity in the alpha-band (7–13 Hz) may index, or even causally support, conscious perception. But such results also showcase an increasingly acknowledged difficulty in NCC research; the challenge of separating neural activity necessary for conscious experience to arise (prerequisites) from neural activity underlying the conscious experience itself (substrates) or its results (consequences). PMID:28736543

Oscillatory Protein Expression Dynamics Endows Stem Cells with Robust Differentiation Potential

PubMed Central

Kaneko, Kunihiko

2011-01-01

The lack of understanding of stem cell differentiation and proliferation is a fundamental problem in developmental biology. Although gene regulatory networks (GRNs) for stem cell differentiation have been partially identified, the nature of differentiation dynamics and their regulation leading to robust development remain unclear. Herein, using a dynamical system modeling cell approach, we performed simulations of the developmental process using all possible GRNs with a few genes, and screened GRNs that could generate cell type diversity through cell-cell interactions. We found that model stem cells that both proliferated and differentiated always exhibited oscillatory expression dynamics, and the differentiation frequency of such stem cells was regulated, resulting in a robust number distribution. Moreover, we uncovered the common regulatory motifs for stem cell differentiation, in which a combination of regulatory motifs that generated oscillatory expression dynamics and stabilized distinct cellular states played an essential role. These findings may explain the recently observed heterogeneity and dynamic equilibrium in cellular states of stem cells, and can be used to predict regulatory networks responsible for differentiation in stem cell systems. PMID:22073296

Microrheology: Structural evolution under static and dynamic conditions by simultaneous analysis of confocal microscopy and diffusing wave spectroscopy

NASA Astrophysics Data System (ADS)

Nicolas, Yves; Paques, Marcel; Knaebel, Alexandra; Steyer, Alain; Munch, Jean-Pierre; Blijdenstein, Theo B. J.; van Aken, George A.

2003-08-01

An oscillatory shear configuration was developed to improve understanding of structural evolution during deformation. It combines an inverted confocal scanning laser microscope (CSLM) and a special sample holder that can apply to the sample specific deformation: oscillatory shear or steady strain. In this configuration, a zero-velocity plane is created in the sample by moving two plates in opposite directions, thereby providing stable observation conditions of the structural behavior under deformation. The configuration also includes diffusion wave spectroscopy (DWS) to monitor the network properties via particle mobility under static and dynamic conditions. CSLM and DWS can be performed simultaneously and three-dimensional images can be obtained under static conditions. This configuration is mainly used to study mechanistic phenomena like particle interaction, aggregation, gelation and network disintegration, interactions at interfaces under static and dynamic conditions in semisolid food materials (desserts, dressings, sauces, dairy products) and in nonfood materials (mineral emulsions, etc.). Preliminary data obtained with this new oscillatory shear configuration are described that demonstrate their capabilities and the potential contribution to other areas of application also.

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.

Oscillations and Multiple Equilibria in Microvascular Blood Flow.

PubMed

Karst, Nathaniel J; Storey, Brian D; Geddes, John B

2015-07-01

We investigate the existence of oscillatory dynamics and multiple steady-state flow rates in a network with a simple topology and in vivo microvascular blood flow constitutive laws. Unlike many previous analytic studies, we employ the most biologically relevant models of the physical properties of whole blood. Through a combination of analytic and numeric techniques, we predict in a series of two-parameter bifurcation diagrams a range of dynamical behaviors, including multiple equilibria flow configurations, simple oscillations in volumetric flow rate, and multiple coexistent limit cycles at physically realizable parameters. We show that complexity in network topology is not necessary for complex behaviors to arise and that nonlinear rheology, in particular the plasma skimming effect, is sufficient to support oscillatory dynamics similar to those observed in vivo.

Oscillatory Synchronous Inhibition in the Basolateral Amygdala and its Primary Dependence on NR2A-containing NMDA Receptors.

PubMed

Aroniadou-Anderjaska, Vassiliki; Pidoplichko, Volodymyr I; Figueiredo, Taiza H; Braga, Maria F M

2018-03-01

Synchronous, rhythmic firing of GABAergic interneurons is a fundamental mechanism underlying the generation of brain oscillations, and evidence suggests that NMDA receptors (NMDARs) play a key role in oscillatory activity by regulating the activity of interneurons. Consistent with this, derangement of brain rhythms in certain neuropsychiatric disorders, notably schizophrenia and autism, is associated with NMDAR hypofunction and loss of inhibitory interneurons. In the basolateral amygdala (BLA)-dysfunction of which is involved in a host of neuropsychiatric diseases-, principal neurons display spontaneous, rhythmic "bursts" of inhibitory activity, which could potentially be involved in the orchestration of oscillations in the BLA network; here, we investigated the role of NMDARs in these inhibitory oscillations. Rhythmic bursts of spontaneous IPSCs (0.5 Hz average burst frequency) recorded from rat BLA principal cells were blocked or significantly suppressed by D-AP5, and could be driven by NMDAR activation alone. BLA interneurons generated spontaneous bursts of suprathreshold EPSCs at a similar frequency, which were also blocked or reduced by D-AP5. PEAQX (GluN2A-NMDAR antagonist; 0.4 μM) or Ro-25-6981 (GluN2B-NMDAR antagonist; 5 μM) suppressed the IPSC and EPSC bursts; suppression by PEAQX was significantly greater than that by Ro-25-6981. Immunohistochemical labeling revealed the presence of both GluN2A- and GluN2B-NMDARs on GABAergic BLA interneurons, while, functionally, GluN2A-NMDARs have the dominant role, as suggested by a greater reduction of NMDA-evoked currents by PEAQX versus Ro-25-6981. Entrainment of BLA principal neurons in an oscillatory generation of inhibitory activity depends primarily on activation of GluN2A-NMDARs, and interneuronal GluN2A-NMDARs may play a significant role. Published by Elsevier Ltd.

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.

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.

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.

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.

Asymmetric right/left encoding of emotions in the human subthalamic nucleus

PubMed Central

Eitan, Renana; Shamir, Reuben R.; Linetsky, Eduard; Rosenbluh, Ovadya; Moshel, Shay; Ben-Hur, Tamir; Bergman, Hagai; Israel, Zvi

2013-01-01

Emotional processing is lateralized to the non-dominant brain hemisphere. However, there is no clear spatial model for lateralization of emotional domains in the basal ganglia. The subthalamic nucleus (STN), an input structure in the basal ganglia network, plays a major role in the pathophysiology of Parkinson's disease (PD). This role is probably not limited only to the motor deficits of PD, but may also span the emotional and cognitive deficits commonly observed in PD patients. Beta oscillations (12–30 Hz), the electrophysiological signature of PD, are restricted to the dorsolateral part of the STN that corresponds to the anatomically defined sensorimotor STN. The more medial, more anterior and more ventral parts of the STN are thought to correspond to the anatomically defined limbic and associative territories of the STN. Surprisingly, little is known about the electrophysiological properties of the non-motor domains of the STN, nor about electrophysiological differences between right and left STNs. In this study, microelectrodes were utilized to record the STN spontaneous spiking activity and responses to vocal non-verbal emotional stimuli during deep brain stimulation (DBS) surgeries in human PD patients. The oscillation properties of the STN neurons were used to map the dorsal oscillatory and the ventral non-oscillatory regions of the STN. Emotive auditory stimulation evoked activity in the ventral non-oscillatory region of the right STN. These responses were not observed in the left ventral STN or in the dorsal regions of either the right or left STN. Therefore, our results suggest that the ventral non-oscillatory regions are asymmetrically associated with non-motor functions, with the right ventral STN associated with emotional processing. These results suggest that DBS of the right ventral STN may be associated with beneficial or adverse emotional effects observed in PD patients and may relieve mental symptoms in other neurological and psychiatric diseases. PMID:24194703

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

Neural network communication facilitates verbal working memory.

PubMed

Kustermann, Thomas; Rockstroh, Brigitte; Miller, Gregory A; Popov, Tzvetan

2018-05-28

Oscillatory brain activity in the theta, alpha, and gamma frequency ranges has been associated with working memory (WM). In addition to alpha and theta activity associated with WM retention, and gamma band activity with item encoding, activity in the alpha band is related to the deployment of attention resources and information. The present study sought to specify distinct roles of neuromagnetic 4-7 Hz theta, 9-13 Hz alpha, and 50-70 Hz gamma power modulation and communication in fronto-parietal networks during cued, hemifield-specific item presentation in a modified Sternberg verbal WM task in 14 student volunteers. Lateralized posterior alpha and gamma power during encoding suggest a preparatory role of alpha oscillations. Bilateral alpha power increases during maintenance reflect information retention for the non-lateralized probe response. Lateralized alpha power increase during encoding was apparently driven by a monotonic increase in fronto-parietal 6 Hz phase, suggesting a mechanism facilitating WM encoding and successful performance. Copyright © 2018 Elsevier B.V. All rights reserved.

Changes of oscillatory activity in pitch processing network and related tinnitus relief induced by acoustic CR neuromodulation

PubMed Central

Adamchic, Ilya; Hauptmann, Christian; Tass, Peter A.

2012-01-01

Chronic subjective tinnitus is characterized by abnormal neuronal synchronization in the central auditory system. As shown in a controlled clinical trial, acoustic coordinated reset (CR) neuromodulation causes a significant relief of tinnitus symptoms along with a significant decrease of pathological oscillatory activity in a network comprising auditory and non-auditory brain areas, which is often accompanied with a significant tinnitus pitch change. Here we studied if the tinnitus pitch change correlates with a reduction of tinnitus loudness and/or annoyance as assessed by visual analog scale (VAS) scores. Furthermore, we studied if the changes of the pattern of brain synchrony in tinnitus patients induced by 12 weeks of CR therapy depend on whether or not the patients undergo a pronounced tinnitus pitch change. Therefore, we applied standardized low-resolution brain electromagnetic tomography (sLORETA) to EEG recordings from two groups of patients with a sustained CR-induced relief of tinnitus symptoms with and without tinnitus pitch change. We found that absolute changes of VAS loudness and VAS annoyance scores significantly correlate with the modulus, i.e., the absolute value, of the tinnitus pitch change. Moreover, as opposed to patients with small or no pitch change we found a significantly stronger decrease in gamma power in patients with pronounced tinnitus pitch change in right parietal cortex (Brodmann area, BA 40), right frontal cortex (BA 9, 46), left temporal cortex (BA 22, 42), and left frontal cortex (BA 4, 6), combined with a significantly stronger increase of alpha (10–12 Hz) activity in the right and left anterior cingulate cortex (ACC; BA 32, 24). In addition, we revealed a significantly lower functional connectivity in the gamma band between the right dorsolateral prefrontal cortex (BA 46) and the right ACC (BA 32) after 12 weeks of CR therapy in patients with pronounced pitch change. Our results indicate a substantial, CR-induced reduction of tinnitus-related auditory binding in a pitch processing network. PMID:22493570

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.

4 Hz oscillations synchronize prefrontal-amygdala circuits during fear behaviour

PubMed Central

Karalis, Nikolaos; Dejean, Cyril; Chaudun, Fabrice; Khoder, Suzana; Rozeske, Robert R.; Wurtz, Hélène; Bagur, Sophie; Benchenane, Karim; Sirota, Anton; Courtin, Julien; Herry, Cyril

2016-01-01

Fear expression relies on the coordinated activity of prefrontal and amygdala circuits, yet the mechanisms allowing long-range network synchronization during fear remain unknown. Using a combination of extracellular recordings, pharmacological, and optogenetic manipulations we report that freezing, a behavioural expression of fear, temporally coincides with the development of sustained, internally generated 4 Hz oscillations within prefrontal-amygdala circuits. 4 Hz oscillations predict freezing onset and offset and synchronize prefrontal-amygdala circuits. Optogenetic induction of prefrontal 4 Hz oscillations coordinates prefrontal-amygdala activity and elicits fear behaviour. These results unravel a novel sustained oscillatory mechanism mediating prefrontal-amygdala coupling during fear behaviour. PMID:26878674

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

PubMed

Puig, M Victoria; Gener, Thomas

2015-07-15

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

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.

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.

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

A Clb/Cdk1-mediated regulation of Fkh2 synchronizes CLB expression in the budding yeast cell cycle.

PubMed

Linke, Christian; Chasapi, Anastasia; González-Novo, Alberto; Al Sawad, Istabrak; Tognetti, Silvia; Klipp, Edda; Loog, Mart; Krobitsch, Sylvia; Posas, Francesc; Xenarios, Ioannis; Barberis, Matteo

2017-01-01

Precise timing of cell division is achieved by coupling waves of cyclin-dependent kinase (Cdk) activity with a transcriptional oscillator throughout cell cycle progression. Although details of transcription of cyclin genes are known, it is unclear which is the transcriptional cascade that modulates their expression in a timely fashion. Here, we demonstrate that a Clb/Cdk1-mediated regulation of the Fkh2 transcription factor synchronizes the temporal mitotic CLB expression in budding yeast. A simplified kinetic model of the cyclin/Cdk network predicts a linear cascade where a Clb/Cdk1-mediated regulation of an activator molecule drives CLB3 and CLB2 expression. Experimental validation highlights Fkh2 as modulator of CLB3 transcript levels, besides its role in regulating CLB2 expression. A Boolean model based on the minimal number of interactions needed to capture the information flow of the Clb/Cdk1 network supports the role of an activator molecule in the sequential activation, and oscillatory behavior, of mitotic Clb cyclins. This work illustrates how transcription and phosphorylation networks can be coupled by a Clb/Cdk1-mediated regulation that synchronizes them.

Frequency-Dependent Enhancement of Fluid Intelligence Induced by Transcranial Oscillatory Potentials

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

Santarnecchi, Emiliano; Polizzotto, Nicola Riccardo; Godone, Marco

Everyday problem solving requires the ability to go beyond experience by efficiently encoding and manipulating new information, i.e., fluid intelligence (Gf) [1]. Performance in tasks involving Gf, such as logical and abstract reasoning, has been shown to rely on distributed neural networks, with a crucial role played by prefrontal regions [2]. Synchronization of neuronal activity in the gamma band is a ubiquitous phenomenon within the brain; however, no evidence of its causal involvement in cognition exists to date [3]. Here, we show an enhancement of Gf ability in a cognitive task induced by exogenous rhythmic stimulation within the gamma band.more » Imperceptible alternating current [4] delivered through the scalp over the left middle frontal gyrus resulted in a frequency-specific shortening of the time required to find the correct solution in a visuospatial abstract reasoning task classically employed to measure Gf abilities (i.e., Raven’s matrices) [5]. Crucially, gamma-band stimulation (γ-tACS) selectively enhanced performance only on more complex trials involving conditional/logical reasoning. The finding presented here supports a direct involvement of gamma oscillatory activity in the mechanisms underlying higher-order human cognition.« less

Oscillatory activity in the basal ganglia and deep brain stimulation.

PubMed

Guridi, Jorge; Alegre, Manuel

2017-01-01

Over the past 10 years, research into the neurophysiology of the basal ganglia has provided new insights into the pathophysiology of movement disorders. The presence of pathological oscillations at specific frequencies has been linked to different signs and symptoms in PD and dystonia, suggesting a new model to explain basal ganglia dysfunction. These advances occurred in parallel with improvements in imaging and neurosurgical techniques, both of which having facilitated the more widespread use of DBS to modulate dysfunctional circuits. High-frequency stimulation is thought to disrupt pathological activity in the motor cortex/basal ganglia network; however, it is not easy to explain all of its effects based only on changes in network oscillations. In this viewpoint, we suggest that a return to classic anatomical concepts might help to understand some apparently paradoxical findings. © 2016 International Parkinson and Movement Disorder Society. © 2016 International Parkinson and Movement Disorder Society.

Abdominal expiratory activity in the rat brainstem–spinal cord in situ: patterns, origins and implications for respiratory rhythm generation

PubMed Central

Abdala, A P L; Rybak, I A; Smith, J C; Paton, J F R

2009-01-01

We studied respiratory neural activity generated during expiration. Motoneuronal activity was recorded simultaneously from abdominal (AbN), phrenic (PN), hypoglossal (HN) and central vagus nerves from neonatal and juvenile rats in situ. During eupnoeic activity, low-amplitude post-inspiratory (post-I) discharge was only present in AbN motor outflow. Expression of AbN late-expiratory (late-E) activity, preceding PN bursts, occurred during hypercapnia. Biphasic expiratory (biphasic-E) activity with pre-inspiratory (pre-I) and post-I discharges occurred only during eucapnic anoxia or hypercapnic anoxia. Late-E activity generated during hypercapnia (7–10% CO2) was abolished with pontine transections or chemical suppression of retrotrapezoid nucleus/ventrolateral parafacial (RTN/vlPF). AbN late-E activity during hypercapnia is coupled with augmented pre-I discharge in HN, truncated PN burst, and was quiescent during inspiration. Our data suggest that the pons provides a necessary excitatory drive to an additional neural oscillatory mechanism that is only activated under conditions of high respiratory drive to generate late-E activity destined for AbN motoneurones. This mechanism may arise from neurons located in the RTN/vlPF or the latter may relay late-E activity generated elsewhere. We hypothesize that this oscillatory mechanism is not a necessary component of the respiratory central pattern generator but constitutes a defensive mechanism activated under critical metabolic conditions to provide forced expiration and reduced upper airway resistance simultaneously. Possible interactions of this oscillator with components of the brainstem respiratory network are discussed. PMID:19491247

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.

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

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

Neuromuscular control of the point to point and oscillatory movements of a sagittal arm with the actor-critic reinforcement learning method.

PubMed

Golkhou, Vahid; Parnianpour, Mohamad; Lucas, Caro

2005-04-01

In this study, we have used a single link system with a pair of muscles that are excited with alpha and gamma signals to achieve both point to point and oscillatory movements with variable amplitude and frequency.The system is highly nonlinear in all its physical and physiological attributes. The major physiological characteristics of this system are simultaneous activation of a pair of nonlinear muscle-like-actuators for control purposes, existence of nonlinear spindle-like sensors and Golgi tendon organ-like sensor, actions of gravity and external loading. Transmission delays are included in the afferent and efferent neural paths to account for a more accurate representation of the reflex loops.A reinforcement learning method with an actor-critic (AC) architecture instead of middle and low level of central nervous system (CNS), is used to track a desired trajectory. The actor in this structure is a two layer feedforward neural network and the critic is a model of the cerebellum. The critic is trained by state-action-reward-state-action (SARSA) method. The critic will train the actor by supervisory learning based on the prior experiences. Simulation studies of oscillatory movements based on the proposed algorithm demonstrate excellent tracking capability and after 280 epochs the RMS error for position and velocity profiles were 0.02, 0.04 rad and rad/s, respectively.

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

Spike-timing-dependent plasticity in the human dorso-lateral prefrontal cortex.

PubMed

Casula, Elias Paolo; Pellicciari, Maria Concetta; Picazio, Silvia; Caltagirone, Carlo; Koch, Giacomo

2016-12-01

Changes in the synaptic strength of neural connections are induced by repeated coupling of activity of interconnected neurons with precise timing, a phenomenon known as spike-timing-dependent plasticity (STDP). It is debated if this mechanism exists in large-scale cortical networks in humans. We combined transcranial magnetic stimulation (TMS) with concurrent electroencephalography (EEG) to directly investigate the effects of two paired associative stimulation (PAS) protocols (fronto-parietal and parieto-frontal) of pre and post-synaptic inputs within the human fronto-parietal network. We found evidence that the dorsolateral prefrontal cortex (DLPFC) has the potential to form robust STDP. Long-term potentiation/depression of TMS-evoked cortical activity is prompted after that DLPFC stimulation is followed/preceded by posterior parietal stimulation. Such bidirectional changes are paralleled by sustained increase/decrease of high-frequency oscillatory activity, likely reflecting STDP responsivity. The current findings could be important to drive plasticity of damaged cortical circuits in patients with cognitive or psychiatric disorders. Copyright © 2016 Elsevier Inc. All rights reserved.

Excitatory motor neurons are local oscillators for backward locomotion

PubMed Central

Guan, Sihui Asuka; Fouad, Anthony D; Meng, Jun; Kawano, Taizo; Huang, Yung-Chi; Li, Yi; Alcaire, Salvador; Hung, Wesley; Lu, Yangning; Qi, Yingchuan Billy; Jin, Yishi; Alkema, Mark; Fang-Yen, Christopher

2018-01-01

Cell- or network-driven oscillators underlie motor rhythmicity. The identity of C. elegans oscillators remains unknown. Through cell ablation, electrophysiology, and calcium imaging, we show: (1) forward and backward locomotion is driven by different oscillators; (2) the cholinergic and excitatory A-class motor neurons exhibit intrinsic and oscillatory activity that is sufficient to drive backward locomotion in the absence of premotor interneurons; (3) the UNC-2 P/Q/N high-voltage-activated calcium current underlies A motor neuron’s oscillation; (4) descending premotor interneurons AVA, via an evolutionarily conserved, mixed gap junction and chemical synapse configuration, exert state-dependent inhibition and potentiation of A motor neuron’s intrinsic activity to regulate backward locomotion. Thus, motor neurons themselves derive rhythms, which are dually regulated by the descending interneurons to control the reversal motor state. These and previous findings exemplify compression: essential circuit properties are conserved but executed by fewer numbers and layers of neurons in a small locomotor network. PMID:29360035

Excitatory motor neurons are local oscillators for backward locomotion.

PubMed

Gao, Shangbang; Guan, Sihui Asuka; Fouad, Anthony D; Meng, Jun; Kawano, Taizo; Huang, Yung-Chi; Li, Yi; Alcaire, Salvador; Hung, Wesley; Lu, Yangning; Qi, Yingchuan Billy; Jin, Yishi; Alkema, Mark; Fang-Yen, Christopher; Zhen, Mei

2018-01-23

Cell- or network-driven oscillators underlie motor rhythmicity. The identity of C. elegans oscillators remains unknown. Through cell ablation, electrophysiology, and calcium imaging, we show: (1) forward and backward locomotion is driven by different oscillators; (2) the cholinergic and excitatory A-class motor neurons exhibit intrinsic and oscillatory activity that is sufficient to drive backward locomotion in the absence of premotor interneurons; (3) the UNC-2 P/Q/N high-voltage-activated calcium current underlies A motor neuron's oscillation; (4) descending premotor interneurons AVA, via an evolutionarily conserved, mixed gap junction and chemical synapse configuration, exert state-dependent inhibition and potentiation of A motor neuron's intrinsic activity to regulate backward locomotion. Thus, motor neurons themselves derive rhythms, which are dually regulated by the descending interneurons to control the reversal motor state. These and previous findings exemplify compression: essential circuit properties are conserved but executed by fewer numbers and layers of neurons in a small locomotor network. © 2017, Gao et al.

Development of pacemaker properties and rhythmogenic mechanisms in the mouse embryonic respiratory network

PubMed Central

Chevalier, Marc; Toporikova, Natalia; Simmers, John; Thoby-Brisson, Muriel

2016-01-01

Breathing is a vital rhythmic behavior generated by hindbrain neuronal circuitry, including the preBötzinger complex network (preBötC) that controls inspiration. The emergence of preBötC network activity during prenatal development has been described, but little is known regarding inspiratory neurons expressing pacemaker properties at embryonic stages. Here, we combined calcium imaging and electrophysiological recordings in mouse embryo brainstem slices together with computational modeling to reveal the existence of heterogeneous pacemaker oscillatory properties relying on distinct combinations of burst-generating INaP and ICAN conductances. The respective proportion of the different inspiratory pacemaker subtypes changes during prenatal development. Concomitantly, network rhythmogenesis switches from a purely INaP/ICAN-dependent mechanism at E16.5 to a combined pacemaker/network-driven process at E18.5. Our results provide the first description of pacemaker bursting properties in embryonic preBötC neurons and indicate that network rhythmogenesis undergoes important changes during prenatal development through alterations in both circuit properties and the biophysical characteristics of pacemaker neurons. DOI: http://dx.doi.org/10.7554/eLife.16125.001 PMID:27434668

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

Anatomical and functional assemblies of brain BOLD oscillations

PubMed Central

Baria, Alexis T.; Baliki, Marwan N.; Parrish, Todd; Apkarian, A. Vania

2011-01-01

Brain oscillatory activity has long been thought to have spatial properties, the details of which are unresolved. Here we examine spatial organizational rules for the human brain oscillatory activity as measured by blood oxygen level-dependent (BOLD). Resting state BOLD signal was transformed into frequency space (Welch’s method), averaged across subjects, and its spatial distribution studied as a function of four frequency bands, spanning the full bandwidth of BOLD. The brain showed anatomically constrained distribution of power for each frequency band. This result was replicated on a repository dataset of 195 subjects. Next, we examined larger-scale organization by parceling the neocortex into regions approximating Brodmann Areas (BAs). This indicated that BAs of simple function/connectivity (unimodal), vs. complex properties (transmodal), are dominated by low frequency BOLD oscillations, and within the visual ventral stream we observe a graded shift of power to higher frequency bands for BAs further removed from the primary visual cortex (increased complexity), linking frequency properties of BOLD to hodology. Additionally, BOLD oscillation properties for the default mode network demonstrated that it is composed of distinct frequency dependent regions. When the same analysis was performed on a visual-motor task, frequency-dependent global and voxel-wise shifts in BOLD oscillations could be detected at brain sites mostly outside those identified with general linear modeling. Thus, analysis of BOLD oscillations in full bandwidth uncovers novel brain organizational rules, linking anatomical structures and functional networks to characteristic BOLD oscillations. The approach also identifies changes in brain intrinsic properties in relation to responses to external inputs. PMID:21613505

Role of xanthine oxidoreductase and NAD(P)H oxidase in endothelial superoxide production in response to oscillatory shear stress

NASA Technical Reports Server (NTRS)

McNally, J. Scott; Davis, Michael E.; Giddens, Don P.; Saha, Aniket; Hwang, Jinah; Dikalov, Sergey; Jo, Hanjoong; Harrison, David G.

2003-01-01

Oscillatory shear stress occurs at sites of the circulation that are vulnerable to atherosclerosis. Because oxidative stress contributes to atherosclerosis, we sought to determine whether oscillatory shear stress increases endothelial production of reactive oxygen species and to define the enzymes responsible for this phenomenon. Bovine aortic endothelial cells were exposed to static, laminar (15 dyn/cm2), and oscillatory shear stress (+/-15 dyn/cm2). Oscillatory shear increased superoxide (O2.-) production by more than threefold over static and laminar conditions as detected using electron spin resonance (ESR). This increase in O2*- was inhibited by oxypurinol and culture of endothelial cells with tungsten but not by inhibitors of other enzymatic sources. Oxypurinol also prevented H2O2 production in response to oscillatory shear stress as measured by dichlorofluorescin diacetate and Amplex Red fluorescence. Xanthine-dependent O2*- production was increased in homogenates of endothelial cells exposed to oscillatory shear stress. This was associated with decreased xanthine dehydrogenase (XDH) protein levels and enzymatic activity resulting in an elevated ratio of xanthine oxidase (XO) to XDH. We also studied endothelial cells lacking the p47phox subunit of the NAD(P)H oxidase. These cells exhibited dramatically depressed O2*- production and had minimal XO protein and activity. Transfection of these cells with p47phox restored XO protein levels. Finally, in bovine aortic endothelial cells, prolonged inhibition of the NAD(P)H oxidase with apocynin decreased XO protein levels and prevented endothelial cell stimulation of O2*- production in response to oscillatory shear stress. These data suggest that the NAD(P)H oxidase maintains endothelial cell XO levels and that XO is responsible for increased reactive oxygen species production in response to oscillatory shear stress.

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

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.

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.

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.

Spatial mapping reveals multi-step pattern of wound healing in Physarum polycephalum

NASA Astrophysics Data System (ADS)

Bäuerle, Felix K.; Kramar, Mirna; Alim, Karen

2017-11-01

Wounding is a severe impairment of function, especially for an exposed organism like the network-forming true slime mould Physarum polycephalum. The tubular network making up the organism’s body plan is entirely interconnected and shares a common cytoplasm. Oscillatory contractions of the enclosing tube walls drive the shuttle streaming of the cytoplasm. Cytoplasmic flows underlie the reorganization of the network for example by movement toward attractive stimuli or away from repellants. Here, we follow the reorganization of P. polycephalum networks after severe wounding. Spatial mapping of the contraction changes in response to wounding reveal a multi-step pattern. Phases of increased activity alternate with cessation of contractions and stalling of flows, giving rise to coordinated transport and growth at the severing site. Overall, severing surprisingly acts like an attractive stimulus enabling healing of severed tubes. The reproducible cessation of contractions arising during this wound-healing response may open up new venues to investigate the biochemical wiring underlying P. polycephalum’s complex behaviours.

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

PubMed Central

Le Magueresse, Corentin; Monyer, Hannah

2012-01-01

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

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

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

Changes of spontaneous oscillatory activity to tonic heat pain.

PubMed

Peng, Weiwei; Hu, Li; Zhang, Zhiguo; Hu, Yong

2014-01-01

Transient painful stimuli could induce suppression of alpha oscillatory activities and enhancement of gamma oscillatory activities that also could be greatly modulated by attention. Here, we attempted to characterize changes in cortical activities during tonic heat pain perception and investigated the influence of directed/distracted attention on these responses. We collected 5-minute long continuous Electroencephalography (EEG) data from 38 healthy volunteers during four conditions presented in a counterbalanced order: (A) resting condition; (B) innoxious-distracted condition; (C) noxious-distracted condition; (D) noxious-attended condition. The effects of tonic heat pain stimulation and selective attention on oscillatory activities were investigated by comparing the EEG power spectra among the four experimental conditions and assessing the relationship between spectral power difference and subjective pain intensity. The change of oscillatory activities in condition D was characterized by stable and persistent decrease of alpha oscillation power over contralateral-central electrodes and widespread increase of gamma oscillation power, which were even significantly correlated with subjective pain intensity. Since EEG responses in the alpha and gamma frequency band were affected by attention in different manners, they are likely related to different aspects of the multidimensional sensory experience of pain. The observed contralateral-central alpha suppression (conditions D vs. B and D vs. C) may reflect primarily a top-down cognitive process such as attention, while the widespread gamma enhancement (conditions D vs. A) may partly reflect tonic pain processing, representing the summary effects of bottom-up stimulus-related and top-down subject-driven cognitive processes.

Changes of Spontaneous Oscillatory Activity to Tonic Heat Pain

PubMed Central

Zhang, Zhiguo; Hu, Yong

2014-01-01

Transient painful stimuli could induce suppression of alpha oscillatory activities and enhancement of gamma oscillatory activities that also could be greatly modulated by attention. Here, we attempted to characterize changes in cortical activities during tonic heat pain perception and investigated the influence of directed/distracted attention on these responses. We collected 5-minute long continuous Electroencephalography (EEG) data from 38 healthy volunteers during four conditions presented in a counterbalanced order: (A) resting condition; (B) innoxious-distracted condition; (C) noxious-distracted condition; (D) noxious-attended condition. The effects of tonic heat pain stimulation and selective attention on oscillatory activities were investigated by comparing the EEG power spectra among the four experimental conditions and assessing the relationship between spectral power difference and subjective pain intensity. The change of oscillatory activities in condition D was characterized by stable and persistent decrease of alpha oscillation power over contralateral-central electrodes and widespread increase of gamma oscillation power, which were even significantly correlated with subjective pain intensity. Since EEG responses in the alpha and gamma frequency band were affected by attention in different manners, they are likely related to different aspects of the multidimensional sensory experience of pain. The observed contralateral-central alpha suppression (conditions D vs. B and D vs. C) may reflect primarily a top-down cognitive process such as attention, while the widespread gamma enhancement (conditions D vs. A) may partly reflect tonic pain processing, representing the summary effects of bottom-up stimulus-related and top-down subject-driven cognitive processes. PMID:24603703

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

Bifurcation Analysis on Phase-Amplitude Cross-Frequency Coupling in Neural Networks with Dynamic Synapses

PubMed Central

Sase, Takumi; Katori, Yuichi; Komuro, Motomasa; Aihara, Kazuyuki

2017-01-01

We investigate a discrete-time network model composed of excitatory and inhibitory neurons and dynamic synapses with the aim at revealing dynamical properties behind oscillatory phenomena possibly related to brain functions. We use a stochastic neural network model to derive the corresponding macroscopic mean field dynamics, and subsequently analyze the dynamical properties of the network. In addition to slow and fast oscillations arising from excitatory and inhibitory networks, respectively, we show that the interaction between these two networks generates phase-amplitude cross-frequency coupling (CFC), in which multiple different frequency components coexist and the amplitude of the fast oscillation is modulated by the phase of the slow oscillation. Furthermore, we clarify the detailed properties of the oscillatory phenomena by applying the bifurcation analysis to the mean field model, and accordingly show that the intermittent and the continuous CFCs can be characterized by an aperiodic orbit on a closed curve and one on a torus, respectively. These two CFC modes switch depending on the coupling strength from the excitatory to inhibitory networks, via the saddle-node cycle bifurcation of a one-dimensional torus in map (MT1SNC), and may be associated with the function of multi-item representation. We believe that the present model might have potential for studying possible functional roles of phase-amplitude CFC in the cerebral cortex. PMID:28424606

Memory traces of long-range coordinated oscillations in the sleeping human brain.

PubMed

Piantoni, Giovanni; Van Der Werf, Ysbrand D; Jensen, Ole; Van Someren, Eus J W

2015-01-01

Cognition involves coordinated activity across distributed neuronal networks. Neuronal activity during learning triggers cortical plasticity that allows for reorganization of the neuronal network and integration of new information. Animal studies have shown post-learning reactivation of learning-elicited neuronal network activity during subsequent sleep, supporting consolidation of the reorganization. However, no previous studies, to our knowledge, have demonstrated reactivation of specific learning-elicited long-range functional connectivity during sleep in humans. We here show reactivation of learning-induced long-range synchronization of magnetoencephalography power fluctuations in human sleep. Visuomotor learning elicited a specific profile of long-range cortico-cortical synchronization of slow (0.1 Hz) fluctuations in beta band (12-30 Hz) power. The parieto-occipital part of this synchronization profile reappeared in delta band (1-3.5 Hz) power fluctuations during subsequent sleep, but not during the intervening wakefulness period. Individual differences in the reactivated synchronization predicted postsleep performance improvement. The presleep resting-state synchronization profile was not reactivated during sleep. The findings demonstrate reactivation of long-range coordination of neuronal activity in humans, more specifically of reactivation of coupling of infra-slow fluctuations in oscillatory power. The spatiotemporal profile of delta power fluctuations during sleep may subserve memory consolidation by echoing coordinated activation elicited by prior learning. © 2014 Wiley Periodicals, Inc.

Cerebral oscillatory activity during simulated driving using MEG.

PubMed

Sakihara, Kotoe; Hirata, Masayuki; Ebe, Kazutoshi; Kimura, Kenji; Yi Ryu, Seong; Kono, Yoshiyuki; Muto, Nozomi; Yoshioka, Masako; Yoshimine, Toshiki; Yorifuji, Shiro

2014-01-01

We aimed to examine cerebral oscillatory differences associated with psychological processes during simulated car driving. We recorded neuromagnetic signals in 14 healthy volunteers using magnetoencephalography (MEG) during simulated driving. MEG data were analyzed using synthetic aperture magnetometry to detect the spatial distribution of cerebral oscillations. Group effects between subjects were analyzed statistically using a non-parametric permutation test. Oscillatory differences were calculated by comparison between "passive viewing" and "active driving." "Passive viewing" was the baseline, and oscillatory differences during "active driving" showed an increase or decrease in comparison with a baseline. Power increase in the theta band was detected in the superior frontal gyrus (SFG) during active driving. Power decreases in the alpha, beta, and low gamma bands were detected in the right inferior parietal lobe (IPL), left postcentral gyrus (PoCG), middle temporal gyrus (MTG), and posterior cingulate gyrus (PCiG) during active driving. Power increase in the theta band in the SFG may play a role in attention. Power decrease in the right IPL may reflect selectively divided attention and visuospatial processing, whereas that in the left PoCG reflects sensorimotor activation related to driving manipulation. Power decreases in the MTG and PCiG may be associated with object recognition.

Behavioral relevance of gamma-band activity for short-term memory-based auditory decision-making.

PubMed

Kaiser, Jochen; Heidegger, Tonio; Lutzenberger, Werner

2008-06-01

Oscillatory activity in the gamma-band range has been established as a correlate of cognitive processes, including perception, attention and memory. Only a few studies, however, have provided evidence for an association between gamma-band activity (GBA) and measures of behavioral performance. Here we focused on the comparison between sample and test stimuli S1 and S2 during an auditory spatial short-term memory task. Applying statistical probability mapping to magnetoencephalographic recordings from 28 human subjects, we identified GBA components distinguishing nonidentical from identical S1-S2 pairs. This activity was found at frequencies between 65 and 90 Hz and was localized over posterior cortical regions contralateral to the hemifield in which the stimuli were presented. The 10 best task performers showed higher amplitudes of this GBA component than the 10 worst performers. This group difference was most pronounced between about 150 and 300 ms after stimulus onset. Apparently the decision about whether test stimuli matched the stored representation of previously presented sample sounds relied partly on the oscillatory activation of networks representing differences between both stimuli. This result could be replicated by reanalyzing the combined data from two previous studies assessing short-term memory for sound duration and sound lateralization, respectively. Similarly to our main study, GBA amplitudes to nonmatching vs. matching S1-S2 pairs were higher in good performers than poor performers. The present findings demonstrate the behavioral relevance of GBA.

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.

Local Network-Level Integration Mediates Effects of Transcranial Alternating Current Stimulation.

PubMed

Fuscà, Marco; Ruhnau, Philipp; Neuling, Toralf; Weisz, Nathan

2018-05-01

Transcranial alternating current stimulation (tACS) has been proposed as a tool to draw causal inferences on the role of oscillatory activity in cognitive functioning and has the potential to induce long-term changes in cerebral networks. However, effectiveness of tACS underlies high variability and dependencies, which, as previous modeling works have suggested, may be mediated by local and network-level brain states. We used magnetoencephalography to record brain activity from 17 healthy participants at rest as they kept their eyes open (EO) or eyes closed (EC) while being stimulated with sham, weak, or strong alpha-tACS using a montage commonly assumed to target occipital areas. We reconstructed the activity of sources in all stimulation conditions by means of beamforming. The analysis of resting-state brain activity revealed an interaction of the external stimulation with the endogenous alpha power increase from EO to EC. This interaction was localized to the posterior cingulate, a region remote from occipital cortex. This suggests state-dependent (EO vs. EC) long-range effects of tACS. In a follow-up analysis of this online-tACS effect, we find evidence that this state-dependency effect is mediated by functional network changes: connection strength from the precuneus was significantly correlated with the state-dependency effect in the posterior cingulate during tACS. No analogous correlation could be found for alpha power modulations in occipital cortex. Altogether, this is the first strong evidence to illustrate how functional network architectures can shape tACS effects.

Chirp-evoked potentials in the awake and anesthetized rat. A procedure to assess changes in cortical oscillatory activity.

PubMed

Pérez-Alcázar, M; Nicolás, M J; Valencia, M; Alegre, M; Iriarte, J; Artieda, J

2008-03-01

Steady-state potentials are oscillatory responses generated by rhythmic stimulation of a sensory pathway. The frequency of the response, which follows the frequency of stimulation and potentially indicates the preferential working frequency of the auditory neural network, is maximal at a stimulus rate of 40 Hz for auditory stimuli in humans, but may be different in other species. Our aim was to explore the responses to different frequencies in the rat. The stimulus was a tone modulated in amplitude by a sinusoid with linearly-increasing frequency from 1 to 250 Hz ("chirp"). Time-frequency transforms were used for response analysis in 12 animals, awake and under ketamine/xylazine anesthesia. We studied whether the responses were due to increases in amplitude or to phase-locking phenomena, using single-sweep time-frequency transforms and inter-trial phase analysis. A progressive decrease in the amplitude of the response was observed from the maximal values (around 15 Hz) up to the limit of the test (250 Hz). The high-frequency component was mainly due to phase-locking phenomena with a smaller amplitude contribution. Under anesthesia, the amplitude and phase-locking of lower frequencies (under 100 Hz) decreased, while the phase-locking over 200 Hz increased. In conclusion, amplitude-modulation following responses differ between humans and rats in response range and frequency of maximal amplitude. Anesthesia with ketamine/xylazine modifies differentially the amplitude and the phase-locking of the responses. These findings should be taken into account when assessing the changes in cortical oscillatory activity related to different drugs, in healthy rodents and in animal models of neurodegenerative diseases.

Resting-State Pallidal-Cortical Oscillatory Couplings in Patients With Predominant Phasic and Tonic Dystonia.

PubMed

Yokochi, Fusako; Kato, Kenji; Iwamuro, Hirokazu; Kamiyama, Tsutomu; Kimura, Katsuo; Yugeta, Akihiro; Okiyama, Ryoichi; Taniguchi, Makoto; Kumada, Satoko; Ushiba, Junichi

2018-01-01

Pallidal deep brain stimulation (DBS) improves the symptoms of dystonia. The improvement processes of dystonic movements (phasic symptoms) and tonic symptoms differ. Phasic symptoms improve rapidly after starting DBS treatment, but tonic symptoms improve gradually. This difference implies distinct neuronal mechanisms for phasic and tonic symptoms in the underlying cortico-basal ganglia neuronal network. Phasic symptoms are related to the pallido-thalamo-cortical pathway. The pathway related to tonic symptoms has been assumed to be different from that for phasic symptoms. In the present study, local field potentials of the globus pallidus internus (GPi) and globus pallidus externus (GPe) and electroencephalograms from the motor cortex (MCx) were recorded in 19 dystonia patients to analyze the differences between the two types of symptoms. The 19 patients were divided into two groups, 10 with predominant phasic symptoms (phasic patients) and 9 with predominant tonic symptoms (tonic patients). To investigate the distinct features of oscillations and functional couplings across the GPi, GPe, and MCx by clinical phenotype, power and coherence were calculated over the delta (2-4 Hz), theta (5-7 Hz), alpha (8-13 Hz), and beta (14-35 Hz) frequencies. In phasic patients, the alpha spectral peaks emerged in the GPi oscillatory activities, and alpha GPi coherence with the GPe and MCx was higher than in tonic patients. On the other hand, delta GPi oscillatory activities were prominent, and delta GPi-GPe coherence was significantly higher in tonic than in phasic patients. However, there was no significant delta coherence between the GPi/GPe and MCx in tonic patients. These results suggest that different pathophysiological cortico-pallidal oscillations are related to tonic and phasic symptoms.

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

Brain Oscillatory Activity during Spatial Navigation: Theta and Gamma Activity Link Medial Temporal and Parietal Regions

ERIC Educational Resources Information Center

White, David J.; Congedo, Marco; Ciorciari, Joseph; Silberstein, Richard B.

2012-01-01

Brain oscillatory correlates of spatial navigation were investigated using blind source separation (BSS) and standardized low resolution electromagnetic tomography (sLORETA) analyses of 62-channel EEG recordings. Twenty-five participants were instructed to navigate to distinct landmark buildings in a previously learned virtual reality town…

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.

Binary Oscillatory Crossflow Electrophoresis

NASA Technical Reports Server (NTRS)

Molloy, Richard F.; Gallagher, Christopher T.; Leighton, David T., Jr.

1996-01-01

We present preliminary results of our implementation of a novel electrophoresis separation technique: Binary Oscillatory Cross flow Electrophoresis (BOCE). The technique utilizes the interaction of two driving forces, an oscillatory electric field and an oscillatory shear flow, to create an active binary filter for the separation of charged species. Analytical and numerical studies have indicated that this technique is capable of separating proteins with electrophoretic mobilities differing by less than 10%. With an experimental device containing a separation chamber 20 cm long, 5 cm wide, and 1 mm thick, an order of magnitude increase in throughput over commercially available electrophoresis devices is theoretically possible.

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

State-dependent spike and local field synchronization between motor cortex and substantia nigra in hemiparkinsonian rats.

PubMed

Brazhnik, Elena; Cruz, Ana V; Avila, Irene; Wahba, Marian I; Novikov, Nikolay; Ilieva, Neda M; McCoy, Alex J; Gerber, Colin; Walters, Judith R

2012-06-06

Excessive beta frequency oscillatory and synchronized activity has been reported in the basal ganglia of parkinsonian patients and animal models of the disease. To gain insight into processes underlying this activity, this study explores relationships between oscillatory activity in motor cortex and basal ganglia output in behaving rats after dopamine cell lesion. During inattentive rest, 7 d after lesion, increases in motor cortex-substantia nigra pars reticulata (SNpr) coherence emerged in the 8-25 Hz range, with significant increases in local field potential (LFP) power in SNpr but not motor cortex. In contrast, during treadmill walking, marked increases in both motor cortex and SNpr LFP power, as well as coherence, emerged in the 25-40 Hz band with a peak frequency at 30-35 Hz. Spike-triggered waveform averages showed that 77% of SNpr neurons, 77% of putative cortical interneurons, and 44% of putative pyramidal neurons were significantly phase-locked to the increased cortical LFP activity in the 25-40 Hz range. Although the mean lag between cortical and SNpr LFPs fluctuated around zero, SNpr neurons phase-locked to cortical LFP oscillations fired, on average, 17 ms after synchronized spiking in motor cortex. High coherence between LFP oscillations in cortex and SNpr supports the view that cortical activity facilitates entrainment and synchronization of activity in basal ganglia after loss of dopamine. However, the dramatic increases in cortical power and relative timing of phase-locked spiking in these areas suggest that additional processes help shape the frequency-specific tuning of the basal ganglia-thalamocortical network during ongoing motor activity.

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

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.

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.

The spectro-contextual encoding and retrieval theory of episodic memory.

PubMed

Watrous, Andrew J; Ekstrom, Arne D

2014-01-01

The spectral fingerprint hypothesis, which posits that different frequencies of oscillations underlie different cognitive operations, provides one account for how interactions between brain regions support perceptual and attentive processes (Siegel etal., 2012). Here, we explore and extend this idea to the domain of human episodic memory encoding and retrieval. Incorporating findings from the synaptic to cognitive levels of organization, we argue that spectrally precise cross-frequency coupling and phase-synchronization promote the formation of hippocampal-neocortical cell assemblies that form the basis for episodic memory. We suggest that both cell assembly firing patterns as well as the global pattern of brain oscillatory activity within hippocampal-neocortical networks represents the contents of a particular memory. Drawing upon the ideas of context reinstatement and multiple trace theory, we argue that memory retrieval is driven by internal and/or external factors which recreate these frequency-specific oscillatory patterns which occur during episodic encoding. These ideas are synthesized into a novel model of episodic memory (the spectro-contextual encoding and retrieval theory, or "SCERT") that provides several testable predictions for future research.

Application of describing function analysis to a model of deep brain stimulation.

PubMed

Davidson, Clare Muireann; de Paor, Annraoi M; Lowery, Madeleine M

2014-03-01

Deep brain stimulation effectively alleviates motor symptoms of medically refractory Parkinson's disease, and also relieves many other treatment-resistant movement and affective disorders. Despite its relative success as a treatment option, the basis of its efficacy remains elusive. In Parkinson's disease, increased functional connectivity and oscillatory activity occur within the basal ganglia as a result of dopamine loss. A correlative relationship between pathological oscillatory activity and the motor symptoms of the disease, in particular bradykinesia, rigidity, and tremor, has been established. Suppression of the oscillations by either dopamine replacement or DBS also correlates with an improvement in motor symptoms. DBS parameters are currently chosen empirically using a "trial and error" approach, which can be time-consuming and costly. The work presented here amalgamates concepts from theories of neural network modeling with nonlinear control engineering to describe and analyze a model of synchronous neural activity and applied stimulation. A theoretical expression for the optimum stimulation parameters necessary to suppress oscillations is derived. The effect of changing stimulation parameters (amplitude and pulse duration) on induced oscillations is studied in the model. Increasing either stimulation pulse duration or amplitude enhanced the level of suppression. The predicted parameters were found to agree well with clinical measurements reported in the literature for individual patients. It is anticipated that the simplified model described may facilitate the development of protocols to aid optimum stimulation parameter choice on a patient by patient basis.

Synconset Waves and Chains: Spiking Onsets in Synchronous Populations Predict and Are Predicted by Network Structure

PubMed Central

Raghavan, Mohan; Amrutur, Bharadwaj; Narayanan, Rishikesh; Sikdar, Sujit Kumar

2013-01-01

Synfire waves are propagating spike packets in synfire chains, which are feedforward chains embedded in random networks. Although synfire waves have proved to be effective quantification for network activity with clear relations to network structure, their utilities are largely limited to feedforward networks with low background activity. To overcome these shortcomings, we describe a novel generalisation of synfire waves, and define ‘synconset wave’ as a cascade of first spikes within a synchronisation event. Synconset waves would occur in ‘synconset chains’, which are feedforward chains embedded in possibly heavily recurrent networks with heavy background activity. We probed the utility of synconset waves using simulation of single compartment neuron network models with biophysically realistic conductances, and demonstrated that the spread of synconset waves directly follows from the network connectivity matrix and is modulated by top-down inputs and the resultant oscillations. Such synconset profiles lend intuitive insights into network organisation in terms of connection probabilities between various network regions rather than an adjacency matrix. To test this intuition, we develop a Bayesian likelihood function that quantifies the probability that an observed synfire wave was caused by a given network. Further, we demonstrate it's utility in the inverse problem of identifying the network that caused a given synfire wave. This method was effective even in highly subsampled networks where only a small subset of neurons were accessible, thus showing it's utility in experimental estimation of connectomes in real neuronal-networks. Together, we propose synconset chains/waves as an effective framework for understanding the impact of network structure on function, and as a step towards developing physiology-driven network identification methods. Finally, as synconset chains extend the utilities of synfire chains to arbitrary networks, we suggest utilities of our framework to several aspects of network physiology including cell assemblies, population codes, and oscillatory synchrony. PMID:24116018

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.

Modulation of alpha and gamma oscillations related to retrospectively orienting attention within working memory.

PubMed

Poch, Claudia; Campo, Pablo; Barnes, Gareth R

2014-07-01

Selective attention mechanisms allow us to focus on information that is relevant to the current behavior and, equally important, ignore irrelevant information. An influential model proposes that oscillatory neural activity in the alpha band serves as an active functional inhibitory mechanism. Recent studies have shown that, in the same way that attention can be selectively oriented to bias sensory processing in favor of relevant stimuli in perceptual tasks, it is also possible to retrospectively orient attention to internal representations held in working memory. However, these studies have not explored the associated oscillatory phenomena. In the current study, we analysed the patterns of neural oscillatory activity recorded with magnetoencephalography while participants performed a change detection task, in which a spatial retro-cue was presented during the maintenance period, indicating which item or items were relevant for subsequent retrieval. Participants benefited from retro-cues in terms of accuracy and reaction time. Retro-cues also modulated oscillatory activity in the alpha and gamma frequency bands. We observed greater alpha activity in a ventral visual region ipsilateral to the attended hemifield, thus supporting its suppressive role, i.e., a functional disengagement of task-irrelevant regions. Accompanying this modulation, we found an increase in gamma activity contralateral to the attended hemifield, which could reflect attentional orienting and selective processing. These findings suggest that the oscillatory mechanisms underlying attentional orienting to representations held in working memory are similar to those engaged when attention is oriented in the perceptual space. © 2014 The Authors. European Journal of Neuroscience published by Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

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

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.

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

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

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

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.

Cerebral oscillatory activity during simulated driving using MEG

PubMed Central

Sakihara, Kotoe; Hirata, Masayuki; Ebe, Kazutoshi; Kimura, Kenji; Yi Ryu, Seong; Kono, Yoshiyuki; Muto, Nozomi; Yoshioka, Masako; Yoshimine, Toshiki; Yorifuji, Shiro

2014-01-01

We aimed to examine cerebral oscillatory differences associated with psychological processes during simulated car driving. We recorded neuromagnetic signals in 14 healthy volunteers using magnetoencephalography (MEG) during simulated driving. MEG data were analyzed using synthetic aperture magnetometry to detect the spatial distribution of cerebral oscillations. Group effects between subjects were analyzed statistically using a non-parametric permutation test. Oscillatory differences were calculated by comparison between “passive viewing” and “active driving.” “Passive viewing” was the baseline, and oscillatory differences during “active driving” showed an increase or decrease in comparison with a baseline. Power increase in the theta band was detected in the superior frontal gyrus (SFG) during active driving. Power decreases in the alpha, beta, and low gamma bands were detected in the right inferior parietal lobe (IPL), left postcentral gyrus (PoCG), middle temporal gyrus (MTG), and posterior cingulate gyrus (PCiG) during active driving. Power increase in the theta band in the SFG may play a role in attention. Power decrease in the right IPL may reflect selectively divided attention and visuospatial processing, whereas that in the left PoCG reflects sensorimotor activation related to driving manipulation. Power decreases in the MTG and PCiG may be associated with object recognition. PMID:25566017

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.

Oscillations in sensorimotor cortex in movement disorders: an electrocorticography study.

PubMed

Crowell, Andrea L; Ryapolova-Webb, Elena S; Ostrem, Jill L; Galifianakis, Nicholas B; Shimamoto, Shoichi; Lim, Daniel A; Starr, Philip A

2012-02-01

Movement disorders of basal ganglia origin may arise from abnormalities in synchronized oscillatory activity in a network that includes the basal ganglia, thalamus and motor cortices. In humans, much has been learned from the study of basal ganglia local field potentials recorded from temporarily externalized deep brain stimulator electrodes. These studies have led to the theory that Parkinson's disease has characteristic alterations in the beta frequency band (13-30 Hz) in the basal ganglia-thalamocortical network. However, different disorders have rarely been compared using recordings in the same structure under the same behavioural conditions, limiting straightforward assessment of current hypotheses. To address this, we utilized subdural electrocorticography to study cortical oscillations in the three most common movement disorders: Parkinson's disease, primary dystonia and essential tremor. We recorded local field potentials from the arm area of primary motor and sensory cortices in 31 subjects using strip electrodes placed temporarily during routine surgery for deep brain stimulator placement. We show that: (i) primary motor cortex broadband gamma power is increased in Parkinson's disease compared with the other conditions, both at rest and during a movement task; (ii) primary motor cortex high beta (20-30 Hz) power is increased in Parkinson's disease during the 'stop' phase of a movement task; (iii) the alpha-beta peaks in the motor and sensory cortical power spectra occur at higher frequencies in Parkinson's disease than in the other two disorders; and (iv) patients with dystonia have impaired movement-related beta band desynchronization in primary motor and sensory cortices. The findings support the emerging hypothesis that disease states reflect abnormalities in synchronized oscillatory activity. This is the first study of sensorimotor cortex local field potentials in the three most common movement disorders.

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

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

PubMed

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

2018-02-27

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

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.

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.

A Realtime Active Feedback Control System For Coupled Nonlinear Chemical Oscillators

NASA Astrophysics Data System (ADS)

Tompkins, Nathan; Fraden, Seth

2012-02-01

We study the manipulation and control of oscillatory networks. As a model system we use an emulsion of Belousov-Zhabotinsky (BZ) oscillators packed on a hexagonal lattice. Each drop is observed and perturbed by a Programmable Illumination Microscope (PIM). The PIM allows us to track individual BZ oscillators, calculate the phase and order parameters of every drop, and selectively perturb specific drops with photo illumination, all in realtime. To date we have determined the native attractor patterns for drops in 1D arrays and 2D hexagonal packing as a function of coupling strength as well as determined methods to move the system from one attractor basin to another. Current work involves implementing these attractor control methods with our experimental system and future work will likely include implementing a model neural network for use with photo controllable BZ emulsions.

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

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.

Metabotropic glutamate receptors activate dendritic calcium waves and TRPM channels which drive rhythmic respiratory patterns in mice

PubMed Central

Mironov, S L

2008-01-01

Respiration in vertebrates is generated by a compact network which is located in the lower brainstem but cellular mechanisms which underlie persistent oscillatory activity of the respiratory network are yet unknown. Using two-photon imaging and patch-clamp recordings in functional brainstem preparations of mice containing pre-Bötzinger complex (preBötC), we examined the actions of metabotropic glutamate receptors (mGluR1/5) on the respiratory patterns. The agonist DHPG potentiated and antagonist LY367385 depressed respiration-related activities. In the inspiratory neurons, we observed rhythmic activation of non-selective channels which had a conductance of 24 pS. Their activity was enhanced with membrane depolarization and after elevation of calcium from the cytoplasmic side of the membrane. They were activated by a non-hydrolysable PIP2 analogue and blocked by flufenamate, ATP4− and Gd3+. All these properties correspond well to those of TRPM4 channels. Calcium imaging of functional slices revealed rhythmic transients in small clusters of neurons present in a network. Calcium transients in the soma were preceded by the waves in dendrites which were dependent on mGluR activation. Initiation and propagation of waves required calcium influx and calcium release from internal stores. Calcium waves activated TPRM4-like channels in the soma and promoted generation of inspiratory bursts. Simulations of activity of neurons communicated via dendritic calcium waves showed emerging activity within neuronal clusters and its synchronization between the clusters. The experimental and theoretical data provide a subcellular basis for a recently proposed group-pacemaker hypothesis and describe a novel mechanism of rhythm generation in neuronal networks. PMID:18308826

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.

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...

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.

From Shortage to Surge: A Developmental Switch in Hippocampal–Prefrontal Coupling in a Gene–Environment Model of Neuropsychiatric Disorders

PubMed Central

Hartung, Henrike; Cichon, Nicole; De Feo, Vito; Riemann, Stephanie; Schildt, Sandra; Lindemann, Christoph; Mulert, Christoph; Gogos, Joseph A.; Hanganu-Opatz, Ileana L.

2016-01-01

Cognitive deficits represent a major burden of neuropsychiatric disorders and result in part from abnormal communication within hippocampal–prefrontal circuits. While it has been hypothesized that this network dysfunction arises during development, long before the first clinical symptoms, experimental evidence is still missing. Here, we show that pre-juvenile mice mimicking genetic and environmental risk factors of disease (dual-hit GE mice) have poorer recognition memory that correlates with augmented coupling by synchrony and stronger directed interactions between prefrontal cortex and hippocampus. The network dysfunction emerges already during neonatal development, yet it initially consists in a diminished hippocampal theta drive and consequently, a weaker and disorganized entrainment of local prefrontal circuits in discontinuous oscillatory activity in dual-hit GE mice when compared with controls. Thus, impaired maturation of functional communication within hippocampal–prefrontal networks switching from hypo- to hyper-coupling may represent a mechanism underlying the pathophysiology of cognitive deficits in neuropsychiatric disorders. PMID:27613435

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

Rhythmic Components in Extracranial Brain Signals Reveal Multifaceted Task Modulation of Overlapping Neuronal Activity

PubMed Central

van Ede, Freek; Maris, Eric

2016-01-01

Oscillatory neuronal activity is implicated in many cognitive functions, and its phase coupling between sensors may reflect networks of communicating neuronal populations. Oscillatory activity is often studied using extracranial recordings and compared between experimental conditions. This is challenging, because there is overlap between sensor-level activity generated by different sources, and this can obscure differential experimental modulations of these sources. Additionally, in extracranial data, sensor-level phase coupling not only reflects communicating populations, but can also be generated by a current dipole, whose sensor-level phase coupling does not reflect source-level interactions. We present a novel method, which is capable of separating and characterizing sources on the basis of their phase coupling patterns as a function of space, frequency and time (trials). Importantly, this method depends on a plausible model of a neurobiological rhythm. We present this model and an accompanying analysis pipeline. Next, we demonstrate our approach, using magnetoencephalographic (MEG) recordings during a cued tactile detection task as a case study. We show that the extracted components have overlapping spatial maps and frequency content, which are difficult to resolve using conventional pairwise measures. Because our decomposition also provides trial loadings, components can be readily contrasted between experimental conditions. Strikingly, we observed heterogeneity in alpha and beta sources with respect to whether their activity was suppressed or enhanced as a function of attention and performance, and this happened both in task relevant and irrelevant regions. This heterogeneity contrasts with the common view that alpha and beta amplitude over sensory areas are always negatively related to attention and performance. PMID:27336159

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.

Detecting Mild Traumatic Brain Injury Using Resting State Magnetoencephalographic Connectivity

PubMed Central

da Costa, Leodante; Jetly, Rakesh; Pang, Elizabeth W.; Taylor, Margot J.

2016-01-01

Accurate means to detect mild traumatic brain injury (mTBI) using objective and quantitative measures remain elusive. Conventional imaging typically detects no abnormalities despite post-concussive symptoms. In the present study, we recorded resting state magnetoencephalograms (MEG) from adults with mTBI and controls. Atlas-guided reconstruction of resting state activity was performed for 90 cortical and subcortical regions, and calculation of inter-regional oscillatory phase synchrony at various frequencies was performed. We demonstrate that mTBI is associated with reduced network connectivity in the delta and gamma frequency range (>30 Hz), together with increased connectivity in the slower alpha band (8–12 Hz). A similar temporal pattern was associated with correlations between network connectivity and the length of time between the injury and the MEG scan. Using such resting state MEG network synchrony we were able to detect mTBI with 88% accuracy. Classification confidence was also correlated with clinical symptom severity scores. These results provide the first evidence that imaging of MEG network connectivity, in combination with machine learning, has the potential to accurately detect and determine the severity of mTBI. PMID:27906973

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.

Mechanisms of deep brain stimulation

PubMed Central

Cheng, Jennifer J.; Eskandar, Emad N.

2015-01-01

Deep brain stimulation (DBS) is widely used for the treatment of movement disorders including Parkinson's disease, essential tremor, and dystonia and, to a lesser extent, certain treatment-resistant neuropsychiatric disorders including obsessive-compulsive disorder. Rather than a single unifying mechanism, DBS likely acts via several, nonexclusive mechanisms including local and network-wide electrical and neurochemical effects of stimulation, modulation of oscillatory activity, synaptic plasticity, and, potentially, neuroprotection and neurogenesis. These different mechanisms vary in importance depending on the condition being treated and the target being stimulated. Here we review each of these in turn and illustrate how an understanding of these mechanisms is inspiring next-generation approaches to DBS. PMID:26510756

State-Dependent Spike and Local Field Synchronization between Motor Cortex and Substantia Nigra in Hemiparkinsonian Rats

PubMed Central

Brazhnik, Elena; Cruz, Ana V.; Avila, Irene; Wahba, Marian I.; Novikov, Nikolay; Ilieva, Neda M.; McCoy, Alex J.; Gerber, Colin; Walters, Judith. R.

2012-01-01

Excessive beta frequency oscillatory and synchronized activity has been reported in the basal ganglia of Parkinsonian patients and animal models of the disease. To gain insight into processes underlying this activity, this study explores relationships between oscillatory activity in motor cortex and basal ganglia output in behaving rats after dopamine cell lesion. During inattentive rest, seven days after lesion, increases in motor cortex-substantia nigra pars reticulata (SNpr) coherence emerged in the 8–25 Hz range, with significant increases in local field potential (LFP) power in SNpr but not motor cortex. In contrast, during treadmill walking, marked increases in both motor cortex and SNpr LFP power, as well as coherence, emerged in the 25–40 Hz band with a peak frequency at 30–35 Hz. Spike-triggered waveform averages showed that 77% of SNpr neurons, 77% of putative cortical interneurons and 44% of putative pyramidal neurons were significantly phase-locked to the increased cortical LFP activity in the 25–40 Hz range. Although the mean lag between cortical and SNpr LFPs fluctuated around zero, SNpr neurons phase-locked to cortical LFP oscillations fired, on average, 17 ms after synchronized spiking in motor cortex. High coherence between LFP oscillations in cortex and SNpr supports the view that cortical activity facilitates entrainment and synchronization of activity in basal ganglia after loss of dopamine. However, the dramatic increases in cortical power and relative timing of phase-locked spiking in these areas suggest that additional processes help shape the frequency-specific tuning of the basal ganglia-thalamocortical network during ongoing motor activity. PMID:22674263

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...

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

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.

Genome-wide association analysis links multiple psychiatric liability genes to oscillatory brain activity.

PubMed

Smit, Dirk J A; Wright, Margaret J; Meyers, Jacquelyn L; Martin, Nicholas G; Ho, Yvonne Y W; Malone, Stephen M; Zhang, Jian; Burwell, Scott J; Chorlian, David B; de Geus, Eco J C; Denys, Damiaan; Hansell, Narelle K; Hottenga, Jouke-Jan; McGue, Matt; van Beijsterveldt, Catharina E M; Jahanshad, Neda; Thompson, Paul M; Whelan, Christopher D; Medland, Sarah E; Porjesz, Bernice; Lacono, William G; Boomsma, Dorret I

2018-06-26

Oscillatory activity is crucial for information processing in the brain, and has a long history as a biomarker for psychopathology. Variation in oscillatory activity is highly heritable, but current understanding of specific genetic influences remains limited. We performed the largest genome-wide association study to date of oscillatory power during eyes-closed resting electroencephalogram (EEG) across a range of frequencies (delta 1-3.75 Hz, theta 4-7.75 Hz, alpha 8-12.75 Hz, and beta 13-30 Hz) in 8,425 subjects. Additionally, we performed KGG positional gene-based analysis and brain-expression analyses. GABRA2-a known genetic marker for alcohol use disorder and epilepsy-significantly affected beta power, consistent with the known relation between GABA A interneuron activity and beta oscillations. Tissue-specific SNP-based imputation of gene-expression levels based on the GTEx database revealed that hippocampal GABRA2 expression may mediate this effect. Twenty-four genes at 3p21.1 were significant for alpha power (FDR q < .05). SNPs in this region were linked to expression of GLYCTK in hippocampal tissue, and GNL3 and ITIH4 in the frontal cortex-genes that were previously implicated in schizophrenia and bipolar disorder. In sum, we identified several novel genetic variants associated with oscillatory brain activity; furthermore, we replicated and advanced understanding of previously known genes associated with psychopathology (i.e., schizophrenia and alcohol use disorders). Importantly, these psychopathological liability genes affect brain functioning, linking the genes' expression to specific cortical/subcortical brain regions. © 2018 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

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

PubMed

Bathellier, Brice; Carleton, Alan; Gerstner, Wulfram

2008-12-01

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

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.

Shadows of Music-Language Interaction on Low Frequency Brain Oscillatory Patterns

ERIC Educational Resources Information Center

Carrus, Elisa; Koelsch, Stefan; Bhattacharya, Joydeep

2011-01-01

Electrophysiological studies investigating similarities between music and language perception have relied exclusively on the signal averaging technique, which does not adequately represent oscillatory aspects of electrical brain activity that are relevant for higher cognition. The current study investigated the patterns of brain 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 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.

Synthetic quorum sensing in model microcapsule colonies

NASA Astrophysics Data System (ADS)

Shum, Henry; Balazs, Anna C.

2017-08-01

Biological quorum sensing refers to the ability of cells to gauge their population density and collectively initiate a new behavior once a critical density is reached. Designing synthetic materials systems that exhibit quorum sensing-like behavior could enable the fabrication of devices with both self-recognition and self-regulating functionality. Herein, we develop models for a colony of synthetic microcapsules that communicate by producing and releasing signaling molecules. Production of the chemicals is regulated by a biomimetic negative feedback loop, the “repressilator” network. Through theory and simulation, we show that the chemical behavior of such capsules is sensitive to both the density and number of capsules in the colony. For example, decreasing the spacing between a fixed number of capsules can trigger a transition in chemical activity from the steady, repressed state to large-amplitude oscillations in chemical production. Alternatively, for a fixed density, an increase in the number of capsules in the colony can also promote a transition into the oscillatory state. This configuration-dependent behavior of the capsule colony exemplifies quorum-sensing behavior. Using our theoretical model, we predict the transitions from the steady state to oscillatory behavior as a function of the colony size and capsule density.

Emotions and stress increase respiratory resistance in asthma.

PubMed

Ritz, T; Steptoe, A; DeWilde, S; Costa, M

2000-01-01

Clinical reports suggest that various emotions and types of stress can precipitate asthmatic symptoms, but there is little experimental evidence to substantiate this claim. We studied the impact of different emotional states and stress on respiratory resistance in asthmatic and nonasthmatic individuals. Participants (24 asthmatic and 24 nonasthmatic patients) viewed short film sequences selected to induce anxiety, anger, depression, elation, happiness, contentment, or a neutral affective state and completed two stressful tasks, mental arithmetic to induce active coping efforts and viewing of medical slides to induce passive coping efforts. Oscillatory resistance, heart rate, blood pressure, baroreflex sensitivity, skin conductance level, respiration rate and volume, and self-reported affective state were measured throughout the session. Uniform increases in oscillatory resistance were found in all emotional states compared with the neutral state and during mental arithmetic in both groups. Asthmatic patients showed stronger reactions to the medical slides than healthy control subjects, with significant increases in oscillatory resistance, blood pressure, skin conductance level, and minute volume, as well as higher levels of self-reported depression, arousal, and shortness of breath. Changes in oscillatory resistance were inconsistently correlated with other physiological indices. Various emotional states and stress increase oscillatory resistance largely independently of concurrent increases in autonomic or ventilatory activity. The particular sensitivity of asthmatics to passive coping demand requires additional research.

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…

Resting-State Oscillatory Activity in Autism Spectrum Disorders

ERIC Educational Resources Information Center

Cornew, Lauren; Roberts, Timothy P. L.; Blaskey, Lisa; Edgar, J. Christopher

2012-01-01

Neural oscillatory anomalies in autism spectrum disorders (ASD) suggest an excitatory/inhibitory imbalance; however, the nature and clinical relevance of these anomalies are unclear. Whole-cortex magnetoencephalography data were collected while 50 children (27 with ASD, 23 controls) underwent an eyes-closed resting-state exam. A Fast Fourier…

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

PubMed

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

2013-01-01

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

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.

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.

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.

Motor cortex synchronization influences the rhythm of motor performance in premanifest huntington's disease.

PubMed

Casula, Elias P; Mayer, Isabella M S; Desikan, Mahalekshmi; Tabrizi, Sarah J; Rothwell, John C; Orth, Michael

2018-03-01

In Huntington's disease there is evidence of structural damage in the motor system, but it is still unclear how to link this to the behavioral disorder of movement. One feature of choreic movement is variable timing and coordination between sequences of actions. We postulate this results from desynchronization of neural activity in cortical motor areas. The objective of this study was to explore the ability to synchronize activity in a motor network using transcranial magnetic stimulation and to relate this to timing of motor performance. We examined synchronization in oscillatory activity of cortical motor areas in response to an external input produced by a pulse of transcranial magnetic stimulation. We combined this with EEG to compare the response of 16 presymptomatic Huntington's disease participants with 16 age-matched healthy volunteers to test whether the strength of synchronization relates to the variability of motor performance at the following 2 tasks: a grip force task and a speeded-tapping task. Phase synchronization in response to M1 stimulation was lower in Huntington's disease than healthy volunteers (P < .01), resulting in a reduced cortical activity at global (P < .02) and local levels (P < .01). Participants who showed better timed motor performance also showed stronger oscillatory synchronization (r = -0.356; P < .05) and higher cortical activity (r = -0.393; P < .05). Our data may model the ability of the motor command to respond to more subtle, physiological inputs from other brain areas. This novel insight indicates that impairments of the timing accuracy of synchronization and desynchronization could be a physiological basis for some key clinical features of Huntington's disease. © 2018 International Parkinson and Movement Disorder Society. © 2018 International Parkinson and Movement Disorder Society.

Subthalamic Synchronized Oscillatory Activity Correlates With Motor Impairment in Patients With Parkinson’s Disease

PubMed Central

Neumann, Wolf-Julian; Degen, Katharina; Schneider, Gerd-Helge; Brücke, Christof; Huebl, Julius; Brown, Peter; Kühn, Andrea A.

2016-01-01

Objective Beta band oscillations in the subthalamic nucleus (STN) have been proposed as a pathophysiological signature in patients with Parkinson’s disease (PD). The aim of this study was to investigate the potential association between oscillatory activity in the STN and symptom severity in PD. Methods Subthalamic local field potentials were recorded from 63 PD patients in a dopaminergic OFF state. Power-spectra were analyzed for the frequency range from 5 to 95 Hz and correlated with individual UPDRS-III motor scores in the OFF state. Results A correlation between total UPDRS-III scores and 8 to 35 Hz activity was revealed across all patients (ρ = 0.44, P <.0001). When correlating each frequency bin, a narrow range from 10 to 15 Hz remained significant for the correlation (false discovery rate corrected P <.05). Conclusion Our results show a correlation between local STN 8 to 35 Hz power and impairment in PD, further supporting the role of subthalamic oscillatory activity as a potential biomarker for PD. PMID:27548068

Reversing pathologically increased EEG power by acoustic coordinated reset neuromodulation

PubMed Central

Adamchic, Ilya; Toth, Timea; Hauptmann, Christian; Tass, Peter Alexander

2014-01-01

Acoustic Coordinated Reset (CR) neuromodulation is a patterned stimulation with tones adjusted to the patient's dominant tinnitus frequency, which aims at desynchronizing pathological neuronal synchronization. In a recent proof-of-concept study, CR therapy, delivered 4–6 h/day more than 12 weeks, induced a significant clinical improvement along with a significant long-lasting decrease of pathological oscillatory power in the low frequency as well as γ band and an increase of the α power in a network of tinnitus-related brain areas. As yet, it remains unclear whether CR shifts the brain activity toward physiological levels or whether it induces clinically beneficial, but nonetheless abnormal electroencephalographic (EEG) patterns, for example excessively decreased δ and/or γ. Here, we compared the patients' spontaneous EEG data at baseline as well as after 12 weeks of CR therapy with the spontaneous EEG of healthy controls by means of Brain Electrical Source Analysis source montage and standardized low-resolution brain electromagnetic tomography techniques. The relationship between changes in EEG power and clinical scores was investigated using a partial least squares approach. In this way, we show that acoustic CR neuromodulation leads to a normalization of the oscillatory power in the tinnitus-related network of brain areas, most prominently in temporal regions. A positive association was found between the changes in tinnitus severity and the normalization of δ and γ power in the temporal, parietal, and cingulate cortical regions. Our findings demonstrate a widespread CR-induced normalization of EEG power, significantly associated with a reduction of tinnitus severity. PMID:23907785

The predictive roles of neural oscillations in speech motor adaptability.

PubMed

Sengupta, Ranit; Nasir, Sazzad M

2016-06-01

The human speech system exhibits a remarkable flexibility by adapting to alterations in speaking environments. While it is believed that speech motor adaptation under altered sensory feedback involves rapid reorganization of speech motor networks, the mechanisms by which different brain regions communicate and coordinate their activity to mediate adaptation remain unknown, and explanations of outcome differences in adaption remain largely elusive. In this study, under the paradigm of altered auditory feedback with continuous EEG recordings, the differential roles of oscillatory neural processes in motor speech adaptability were investigated. The predictive capacities of different EEG frequency bands were assessed, and it was found that theta-, beta-, and gamma-band activities during speech planning and production contained significant and reliable information about motor speech adaptability. It was further observed that these bands do not work independently but interact with each other suggesting an underlying brain network operating across hierarchically organized frequency bands to support motor speech adaptation. These results provide novel insights into both learning and disorders of speech using time frequency analysis of neural oscillations. Copyright © 2016 the American Physiological Society.

Aging transition in systems of oscillators with global distributed-delay coupling.

PubMed

Rahman, B; Blyuss, K B; Kyrychko, Y N

2017-09-01

We consider a globally coupled network of active (oscillatory) and inactive (nonoscillatory) oscillators with distributed-delay coupling. Conditions for aging transition, associated with suppression of oscillations, are derived for uniform and gamma delay distributions in terms of coupling parameters and the proportion of inactive oscillators. The results suggest that for the uniform distribution increasing the width of distribution for the same mean delay allows aging transition to happen for a smaller coupling strength and a smaller proportion of inactive elements. For gamma distribution with sufficiently large mean time delay, it may be possible to achieve aging transition for an arbitrary proportion of inactive oscillators, as long as the coupling strength lies in a certain range.

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

NASA Astrophysics Data System (ADS)

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

2011-08-01

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

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…

Modulation of short-term plasticity in the corticothalamic circuit by group III metabotropic glutamate receptors.

PubMed

Kyuyoung, Christine L; Huguenard, John R

2014-01-08

Recurrent connections in the corticothalamic circuit underlie oscillatory behavior in this network and range from normal sleep rhythms to the abnormal spike-wave discharges seen in absence epilepsy. The propensity of thalamic neurons to fire postinhibitory rebound bursts mediated by low-threshold calcium spikes renders the circuit vulnerable to both increased excitation and increased inhibition, such as excessive excitatory cortical drive to thalamic reticular (RT) neurons or heightened inhibition of thalamocortical relay (TC) neurons by RT. In this context, a protective role may be played by group III metabotropic receptors (mGluRs), which are uniquely located in the presynaptic active zone and typically act as autoreceptors or heteroceptors to depress synaptic release. Here, we report that these receptors regulate short-term plasticity at two loci in the corticothalamic circuit in rats: glutamatergic cortical synapses onto RT neurons and GABAergic synapses onto TC neurons in somatosensory ventrobasal thalamus. The net effect of group III mGluR activation at these synapses is to suppress thalamic oscillations as assayed in vitro. These findings suggest a functional role of these receptors to modulate corticothalamic transmission and protect against prolonged activity in the network.

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

The Electro-Oxidation of Ethylene Glycol on Platinum over a Wide pH Range: Oscillations and Temperature Effects

PubMed Central

Sitta, Elton; Nagao, Raphael; Varela, Hamilton

2013-01-01

We report a comprehensive study of the electro-oxidation of ethylene glycol (EG) on platinum with emphasis on the effects exerted by the electrolyte pH, the EG concentration, and temperature, under both regular and oscillatory conditions. We extracted and discussed parameters such as voltammetric activity, reaction orders (with respect to [EG]), oscillation’s amplitude, frequency and waveform, and the evolution of the mean electrode potential at six pH values from 0 to 14. In addition, we obtained the apparent activation energies under several different conditions. Overall, we observed that increasing the electrolyte pH results in a discontinuous transition in most properties studied under both voltammetric and oscillatory regimes. As a relevant result in this direction, we found that the increase in the reaction order with pH is mediated by a minimum (~ 0) at pH = 12. Furthermore, the solution pH strongly affects all features investigated, c.f. the considerable increase in the oscillatory frequency and the decrease in the, oscillatory, activation energy as the pH increase. We suggest that adsorbed CO is probably the main surface-blocking species at low pH, and its absence at high pH is likely to be the main reason behind the differences observed. The size of the parameter region investigated and the amount of comparable parameters and properties presented in this study, as well as the discussion that followed illustrate the strategy of combining investigations under conventional and oscillatory regimes of electrocatalytic systems. PMID:24058650

Combining in silico evolution and nonlinear dimensionality reduction to redesign responses of signaling networks

NASA Astrophysics Data System (ADS)

Prescott, Aaron M.; Abel, Steven M.

2016-12-01

The rational design of network behavior is a central goal of synthetic biology. Here, we combine in silico evolution with nonlinear dimensionality reduction to redesign the responses of fixed-topology signaling networks and to characterize sets of kinetic parameters that underlie various input-output relations. We first consider the earliest part of the T cell receptor (TCR) signaling network and demonstrate that it can produce a variety of input-output relations (quantified as the level of TCR phosphorylation as a function of the characteristic TCR binding time). We utilize an evolutionary algorithm (EA) to identify sets of kinetic parameters that give rise to: (i) sigmoidal responses with the activation threshold varied over 6 orders of magnitude, (ii) a graded response, and (iii) an inverted response in which short TCR binding times lead to activation. We also consider a network with both positive and negative feedback and use the EA to evolve oscillatory responses with different periods in response to a change in input. For each targeted input-output relation, we conduct many independent runs of the EA and use nonlinear dimensionality reduction to embed the resulting data for each network in two dimensions. We then partition the results into groups and characterize constraints placed on the parameters by the different targeted response curves. Our approach provides a way (i) to guide the design of kinetic parameters of fixed-topology networks to generate novel input-output relations and (ii) to constrain ranges of biological parameters using experimental data. In the cases considered, the network topologies exhibit significant flexibility in generating alternative responses, with distinct patterns of kinetic rates emerging for different targeted responses.

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.

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.

Oscillatory lower body negative pressure impairs working memory task-related functional hyperemia in healthy volunteers.

PubMed

Merchant, Sana; Medow, Marvin S; Visintainer, Paul; Terilli, Courtney; Stewart, Julian M

2017-04-01

Neurovascular coupling (NVC) describes the link between an increase in task-related neural activity and increased cerebral blood flow denoted "functional hyperemia." We previously showed induced cerebral blood flow oscillations suppressed functional hyperemia; conversely functional hyperemia also suppressed cerebral blood flow oscillations. We used lower body negative pressure (OLBNP) oscillations to force oscillations in middle cerebral artery cerebral blood flow velocity (CBFv). Here, we used N-back testing, an intellectual memory challenge as a neural activation task, to test the hypothesis that OLBNP-induced oscillatory cerebral blood flow can reduce functional hyperemia and NVC produced by a working memory task and can interfere with working memory. We used OLBNP (-30 mmHg) at 0.03, 0.05, and 0.10 Hz and measured spectral power of CBFv at all frequencies. Neither OLBNP nor N-back, alone or combined, affected hemodynamic parameters. 2-Back power and OLBNP individually were compared with 2-back power during OLBNP. 2-Back alone produced a narrow band increase in oscillatory arterial pressure (OAP) and oscillatory cerebral blood flow power centered at 0.0083 Hz. Functional hyperemia in response to 2-back was reduced to near baseline and 2-back memory performance was decreased by 0.03-, 0.05-, and 0.10-Hz OLBNP. OLBNP alone produced increased oscillatory power at frequencies of oscillation not suppressed by added 2-back. However, 2-back preceding OLBNP suppressed OLBNP power. OLBNP-driven oscillatory CBFv blunts NVC and memory performance, while memory task reciprocally interfered with forced CBFv oscillations. This shows that induced cerebral blood flow oscillations suppress functional hyperemia and functional hyperemia suppresses cerebral blood flow oscillations. NEW & NOTEWORTHY We show that induced cerebral blood flow oscillations suppress functional hyperemia produced by a working memory task as well as memory task performance. We conclude that oscillatory cerebral blood flow produces causal reductions of memory task neurovascular coupling and memory task performance. Reductions of functional hyperemia are constrained by autoregulation. Copyright © 2017 the American Physiological Society.

Contribution of near-threshold currents to intrinsic oscillatory activity in rat medial entorhinal cortex layer II stellate cells

PubMed Central

Boehlen, Anne; Henneberger, Christian; Erchova, Irina

2013-01-01

The temporal lobe is well known for its oscillatory activity associated with exploration, navigation, and learning. Intrinsic membrane potential oscillations (MPOs) and resonance of stellate cells (SCs) in layer II of the entorhinal cortex are thought to contribute to network oscillations and thereby to the encoding of spatial information. Generation of both MPOs and resonance relies on the expression of specific voltage-dependent ion currents such as the hyperpolarization-activated cation current (IH), the persistent sodium current (INaP), and the noninactivating muscarine-modulated potassium current (IM). However, the differential contributions of these currents remain a matter of debate. We therefore examined how they modify neuronal excitability near threshold and generation of near-threshold MPOs and resonance in vitro. We found that resonance mainly relied on IH and was reduced by IH blockers and modulated by cAMP and an IM enhancer but that neither of the currents exhibited full control over MPOs in these cells. As previously reported, IH controlled a theta-frequency component of MPOs such that blockade of IH resulted in fewer regular oscillations that retained low-frequency components and high peak amplitude. However, pharmacological inhibition and augmentation of IM also affected MPO frequencies and amplitudes. In contrast to other cell types, inhibition of INaP did not result in suppression of MPOs but only in a moderation of their properties. We reproduced the experimentally observed effects in a single-compartment stochastic model of SCs, providing further insight into the interactions between different ionic conductances. PMID:23076110

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.

Desynchronization of slow oscillations in the basal ganglia during natural sleep.

PubMed

Mizrahi-Kliger, Aviv D; Kaplan, Alexander; Israel, Zvi; Bergman, Hagai

2018-05-01

Slow oscillations of neuronal activity alternating between firing and silence are a hallmark of slow-wave sleep (SWS). These oscillations reflect the default activity present in all mammalian species, and are ubiquitous to anesthesia, brain slice preparations, and neuronal cultures. In all these cases, neuronal firing is highly synchronous within local circuits, suggesting that oscillation-synchronization coupling may be a governing principle of sleep physiology regardless of anatomical connectivity. To investigate whether this principle applies to overall brain organization, we recorded the activity of individual neurons from basal ganglia (BG) structures and the thalamocortical (TC) network over 70 full nights of natural sleep in two vervet monkeys. During SWS, BG neurons manifested slow oscillations (∼0.5 Hz) in firing rate that were as prominent as in the TC network. However, in sharp contrast to any neural substrate explored thus far, the slow oscillations in all BG structures were completely desynchronized between individual neurons. Furthermore, whereas in the TC network single-cell spiking was locked to slow oscillations in the local field potential (LFP), the BG LFP exhibited only weak slow oscillatory activity and failed to entrain nearby cells. We thus show that synchrony is not inherent to slow oscillations, and propose that the BG desynchronization of slow oscillations could stem from its unique anatomy and functional connectivity. Finally, we posit that BG slow-oscillation desynchronization may further the reemergence of slow-oscillation traveling waves from multiple independent origins in the frontal cortex, thus significantly contributing to normal SWS.

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

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.

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

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.

EEG-Informed fMRI Reveals a Disturbed Gamma-Band–Specific Network in Subjects at High Risk for Psychosis

PubMed Central

Leicht, Gregor; Vauth, Sebastian; Polomac, Nenad; Andreou, Christina; Rauh, Jonas; Mußmann, Marius; Karow, Anne; Mulert, Christoph

2016-01-01

Objectives. Abnormalities of oscillatory gamma activity are supposed to reflect a core pathophysiological mechanism underlying cognitive disturbances in schizophrenia. The auditory evoked gamma-band response (aeGBR) is known to be reduced across all stages of the disease. The present study aimed to elucidate alterations of an aeGBR-specific network mediated by gamma oscillations in the high-risk state of psychosis (HRP) by means of functional magnetic resonance imaging (fMRI) informed by electroencephalography (EEG). Methods. EEG and fMRI were simultaneously recorded from 27 HRP individuals and 26 healthy controls (HC) during performance of a cognitively demanding auditory reaction task. We used single trial coupling of the aeGBR with the corresponding blood oxygen level depending response (EEG-informed fMRI). Results. A gamma-band–specific network was significantly lower active in HRP subjects compared with HC (random effects analysis, P < .01, Bonferroni-corrected for multiple comparisons) accompanied by a worse task performance. This network involved the bilateral auditory cortices, the thalamus and frontal brain regions including the anterior cingulate cortex, as well as the bilateral dorsolateral prefrontal cortex. Conclusions. For the first time we report a reduced activation of an aeGBR-specific network in HRP subjects brought forward by EEG-informed fMRI. Because the HRP reflects the clinical risk for conversion to psychotic disorders including schizophrenia and the aeGBR has repeatedly been shown to be altered in patients with schizophrenia the results of our study point towards a potential applicability of aeGBR disturbances as a marker for the prediction of transition of HRP subjects to schizophrenia. PMID:26163477

EEG-Informed fMRI Reveals a Disturbed Gamma-Band-Specific Network in Subjects at High Risk for Psychosis.

PubMed

Leicht, Gregor; Vauth, Sebastian; Polomac, Nenad; Andreou, Christina; Rauh, Jonas; Mußmann, Marius; Karow, Anne; Mulert, Christoph

2016-01-01

Abnormalities of oscillatory gamma activity are supposed to reflect a core pathophysiological mechanism underlying cognitive disturbances in schizophrenia. The auditory evoked gamma-band response (aeGBR) is known to be reduced across all stages of the disease. The present study aimed to elucidate alterations of an aeGBR-specific network mediated by gamma oscillations in the high-risk state of psychosis (HRP) by means of functional magnetic resonance imaging (fMRI) informed by electroencephalography (EEG). EEG and fMRI were simultaneously recorded from 27 HRP individuals and 26 healthy controls (HC) during performance of a cognitively demanding auditory reaction task. We used single trial coupling of the aeGBR with the corresponding blood oxygen level depending response (EEG-informed fMRI). A gamma-band-specific network was significantly lower active in HRP subjects compared with HC (random effects analysis, P < .01, Bonferroni-corrected for multiple comparisons) accompanied by a worse task performance. This network involved the bilateral auditory cortices, the thalamus and frontal brain regions including the anterior cingulate cortex, as well as the bilateral dorsolateral prefrontal cortex. For the first time we report a reduced activation of an aeGBR-specific network in HRP subjects brought forward by EEG-informed fMRI. Because the HRP reflects the clinical risk for conversion to psychotic disorders including schizophrenia and the aeGBR has repeatedly been shown to be altered in patients with schizophrenia the results of our study point towards a potential applicability of aeGBR disturbances as a marker for the prediction of transition of HRP subjects to schizophrenia. © The Author 2015. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center.

Dopamine Induces Oscillatory Activities in Human Midbrain Neurons with Parkin Mutations.

PubMed

Zhong, Ping; Hu, Zhixing; Jiang, Houbo; Yan, Zhen; Feng, Jian

2017-05-02

Locomotor symptoms in Parkinson's disease (PD) are accompanied by widespread oscillatory neuronal activities in basal ganglia. Here, we show that activation of dopamine D1-class receptors elicits a large rhythmic bursting of spontaneous excitatory postsynaptic currents (sEPSCs) in midbrain neurons differentiated from induced pluripotent stem cells (iPSCs) of PD patients with parkin mutations, but not normal subjects. Overexpression of wild-type parkin, but not its PD-causing mutant, abolishes the oscillatory activities in patient neurons. Dopamine induces a delayed enhancement in the amplitude of spontaneous, but not miniature, EPSCs, thus increasing quantal content. The results suggest that presynaptic regulation of glutamatergic transmission by dopamine D1-class receptors is significantly potentiated by parkin mutations. The aberrant dopaminergic regulation of presynaptic glutamatergic transmission in patient-specific iPSC-derived midbrain neurons provides a mechanistic clue to PD pathophysiology, and it demonstrates the usefulness of this model system in understanding how mutations of parkin cause movement symptoms in Parkinson's disease. Copyright © 2017 The Author(s). Published by Elsevier Inc. All rights reserved.

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.

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.

Paradoxical Expectation: Oscillatory Brain Activity Reveals Social Interaction Impairment in Schizophrenia.

PubMed

Billeke, Pablo; Armijo, Alejandra; Castillo, Daniel; López, Tamara; Zamorano, Francisco; Cosmelli, Diego; Aboitiz, Francisco

2015-09-15

People with schizophrenia show social impairments that are related to functional outcomes. We tested the hypothesis that social interaction impairments in people with schizophrenia are related to alterations in the predictions of others' behavior and explored their underlying neurobiological mechanisms. Electroencephalography was performed in 20 patients with schizophrenia and 25 well-matched control subjects. Participants played as proposers in the repeated version of the Ultimatum Game believing that they were playing with another human or with a computer. The power of oscillatory brain activity was obtained by means of the wavelet transform. We performed a trial-by-trial correlation between the oscillatory activity and the risk of the offer. Control subjects adapted their offers when playing with computers and tended to maintain their offers when playing with humans, as such revealing learning and bargaining strategies, respectively. People with schizophrenia presented the opposite pattern of behavior in both games. During the anticipation of others' responses, the power of alpha oscillations correlated with the risk of the offers made, in a different way in both games. Patients with schizophrenia presented a greater correlation in computer games than in human games; control subjects showed the opposite pattern. The alpha activity correlated with positive symptoms. Our results reveal an alteration in social interaction in patients with schizophrenia that is related to oscillatory brain activity, suggesting maladjustment of expectation when patients face social and nonsocial agents. This alteration is related to psychotic symptoms and could guide further therapies for improving social functioning in patients with schizophrenia. Copyright © 2015 Society of Biological Psychiatry. Published by Elsevier Inc. 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.

Role of slow oscillatory activity and slow wave sleep in consolidation of episodic-like memory in rats.

PubMed

Oyanedel, Carlos N; Binder, Sonja; Kelemen, Eduard; Petersen, Kimberley; Born, Jan; Inostroza, Marion

2014-12-15

Our previous experiments showed that sleep in rats enhances consolidation of hippocampus dependent episodic-like memory, i.e. the ability to remember an event bound into specific spatio-temporal context. Here we tested the hypothesis that this enhancing effect of sleep is linked to the occurrence of slow oscillatory and spindle activity during slow wave sleep (SWS). Rats were tested on an episodic-like memory task and on three additional tasks covering separately the where (object place recognition), when (temporal memory), and what (novel object recognition) components of episodic memory. In each task, the sample phase (encoding) was followed by an 80-min retention interval that covered either a period of regular morning sleep or sleep deprivation. Memory during retrieval was tested using preferential exploration of novelty vs. familiarity. Consistent with previous findings, the rats which had slept during the retention interval showed significantly stronger episodic-like memory and spatial memory, and a trend of improved temporal memory (although not significant). Object recognition memory was similarly retained across sleep and sleep deprivation retention intervals. Recall of episodic-like memory was associated with increased slow oscillatory activity (0.85-2.0Hz) during SWS in the retention interval. Spatial memory was associated with increased proportions of SWS. Against our hypothesis, a relationship between spindle activity and episodic-like memory performance was not detected, but spindle activity was associated with object recognition memory. The results provide support for the role of SWS and slow oscillatory activity in consolidating hippocampus-dependent memory, the role of spindles in this process needs to be further examined. Copyright © 2014 The Authors. Published by Elsevier B.V. All rights reserved.

Gender agreement violations modulate beta oscillatory dynamics during sentence comprehension: A comparison of second language learners and native speakers.

PubMed

Lewis, Ashley Glen; Lemhӧfer, Kristin; Schoffelen, Jan-Mathijs; Schriefers, Herbert

2016-08-01

For native speakers, many studies suggest a link between oscillatory neural activity in the beta frequency range and syntactic processing. For late second language (L2) learners on the other hand, the extent to which the neural architecture supporting syntactic processing is similar to or different from that of native speakers is still unclear. In a series of four experiments, we used electroencephalography to investigate the link between beta oscillatory activity and the processing of grammatical gender agreement in Dutch determiner-noun pairs, for Dutch native speakers, and for German L2 learners of Dutch. In Experiment 1 we show that for native speakers, grammatical gender agreement violations are yet another among many syntactic factors that modulate beta oscillatory activity during sentence comprehension. Beta power is higher for grammatically acceptable target words than for those that mismatch in grammatical gender with their preceding determiner. In Experiment 2 we observed no such beta modulations for L2 learners, irrespective of whether trials were sorted according to objective or subjective syntactic correctness. Experiment 3 ruled out that the absence of a beta effect for the L2 learners in Experiment 2 was due to repetition of the target nouns in objectively correct and incorrect determiner-noun pairs. Finally, Experiment 4 showed that when L2 learners are required to explicitly focus on grammatical information, they show modulations of beta oscillatory activity, comparable to those of native speakers, but only when trials are sorted according to participants' idiosyncratic lexical representations of the grammatical gender of target nouns. Together, these findings suggest that beta power in L2 learners is sensitive to violations of grammatical gender agreement, but only when the importance of grammatical information is highlighted, and only when participants' subjective lexical representations are taken into account. Copyright © 2016 Elsevier Ltd. All rights reserved.

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

Memory improvement via slow-oscillatory stimulation during sleep in older adults.

PubMed

Westerberg, Carmen E; Florczak, Susan M; Weintraub, Sandra; Mesulam, M-Marsel; Marshall, Lisa; Zee, Phyllis C; Paller, Ken A

2015-09-01

We examined the intriguing but controversial idea that disrupted sleep-dependent consolidation contributes to age-related memory decline. Slow-wave activity during sleep may help strengthen neural connections and provide memories with long-term stability, in which case decreased slow-wave activity in older adults could contribute to their weaker memories. One prediction from this account is that age-related memory deficits should be reduced by artificially enhancing slow-wave activity. In young adults, applying transcranial current oscillating at a slow frequency (0.75 Hz) during sleep improves memory. Here, we tested whether this procedure can improve memory in older adults. In 2 sessions separated by 1 week, we applied either slow-oscillatory stimulation or sham stimulation during an afternoon nap in a double-blind, crossover design. Memory tests were administered before and after sleep. A larger improvement in word-pair recall and higher slow-wave activity was observed with slow-oscillatory stimulation than with sham stimulation. This is the first demonstration that this procedure can improve memory in older adults, suggesting that declarative memory performance in older adults is partly dependent on slow-wave activity during sleep. Copyright © 2015 Elsevier Inc. All rights reserved.

Neuroimaging and Neuromodulation: Complementary Approaches for Identifying the Neuronal Correlates of Tinnitus

PubMed Central

Langguth, Berthold; Schecklmann, Martin; Lehner, Astrid; Landgrebe, Michael; Poeppl, Timm Benjamin; Kreuzer, Peter Michal; Schlee, Winfried; Weisz, Nathan; Vanneste, Sven; De Ridder, Dirk

2012-01-01

An inherent limitation of functional imaging studies is their correlational approach. More information about critical contributions of specific brain regions can be gained by focal transient perturbation of neural activity in specific regions with non-invasive focal brain stimulation methods. Functional imaging studies have revealed that tinnitus is related to alterations in neuronal activity of central auditory pathways. Modulation of neuronal activity in auditory cortical areas by repetitive transcranial magnetic stimulation (rTMS) can reduce tinnitus loudness and, if applied repeatedly, exerts therapeutic effects, confirming the relevance of auditory cortex activation for tinnitus generation and persistence. Measurements of oscillatory brain activity before and after rTMS demonstrate that the same stimulation protocol has different effects on brain activity in different patients, presumably related to interindividual differences in baseline activity in the clinically heterogeneous study cohort. In addition to alterations in auditory pathways, imaging techniques also indicate the involvement of non-auditory brain areas, such as the fronto-parietal “awareness” network and the non-tinnitus-specific distress network consisting of the anterior cingulate cortex, anterior insula, and amygdale. Involvement of the hippocampus and the parahippocampal region putatively reflects the relevance of memory mechanisms in the persistence of the phantom percept and the associated distress. Preliminary studies targeting the dorsolateral prefrontal cortex, the dorsal anterior cingulate cortex, and the parietal cortex with rTMS and with transcranial direct current stimulation confirm the relevance of the mentioned non-auditory networks. Available data indicate the important value added by brain stimulation as a complementary approach to neuroimaging for identifying the neuronal correlates of the various clinical aspects of tinnitus. PMID:22509155

Sing the mind electric - principles of deep brain stimulation.

PubMed

Kringelbach, Morten L; Green, Alexander L; Owen, Sarah L F; Schweder, Patrick M; Aziz, Tipu Z

2010-10-01

The remarkable efficacy of deep brain stimulation (DBS) for a range of treatment-resistant disorders is still not matched by a comparable understanding of the underlying neural mechanisms. Some progress has been made using translational research with a range of neuroscientific techniques, and here we review the most promising emerging principles. On balance, DBS appears to work by restoring normal oscillatory activity between a network of key brain regions. Further research using this causal neuromodulatory tool may provide vital insights into fundamental brain function, as well as guide targets for future treatments. In particular, DBS could have an important role in restoring the balance of the brain's default network and thus repairing the malignant brain states associated with affective disorders, which give rise to serious disabling problems such as anhedonia, the lack of pleasure. At the same time, it is important to proceed with caution and not repeat the errors from the era of psychosurgery. © 2010 The Authors. European Journal of Neuroscience © 2010 Federation of European Neuroscience Societies and Blackwell Publishing Ltd.

Theta and Alpha Oscillations Are Traveling Waves in the Human Neocortex.

PubMed

Zhang, Honghui; Watrous, Andrew J; Patel, Ansh; Jacobs, Joshua

2018-06-01

Human cognition requires the coordination of neural activity across widespread brain networks. Here, we describe a new mechanism for large-scale coordination in the human brain: traveling waves of theta and alpha oscillations. Examining direct brain recordings from neurosurgical patients performing a memory task, we found contiguous clusters of cortex in individual patients with oscillations at specific frequencies within 2 to 15 Hz. These oscillatory clusters displayed spatial phase gradients, indicating that they formed traveling waves that propagated at ∼0.25-0.75 m/s. Traveling waves were relevant behaviorally because their propagation correlated with task events and was more consistent when subjects performed the task well. Human traveling theta and alpha waves can be modeled by a network of coupled oscillators because the direction of wave propagation correlated with the spatial orientation of local frequency gradients. Our findings suggest that oscillations support brain connectivity by organizing neural processes across space and time. Copyright © 2018 Elsevier Inc. All rights reserved.

Contractile and chiral activities codetermine the helicity of swimming droplet trajectories

NASA Astrophysics Data System (ADS)

Tjhung, Elsen; Cates, Michael E.; Marenduzzo, Davide

2017-05-01

Active fluids are a class of nonequilibrium systems where energy is injected into the system continuously by the constituent particles themselves. Many examples, such as bacterial suspensions and actomyosin networks, are intrinsically chiral at a local scale, so that their activity involves torque dipoles alongside the force dipoles usually considered. Although many aspects of active fluids have been studied, the effects of chirality on them are much less known. Here, we study by computer simulation the dynamics of an unstructured droplet of chiral active fluid in three dimensions. Our model considers only the simplest possible combination of chiral and achiral active stresses, yet this leads to an unprecedented range of complex motilities, including oscillatory swimming, helical swimming, and run-and-tumble motion. Strikingly, whereas the chirality of helical swimming is the same as the microscopic chirality of torque dipoles in one regime, the two are opposite in another. Some of the features of these motility modes resemble those of some single-celled protozoa, suggesting that underlying mechanisms may be shared by some biological systems and synthetic active droplets.

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.

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

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…

Localizing epileptic seizure onsets with Granger causality

NASA Astrophysics Data System (ADS)

Adhikari, Bhim M.; Epstein, Charles M.; Dhamala, Mukesh

2013-09-01

Accurate localization of the epileptic seizure onset zones (SOZs) is crucial for successful surgery, which usually depends on the information obtained from intracranial electroencephalography (IEEG) recordings. The visual criteria and univariate methods of analyzing IEEG recordings have not always produced clarity on the SOZs for resection and ultimate seizure freedom for patients. Here, to contribute to improving the localization of the SOZs and to understanding the mechanism of seizure propagation over the brain, we applied spectral interdependency methods to IEEG time series recorded from patients during seizures. We found that the high-frequency (>80 Hz) Granger causality (GC) occurs before the onset of any visible ictal activity and causal relationships involve the recording electrodes where clinically identifiable seizures later develop. These results suggest that high-frequency oscillatory network activities precede and underlie epileptic seizures, and that GC spectral measures derived from IEEG can assist in precise delineation of seizure onset times and SOZs.

Anti-Stress, Behavioural and Magnetoencephalography Effects of an L-Theanine-Based Nutrient Drink: A Randomised, Double-Blind, Placebo-Controlled, Crossover Trial.

PubMed

White, David J; de Klerk, Suzanne; Woods, William; Gondalia, Shakuntla; Noonan, Chris; Scholey, Andrew B

2016-01-19

L-theanine (γ-glutamylethylamide) is an amino acid found primarily in the green tea plant. This study explored the effects of an L-theanine-based nutrient drink on mood responses to a cognitive stressor. Additional measures included an assessment of cognitive performance and resting state alpha oscillatory activity using magnetoencephalography (MEG). Thirty-four healthy adults aged 18-40 participated in this double-blind, placebo-controlled, balanced crossover study. The primary outcome measure, subjective stress response to a multitasking cognitive stressor, was significantly reduced one hour after administration of the L-theanine drink when compared to placebo. The salivary cortisol response to the stressor was reduced three hours post-dose following active treatment. No treatment-related cognitive performance changes were observed. Resting state alpha oscillatory activity was significantly greater in posterior MEG sensors after active treatment compared to placebo two hours post-dose; however, this effect was only apparent for those higher in trait anxiety. This change in resting state alpha oscillatory activity was not correlated with the change in subjective stress response or the cortisol response, suggesting further research is required to assess the functional relevance of these treatment-related changes in resting alpha activity. These findings further support the anti-stress effects of L-theanine.

Complex motor-cognitive factors processed in the anterior nucleus of the thalamus: an intracerebral recording study.

PubMed

Bočková, Martina; Chládek, Jan; Jurák, Pavel; Halámek, Josef; Štillová, Klára; Baláž, Marek; Chrastina, Jan; Rektor, Ivan

2015-03-01

Cognitive adverse effects were reported after the deep brain stimulation (DBS) of the anterior nucleus of the thalamus (AN) in epilepsy. As the AN may have an influence on widespread neocortical networks, we hypothesized that the AN, in addition to its participation in memory processing, may also participate in cognitive activities linked with the frontal neocortical structures. The aim of this study was to investigate whether the AN might participate in complex motor-cognitive activities. Three pharmacoresistant epilepsy patients implanted with AN-DBS electrodes performed two tasks involving the writing of single letters: (1) copying letters from a monitor; and (2) writing of any letter other than that appearing on the monitor. The cognitive load of the second task was increased. The task-related oscillatory changes and evoked potentials were assessed. Local event-related alpha and beta desynchronization were more expressed during the second task while the lower gamma synchronization decreased. The local field event-related potentials were elicited by the two tasks without any specific differences. The AN participates in cognitive networks processing complex motor-cognitive tasks. Attention should be paid to executive functions in subjects undergoing AN-DBS.

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

The Myotonometer: Not a Valid Measurement Tool for Active Hamstring Musculotendinous Stiffness.

PubMed

Pamukoff, Derek N; Bell, Sarah E; Ryan, Eric D; Blackburn, J Troy

2016-05-01

Hamstring musculotendinous stiffness (MTS) is associated with lower-extremity injury risk (ie, hamstring strain, anterior cruciate ligament injury) and is commonly assessed using the damped oscillatory technique. However, despite a preponderance of studies that measure MTS reliably in laboratory settings, there are no valid clinical measurement tools. A valid clinical measurement technique is needed to assess MTS and permit identification of individuals at heightened risk of injury and track rehabilitation progress. To determine the validity and reliability of the Myotonometer for measuring active hamstring MTS. Descriptive laboratory study. Laboratory. 33 healthy participants (15 men, age 21.33 ± 2.94 y, height 172.03 ± 16.36 cm, mass 74.21 ± 16.36 kg). Hamstring MTS was assessed using the damped oscillatory technique and the Myotonometer. Intraclass correlations were used to determine the intrasession, intersession, and interrater reliability of the Myotonometer. Criterion validity was assessed via Pearson product-moment correlation between MTS measures obtained from the Myotonometer and from the damped oscillatory technique. The Myotonometer demonstrated good intrasession (ICC3,1 = .807) and interrater reliability (ICC2,k = .830) and moderate intersession reliability (ICC2,k = .693). However, it did not provide a valid measurement of MTS compared with the damped oscillatory technique (r = .346, P = .061). The Myotonometer does not provide a valid measure of active hamstring MTS. Although the Myotonometer does not measure active MTS, it possesses good reliability and portability and could be used clinically to measure tissue compliance, muscle tone, or spasticity associated with multiple musculoskeletal disorders. Future research should focus on portable and clinically applicable tools to measure active hamstring MTS in efforts to prevent and monitor injuries.

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.

Prestimulus EEG Power Predicts Conscious Awareness But Not Objective Visual Performance

PubMed Central

Veniero, Domenica

2017-01-01

Abstract Prestimulus oscillatory neural activity has been linked to perceptual outcomes during performance of psychophysical detection and discrimination tasks. Specifically, the power and phase of low frequency oscillations have been found to predict whether an upcoming weak visual target will be detected or not. However, the mechanisms by which baseline oscillatory activity influences perception remain unclear. Recent studies suggest that the frequently reported negative relationship between α power and stimulus detection may be explained by changes in detection criterion (i.e., increased target present responses regardless of whether the target was present/absent) driven by the state of neural excitability, rather than changes in visual sensitivity (i.e., more veridical percepts). Here, we recorded EEG while human participants performed a luminance discrimination task on perithreshold stimuli in combination with single-trial ratings of perceptual awareness. Our aim was to investigate whether the power and/or phase of prestimulus oscillatory activity predict discrimination accuracy and/or perceptual awareness on a trial-by-trial basis. Prestimulus power (3–28 Hz) was inversely related to perceptual awareness ratings (i.e., higher ratings in states of low prestimulus power/high excitability) but did not predict discrimination accuracy. In contrast, prestimulus oscillatory phase did not predict awareness ratings or accuracy in any frequency band. These results provide evidence that prestimulus α power influences the level of subjective awareness of threshold visual stimuli but does not influence visual sensitivity when a decision has to be made regarding stimulus features. Hence, we find a clear dissociation between the influence of ongoing neural activity on conscious awareness and objective performance. PMID:29255794

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.

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

Representation of time interval entrained by periodic stimuli in the visual thalamus of pigeons

PubMed Central

Wang, Shu-Rong

2017-01-01

Animals use the temporal information from previously experienced periodic events to instruct their future behaviors. The retina and cortex are involved in such behavior, but it remains largely unknown how the thalamus, transferring visual information from the retina to the cortex, processes the periodic temporal patterns. Here we report that the luminance cells in the nucleus dorsolateralis anterior thalami (DLA) of pigeons exhibited oscillatory activities in a temporal pattern identical to the rhythmic luminance changes of repetitive light/dark (LD) stimuli with durations in the seconds-to-minutes range. Particularly, after LD stimulation, the DLA cells retained the entrained oscillatory activities with an interval closely matching the duration of the LD cycle. Furthermore, the post-stimulus oscillatory activities of the DLA cells were sustained without feedback inputs from the pallium (equivalent to the mammalian cortex). Our study suggests that the experience-dependent representation of time interval in the brain might not be confined to the pallial/cortical level, but may occur as early as at the thalamic level. PMID:29284554

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.

Sight restoration after congenital blindness does not reinstate alpha oscillatory activity in humans

PubMed Central

Bottari, Davide; Troje, Nikolaus F.; Ley, Pia; Hense, Marlene; Kekunnaya, Ramesh; Röder, Brigitte

2016-01-01

Functional brain development is characterized by sensitive periods during which experience must be available to allow for the full development of neural circuits and associated behavior. Yet, only few neural markers of sensitive period plasticity in humans are known. Here we employed electroencephalographic recordings in a unique sample of twelve humans who had been blind from birth and regained sight through cataract surgery between four months and 16 years of age. Two additional control groups were tested: a group of visually impaired individuals without a history of total congenital blindness and a group of typically sighted individuals. The EEG was recorded while participants performed a visual discrimination task involving intact and scrambled biological motion stimuli. Posterior alpha and theta oscillations were evaluated. The three groups showed indistinguishable behavioral performance and in all groups evoked theta activity varied with biological motion processing. By contrast, alpha oscillatory activity was significantly reduced only in individuals with a history of congenital cataracts. These data document on the one hand brain mechanisms of functional recovery (related to theta oscillations) and on the other hand, for the first time, a sensitive period for the development of alpha oscillatory activity in humans. PMID:27080158

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.

Deep brain stimulation modulates synchrony within spatially and spectrally distinct resting state networks in Parkinson's disease.

PubMed

Oswal, Ashwini; Beudel, Martijn; Zrinzo, Ludvic; Limousin, Patricia; Hariz, Marwan; Foltynie, Tom; Litvak, Vladimir; Brown, Peter

2016-05-01

Chronic dopamine depletion in Parkinson's disease leads to progressive motor and cognitive impairment, which is associated with the emergence of characteristic patterns of synchronous oscillatory activity within cortico-basal-ganglia circuits. Deep brain stimulation of the subthalamic nucleus is an effective treatment for Parkinson's disease, but its influence on synchronous activity in cortico-basal-ganglia loops remains to be fully characterized. Here, we demonstrate that deep brain stimulation selectively suppresses certain spatially and spectrally segregated resting state subthalamic nucleus-cortical networks. To this end we used a validated and novel approach for performing simultaneous recordings of the subthalamic nucleus and cortex using magnetoencephalography (during concurrent subthalamic nucleus deep brain stimulation). Our results highlight that clinically effective subthalamic nucleus deep brain stimulation suppresses synchrony locally within the subthalamic nucleus in the low beta oscillatory range and furthermore that the degree of this suppression correlates with clinical motor improvement. Moreover, deep brain stimulation relatively selectively suppressed synchronization of activity between the subthalamic nucleus and mesial premotor regions, including the supplementary motor areas. These mesial premotor regions were predominantly coupled to the subthalamic nucleus in the high beta frequency range, but the degree of deep brain stimulation-associated suppression in their coupling to the subthalamic nucleus was not found to correlate with motor improvement. Beta band coupling between the subthalamic nucleus and lateral motor areas was not influenced by deep brain stimulation. Motor cortical coupling with subthalamic nucleus predominantly involved driving of the subthalamic nucleus, with those drives in the higher beta frequency band having much shorter net delays to subthalamic nucleus than those in the lower beta band. These observations raise the possibility that cortical connectivity with the subthalamic nucleus in the high and low beta bands may reflect coupling mediated predominantly by the hyperdirect and indirect pathways to subthalamic nucleus, respectively, and that subthalamic nucleus deep brain stimulation predominantly suppresses the former. Yet only the change in strength of local subthalamic nucleus oscillations correlates with the degree of improvement during deep brain stimulation, compatible with the current view that a strengthened hyperdirect pathway is a prerequisite for locally generated beta activity but that it is the severity of the latter that may determine or index motor impairment. © The Author (2016). Published by Oxford University Press on behalf of the Guarantors of Brain.

Deep brain stimulation modulates synchrony within spatially and spectrally distinct resting state networks in Parkinson’s disease

PubMed Central

Oswal, Ashwini; Beudel, Martijn; Zrinzo, Ludvic; Limousin, Patricia; Hariz, Marwan; Foltynie, Tom; Litvak, Vladimir

2016-01-01

Abstract Chronic dopamine depletion in Parkinson’s disease leads to progressive motor and cognitive impairment, which is associated with the emergence of characteristic patterns of synchronous oscillatory activity within cortico-basal-ganglia circuits. Deep brain stimulation of the subthalamic nucleus is an effective treatment for Parkinson’s disease, but its influence on synchronous activity in cortico-basal-ganglia loops remains to be fully characterized. Here, we demonstrate that deep brain stimulation selectively suppresses certain spatially and spectrally segregated resting state subthalamic nucleus–cortical networks. To this end we used a validated and novel approach for performing simultaneous recordings of the subthalamic nucleus and cortex using magnetoencephalography (during concurrent subthalamic nucleus deep brain stimulation). Our results highlight that clinically effective subthalamic nucleus deep brain stimulation suppresses synchrony locally within the subthalamic nucleus in the low beta oscillatory range and furthermore that the degree of this suppression correlates with clinical motor improvement. Moreover, deep brain stimulation relatively selectively suppressed synchronization of activity between the subthalamic nucleus and mesial premotor regions, including the supplementary motor areas. These mesial premotor regions were predominantly coupled to the subthalamic nucleus in the high beta frequency range, but the degree of deep brain stimulation-associated suppression in their coupling to the subthalamic nucleus was not found to correlate with motor improvement. Beta band coupling between the subthalamic nucleus and lateral motor areas was not influenced by deep brain stimulation. Motor cortical coupling with subthalamic nucleus predominantly involved driving of the subthalamic nucleus, with those drives in the higher beta frequency band having much shorter net delays to subthalamic nucleus than those in the lower beta band. These observations raise the possibility that cortical connectivity with the subthalamic nucleus in the high and low beta bands may reflect coupling mediated predominantly by the hyperdirect and indirect pathways to subthalamic nucleus, respectively, and that subthalamic nucleus deep brain stimulation predominantly suppresses the former. Yet only the change in strength of local subthalamic nucleus oscillations correlates with the degree of improvement during deep brain stimulation, compatible with the current view that a strengthened hyperdirect pathway is a prerequisite for locally generated beta activity but that it is the severity of the latter that may determine or index motor impairment. PMID:27017189

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.

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.

Processing Semblances Induced through Inter-Postsynaptic Functional LINKs, Presumed Biological Parallels of K-Lines Proposed for Building Artificial Intelligence

PubMed Central

Vadakkan, Kunjumon I.

2011-01-01

The internal sensation of memory, which is available only to the owner of an individual nervous system, is difficult to analyze for its basic elements of operation. We hypothesize that associative learning induces the formation of functional LINK between the postsynapses. During memory retrieval, the activation of either postsynapse re-activates the functional LINK evoking a semblance of sensory activity arriving at its opposite postsynapse, nature of which defines the basic unit of internal sensation – namely, the semblion. In neuronal networks that undergo continuous oscillatory activity at certain levels of their organization re-activation of functional LINKs is expected to induce semblions, enabling the system to continuously learn, self-organize, and demonstrate instantiation, features that can be utilized for developing artificial intelligence (AI). This paper also explains suitability of the inter-postsynaptic functional LINKs to meet the expectations of Minsky’s K-lines, basic elements of a memory theory generated to develop AI and methods to replicate semblances outside the nervous system. PMID:21845180

α-Oscillations in the monkey sensorimotor network influence discrimination performance by rhythmical inhibition of neuronal spiking.

PubMed

Haegens, Saskia; Nácher, Verónica; Luna, Rogelio; Romo, Ranulfo; Jensen, Ole

2011-11-29

Extensive work in humans using magneto- and electroencephalography strongly suggests that decreased oscillatory α-activity (8-14 Hz) facilitates processing in a given region, whereas increased α-activity serves to actively suppress irrelevant or interfering processing. However, little work has been done to understand how α-activity is linked to neuronal firing. Here, we simultaneously recorded local field potentials and spikes from somatosensory, premotor, and motor regions while a trained monkey performed a vibrotactile discrimination task. In the local field potentials we observed strong activity in the α-band, which decreased in the sensorimotor regions during the discrimination task. This α-power decrease predicted better discrimination performance. Furthermore, the α-oscillations demonstrated a rhythmic relation with the spiking, such that firing was highest at the trough of the α-cycle. Firing rates increased with a decrease in α-power. These findings suggest that α-oscillations exercise a strong inhibitory influence on both spike timing and firing rate. Thus, the pulsed inhibition by α-oscillations plays an important functional role in the extended sensorimotor system.

Local entrainment of oscillatory activity induced by direct brain stimulation in humans

PubMed Central

Amengual, Julià L.; Vernet, Marine; Adam, Claude; Valero-Cabré, Antoni

2017-01-01

In a quest for direct evidence of oscillation entrainment, we analyzed intracerebral electroencephalographic recordings obtained during intracranial electrical stimulation in a cohort of three medication-resistant epilepsy patients tested pre-surgically. Spectral analyses of non-epileptogenic cerebral sites stimulated directly with high frequency electrical bursts yielded episodic local enhancements of frequency-specific rhythmic activity, phase-locked to each individual pulse. These outcomes reveal an entrainment of physiological oscillatory activity within a frequency band dictated by the rhythm of the stimulation source. Our results support future uses of rhythmic stimulation to elucidate the causal contributions of synchrony to specific aspects of human cognition and to further develop the therapeutic manipulation of dysfunctional rhythmic activity subtending the symptoms of some neuropsychiatric conditions. PMID:28256510

Binary Oscillatory Crossflow Electrophoresis

NASA Technical Reports Server (NTRS)

Molloy, Richard F.; Gallagher, Christopher T.; Leighton, David T., Jr.

1997-01-01

Electrophoresis has long been recognized as an effective analytic technique for the separation of proteins and other charged species, however attempts at scaling up to accommodate commercial volumes have met with limited success. In this report we describe a novel electrophoretic separation technique - Binary Oscillatory Crossflow Electrophoresis (BOCE). Numerical simulations indicate that the technique has the potential for preparative scale throughputs with high resolution, while simultaneously avoiding many problems common to conventional electrophoresis. The technique utilizes the interaction of an oscillatory electric field and a transverse oscillatory shear flow to create an active binary filter for the separation of charged protein species. An oscillatory electric field is applied across the narrow gap of a rectangular channel inducing a periodic motion of charged protein species. The amplitude of this motion depends on the dimensionless electrophoretic mobility, alpha = E(sub o)mu/(omega)d, where E(sub o) is the amplitude of the electric field oscillations, mu is the dimensional mobility, omega is the angular frequency of oscillation and d is the channel gap width. An oscillatory shear flow is induced along the length of the channel resulting in the separation of species with different mobilities. We present a model that predicts the oscillatory behavior of charged species and allows estimation of both the magnitude of the induced convective velocity and the effective diffusivity as a function of a in infinitely long channels. Numerical results indicate that in addition to the mobility dependence, the steady state behavior of solute species may be strongly affected by oscillating fluid into and out of the active electric field region at the ends of the cell. The effect is most pronounced using time dependent shear flows of the same frequency (cos((omega)t)) flow mode) as the electric field oscillations. Under such conditions, experiments indicate that solute is drawn into the cell from reservoirs at both ends of the cell leading to a large mass build up. As a consequence, any initially induced mass flux will vanish after short times. This effect was not captured by the infinite channel model and hence numerical and experimental results deviated significantly. The revised model including finite cell lengths and reservoir volumes allowed quantitative predictions of the time history of the concentration profile throughout the system. This latter model accurately describes the fluxes observed for both oscillatory flow modes in experiments using single protein species. Based on the results obtained from research funded under NASA grant NAG-8-1080.S, we conclude that binary separations are not possible using purely oscillatory flow modes because of end effects associated with the cos((omega)t) mode. Our research shows, however, that a combination of cos(2(omega)t) and steady flow should lead to efficient separation free of end effects. This possibility is currently under investigation.

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.

Noninvasive transcranial focused ultrasonic-magnetic stimulation for modulating brain oscillatory activity

NASA Astrophysics Data System (ADS)

Yuan, Yi; Chen, Yudong; Li, Xiaoli

2016-02-01

A novel technique, transcranial focused ultrasonic-magnetic stimulation (tFUMS), has been developed for noninvasive brain modulation in vivo. tFUMS has a higher spatial resolution (<2 mm) and a higher penetration depth than other noninvasive neuromodulation methods. The in vivo animal experimental results show that tFUMS can not only increase the power of local field potentials and the firing rate of the neurons, but also enhance the effect of transcranial focused ultrasound stimulation on the neuromodulation. The results demonstrate that tFUMS can modulate brain oscillatory activities by stimulating brain tissues.

Oscillation transmission and volume delivery during face mask-delivered HFOV in infants: Bench and in vivo study.

PubMed

De Luca, Daniele; Costa, Roberta; Visconti, Federico; Piastra, Marco; Conti, Giorgio

2016-07-01

Noninvasive high frequency oscillatory ventilation (NHFOV) has not been studied beyond neonatal age and with interfaces other than nasal prongs. We set up a preliminary study to investigate feasibility, oscillation transmission, and volume delivery of face mask-delivered NHFOV in a bench model mimicking a normal 1-year infant without any lung disease and then in vivo in a series of infants with same characteristics. A mannequin with upper airways was connected to an electronic active lung simulator ventilated through NHFOV with varying parameters. Volume delivered by oscillations (oTv), oscillatory pressure ratio, and estimation of ventilation (DCO2) were measured at the lung simulator. Four infants were ventilated with face mask-delivered NHFOV for 2 hr and monitored with respiratory inductance plethismography. Vital parameters, oscillatory pressure ratio, oscillatory (RIPo), and spontaneous cage/abdomen displacement (RIPs) were recorded. There was a dampening of oscillation amplitude both on the bench model and in vivo: oscillatory pressure ratios at the mask were 80% and 17%, respectively. Significant correlations exist between oscillatory pressure ratio (only when this latter was <0.038) and oTv (r = 0.48; P < 0.001) or DCO2 (r = 0.47; P < 0.001). At multivariate analysis, oscillatory pressure ratio was a main determinant of oTv and DCO2. Oscillations were slightly visible on the chest in vivo and RIPo was about 5% of RIPs. NHFOV did not change vital parameters and did not cause discomfort. Face mask-delivered NHFOV is feasible in a model of 1-year infant. No major complications occurred in vivo. Oscillations are superimposed to the spontaneous breathing and are significantly dampened. Pediatr Pulmonol. Pediatr Pulmonol. 2016;51:705-712. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

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.

Altered Neural Oscillations During Multisensory Integration in Adolescents with Fetal Alcohol Spectrum Disorder.

PubMed

Bolaños, Alfredo D; Coffman, Brian A; Candelaria-Cook, Felicha T; Kodituwakku, Piyadasa; Stephen, Julia M

2017-12-01

Children with fetal alcohol spectrum disorder (FASD), who were exposed to alcohol in utero, display a broad range of sensory, cognitive, and behavioral deficits, which are broadly theorized to be rooted in altered brain function and structure. Based on the role of neural oscillations in multisensory integration from past studies, we hypothesized that adolescents with FASD would show a decrease in oscillatory power during event-related gamma oscillatory activity (30 to 100 Hz), when compared to typically developing healthy controls (HC), and that such decrease in oscillatory power would predict behavioral performance. We measured sensory neurophysiology using magnetoencephalography (MEG) during passive auditory, somatosensory, and multisensory (synchronous) stimulation in 19 adolescents (12 to 21 years) with FASD and 23 age- and gender-matched HC. We employed a cross-hemisphere multisensory paradigm to assess interhemispheric connectivity deficits in children with FASD. Time-frequency analysis of MEG data revealed a significant decrease in gamma oscillatory power for both unisensory and multisensory conditions in the FASD group relative to HC, based on permutation testing of significant group differences. Greater beta oscillatory power (15 to 30 Hz) was also noted in the FASD group compared to HC in both unisensory and multisensory conditions. Regression analysis revealed greater predictive power of multisensory oscillations from unisensory oscillations in the FASD group compared to the HC group. Furthermore, multisensory oscillatory power, for both groups, predicted performance on the Intra-Extradimensional Set Shift Task and the Cambridge Gambling Task. Altered oscillatory power in the FASD group may reflect a restricted ability to process somatosensory and multisensory stimuli during day-to-day interactions. These alterations in neural oscillations may be associated with the neurobehavioral deficits experienced by adolescents with FASD and may carry over to adulthood. Copyright © 2017 by the Research Society on Alcoholism.

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

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

Estimating direction in brain-behavior interactions: Proactive and reactive brain states in driving.

PubMed

Garcia, Javier O; Brooks, Justin; Kerick, Scott; Johnson, Tony; Mullen, Tim R; Vettel, Jean M

2017-04-15

Conventional neuroimaging analyses have ascribed function to particular brain regions, exploiting the power of the subtraction technique in fMRI and event-related potential analyses in EEG. Moving beyond this convention, many researchers have begun exploring network-based neurodynamics and coordination between brain regions as a function of behavioral parameters or environmental statistics; however, most approaches average evoked activity across the experimental session to study task-dependent networks. Here, we examined on-going oscillatory activity as measured with EEG and use a methodology to estimate directionality in brain-behavior interactions. After source reconstruction, activity within specific frequency bands (delta: 2-3Hz; theta: 4-7Hz; alpha: 8-12Hz; beta: 13-25Hz) in a priori regions of interest was linked to continuous behavioral measurements, and we used a predictive filtering scheme to estimate the asymmetry between brain-to-behavior and behavior-to-brain prediction using a variant of Granger causality. We applied this approach to a simulated driving task and examined directed relationships between brain activity and continuous driving performance (steering behavior or vehicle heading error). Our results indicated that two neuro-behavioral states may be explored with this methodology: a Proactive brain state that actively plans the response to the sensory information and is characterized by delta-beta activity, and a Reactive brain state that processes incoming information and reacts to environmental statistics primarily within the alpha band. Published by Elsevier Inc.

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

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.

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.

Cross-correlated and oscillatory visual responses of superficial-layer and tecto-reticular neurones in cat superior colliculus.

PubMed

Chabli, A; Guitton, D; Fortin, S; Molotchnikoff, S

2000-03-01

The present study examined, in the superior colliculus (SC) of anaesthetised cats, the functional connectivity between superficial-layer neurones (SLNs) and tectoreticular neurones (TRNs: collicular output cells). TRNs were antidromically identified by electrical stimulation of the predorsal bundle. The auto- and cross-correlation histograms of visual responses of both types of neurones were recorded and analysed. A delayed, sharp peak in cross-correlograms allowed us to verify whether SLN and TRN cells were coupled; in addition, oscillatory activities were compared to verify if rhythmic responses of SLN sites were transmitted to TRN sites. We found that oscillatory activity was rarely observed in spontaneous activity of superficial (1/74) and TRN sites (1/48). Moving light bars induced oscillation in 31% (23/74) of the superficial-layer and in 23% (11/48) of the TRN sites. The strength of the rhythmic responses was determined by specific ranges of stimulus velocity in 83% (19/23) and 64% (7/11) of oscillating SLN and TRN sites, respectively. Frequencies of oscillations ranged between 5 and 125 Hz and were confined, for 53% of the cells, to the 5-20 Hz band. Thus, the band-width of frequencies of the stimulus-related oscillations in the superior colliculus was broader than the gamma range. Analysis of cross-correlation histograms revealed a significant predominant peak with a mean delay of 2.7+/-0.9 ms in 46% (17/37) of SLN-TRN pairs. Most correlated SLN-TRN pairs (88%: 15/17) had superimposed receptive fields, suggesting they were functionally interconnected. However, individual oscillatory frequencies of correlated and oscillatory SLN and TRN cells were never the same (0/8). Together, these results suggest that the neurones in collicular superficial layer contact TRNs and, consequently, support the idea that the superficial layers contribute to collicular outputs producing eye- and head-orienting movements.

Pathological synchronization in Parkinson's disease: networks, models and treatments.

PubMed

Hammond, Constance; Bergman, Hagai; Brown, Peter

2007-07-01

Parkinson's disease is a common and disabling disorder of movement owing to dopaminergic denervation of the striatum. However, it is still unclear how this denervation perverts normal functioning to cause slowing of voluntary movements. Recent work using tissue slice preparations, animal models and in humans with Parkinson's disease has demonstrated abnormally synchronized oscillatory activity at multiple levels of the basal ganglia-cortical loop. This excessive synchronization correlates with motor deficit, and its suppression by dopaminergic therapies, ablative surgery or deep-brain stimulation might provide the basic mechanism whereby diverse therapeutic strategies ameliorate motor impairment in patients with Parkinson's disease. 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/).

Irreducible Representations of Oscillatory and Swirling Flows in Active Soft Matter

NASA Astrophysics Data System (ADS)

Ghose, Somdeb; Adhikari, R.

2014-03-01

Recent experiments imaging fluid flow around swimming microorganisms have revealed complex time-dependent velocity fields that differ qualitatively from the stresslet flow commonly employed in theoretical descriptions of active matter. Here we obtain the most general flow around a finite sized active particle by expanding the surface stress in irreducible Cartesian tensors. This expansion, whose first term is the stresslet, must include, respectively, third-rank polar and axial tensors to minimally capture crucial features of the active oscillatory flow around translating Chlamydomonas and the active swirling flow around rotating Volvox. The representation provides explicit expressions for the irreducible symmetric, antisymmetric, and isotropic parts of the continuum active stress. Antisymmetric active stresses do not conserve orbital angular momentum and our work thus shows that spin angular momentum is necessary to restore angular momentum conservation in continuum hydrodynamic descriptions of active soft matter.

A Spiking Working Memory Model Based on Hebbian Short-Term Potentiation.

PubMed

Fiebig, Florian; Lansner, Anders

2017-01-04

A dominant theory of working memory (WM), referred to as the persistent activity hypothesis, holds that recurrently connected neural networks, presumably located in the prefrontal cortex, encode and maintain WM memory items through sustained elevated activity. Reexamination of experimental data has shown that prefrontal cortex activity in single units during delay periods is much more variable than predicted by such a theory and associated computational models. Alternative models of WM maintenance based on synaptic plasticity, such as short-term nonassociative (non-Hebbian) synaptic facilitation, have been suggested but cannot account for encoding of novel associations. Here we test the hypothesis that a recently identified fast-expressing form of Hebbian synaptic plasticity (associative short-term potentiation) is a possible mechanism for WM encoding and maintenance. Our simulations using a spiking neural network model of cortex reproduce a range of cognitive memory effects in the classical multi-item WM task of encoding and immediate free recall of word lists. Memory reactivation in the model occurs in discrete oscillatory bursts rather than as sustained activity. We relate dynamic network activity as well as key synaptic characteristics to electrophysiological measurements. Our findings support the hypothesis that fast Hebbian short-term potentiation is a key WM mechanism. Working memory (WM) is a key component of cognition. Hypotheses about the neural mechanism behind WM are currently under revision. Reflecting recent findings of fast Hebbian synaptic plasticity in cortex, we test whether a cortical spiking neural network model with such a mechanism can learn a multi-item WM task (word list learning). We show that our model can reproduce human cognitive phenomena and achieve comparable memory performance in both free and cued recall while being simultaneously compatible with experimental data on structure, connectivity, and neurophysiology of the underlying cortical tissue. These findings are directly relevant to the ongoing paradigm shift in the WM field. Copyright © 2017 Fiebig and Lansner.

A Spiking Working Memory Model Based on Hebbian Short-Term Potentiation

PubMed Central

Fiebig, Florian

2017-01-01

A dominant theory of working memory (WM), referred to as the persistent activity hypothesis, holds that recurrently connected neural networks, presumably located in the prefrontal cortex, encode and maintain WM memory items through sustained elevated activity. Reexamination of experimental data has shown that prefrontal cortex activity in single units during delay periods is much more variable than predicted by such a theory and associated computational models. Alternative models of WM maintenance based on synaptic plasticity, such as short-term nonassociative (non-Hebbian) synaptic facilitation, have been suggested but cannot account for encoding of novel associations. Here we test the hypothesis that a recently identified fast-expressing form of Hebbian synaptic plasticity (associative short-term potentiation) is a possible mechanism for WM encoding and maintenance. Our simulations using a spiking neural network model of cortex reproduce a range of cognitive memory effects in the classical multi-item WM task of encoding and immediate free recall of word lists. Memory reactivation in the model occurs in discrete oscillatory bursts rather than as sustained activity. We relate dynamic network activity as well as key synaptic characteristics to electrophysiological measurements. Our findings support the hypothesis that fast Hebbian short-term potentiation is a key WM mechanism. SIGNIFICANCE STATEMENT Working memory (WM) is a key component of cognition. Hypotheses about the neural mechanism behind WM are currently under revision. Reflecting recent findings of fast Hebbian synaptic plasticity in cortex, we test whether a cortical spiking neural network model with such a mechanism can learn a multi-item WM task (word list learning). We show that our model can reproduce human cognitive phenomena and achieve comparable memory performance in both free and cued recall while being simultaneously compatible with experimental data on structure, connectivity, and neurophysiology of the underlying cortical tissue. These findings are directly relevant to the ongoing paradigm shift in the WM field. PMID:28053032

Oscillatory support for rapid frequency change processing in infants.

PubMed

Musacchia, Gabriella; Choudhury, Naseem A; Ortiz-Mantilla, Silvia; Realpe-Bonilla, Teresa; Roesler, Cynthia P; Benasich, April A

2013-11-01

Rapid auditory processing and auditory change detection abilities are crucial aspects of speech and language development, particularly in the first year of life. Animal models and adult studies suggest that oscillatory synchrony, and in particular low-frequency oscillations play key roles in this process. We hypothesize that infant perception of rapid pitch and timing changes is mediated, at least in part, by oscillatory mechanisms. Using event-related potentials (ERPs), source localization and time-frequency analysis of event-related oscillations (EROs), we examined the neural substrates of rapid auditory processing in 4-month-olds. During a standard oddball paradigm, infants listened to tone pairs with invariant standard (STD, 800-800 Hz) and variant deviant (DEV, 800-1200 Hz) pitch. STD and DEV tone pairs were first presented in a block with a short inter-stimulus interval (ISI) (Rapid Rate: 70 ms ISI), followed by a block of stimuli with a longer ISI (Control Rate: 300 ms ISI). Results showed greater ERP peak amplitude in response to the DEV tone in both conditions and later and larger peaks during Rapid Rate presentation, compared to the Control condition. Sources of neural activity, localized to right and left auditory regions, showed larger and faster activation in the right hemisphere for both rate conditions. Time-frequency analysis of the source activity revealed clusters of theta band enhancement to the DEV tone in right auditory cortex for both conditions. Left auditory activity was enhanced only during Rapid Rate presentation. These data suggest that local low-frequency oscillatory synchrony underlies rapid processing and can robustly index auditory perception in young infants. Furthermore, left hemisphere recruitment during rapid frequency change discrimination suggests a difference in the spectral and temporal resolution of right and left hemispheres at a very young age. © 2013 Elsevier Ltd. All rights reserved.

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

Delta and gamma oscillations in operculo-insular cortex underlie innocuous cold thermosensation

PubMed Central

Vinding, Mikkel C.; Allen, Micah; Jensen, Troels Staehelin; Finnerup, Nanna Brix

2017-01-01

Cold-sensitive and nociceptive neural pathways interact to shape the quality and intensity of thermal and pain perception. Yet the central processing of cold thermosensation in the human brain has not been extensively studied. Here, we used magnetoencephalography and EEG in healthy volunteers to investigate the time course (evoked fields and potentials) and oscillatory activity associated with the perception of cold temperature changes. Nonnoxious cold stimuli consisting of Δ3°C and Δ5°C decrements from an adapting temperature of 35°C were delivered on the dorsum of the left hand via a contact thermode. Cold-evoked fields peaked at around 240 and 500 ms, at peak latencies similar to the N1 and P2 cold-evoked potentials. Importantly, cold-related changes in oscillatory power indicated that innocuous thermosensation is mediated by oscillatory activity in the range of delta (1–4 Hz) and gamma (55–90 Hz) rhythms, originating in operculo-insular cortical regions. We suggest that delta rhythms coordinate functional integration between operculo-insular and frontoparietal regions, while gamma rhythms reflect local sensory processing in operculo-insular areas. NEW & NOTEWORTHY Using magnetoencephalography, we identified spatiotemporal features of central cold processing, with respect to the time course, oscillatory profile, and neural generators of cold-evoked responses in healthy human volunteers. Cold thermosensation was associated with low- and high-frequency oscillatory rhythms, both originating in operculo-insular regions. These results support further investigations of central cold processing using magnetoencephalography or EEG and the clinical utility of cold-evoked potentials for neurophysiological assessment of cold-related small-fiber function and damage. PMID:28250150

Pathological ponto-cerebello-thalamo-cortical activations in primary orthostatic tremor during lying and stance.

PubMed

Schöberl, Florian; Feil, Katharina; Xiong, Guoming; Bartenstein, Peter; la Fougére, Christian; Jahn, Klaus; Brandt, Thomas; Strupp, Michael; Dieterich, Marianne; Zwergal, Andreas

2017-01-01

Primary orthostatic tremor is a rare neurological disease characterized mainly by a high frequency tremor of the legs while standing. The aim of this study was to identify the common core structures of the oscillatory circuit in orthostatic tremor and how it is modulated by changes of body position. Ten patients with orthostatic tremor and 10 healthy age-matched control subjects underwent a standardized neurological and neuro-ophthalmological examination including electromyographic and posturographic recordings. Task-dependent changes of cerebral glucose metabolism during lying and standing were measured in all subjects by sequential 18 F-fluorodeoxyglucose-positron emission tomography on separate days. Results were compared between groups and conditions. All the orthostatic tremor patients, but no control subject, showed the characteristic 13-18 Hz tremor in coherent muscles during standing, which ceased in the supine position. While lying, patients had a significantly increased regional cerebral glucose metabolism in the pontine tegmentum, the posterior cerebellum (including the dentate nuclei), the ventral intermediate and ventral posterolateral nucleus of the thalamus, and the primary motor cortex bilaterally compared to controls. Similar glucose metabolism changes occurred with clinical manifestation of the tremor during standing. The glucose metabolism was relatively decreased in mesiofrontal cortical areas (i.e. the medial prefrontal cortex, supplementary motor area and anterior cingulate cortex) and the bilateral anterior insula in orthostatic tremor patients while lying and standing. The mesiofrontal hypometabolism correlated with increased body sway in posturography. This study confirms and further elucidates ponto-cerebello-thalamo-primary motor cortical activations underlying primary orthostatic tremor, which presented consistently in a group of patients. Compared to other tremor disorders one characteristic feature in orthostatic tremor seems to be the involvement of the pontine tegmentum in the pathophysiology of tremor generation. High frequency oscillatory properties of pontine tegmental neurons have been reported in pathological oscillatory eye movements. It is remarkable that the characteristic activation and deactivation pattern in orthostatic tremor is already present in the supine position without tremor presentation. Multilevel changes of neuronal excitability during upright stance may trigger activation of the orthostatic tremor network. Based on the functional imaging data described in this study, it is hypothesized that a mesiofrontal deactivation is another characteristic feature of orthostatic tremor and plays a pivotal role in development of postural unsteadiness during prolonged standing. © The Author (2016). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Mechanically activated fly ash as a high performance binder for civil engineering

NASA Astrophysics Data System (ADS)

Rieger, D.; Kullová, L.; Čekalová, M.; Novotný, P.; Pola, M.

2017-01-01

This study is aimed for investigation of fly ash binder with suitable properties for civil engineering needs. The fly ash from Czech brown coal power plant Prunerov II was used and mechanically activated to achieve suitable particle size for alkaline activation of hardening process. This process is driven by dissolution of aluminosilicate content of fly ash and by subsequent development of inorganic polymeric network called geopolymer. Hardening kinetics at 25 and 30 °C were measured by strain controlled small amplitude oscillatory rheometry with strain of 0.01 % and microstructure of hardened binder was evaluated by scanning electron microscopy. Strength development of hardened binder was investigated according to compressional and flexural strength for a period of 180 days. Our investigation finds out, that mechanically activated fly ash can be comparable to metakaolin geopolymers, according to setting time and mechanical parameters even at room temperature curing. Moreover, on the bases of long time strength development, achieved compressional strength of 134.5 after 180 days is comparable to performance of high grade Portland cement concretes.

The role of the parafascicular complex (CM-Pf) of the human thalamus in the neuronal mechanisms of selective attention.

PubMed

Raeva, S N

2006-03-01

The reactions of 93 neurons in the parafascicular complex (CM-Pf) of the human thalamus were studied by microelectrode recording during stereotaxic neurosurgical operations in patients with spastic torticollis. High reactivity was demonstrated for two previously classified types of neurons with identical irregular (type A) and bursting Ca2+ -dependent (type B) activities in response to presentation of relevant verbal stimuli evoking selective attention in humans. Concordant changes in the network activity of A and B neurons were observed, in the form of linked activatory-inhibitory patterns of responses and the appearance, at the moment of presentation of an imperative morpheme of the command stimulus, of rapidly occurring intercellular interactions consisting of local synchronization with simultaneously developing rhythmic oscillatory (3-4 Hz) activity. Data are presented on the existence of a direct connection between these neuronal rearrangements and activation of selective attention, providing evidence for the involvement of the thalamic parafascicular complex (CM-Pf) in the mechanisms of selective attention and processing of relevant verbal information during the preparative period of voluntary actions.

Phase correlated adequate afferent action potentials as a drive of human spinal oscillators.

PubMed

Schalow, G

1993-12-01

1. By recording, with 2 pairs of wire electrodes, single-fibre action potentials (APs) from lower sacral nerve roots of a brain-dead human and a patient with spinal cord lesion, impulse patterns of afferent APs and impulse trains of oscillatory firing motoneurons could be identified and correlated. 2. Two highly activated secondary muscle spindle afferents increased and decreased their activity at about 0.3 Hz. The duration of the doublet interspike interval of a secondary spindle afferent fibre showed no correlation to the oscillation period of the motoneuron. 3. A continuously oscillatory firing motoneuron innervating the external and sphincter showed more transient breaks with the reduction of the number of phase correlated APs from 2 spindle afferents, indicating a looser oscillation. A transient brake of a 157 msec period alpha 2-oscillation could be correlated to the shift of a interspike interval distribution peak from 150 to 180 msec of the adequate afferent input, which suggests a transient loss of the necessary phase relation. 4. Oscillatory firing alpha 2-motoneurons innervating the external bladder and anal sphincters fired independently according to their phase correlated APs from the urinary bladder stretch receptor and muscle spindle afferents respectively; the bladder motoneuron slightly inhibited the anal motoneuron. 5. Receptors of the afferents and innervation sites of oscillatory firing motoneurons could be located within the urinary tract and the anal canal.

Oscillatory activity in the infant brain reflects object maintenance.

PubMed

Kaufman, Jordy; Csibra, Gergely; Johnson, Mark H

2005-10-18

The apparent failure of infants to understand "object permanence" by reaching for hidden objects is perhaps the most striking and debated phenomenon in cognitive development. Of particular interest is the extent to which infants perceive and remember objects in a similar way to that of adults. Here we report two findings that clarify infant object processing. The first is that 6-mo-old infants are sensitive to visual cues to occlusion, particularly gradual deletion. The second finding is that oscillatory electroencephalogram activity recorded over right temporal channels is involved in object maintenance. This effect occurs only after disappearance in a manner consistent with occlusion and the object's continued existence.

Brain oscillatory substrates of visual short-term memory capacity.

PubMed

Sauseng, Paul; Klimesch, Wolfgang; Heise, Kirstin F; Gruber, Walter R; Holz, Elisa; Karim, Ahmed A; Glennon, Mark; Gerloff, Christian; Birbaumer, Niels; Hummel, Friedhelm C

2009-11-17

The amount of information that can be stored in visual short-term memory is strictly limited to about four items. Therefore, memory capacity relies not only on the successful retention of relevant information but also on efficient suppression of distracting information, visual attention, and executive functions. However, completely separable neural signatures for these memory capacity-limiting factors remain to be identified. Because of its functional diversity, oscillatory brain activity may offer a utile solution. In the present study, we show that capacity-determining mechanisms, namely retention of relevant information and suppression of distracting information, are based on neural substrates independent of each other: the successful maintenance of relevant material in short-term memory is associated with cross-frequency phase synchronization between theta (rhythmical neural activity around 5 Hz) and gamma (> 50 Hz) oscillations at posterior parietal recording sites. On the other hand, electroencephalographic alpha activity (around 10 Hz) predicts memory capacity based on efficient suppression of irrelevant information in short-term memory. Moreover, repetitive transcranial magnetic stimulation at alpha frequency can modulate short-term memory capacity by influencing the ability to suppress distracting information. Taken together, the current study provides evidence for a double dissociation of brain oscillatory correlates of visual short-term memory capacity.

Spectral Variability in the Aged Brain during Fine Motor Control

PubMed Central

Quandt, Fanny; Bönstrup, Marlene; Schulz, Robert; Timmermann, Jan E.; Zimerman, Maximo; Nolte, Guido; Hummel, Friedhelm C.

2016-01-01

Physiological aging is paralleled by a decline of fine motor skills accompanied by structural and functional alterations of the underlying brain network. Here, we aim to investigate age-related changes in the spectral distribution of neuronal oscillations during fine skilled motor function. We employ the concept of spectral entropy in order to describe the flatness and peaked-ness of a frequency spectrum to quantify changes in the spectral distribution of the oscillatory motor response in the aged brain. Electroencephalogram was recorded in elderly (n = 32) and young (n = 34) participants who performed either a cued finger movement or a pinch or a whole hand grip task with their dominant right hand. Whereas young participant showed distinct, well-defined movement-related power decreases in the alpha and upper beta band, elderly participants exhibited a flat broadband, frequency-unspecific power desynchronization. This broadband response was reflected by an increase of spectral entropy over sensorimotor and frontal areas in the aged brain. Neuronal activation patterns differed between motor tasks in the young brain, while the aged brain showed a similar activation pattern in all tasks. Moreover, we found a wider recruitment of the cortical motor network in the aged brain. The present study adds to the understanding of age-related changes of neural coding during skilled motor behavior, revealing a less predictable signal with great variability across frequencies in a wide cortical motor network in the aged brain. The increase in entropy in the aged brain could be a reflection of random noise-like activity or could represent a compensatory mechanism that serves a functional role. PMID:28066231

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.

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.

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.

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.

Development and aminergic neuromodulation of a spinal locomotor network controlling swimming in Xenopus larvae.

PubMed

Sillar, K T; Reith, C A; McDearmid, J R

1998-11-16

In this article we review our research on the development and intrinsic neuromodulation of a spinal network controlling locomotion in a simple vertebrate. Swimming in hatchling Xenopus embryos is generated by a restricted network of well-characterized spinal neurons. This network produces a stereotyped motor pattern which, like real swimming, involves rhythmic activity that alternates across the body and progresses rostrocaudally with a brief delay between muscle segments. The stereotypy results from motoneurons discharging a single impulse in each cycle; because all motoneurons appear to behave similarly there is little scope for altering the output to the myotomes from one cycle to the next. Just one day later, however, Xenopus larvae generate a more complex and flexible motor pattern in which motoneurons can discharge a variable number of impulses which contribute to ventral root bursts in each cycle. This maturation of swimming is due, in part, to the influence of serotonin released from brain-stem raphespinal interneurons whose axonal projections innervate the cord early in larval life. Larval swimming is differentially modulated by both serotonin and by noradrenaline: serotonin leads to relatively fast, intense swimming whereas noradrenaline favors slower, weaker activity. Thus, these two biogenic amines select opposite extremes from the spectrum of possible output patterns that the swimming network can produce. Our studies on the cellular and synaptic effects of the amines indicate that they can control the strength of reciprocal glycinergic inhibition in the spinal cord. Serotonin and noradrenaline act presynaptically on the terminals of glycinergic commissural interneurons to weaken and strengthen, respectively, crossed glycinergic inhibition during swimming. As a result, serotonin reduces and noradrenaline increases interburst intervals. The membrane properties of spinal neurons are also affected by the amines. In particular, serotonin can induce intrinsic oscillatory membrane properties in the presence of NMDA. These depolarizations are slow compared to the cycle periods during swimming and so may contribute to enhancement of swimming over several consecutive cycles of activity.

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.

LES-based characterization of a suction and oscillatory blowing fluidic actuator

NASA Astrophysics Data System (ADS)

Kim, Jeonglae; Moin, Parviz

2015-11-01

Recently, a novel fluidic actuator using steady suction and oscillatory blowing was developed for control of turbulent flows. The suction and oscillatory blowing (SaOB) actuator combines steady suction and pulsed oscillatory blowing into a single device. The actuation is based upon a self-sustained mechanism of confined jets and does not require any moving parts. The control output is determined by a pressure source and the geometric details, and no additional input is needed. While its basic mechanisms have been investigated to some extent, detailed characteristics of internal turbulent flows are not well understood. In this study, internal flows of the SaOB actuator are simulated using large-eddy simulation (LES). Flow characteristics within the actuator are described in detail for a better understanding of the physical mechanisms and improving the actuator design. LES predicts the self-sustained oscillations of the turbulent jet. Switching frequency, maximum velocity at the actuator outlets, and wall pressure distribution are in good agreement with the experimental measurements. The computational results are used to develop simplified boundary conditions for numerical experiments of active flow control. Supported by the Boeing company.

Frequency specific brain networks in Parkinson's disease and comorbid depression.

PubMed

Qian, Long; Zhang, Yi; Zheng, Li; Fu, Xuemei; Liu, Weiguo; Shang, Yuqing; Zhang, Yaoyu; Xu, Yuanyuan; Liu, Yijun; Zhu, Huaiqiu; Gao, Jia-Hong

2017-02-01

The topological organization underlying the human brain was extensively investigated using resting-state functional magnetic resonance imaging, focusing on a low frequency of signal oscillation from 0.01 to 0.1 Hz. However, the frequency specificities with regard to the topological properties of the brain networks have not been fully revealed. In this study, a novel complementary ensemble empirical mode decomposition (CEEMD) method was used to separate the fMRI time series into five characteristic oscillations with distinct frequencies. Then, the small world properties of brain networks were analyzed for each of these five oscillations in patients (n = 67) with depressed Parkinson's disease (DPD, n = 20) , non-depressed Parkinson's disease (NDPD, n = 47) and healthy controls (HC, n = 46). Compared with HC, the results showed decreased network efficiency in characteristic oscillations from 0.05 to 0.12 Hz and from 0.02 to 0.05 Hz for the DPD and NDPD patients, respectively. Furthermore, compared with HC, the most significant inter-group difference across five brain oscillations was found in the basal ganglia (0.01 to 0.05 Hz) and paralimbic-limbic network (0.02 to 0.22 Hz) for the DPD patients, and in the visual cortex (0.02 to 0.05 Hz) for the NDPD patients. Compared with NDPD, the DPD patients showed reduced efficiency of nodes in the basal ganglia network (0.01 to 0.05 Hz). Our results demonstrated that DPD is characterized by a disrupted topological organization in large-scale brain functional networks. Moreover, the CEEMD analysis suggested a prominent dissociation in the topological organization of brain networks between DPD and NDPD in both space and frequency domains. Our findings indicated that these characteristic oscillatory activities in different functional circuits may contribute to distinct motor and non-motor components of clinical impairments in Parkinson's disease.

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.

rTMS Induced Tinnitus Relief Is Related to an Increase in Auditory Cortical Alpha Activity

PubMed Central

Müller, Nadia; Lorenz, Isabel; Langguth, Berthold; Weisz, Nathan

2013-01-01

Chronic tinnitus, the continuous perception of a phantom sound, is a highly prevalent audiological symptom. A promising approach for the treatment of tinnitus is repetitive transcranial magnetic stimulation (rTMS) as this directly affects tinnitus-related brain activity. Several studies indeed show tinnitus relief after rTMS, however effects are moderate and vary strongly across patients. This may be due to a lack of knowledge regarding how rTMS affects oscillatory activity in tinnitus sufferers and which modulations are associated with tinnitus relief. In the present study we examined the effects of five different stimulation protocols (including sham) by measuring tinnitus loudness and tinnitus-related brain activity with Magnetoencephalography before and after rTMS. Changes in oscillatory activity were analysed for the stimulated auditory cortex as well as for the entire brain regarding certain frequency bands of interest (delta, theta, alpha, gamma). In line with the literature the effects of rTMS on tinnitus loudness varied strongly across patients. This variability was also reflected in the rTMS effects on oscillatory activity. Importantly, strong reductions in tinnitus loudness were associated with increases in alpha power in the stimulated auditory cortex, while an unspecific decrease in gamma and alpha power, particularly in left frontal regions, was linked to an increase in tinnitus loudness. The identification of alpha power increase as main correlate for tinnitus reduction sheds further light on the pathophysiology of tinnitus. This will hopefully stimulate the development of more effective therapy approaches. PMID:23390539

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.

Activity patterns in networks stabilized by background oscillations.

PubMed

Hoppensteadt, Frank

2009-07-01

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

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

Endocannabinoid-dependent protection against kainic acid-induced long-term alteration of brain oscillations in guinea pigs.

PubMed

Shubina, Liubov; Aliev, Rubin; Kitchigina, Valentina

2017-04-15

Changes in rhythmic activity can serve as early biomarkers of pathological alterations, but it remains unclear how different types of rhythmic activity are altered during neurodegenerative processes. Glutamatergic neurotoxicity, evoked by kainic acid (KA), causes hyperexcitation and acute seizures that result in delayed brain damage. We employed wide frequency range (0.1-300Hz) local field potential recordings in guinea pigs to study the oscillatory activity of the hippocampus, entorhinal cortex, medial septum, and amygdala in healthy animals for three months after KA introduction. To clarify whether the activation of endocannabinoid (eCB) system can influence toxic KA action, AM404, an eCB reuptake inhibitor, and URB597, an inhibitor of fatty acid amide hydrolase, were applied. The cannabinoid CB1 receptor antagonist AM251 was also tested. Coadministration of AM404 or URB597 with KA reduced acute behavioral seizures, but electrographic seizures were still registered. During the three months following KA injection, various trends in the oscillatory activities were observed, including an increase in activity power at all frequency bands in the hippocampus and a progressive long-term decrease in the medial septum. In the KA- and KA/AM251-treated animals, disturbances of the oscillatory activities were accompanied by cell loss in the dorsal hippocampus and mossy fiber sprouting in the dentate gyrus. Injections of AM404 or URB597 softened alterations in electrical activity of the brain and prevented hippocampal neuron loss and synaptic reorganization. Our results demonstrate the protective potential of the eCB system during excitotoxic influences. Copyright © 2017 Elsevier B.V. All rights reserved.

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.

Locally induced neuronal synchrony precisely propagates to specific cortical areas without rhythm distortion.

PubMed

Toda, Haruo; Kawasaki, Keisuke; Sato, Sho; Horie, Masao; Nakahara, Kiyoshi; Bepari, Asim K; Sawahata, Hirohito; Suzuki, Takafumi; Okado, Haruo; Takebayashi, Hirohide; Hasegawa, Isao

2018-05-16

Propagation of oscillatory spike firing activity at specific frequencies plays an important role in distributed cortical networks. However, there is limited evidence for how such frequency-specific signals are induced or how the signal spectra of the propagating signals are modulated during across-layer (radial) and inter-areal (tangential) neuronal interactions. To directly evaluate the direction specificity of spectral changes in a spiking cortical network, we selectively photostimulated infragranular excitatory neurons in the rat primary visual cortex (V1) at a supra-threshold level with various frequencies, and recorded local field potentials (LFPs) at the infragranular stimulation site, the cortical surface site immediately above the stimulation site in V1, and cortical surface sites outside V1. We found a significant reduction of LFP powers during radial propagation, especially at high-frequency stimulation conditions. Moreover, low-gamma-band dominant rhythms were transiently induced during radial propagation. Contrastingly, inter-areal LFP propagation, directed to specific cortical sites, accompanied no significant signal reduction nor gamma-band power induction. We propose an anisotropic mechanism for signal processing in the spiking cortical network, in which the neuronal rhythms are locally induced/modulated along the radial direction, and then propagate without distortion via intrinsic horizontal connections for spatiotemporally precise, inter-areal communication.

Intra- and interbrain synchronization and network properties when playing guitar in duets

PubMed Central

Sänger, Johanna; Müller, Viktor; Lindenberger, Ulman

2012-01-01

To further test and explore the hypothesis that synchronous oscillatory brain activity supports interpersonally coordinated behavior during dyadic music performance, we simultaneously recorded the electroencephalogram (EEG) from the brains of each of 12 guitar duets repeatedly playing a modified Rondo in two voices by C.G. Scheidler. Indicators of phase locking and of within-brain and between-brain phase coherence were obtained from complex time-frequency signals based on the Gabor transform. Analyses were restricted to the delta (1–4 Hz) and theta (4–8 Hz) frequency bands. We found that phase locking as well as within-brain and between-brain phase-coherence connection strengths were enhanced at frontal and central electrodes during periods that put particularly high demands on musical coordination. Phase locking was modulated in relation to the experimentally assigned musical roles of leader and follower, corroborating the functional significance of synchronous oscillations in dyadic music performance. Graph theory analyses revealed within-brain and hyperbrain networks with small-worldness properties that were enhanced during musical coordination periods, and community structures encompassing electrodes from both brains (hyperbrain modules). We conclude that brain mechanisms indexed by phase locking, phase coherence, and structural properties of within-brain and hyperbrain networks support interpersonal action coordination (IAC). PMID:23226120

Bidirectional Frontoparietal Oscillatory Systems Support Working Memory.

PubMed

Johnson, Elizabeth L; Dewar, Callum D; Solbakk, Anne-Kristin; Endestad, Tor; Meling, Torstein R; Knight, Robert T

2017-06-19

The ability to represent and select information in working memory provides the neurobiological infrastructure for human cognition. For 80 years, dominant views of working memory have focused on the key role of prefrontal cortex (PFC) [1-8]. However, more recent work has implicated posterior cortical regions [9-12], suggesting that PFC engagement during working memory is dependent on the degree of executive demand. We provide evidence from neurological patients with discrete PFC damage that challenges the dominant models attributing working memory to PFC-dependent systems. We show that neural oscillations, which provide a mechanism for PFC to communicate with posterior cortical regions [13], independently subserve communications both to and from PFC-uncovering parallel oscillatory mechanisms for working memory. Fourteen PFC patients and 20 healthy, age-matched controls performed a working memory task where they encoded, maintained, and actively processed information about pairs of common shapes. In controls, the electroencephalogram (EEG) exhibited oscillatory activity in the low-theta range over PFC and directional connectivity from PFC to parieto-occipital regions commensurate with executive processing demands. Concurrent alpha-beta oscillations were observed over parieto-occipital regions, with directional connectivity from parieto-occipital regions to PFC, regardless of processing demands. Accuracy, PFC low-theta activity, and PFC → parieto-occipital connectivity were attenuated in patients, revealing a PFC-independent, alpha-beta system. The PFC patients still demonstrated task proficiency, which indicates that the posterior alpha-beta system provides sufficient resources for working memory. Taken together, our findings reveal neurologically dissociable PFC and parieto-occipital systems and suggest that parallel, bidirectional oscillatory systems form the basis of working memory. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

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.

Rheological aspects of C. elegans suspensions under oscillatory shear

NASA Astrophysics Data System (ADS)

Malvar, Sara; Carmo, Bruno S.; Cunha, Francisco R.

2017-11-01

The rheological nature of an active suspension of nematodes is discussed. The nematode chosen for the study is Caenorhabditis elegans and its motion is subjected to the time reversibility of creeping flows. We investigate how the movement of the nematodes under different volumetric fractions alter the fluid rheological characteristics, considering collective behavior. We provide a deep discussion based on the experimental data obtained through a rotating disk rheometer. Oscillatory shear and step strain tests were conducted in order to present a discussion regarding zero shear viscosity and relaxation time for different nematodes concentrations. Moreover, theassociated time scales coupling provide a good physical comprehension of active suspensions. The authors wish to aknowledge the following Brazilian research foundation: Fapesp.

Goal-directed control with cortical units that are gated by both top-down feedback and oscillatory coherence.

PubMed

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

2014-01-01

The brain is able to flexibly select behaviors that adapt to both its environment and its present goals. This cognitive control is understood to occur within the hierarchy of the cortex and relies strongly on the prefrontal and premotor cortices, which sit at the top of this hierarchy. Pyramidal neurons, the principal neurons in the cortex, have been observed to exhibit much stronger responses when they receive inputs at their soma/basal dendrites that are coincident with inputs at their apical dendrites. This corresponds to inputs from both lower-order regions (feedforward) and higher-order regions (feedback), respectively. In addition to this, coherence between oscillations, such as gamma oscillations, in different neuronal groups has been proposed to modulate and route communication in the brain. In this paper, we develop a simple, but novel, neural mass model in which cortical units (or ensembles) exhibit gamma oscillations when they receive coherent oscillatory inputs from both feedforward and feedback connections. By forming these units into circuits that can perform logic operations, we identify the different ways in which operations can be initiated and manipulated by top-down feedback. We demonstrate that more sophisticated and flexible top-down control is possible when the gain of units is modulated by not only top-down feedback but by coherence between the activities of the oscillating units. With these types of units, it is possible to not only add units to, or remove units from, a higher-level unit's logic operation using top-down feedback, but also to modify the type of role that a unit plays in the operation. Finally, we explore how different network properties affect top-down control and processing in large networks. Based on this, we make predictions about the likely connectivities between certain brain regions that have been experimentally observed to be involved in goal-directed behavior and top-down attention.

Goal-directed control with cortical units that are gated by both top-down feedback and oscillatory coherence

PubMed Central

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

2014-01-01

The brain is able to flexibly select behaviors that adapt to both its environment and its present goals. This cognitive control is understood to occur within the hierarchy of the cortex and relies strongly on the prefrontal and premotor cortices, which sit at the top of this hierarchy. Pyramidal neurons, the principal neurons in the cortex, have been observed to exhibit much stronger responses when they receive inputs at their soma/basal dendrites that are coincident with inputs at their apical dendrites. This corresponds to inputs from both lower-order regions (feedforward) and higher-order regions (feedback), respectively. In addition to this, coherence between oscillations, such as gamma oscillations, in different neuronal groups has been proposed to modulate and route communication in the brain. In this paper, we develop a simple, but novel, neural mass model in which cortical units (or ensembles) exhibit gamma oscillations when they receive coherent oscillatory inputs from both feedforward and feedback connections. By forming these units into circuits that can perform logic operations, we identify the different ways in which operations can be initiated and manipulated by top-down feedback. We demonstrate that more sophisticated and flexible top-down control is possible when the gain of units is modulated by not only top-down feedback but by coherence between the activities of the oscillating units. With these types of units, it is possible to not only add units to, or remove units from, a higher-level unit's logic operation using top-down feedback, but also to modify the type of role that a unit plays in the operation. Finally, we explore how different network properties affect top-down control and processing in large networks. Based on this, we make predictions about the likely connectivities between certain brain regions that have been experimentally observed to be involved in goal-directed behavior and top-down attention. PMID:25152715

Kinetic insights over a PEMFC operating on stationary and oscillatory states.

PubMed

Mota, Andressa; Gonzalez, Ernesto R; Eiswirth, Markus

2011-12-01

Kinetic investigations in the oscillatory state have been carried out in order to shed light on the interplay between the complex kinetics exhibited by a proton exchange membrane fuel cell fed with poisoned H(2) (108 ppm of CO) and the other in serie process. The apparent activation energy (E(a)) in the stationary state was investigated in order to clarify the E(a) observed in the oscillatory state. The apparent activation energy in the stationary state, under potentiostatic control, rendered (a) E(a) ≈ 50-60 kJ mol(-1) over 0.8 V < E < 0.6 V and (b) E(a) ≈ 10 kJ mol(-1) at E = 0.3 V. The former is related to the H(2) adsorption in the vacancies of the surface poisoned by CO and the latter is correlated to the process of proton conductivity in the membrane. The dependence of the period-one oscillations on the temperature yielded a genuine Arrhenius dependence with two E(a) values: (a) E(a) around 70 kJ mol(-1), at high temperatures, and (b) E(a) around 10-15 kJ mol(-1), at lower temperatures. The latter E(a) indicates the presence of protonic mass transport coupled to the essential oscillatory mechanism. These insights point in the right direction to predict spatial couplings between anode and cathode as having the highest strength as well as to speculate the most likely candidates to promote spatial inhomogeneities. © 2011 American Chemical Society

Resting state EEG correlates of memory consolidation.

PubMed

Brokaw, Kate; Tishler, Ward; Manceor, Stephanie; Hamilton, Kelly; Gaulden, Andrew; Parr, Elaine; Wamsley, Erin J

2016-04-01

Numerous studies demonstrate that post-training sleep benefits human memory. At the same time, emerging data suggest that other resting states may similarly facilitate consolidation. In order to identify the conditions under which non-sleep resting states benefit memory, we conducted an EEG (electroencephalographic) study of verbal memory retention across 15min of eyes-closed rest. Participants (n=26) listened to a short story and then either rested with their eyes closed, or else completed a distractor task for 15min. A delayed recall test was administered immediately following the rest period. We found, first, that quiet rest enhanced memory for the short story. Improved memory was associated with a particular EEG signature of increased slow oscillatory activity (<1Hz), in concert with reduced alpha (8-12Hz) activity. Mindwandering during the retention interval was also associated with improved memory. These observations suggest that a short period of quiet rest can facilitate memory, and that this may occur via an active process of consolidation supported by slow oscillatory EEG activity and characterized by decreased attention to the external environment. Slow oscillatory EEG rhythms are proposed to facilitate memory consolidation during sleep by promoting hippocampal-cortical communication. Our findings suggest that EEG slow oscillations could play a significant role in memory consolidation during other resting states as well. Copyright © 2016 Elsevier Inc. All rights reserved.

Learning alters theta amplitude, theta-gamma coupling and neuronal synchronization in inferotemporal cortex.

PubMed

Kendrick, Keith M; Zhan, Yang; Fischer, Hanno; Nicol, Alister U; Zhang, Xuejuan; Feng, Jianfeng

2011-06-09

How oscillatory brain rhythms alone, or in combination, influence cortical information processing to support learning has yet to be fully established. Local field potential and multi-unit neuronal activity recordings were made from 64-electrode arrays in the inferotemporal cortex of conscious sheep during and after visual discrimination learning of face or object pairs. A neural network model has been developed to simulate and aid functional interpretation of learning-evoked changes. Following learning the amplitude of theta (4-8 Hz), but not gamma (30-70 Hz) oscillations was increased, as was the ratio of theta to gamma. Over 75% of electrodes showed significant coupling between theta phase and gamma amplitude (theta-nested gamma). The strength of this coupling was also increased following learning and this was not simply a consequence of increased theta amplitude. Actual discrimination performance was significantly correlated with theta and theta-gamma coupling changes. Neuronal activity was phase-locked with theta but learning had no effect on firing rates or the magnitude or latencies of visual evoked potentials during stimuli. The neural network model developed showed that a combination of fast and slow inhibitory interneurons could generate theta-nested gamma. By increasing N-methyl-D-aspartate receptor sensitivity in the model similar changes were produced as in inferotemporal cortex after learning. The model showed that these changes could potentiate the firing of downstream neurons by a temporal desynchronization of excitatory neuron output without increasing the firing frequencies of the latter. This desynchronization effect was confirmed in IT neuronal activity following learning and its magnitude was correlated with discrimination performance. Face discrimination learning produces significant increases in both theta amplitude and the strength of theta-gamma coupling in the inferotemporal cortex which are correlated with behavioral performance. A network model which can reproduce these changes suggests that a key function of such learning-evoked alterations in theta and theta-nested gamma activity may be increased temporal desynchronization in neuronal firing leading to optimal timing of inputs to downstream neural networks potentiating their responses. In this way learning can produce potentiation in neural networks simply through altering the temporal pattern of their inputs.

Learning alters theta amplitude, theta-gamma coupling and neuronal synchronization in inferotemporal cortex

PubMed Central

2011-01-01

Background How oscillatory brain rhythms alone, or in combination, influence cortical information processing to support learning has yet to be fully established. Local field potential and multi-unit neuronal activity recordings were made from 64-electrode arrays in the inferotemporal cortex of conscious sheep during and after visual discrimination learning of face or object pairs. A neural network model has been developed to simulate and aid functional interpretation of learning-evoked changes. Results Following learning the amplitude of theta (4-8 Hz), but not gamma (30-70 Hz) oscillations was increased, as was the ratio of theta to gamma. Over 75% of electrodes showed significant coupling between theta phase and gamma amplitude (theta-nested gamma). The strength of this coupling was also increased following learning and this was not simply a consequence of increased theta amplitude. Actual discrimination performance was significantly correlated with theta and theta-gamma coupling changes. Neuronal activity was phase-locked with theta but learning had no effect on firing rates or the magnitude or latencies of visual evoked potentials during stimuli. The neural network model developed showed that a combination of fast and slow inhibitory interneurons could generate theta-nested gamma. By increasing N-methyl-D-aspartate receptor sensitivity in the model similar changes were produced as in inferotemporal cortex after learning. The model showed that these changes could potentiate the firing of downstream neurons by a temporal desynchronization of excitatory neuron output without increasing the firing frequencies of the latter. This desynchronization effect was confirmed in IT neuronal activity following learning and its magnitude was correlated with discrimination performance. Conclusions Face discrimination learning produces significant increases in both theta amplitude and the strength of theta-gamma coupling in the inferotemporal cortex which are correlated with behavioral performance. A network model which can reproduce these changes suggests that a key function of such learning-evoked alterations in theta and theta-nested gamma activity may be increased temporal desynchronization in neuronal firing leading to optimal timing of inputs to downstream neural networks potentiating their responses. In this way learning can produce potentiation in neural networks simply through altering the temporal pattern of their inputs. PMID:21658251

Functional network inference of the suprachiasmatic nucleus

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

Abel, John H.; Meeker, Kirsten; Granados-Fuentes, Daniel

2016-04-04

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 frommore » 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.« less

Oscillatory brain activity differentially reflects false belief understanding and complementation syntax processing.

PubMed

Guan, Yao; Farrar, M Jeffrey; Keil, Andreas

2018-02-01

False belief understanding (FBU) enables people to consider conflicting beliefs about the same situation. While language has been demonstrated to be a correlate of FBU, there is still controversy about the extent to which a specific aspect of language, complementation syntax, is a necessary condition for FBU. The present study tested an important notion from the debate proposing that complementation syntax task is redundant to FBU measures. Specifically, we examined electrophysiological correlates of false belief, false complementation, and their respective true conditions in adults using electroencephalography (EEG), focusing on indices of oscillatory brain activity and large-scale connectivity. The results showed strong modulation of parieto-occipital alpha (8-12 Hz) and beta (13-20 Hz) power by the experimental manipulations, with heightened sustained alpha power reflective of effortful internal processing observed in the false compared to the true conditions and reliable beta power reductions sensitive to mentalizing and/or syntactic demands in the belief versus the complementation conditions. In addition, higher coupling between parieto-occipital regions and widespread frontal sites in the beta band was found for the false-belief condition selectively. The result of divergence in beta oscillatory activity and in connectivity between false belief and false complementation does not support the redundancy hypothesis.

EEG Mu (µ) rhythm spectra and oscillatory activity differentiate stuttering from non-stuttering adults.

PubMed

Saltuklaroglu, Tim; Harkrider, Ashley W; Thornton, David; Jenson, David; Kittilstved, Tiffani

2017-06-01

Stuttering is linked to sensorimotor deficits related to internal modeling mechanisms. This study compared spectral power and oscillatory activity of EEG mu (μ) rhythms between persons who stutter (PWS) and controls in listening and auditory discrimination tasks. EEG data were analyzed from passive listening in noise and accurate (same/different) discrimination of tones or syllables in quiet and noisy backgrounds. Independent component analysis identified left and/or right μ rhythms with characteristic alpha (α) and beta (β) peaks localized to premotor/motor regions in 23 of 27 people who stutter (PWS) and 24 of 27 controls. PWS produced μ spectra with reduced β amplitudes across conditions, suggesting reduced forward modeling capacity. Group time-frequency differences were associated with noisy conditions only. PWS showed increased μ-β desynchronization when listening to noise and early in discrimination events, suggesting evidence of heightened motor activity that might be related to forward modeling deficits. PWS also showed reduced μ-α synchronization in discrimination conditions, indicating reduced sensory gating. Together these findings indicate spectral and oscillatory analyses of μ rhythms are sensitive to stuttering. More specifically, they can reveal stuttering-related sensorimotor processing differences in listening and auditory discrimination that also may be influenced by basal ganglia deficits. Copyright © 2017 Elsevier Inc. All rights reserved.

Cerebellar Influence on Motor Cortex Plasticity: Behavioral Implications for Parkinson’s Disease

PubMed Central

Kishore, Asha; Meunier, Sabine; Popa, Traian

2014-01-01

Normal motor behavior involves the creation of appropriate activity patterns across motor networks, enabling firing synchrony, synaptic integration, and normal functioning of these networks. Strong topography-specific connections among the basal ganglia, cerebellum, and their projections to overlapping areas in the motor cortices suggest that these networks could influence each other’s plastic responses and functions. The defective striatal signaling in Parkinson’s disease (PD) could therefore lead to abnormal oscillatory activity and aberrant plasticity at multiple levels within the interlinked motor networks. Normal striatal dopaminergic signaling and cerebellar sensory processing functions influence the scaling and topographic specificity of M1 plasticity. Both these functions are abnormal in PD and appear to contribute to the abnormal M1 plasticity. Defective motor map plasticity and topographic specificity within M1 could lead to incorrect muscle synergies, which could manifest as abnormal or undesired movements, and as abnormal motor learning in PD. We propose that the loss of M1 plasticity in PD reflects a loss of co-ordination among the basal ganglia, cerebellar, and cortical inputs which translates to an abnormal plasticity of motor maps within M1 and eventually to some of the motor signs of PD. The initial benefits of dopamine replacement therapy on M1 plasticity and motor signs are lost during the progressive course of disease. Levodopa-induced dyskinesias in patients with advanced PD is linked to a loss of M1 sensorimotor plasticity and the attenuation of dyskinesias by cerebellar inhibitory stimulation is associated with restoration of M1 plasticity. Complimentary interventions should target reestablishing physiological communication between the striatal and cerebellar circuits, and within striato-cerebellar loop. This may facilitate correct motor synergies and reduce abnormal movements in PD. PMID:24834063

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

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

Cortical oscillations scan using chirp-evoked potentials in 6-hydroxydopamine rat model of Parkinson's disease.

PubMed

Pérez-Alcázar, Marta; Nicolás, María Jesús; Valencia, Miguel; Alegre, Manuel; López-Azcárate, Jon; Iriarte, Jorge; Artieda, Julio

2010-01-15

There has been a growing interest during the last years on the relationship between Parkinson's disease and changes in the oscillatory activity, mostly in the cortico-basal motor loop. As Parkinson's disease (PD) is not limited to motor symptoms, it is logical to assume that the changes in oscillatory activity are not limited to this loop. Steady-state responses (SSR) are the result of averaging individual responses to trains of rhythmic stimuli delivered at a constant frequency. The amplitude of the response varies depending on the stimulus modality and stimulation rate, with a frequency of maximal response that is probably associated to the working frequency of the pathway involved. The study of SSR may be of interest in PD as a non-invasive test of cortical oscillatory activity. Our aim was to study the changes in auditory steady-state responses (ASSR) in the 6-hydroxydopamine (6-OHDA) model of Parkinson's disease in rats. We recorded the ASSR over the auditory cortex in a group of 10 control and 17 6-OHDA lesioned rats (the latter before and after the administration of the dopaminergic agonist apomorphine) both awake and under anesthesia with ketamine/xylazine, using chirp-modulated stimuli. The three conditions (control, lesion, lesion plus apomorphine) were compared with special emphasis on the amplitude, inter-trial phase coherence, and frequency of maximal response. A reduction in the frequency of maximal response (between 40 and 60 Hz) was observed in the 6-OHDA lesioned rats that was normalized after apomorphine injection. The administration of this dopaminergic agonist also reduced the inter-trial phase coherence of the response in frequencies above 170 Hz. These findings suggest that the nigrostriatal dopaminergic system may be involved in the regulation of oscillatory activity not only in motor circuits, but also in sensory responses. Copyright 2009 Elsevier B.V. All rights reserved.

A fast, robust and tunable synthetic gene oscillator.

PubMed

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

2008-11-27

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

On oscillatory microstructure during cellular growth of directionally solidified Sn–36at.%Ni peritectic alloy

PubMed Central

Peng, Peng; Li, Xinzhong; Li, Jiangong; Su, Yanqing; Guo, Jingjie

2016-01-01

An oscillatory microstructure has been observed during deep-cellular growth of directionally solidified Sn–36at.%Ni hyperperitectic alloy containing intermetallic compounds with narrow solubility range. This oscillatory microstructure with a dimension of tens of micrometers has been observed for the first time. The morphology of this wave-like oscillatory structure is similar to secondary dendrite arms, and can be observed only in some local positions of the sample. Through analysis such as successive sectioning of the sample, it can be concluded that this oscillatory microstructure is caused by oscillatory convection of the mushy zone during solidification. And the influence of convection on this oscillatory microstructure was characterized through comparison between experimental and calculations results on the wavelength. Besides, the change in morphology of this oscillatory microstructure has been proved to be caused by peritectic transformation during solidification. Furthermore, the melt concentration increases continuously during solidification of intermetallic compounds with narrow solubility range, which helps formation of this oscillatory microstructure. PMID:27066761

On oscillatory microstructure during cellular growth of directionally solidified Sn-36at.%Ni peritectic alloy.

PubMed

Peng, Peng; Li, Xinzhong; Li, Jiangong; Su, Yanqing; Guo, Jingjie

2016-04-12

An oscillatory microstructure has been observed during deep-cellular growth of directionally solidified Sn-36at.%Ni hyperperitectic alloy containing intermetallic compounds with narrow solubility range. This oscillatory microstructure with a dimension of tens of micrometers has been observed for the first time. The morphology of this wave-like oscillatory structure is similar to secondary dendrite arms, and can be observed only in some local positions of the sample. Through analysis such as successive sectioning of the sample, it can be concluded that this oscillatory microstructure is caused by oscillatory convection of the mushy zone during solidification. And the influence of convection on this oscillatory microstructure was characterized through comparison between experimental and calculations results on the wavelength. Besides, the change in morphology of this oscillatory microstructure has been proved to be caused by peritectic transformation during solidification. Furthermore, the melt concentration increases continuously during solidification of intermetallic compounds with narrow solubility range, which helps formation of this oscillatory microstructure.

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

Slow oscillating transcranial direct current stimulation during sleep has a sleep-stabilizing effect in chronic insomnia: a pilot study.

PubMed

Saebipour, Mohammad R; Joghataei, Mohammad T; Yoonessi, Ali; Sadeghniiat-Haghighi, Khosro; Khalighinejad, Nima; Khademi, Soroush

2015-10-01

Recent evidence suggests that lack of slow-wave activity may play a fundamental role in the pathogenesis of insomnia. Pharmacological approaches and brain stimulation techniques have recently offered solutions for increasing slow-wave activity during sleep. We used slow (0.75 Hz) oscillatory transcranial direct current stimulation during stage 2 of non-rapid eye movement sleeping insomnia patients for resonating their brain waves to the frequency of sleep slow-wave. Six patients diagnosed with either sleep maintenance or non-restorative sleep insomnia entered the study. After 1 night of adaptation and 1 night of baseline polysomnography, patients randomly received sham or real stimulation on the third and fourth night of the experiment. Our preliminary results show that after termination of stimulations (sham or real), slow oscillatory transcranial direct current stimulation increased the duration of stage 3 of non-rapid eye movement sleep by 33 ± 26 min (P = 0.026), and decreased stage 1 of non-rapid eye movement sleep duration by 22 ± 17.7 min (P = 0.028), compared with sham. Slow oscillatory transcranial direct current stimulation decreased stage 1 of non-rapid eye movement sleep and wake time after sleep-onset durations, together, by 55.4 ± 51 min (P = 0.045). Slow oscillatory transcranial direct current stimulation also increased sleep efficiency by 9 ± 7% (P = 0.026), and probability of transition from stage 2 to stage 3 of non-rapid eye movement sleep by 20 ± 17.8% (P = 0.04). Meanwhile, slow oscillatory transcranial direct current stimulation decreased transitions from stage 2 of non-rapid eye movement sleep to wake by 12 ± 6.7% (P = 0.007). Our preliminary results suggest a sleep-stabilizing role for the intervention, which may mimic the effect of sleep slow-wave-enhancing drugs. © 2015 European Sleep Research Society.

The application of large amplitude oscillatory stress in a study of fully formed fibrin clots

NASA Astrophysics Data System (ADS)

Lamer, T. F.; Thomas, B. R.; Curtis, D. J.; Badiei, N.; Williams, P. R.; Hawkins, K.

2017-12-01

The suitability of controlled stress large amplitude oscillatory shear (LAOStress) for the characterisation of the nonlinear viscoelastic properties of fully formed fibrin clots is investigated. Capturing the rich nonlinear viscoelastic behaviour of the fibrin network is important for understanding the structural behaviour of clots formed in blood vessels which are exposed to a wide range of shear stresses. We report, for the first time, that artefacts due to ringing exist in both the sample stress and strain waveforms of a LAOStress measurement which will lead to errors in the calculation of nonlinear viscoelastic properties. The process of smoothing the waveforms eliminates these artefacts whilst retaining essential rheological information. Furthermore, we demonstrate the potential of LAOStress for characterising the nonlinear viscoelastic properties of fibrin clots in response to incremental increases of applied stress up to the point of fracture. Alternating LAOStress and small amplitude oscillatory shear measurements provide detailed information of reversible and irreversible structural changes of the fibrin clot as a consequence of elevated levels of stress. We relate these findings to previous studies involving large scale deformations of fibrin clots. The LAOStress technique may provide useful information to help understand why some blood clots formed in vessels are stable (such as in deep vein thrombosis) and others break off (leading to a life threatening pulmonary embolism).

Observations of Running Penumbral Waves Emerging in a Sunspot

NASA Astrophysics Data System (ADS)

Priya, T. G.; Wenda, Cao; Jiangtao, Su; Jie, Chen; Xinjie, Mao; Yuanyong, Deng; Robert, Erdélyi

2018-01-01

We present results from the investigation of 5 minute umbral oscillations in a single-polarity sunspot of active region NOAA 12132. The spectra of TiO, Hα, and 304 Å are used for corresponding atmospheric heights from the photosphere to lower corona. Power spectrum analysis at the formation height of Hα – 0.6 Å to the Hα center resulted in the detection of 5 minute oscillation signals in intensity interpreted as running waves outside the umbral center, mostly with vertical magnetic field inclination >15°. A phase-speed filter is used to extract the running wave signals with speed v ph > 4 km s‑1, from the time series of Hα – 0.4 Å images, and found twenty-four 3 minute umbral oscillatory events in a duration of one hour. Interestingly, the initial emergence of the 3 minute umbral oscillatory events are noticed closer to or at umbral boundaries. These 3 minute umbral oscillatory events are observed for the first time as propagating from a fraction of preceding running penumbral waves (RPWs). These fractional wavefronts rapidly separate from RPWs and move toward the umbral center, wherein they expand radially outwards suggesting the beginning of a new umbral oscillatory event. We found that most of these umbral oscillatory events develop further into RPWs. We speculate that the waveguides of running waves are twisted in spiral structures and hence the wavefronts are first seen at high latitudes of umbral boundaries and later at lower latitudes of the umbral center.

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.

Oscillatory patterns in sympathetic neural discharge and cardiovascular variables during orthostatic stimulus

NASA Technical Reports Server (NTRS)

Furlan, R.; Porta, A.; Costa, F.; Tank, J.; Baker, L.; Schiavi, R.; Robertson, D.; Malliani, A.; Mosqueda-Garcia, R.

2000-01-01

BACKGROUND: We tested the hypothesis that a common oscillatory pattern might characterize the rhythmic discharge of muscle sympathetic nerve activity (MSNA) and the spontaneous variability of heart rate and systolic arterial pressure (SAP) during a physiological increase of sympathetic activity induced by the head-up tilt maneuver. METHODS AND RESULTS: Ten healthy subjects underwent continuous recordings of ECG, intra-arterial pressure, respiratory activity, central venous pressure, and MSNA, both in the recumbent position and during 75 degrees head-up tilt. Venous samplings for catecholamine assessment were obtained at rest and during the fifth minute of tilt. Spectrum and cross-spectrum analyses of R-R interval, SAP, and MSNA variabilities and of respiratory activity provided the low (LF, 0.1 Hz) and high frequency (HF, 0.27 Hz) rhythmic components of each signal and assessed their linear relationships. Compared with the recumbent position, tilt reduced central venous pressure, but blood pressure was unchanged. Heart rate, MSNA, and plasma epinephrine and norepinephrine levels increased, suggesting a marked enhancement of overall sympathetic activity. During tilt, LF(MSNA) increased compared with the level in the supine position; this mirrored similar changes observed in the LF components of R-R interval and SAP variabilities. The increase of LF(MSNA) was proportional to the amount of the sympathetic discharge. The coupling between LF components of MSNA and R-R interval and SAP variabilities was enhanced during tilt compared with rest. CONCLUSIONS: During the sympathetic activation induced by tilt, a similar oscillatory pattern based on an increased LF rhythmicity characterized the spontaneous variability of neural sympathetic discharge, R-R interval, and arterial pressure.

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

Yoneda, Akihiro, E-mail: ayoneda@sci.hokudai.ac.jp; Division of Molecular Therapeutics, Center for Food & Medical Innovation, Hokkaido University; Watanabe, Tomomasa

In mammals, phospholipase Cζ (PLCζ) has the ability to trigger calcium (Ca{sup 2+}) oscillations in oocytes, leading to oocyte activation. Although there is a species-specific difference in the PLCζ-induced Ca{sup 2+} oscillatory pattern, whether PLCζ-induced Ca{sup 2+} oscillations affect preimplantation embryonic development remains unclear. Here, we show that Ca{sup 2+} oscillations in mouse PLCζ cRNA-injected oocytes stopped just before pronuclear formation, while that in porcine PLCζ cRNA-injected oocytes continued for several hours after pronuclei had been formed. This difference of Ca{sup 2+} oscillations in oocytes after pronuclear formation was dependent on the difference in the nuclear localization signal (NLS) sequencemore » of PLCζ between the mouse and pig. However, mouse and porcine PLCζ cRNA-injected oocytes parthenogenetically developed to blastocysts regardless of the absence or presence of Ca{sup 2+} oscillations after pronuclear formation. Furthermore, the developmental rate of mouse or porcine PLCζ-activated oocytes injected with round spermatids to the blastocyst stage was not significantly different from that of strontium-activated oocytes injected with round spermatids. These results suggest that the PLCζ-induced Ca{sup 2+} oscillatory pattern in mouse oocytes is dependent on the NLS sequence of PLCζ and injection of PLCζ may be a useful method for activation of round spermatid-injected and somatic nuclear transferred oocytes. - Highlights: • Porcine PLCζ-induced Ca{sup 2+} oscillations continued after pronuclear formation. • The Ca{sup 2+} oscillatory pattern was dependent on the difference in the NLS sequence of PLCζ. • PLCζ-activated oocytes parthenogenetically developed to blastocysts. • PLCζ-activated oocytes injected with round spermatids developed to blastocysts.« less

Influence of chronic endurance exercise training on conduit artery retrograde and oscillatory shear in older adults.

PubMed

Casey, Darren P; Schneider, Aaron C; Ueda, Kenichi

2016-10-01

With aging, there tends to be an increase in retrograde and oscillatory shear in peripheral conduit arteries of humans. Whether the increase in shear rate is due to the aging process or an effect of a less active lifestyle that often accompanies aging is unknown. Therefore, we examined whether chronic endurance exercise training attenuates conduit artery retrograde and oscillatory shear in older adults. Brachial and common femoral artery mean blood velocities and diameter were determined via Doppler ultrasound under resting conditions, and shear rate was calculated in 13 young (24 ± 2 years), 17 older untrained (66 ± 3 years), and 16 older endurance exercise-trained adults (66 ± 7 years). Brachial artery retrograde (-9.1 ± 6.4 vs. -12.6 ± 9.4 s(-1); P = 0.35) and oscillatory (0.14 ± 0.08 vs. 0.14 ± 0.08 arbitrary units; P = 0.99) shear were similar between the older trained and untrained groups, whereas brachial artery retrograde and oscillatory shear were greater in older untrained compared to young adults (-5.0 ± 3.4, 0.08 ± 0.05 s(-1) arbitrary units, P = 0.017 and 0.048, respectively). There was no difference between the young and older trained brachial retrograde (P = 0.29) and oscillatory (P = 0.07) shear. Common femoral artery retrograde (-6.3 ± 2.9 s(-1)) and oscillatory (0.21 ± 0.08 arbitrary units) shear were reduced in older trained compared to the older untrained group (-10.4 ± 4.1 and 0.30 ± 0.09 s(-1) arbitrary units, both P = 0.005 and 0.006, respectively), yet similar to young adults (-7.1 ± 3.5 and 0.19 ± 0.06 s(-1) arbitrary units, P = 0.81 and 0.87, respectively). Our results suggest that chronic endurance exercise training in older adults ameliorates retrograde and oscillatory shear rate patterns, particularly in the common femoral artery.

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.

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.

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

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.

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

PubMed

Campbell, S; Wang, D

1996-01-01

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

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

PubMed Central

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

2016-01-01

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

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.

Development of a morphing structure with the incorporation of central pattern generators

NASA Astrophysics Data System (ADS)

Bliss, Thomas K.; Bart-Smith, Hilary; Iwasaki, Tetsuya

2006-03-01

The Manta Ray, Manta birostris, is an amazing creature, propelling itself through the water with the elegant and complex flapping of its wings. Achieving outstanding efficiencies, engineers are looking for ways to mimic its flight through the water and harness its propulsive techniques. This study combines two biologically inspired aspects to achieve this goal: morphing structures actuated with a biomimetic neural network control system. It is believed that this combination will prove capable of producing the oscillatory motions necessary for locomotion. In this paper, a four-truss structure with three actuators is chosen and its performance capabilities are analyzed. A synthetic central pattern generator, which provides the fundamental control mechanisms for rhythmic motion in animals, is designed to realize an oscillatory control of the three actuators. The control system is simulated using Matlab, then combined with LabVIEW to control the four-truss structure. The system's performance is analyzed, with specific attention to both transient and steady-state behavior.

Oscillatory magnetic brain activity is related to dissociative symptoms and childhood adversities - A study in women with multiple trauma.

PubMed

Schalinski, I; Moran, J K; Elbert, T; Reindl, V; Wienbruch, C

2017-08-15

Individuals with trauma-related disorders are complex and heterogeneous; part of this complexity derives from additional psychopathology like dissociation as well as environmental adversities such as traumatic stress, experienced throughout the lifespan. Understanding the neurophysiological abnormalities in Post-traumatic stress disorder (PTSD) requires a simultaneous consideration of these factors. Resting state magnetoencephalography (MEG) recordings were obtained from 41 women with PTSD and comorbid depressive symptoms, and 16 healthy women. Oscillatory brain activity was extracted for five frequency bands and 11 source locations, and analyzed in relation to shutdown dissociation and adversity-related measures. Dissociative symptoms were related to increased delta and lowered beta power. Adversity-related measures modulated theta and alpha oscillatory power (in particular childhood sexual abuse) and differed between patients and controls. Findings are based on women with comorbid depressive symptoms and therefore may not be applicable for men or groups with other clinical profiles. In respect to childhood adversities, we had no reliable source for the early infancy. Trauma-related abnormalities in neural organization vary with both exposure to adversities as well as their potential to evoke ongoing shutdown responses. Copyright © 2017 Elsevier B.V. All rights reserved.

Training Working Memory in Childhood Enhances Coupling between Frontoparietal Control Network and Task-Related Regions.

PubMed

Barnes, Jessica J; Nobre, Anna Christina; Woolrich, Mark W; Baker, Kate; Astle, Duncan E

2016-08-24

Working memory is a capacity upon which many everyday tasks depend and which constrains a child's educational progress. We show that a child's working memory can be significantly enhanced by intensive computer-based training, relative to a placebo control intervention, in terms of both standardized assessments of working memory and performance on a working memory task performed in a magnetoencephalography scanner. Neurophysiologically, we identified significantly increased cross-frequency phase amplitude coupling in children who completed training. Following training, the coupling between the upper alpha rhythm (at 16 Hz), recorded in superior frontal and parietal cortex, became significantly coupled with high gamma activity (at ∼90 Hz) in inferior temporal cortex. This altered neural network activity associated with cognitive skill enhancement is consistent with a framework in which slower cortical rhythms enable the dynamic regulation of higher-frequency oscillatory activity related to task-related cognitive processes. Whether we can enhance cognitive abilities through intensive training is one of the most controversial topics of cognitive psychology in recent years. This is particularly controversial in childhood, where aspects of cognition, such as working memory, are closely related to school success and are implicated in numerous developmental disorders. We provide the first neurophysiological account of how working memory training may enhance ability in childhood, using a brain recording technique called magnetoencephalography. We borrowed an analysis approach previously used with intracranial recordings in adults, or more typically in other animal models, called "phase amplitude coupling." Copyright © 2016 Barnes et al.

A cortical network model of cognitive and emotional influences in human decision making.

PubMed

Nazir, Azadeh Hassannejad; Liljenström, Hans

2015-10-01

Decision making (DM)(2) is a complex process that appears to involve several brain structures. In particular, amygdala, orbitofrontal cortex (OFC) and lateral prefrontal cortex (LPFC) seem to be essential in human decision making, where both emotional and cognitive aspects are taken into account. In this paper, we present a computational network model representing the neural information processing of DM, from perception to behavior. We model the population dynamics of the three neural structures (amygdala, OFC and LPFC), as well as their interaction. In our model, the neurodynamic activity of amygdala and OFC represents the neural correlates of secondary emotion, while the activity of certain neural populations in OFC alone represents the outcome expectancy of different options. The cognitive/rational aspect of DM is associated with LPFC. Our model is intended to give insights on the emotional and cognitive processes involved in DM under various internal and external contexts. Different options for actions are represented by the oscillatory activity of cell assemblies, which may change due to experience and learning. Knowledge and experience of the outcome of our decisions and actions can eventually result in changes in our neural structures, attitudes and behaviors. Simulation results may have implications for how we make decisions for our individual actions, as well as for societal choices, where we take examples from transport and its impact on CO2 emissions and climate change. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Training Working Memory in Childhood Enhances Coupling between Frontoparietal Control Network and Task-Related Regions

PubMed Central

Barnes, Jessica J.; Nobre, Anna Christina; Woolrich, Mark W.; Baker, Kate

2016-01-01

Working memory is a capacity upon which many everyday tasks depend and which constrains a child's educational progress. We show that a child's working memory can be significantly enhanced by intensive computer-based training, relative to a placebo control intervention, in terms of both standardized assessments of working memory and performance on a working memory task performed in a magnetoencephalography scanner. Neurophysiologically, we identified significantly increased cross-frequency phase amplitude coupling in children who completed training. Following training, the coupling between the upper alpha rhythm (at 16 Hz), recorded in superior frontal and parietal cortex, became significantly coupled with high gamma activity (at ∼90 Hz) in inferior temporal cortex. This altered neural network activity associated with cognitive skill enhancement is consistent with a framework in which slower cortical rhythms enable the dynamic regulation of higher-frequency oscillatory activity related to task-related cognitive processes. SIGNIFICANCE STATEMENT Whether we can enhance cognitive abilities through intensive training is one of the most controversial topics of cognitive psychology in recent years. This is particularly controversial in childhood, where aspects of cognition, such as working memory, are closely related to school success and are implicated in numerous developmental disorders. We provide the first neurophysiological account of how working memory training may enhance ability in childhood, using a brain recording technique called magnetoencephalography. We borrowed an analysis approach previously used with intracranial recordings in adults, or more typically in other animal models, called “phase amplitude coupling.” PMID:27559180

Delayed reverberation through time windows as a key to cerebellar function.

PubMed

Kistler, W M; Leo van Hemmen, J

1999-11-01

We present a functional model of the cerebellum comprising cerebellar cortex, inferior olive, deep cerebellar nuclei, and brain stem nuclei. The discerning feature of the model being time coding, we consistently describe the system in terms of postsynaptic potentials, synchronous action potentials, and propagation delays. We show by means of detailed single-neuron modeling that (i) Golgi cells can fulfill a gating task in that they form short and well-defined time windows within which granule cells can reach firing threshold, thus organizing neuronal activity in discrete 'time slices', and that (ii) rebound firing in cerebellar nuclei cells is a robust mechanism leading to a delayed reverberation of Purkinje cell activity through cerebellar-reticular projections back to the cerebellar cortex. Computer simulations of the whole cerebellar network consisting of several thousand neurons reveal that reverberation in conjunction with long-term plasticity at the parallel fiber-Purkinje cell synapses enables the system to learn, store, and recall spatio-temporal patterns of neuronal activity. Climbing fiber spikes act both as a synchronization and as a teacher signal, not as an error signal. They are due to intrinsic oscillatory properties of inferior olivary neurons and to delayed reverberation within the network. In addition to clear experimental predictions the present theory sheds new light on a number of experimental observation such as the synchronicity of climbing fiber spikes and provides a novel explanation of how the cerebellum solves timing tasks on a time scale of several hundreds of milliseconds.

Spike Phase Locking in CA1 Pyramidal Neurons depends on Background Conductance and Firing Rate

PubMed Central

Broiche, Tilman; Malerba, Paola; Dorval, Alan D.; Borisyuk, Alla; Fernandez, Fernando R.; White, John A.

2012-01-01

Oscillatory activity in neuronal networks correlates with different behavioral states throughout the nervous system, and the frequency-response characteristics of individual neurons are believed to be critical for network oscillations. Recent in vivo studies suggest that neurons experience periods of high membrane conductance, and that action potentials are often driven by membrane-potential fluctuations in the living animal. To investigate the frequency-response characteristics of CA1 pyramidal neurons in the presence of high conductance and voltage fluctuations, we performed dynamic-clamp experiments in rat hippocampal brain slices. We drove neurons with noisy stimuli that included a sinusoidal component ranging, in different trials, from 0.1 to 500 Hz. In subsequent data analysis, we determined action potential phase-locking profiles with respect to background conductance, average firing rate, and frequency of the sinusoidal component. We found that background conductance and firing rate qualitatively change the phase-locking profiles of CA1 pyramidal neurons vs. frequency. In particular, higher average spiking rates promoted band-pass profiles, and the high-conductance state promoted phase-locking at frequencies well above what would be predicted from changes in the membrane time constant. Mechanistically, spike-rate adaptation and frequency resonance in the spike-generating mechanism are implicated in shaping the different phase-locking profiles. Our results demonstrate that CA1 pyramidal cells can actively change their synchronization properties in response to global changes in activity associated with different behavioral states. PMID:23055508

Synchronisation signatures in the listening brain: a perspective from non-invasive neuroelectrophysiology.

PubMed

Weisz, Nathan; Obleser, Jonas

2014-01-01

Human magneto- and electroencephalography (M/EEG) are capable of tracking brain activity at millisecond temporal resolution in an entirely non-invasive manner, a feature that offers unique opportunities to uncover the spatiotemporal dynamics of the hearing brain. In general, precise synchronisation of neural activity within as well as across distributed regions is likely to subserve any cognitive process, with auditory cognition being no exception. Brain oscillations, in a range of frequencies, are a putative hallmark of this synchronisation process. Embedded in a larger effort to relate human cognition to brain oscillations, a field of research is emerging on how synchronisation within, as well as between, brain regions may shape auditory cognition. Combined with much improved source localisation and connectivity techniques, it has become possible to study directly the neural activity of auditory cortex with unprecedented spatio-temporal fidelity and to uncover frequency-specific long-range connectivities across the human cerebral cortex. In the present review, we will summarise recent contributions mainly of our laboratories to this emerging domain. We present (1) a more general introduction on how to study local as well as interareal synchronisation in human M/EEG; (2) how these networks may subserve and influence illusory auditory perception (clinical and non-clinical) and (3) auditory selective attention; and (4) how oscillatory networks further reflect and impact on speech comprehension. This article is part of a Special Issue entitled Human Auditory Neuroimaging. Copyright © 2013 Elsevier B.V. All rights reserved.

The olivo-cerebellar system: a key to understanding the functional significance of intrinsic oscillatory brain properties

PubMed Central

Llinás, Rodolfo R.

2014-01-01

The reflexological view of brain function (Sherrington, 1906) has played a crucial role in defining both the nature of connectivity and the role of the synaptic interactions among neuronal circuits. One implicit assumption of this view, however, has been that CNS function is fundamentally driven by sensory input. This view was questioned as early as the beginning of the last century when a possible role for intrinsic activity in CNS function was proposed by Thomas Graham Brow (Brown, 1911, 1914). However, little progress was made in addressing intrinsic neuronal properties in vertebrates until the discovery of calcium conductances in vertebrate central neurons leading dendritic electroresponsiveness (Llinás and Hess, 1976; Llinás and Sugimori, 1980a,b) and subthreshold neuronal oscillation in mammalian inferior olive (IO) neurons (Llinás and Yarom, 1981a,b). This happened in parallel with a similar set of findings concerning invertebrate neuronal system (Marder and Bucher, 2001). The generalization into a more global view of intrinsic rhythmicity, at forebrain level, occurred initially with the demonstration that the thalamus has similar oscillatory properties (Llinás and Jahnsen, 1982) and the ionic properties responsible for some oscillatory activity were, in fact, similar to those in the IO (Jahnsen and Llinás, 1984; Llinás, 1988). Thus, lending support to the view that not only motricity, but cognitive properties, are organized as coherent oscillatory states (Pare et al., 1992; Singer, 1993; Hardcastle, 1997; Llinás et al., 1998; Varela et al., 2001). PMID:24478634

Dynamic processes in regulation and some implications for biofeedback and biobehavioral interventions.

PubMed

Lehrer, Paul; Eddie, David

2013-06-01

Systems theory has long been used in psychology, biology, and sociology. This paper applies newer methods of control systems modeling for assessing system stability in health and disease. Control systems can be characterized as open or closed systems with feedback loops. Feedback produces oscillatory activity, and the complexity of naturally occurring oscillatory patterns reflects the multiplicity of feedback mechanisms, such that many mechanisms operate simultaneously to control the system. Unstable systems, often associated with poor health, are characterized by absence of oscillation, random noise, or a very simple pattern of oscillation. This modeling approach can be applied to a diverse range of phenomena, including cardiovascular and brain activity, mood and thermal regulation, and social system stability. External system stressors such as disease, psychological stress, injury, or interpersonal conflict may perturb a system, yet simultaneously stimulate oscillatory processes and exercise control mechanisms. Resonance can occur in systems with negative feedback loops, causing high-amplitude oscillations at a single frequency. Resonance effects can be used to strengthen modulatory oscillations, but may obscure other information and control mechanisms, and weaken system stability. Positive as well as negative feedback loops are important for system function and stability. Examples are presented of oscillatory processes in heart rate variability, and regulation of autonomic, thermal, pancreatic and central nervous system processes, as well as in social/organizational systems such as marriages and business organizations. Resonance in negative feedback loops can help stimulate oscillations and exercise control reflexes, but also can deprive the system of important information. Empirical hypotheses derived from this approach are presented, including that moderate stress may enhance health and functioning.

A coupled-oscillator model of olfactory bulb gamma oscillations

PubMed Central

2017-01-01

The olfactory bulb transforms not only the information content of the primary sensory representation, but also its underlying coding metric. High-variance, slow-timescale primary odor representations are transformed by bulbar circuitry into secondary representations based on principal neuron spike patterns that are tightly regulated in time. This emergent fast timescale for signaling is reflected in gamma-band local field potentials, presumably serving to efficiently integrate olfactory sensory information into the temporally regulated information networks of the central nervous system. To understand this transformation and its integration with interareal coordination mechanisms requires that we understand its fundamental dynamical principles. Using a biophysically explicit, multiscale model of olfactory bulb circuitry, we here demonstrate that an inhibition-coupled intrinsic oscillator framework, pyramidal resonance interneuron network gamma (PRING), best captures the diversity of physiological properties exhibited by the olfactory bulb. Most importantly, these properties include global zero-phase synchronization in the gamma band, the phase-restriction of informative spikes in principal neurons with respect to this common clock, and the robustness of this synchronous oscillatory regime to multiple challenging conditions observed in the biological system. These conditions include substantial heterogeneities in afferent activation levels and excitatory synaptic weights, high levels of uncorrelated background activity among principal neurons, and spike frequencies in both principal neurons and interneurons that are irregular in time and much lower than the gamma frequency. This coupled cellular oscillator architecture permits stable and replicable ensemble responses to diverse sensory stimuli under various external conditions as well as to changes in network parameters arising from learning-dependent synaptic plasticity. PMID:29140973

Complex behavior in chains of nonlinear oscillators.

PubMed

Alonso, Leandro M

2017-06-01

This article outlines sufficient conditions under which a one-dimensional chain of identical nonlinear oscillators can display complex spatio-temporal behavior. The units are described by phase equations and consist of excitable oscillators. The interactions are local and the network is poised to a critical state by balancing excitation and inhibition locally. The results presented here suggest that in networks composed of many oscillatory units with local interactions, excitability together with balanced interactions is sufficient to give rise to complex emergent features. For values of the parameters where complex behavior occurs, the system also displays a high-dimensional bifurcation where an exponentially large number of equilibria are borne in pairs out of multiple saddle-node bifurcations.

Optimal spatiotemporal representation of multichannel EEG for recognition of brain states associated with distinct visual stimulus

NASA Astrophysics Data System (ADS)

Hramov, Alexander; Musatov, Vyacheslav Yu.; Runnova, Anastasija E.; Efremova, Tatiana Yu.; Koronovskii, Alexey A.; Pisarchik, Alexander N.

2018-04-01

In the paper we propose an approach based on artificial neural networks for recognition of different human brain states associated with distinct visual stimulus. Based on the developed numerical technique and the analysis of obtained experimental multichannel EEG data, we optimize the spatiotemporal representation of multichannel EEG to provide close to 97% accuracy in recognition of the EEG brain states during visual perception. Different interpretations of an ambiguous image produce different oscillatory patterns in the human EEG with similar features for every interpretation. Since these features are inherent to all subjects, a single artificial network can classify with high quality the associated brain states of other subjects.

Beta band oscillations in motor cortex reflect neural population signals that delay movement onset

PubMed Central

Khanna, Preeya; Carmena, Jose M

2017-01-01

Motor cortical beta oscillations have been reported for decades, yet their behavioral correlates remain unresolved. Some studies link beta oscillations to changes in underlying neural activity, but the specific behavioral manifestations of these reported changes remain elusive. To investigate how changes in population neural activity, beta oscillations, and behavior are linked, we recorded multi-scale neural activity from motor cortex while three macaques performed a novel neurofeedback task. Subjects volitionally brought their beta oscillatory power to an instructed state and subsequently executed an arm reach. Reaches preceded by a reduction in beta power exhibited significantly faster movement onset times than reaches preceded by an increase in beta power. Further, population neural activity was found to shift farther from a movement onset state during beta oscillations that were neurofeedback-induced or naturally occurring during reaching tasks. This finding establishes a population neural basis for slowed movement onset following periods of beta oscillatory activity. DOI: http://dx.doi.org/10.7554/eLife.24573.001 PMID:28467303

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.

LFP Oscillations in the Mesencephalic Locomotor Region during Voluntary Locomotion

PubMed Central

Noga, Brian R.; Sanchez, Francisco J.; Villamil, Luz M.; O’Toole, Christopher; Kasicki, Stefan; Olszewski, Maciej; Cabaj, Anna M.; Majczyński, Henryk; Sławińska, Urszula; Jordan, Larry M.

2017-01-01

Oscillatory rhythms in local field potentials (LFPs) are thought to coherently bind cooperating neuronal ensembles to produce behaviors, including locomotion. LFPs recorded from sites that trigger locomotion have been used as a basis for identification of appropriate targets for deep brain stimulation (DBS) to enhance locomotor recovery in patients with gait disorders. Theta band activity (6–12 Hz) is associated with locomotor activity in locomotion-inducing sites in the hypothalamus and in the hippocampus, but the LFPs that occur in the functionally defined mesencephalic locomotor region (MLR) during locomotion have not been determined. Here we record the oscillatory activity during treadmill locomotion in MLR sites effective for inducing locomotion with electrical stimulation in rats. The results show the presence of oscillatory theta rhythms in the LFPs recorded from the most effective MLR stimulus sites (at threshold ≤60 μA). Theta activity increased at the onset of locomotion, and its power was correlated with the speed of locomotion. In animals with higher thresholds (>60 μA), the correlation between locomotor speed and theta LFP oscillations was less robust. Changes in the gamma band (previously recorded in vitro in the pedunculopontine nucleus (PPN), thought to be a part of the MLR) were relatively small. Controlled locomotion was best achieved at 10–20 Hz frequencies of MLR stimulation. Our results indicate that theta and not delta or gamma band oscillation is a suitable biomarker for identifying the functional MLR sites. PMID:28579945

Induction of θ-frequency oscillations in the rat medial septal diagonal band slice by metabotropic glutamate receptor agonists.

PubMed

Lu, C B; Ouyang, G; Henderson, Z; Li, X

2011-03-17

The aim of this study was to examine the role of metabotropic glutamate receptors (mGluR) in the generation of oscillatory field activity at theta frequency (4-12 Hz) in the medial septal slice prepared from rat brain. Bath application of mGluR agonists and antagonists showed that activation of mGluR1-type receptors produces persistent theta frequency oscillations in a dose-responsive manner. This activity, induced by the group I mGluR agonist (RS)-3,5-dihydroxyphenylglycine (DHPG), was reduced by ionotropic glutamate receptor antagonists and abolished by further addition of a GABAA receptor antagonist. However, addition of a GABAA receptor antagonist on its own converted the DHPG-induced oscillations to intermittent episodes of accentuated theta frequency activity following a burst. In a proportion of slices, DHPG induced large amplitude field population spiking activity (100-300 μV) which is correlated linearly with the field theta oscillations and is sensitive to glutamate receptor antagonists, suggesting a role of this type of spikes in theta generation induced by DHPG. These data demonstrate that DHPG-sensitive neuronal networks within medial septum generate theta rhythmic activity and are differentially modulated by excitatory and inhibitory ionotropic neurotransmissions. Copyright © 2011 IBRO. Published by Elsevier Ltd. All rights reserved.

Event-related theta synchronization predicts deficit in facial affect recognition in schizophrenia.

PubMed

Csukly, Gábor; Stefanics, Gábor; Komlósi, Sarolta; Czigler, István; Czobor, Pál

2014-02-01

Growing evidence suggests that abnormalities in the synchronized oscillatory activity of neurons in schizophrenia may lead to impaired neural activation and temporal coding and thus lead to neurocognitive dysfunctions, such as deficits in facial affect recognition. To gain an insight into the neurobiological processes linked to facial affect recognition, we investigated both induced and evoked oscillatory activity by calculating the Event Related Spectral Perturbation (ERSP) and the Inter Trial Coherence (ITC) during facial affect recognition. Fearful and neutral faces as well as nonface patches were presented to 24 patients with schizophrenia and 24 matched healthy controls while EEG was recorded. The participants' task was to recognize facial expressions. Because previous findings with healthy controls showed that facial feature decoding was associated primarily with oscillatory activity in the theta band, we analyzed ERSP and ITC in this frequency band in the time interval of 140-200 ms, which corresponds to the N170 component. Event-related theta activity and phase-locking to facial expressions, but not to nonface patches, predicted emotion recognition performance in both controls and patients. Event-related changes in theta amplitude and phase-locking were found to be significantly weaker in patients compared with healthy controls, which is in line with previous investigations showing decreased neural synchronization in the low frequency bands in patients with schizophrenia. Neural synchrony is thought to underlie distributed information processing. Our results indicate a less effective functioning in the recognition process of facial features, which may contribute to a less effective social cognition in schizophrenia. PsycINFO Database Record (c) 2014 APA, all rights reserved.

Relationship between oscillatory neuronal activity during reward processing and trait impulsivity and sensation seeking.

PubMed

Leicht, Gregor; Troschütz, Stefan; Andreou, Christina; Karamatskos, Evangelos; Ertl, Matthias; Naber, Dieter; Mulert, Christoph

2013-01-01

The processing of reward and punishment stimuli in humans appears to involve brain oscillatory activity of several frequencies, probably each with a distinct function. The exact nature of associations of these electrophysiological measures with impulsive or risk-seeking personality traits is not completely clear. Thus, the aim of the present study was to investigate event-related oscillatory activity during reward processing across a wide spectrum of frequencies, and its associations with impulsivity and sensation seeking in healthy subjects. During recording of a 32-channel EEG 22 healthy volunteers were characterized with the Barratt Impulsiveness and the Sensation Seeking Scale and performed a computerized two-choice gambling task comprising different feedback options with positive vs. negative valence (gain or loss) and high or low magnitude (5 vs. 25 points). We observed greater increases of amplitudes of the feedback-related negativity and of activity in the theta, alpha and low-beta frequency range following loss feedback and, in contrast, greater increase of activity in the high-beta frequency range following gain feedback. Significant magnitude effects were observed for theta and delta oscillations, indicating greater amplitudes upon feedback concerning large stakes. The theta amplitude changes during loss were negatively correlated with motor impulsivity scores, whereas alpha and low-beta increase upon loss and high-beta increase upon gain were positively correlated with various dimensions of sensation seeking. The findings suggest that the processing of feedback information involves several distinct processes, which are subserved by oscillations of different frequencies and are associated with different personality traits.

The importance of individual frequencies of endogenous brain oscillations for auditory cognition - A short review.

PubMed

Baltus, Alina; Herrmann, Christoph Siegfried

2016-06-01

Oscillatory EEG activity in the human brain with frequencies in the gamma range (approx. 30-80Hz) is known to be relevant for a large number of cognitive processes. Interestingly, each subject reveals an individual frequency of the auditory gamma-band response (GBR) that coincides with the peak in the auditory steady state response (ASSR). A common resonance frequency of auditory cortex seems to underlie both the individual frequency of the GBR and the peak of the ASSR. This review sheds light on the functional role of oscillatory gamma activity for auditory processing. For successful processing, the auditory system has to track changes in auditory input over time and store information about past events in memory which allows the construction of auditory objects. Recent findings support the idea of gamma oscillations being involved in the partitioning of auditory input into discrete samples to facilitate higher order processing. We review experiments that seem to suggest that inter-individual differences in the resonance frequency are behaviorally relevant for gap detection and speech processing. A possible application of these resonance frequencies for brain computer interfaces is illustrated with regard to optimized individual presentation rates for auditory input to correspond with endogenous oscillatory activity. This article is part of a Special Issue entitled SI: Auditory working memory. Copyright © 2015 Elsevier B.V. All rights reserved.

Integration of actomyosin contractility with cell-cell adhesion during dorsal closure.

PubMed

Duque, Julia; Gorfinkiel, Nicole

2016-12-15

In this work, we combine genetic perturbation, time-lapse imaging and quantitative image analysis to investigate how pulsatile actomyosin contractility drives cell oscillations, apical cell contraction and tissue closure during morphogenesis of the amnioserosa, the main force-generating tissue during the dorsal closure in Drosophila We show that Myosin activity determines the oscillatory and contractile behaviour of amnioserosa cells. Reducing Myosin activity prevents cell shape oscillations and reduces cell contractility. By contrast, increasing Myosin activity increases the amplitude of cell shape oscillations and the time cells spend in the contracted phase relative to the expanded phase during an oscillatory cycle, promoting cell contractility and tissue closure. Furthermore, we show that in AS cells, Rok controls Myosin foci formation and Mbs regulates not only Myosin phosphorylation but also adhesion dynamics through control of Moesin phosphorylation, showing that Mbs coordinates actomyosin contractility with cell-cell adhesion during amnioserosa morphogenesis. © 2016. Published by The Company of Biologists Ltd.

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.

Hippocampal Sharp Wave Bursts Coincide with Neocortical "Up-State" Transitions

ERIC Educational Resources Information Center

Battaglia, Francesco P.; Sutherland, Gary R.; McNaughton, Bruce L.

2004-01-01

The sleeping neocortex shows nested oscillatory activity in different frequency ranges, characterized by fluctuations between "up-states" and "down-states." High-density neuronal ensemble recordings in rats now reveal the interaction between synchronized activity in the hippocampus and neocortex: Electroencephalographic sharp…

Remote sensor response study in the regime of the microwave radiation-induced magnetoresistance oscillations

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

Ye, Tianyu; Mani, R. G.; Wegscheider, W.

2013-11-04

A concurrent remote sensing and magneto-transport study of the microwave excited two dimensional electron system (2DES) at liquid helium temperatures has been carried out using a carbon detector to remotely sense the microwave activity of the 2D electron system in the GaAs/AlGaAs heterostructure during conventional magneto-transport measurements. Various correlations are observed and reported between the oscillatory magnetotransport and the remotely sensed reflection. In addition, the oscillatory remotely sensed signal is shown to exhibit a power law type variation in its amplitude, similar to the radiation-induced magnetoresistance oscillations.

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.

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.

Oscillatory activity reflects differential use of spatial reference frames by sighted and blind individuals in tactile attention.

PubMed

Schubert, Jonathan T W; Buchholz, Verena N; Föcker, Julia; Engel, Andreas K; Röder, Brigitte; Heed, Tobias

2015-08-15

Touch can be localized either on the skin in anatomical coordinates, or, after integration with posture, in external space. Sighted individuals are thought to encode touch in both coordinate systems concurrently, whereas congenitally blind individuals exhibit a strong bias for using anatomical coordinates. We investigated the neural correlates of this differential dominance in the use of anatomical and external reference frames by assessing oscillatory brain activity during a tactile spatial attention task. The EEG was recorded while sighted and congenitally blind adults received tactile stimulation to uncrossed and crossed hands while detecting rare tactile targets at one cued hand only. In the sighted group, oscillatory alpha-band activity (8-12Hz) in the cue-target interval was reduced contralaterally and enhanced ipsilaterally with uncrossed hands. Hand crossing attenuated the degree of posterior parietal alpha-band lateralization, indicating that attention deployment was affected by external spatial coordinates. Beamforming suggested that this posture effect originated in the posterior parietal cortex. In contrast, cue-related lateralization of central alpha-band as well as of beta-band activity (16-24Hz) were unaffected by hand crossing, suggesting that these oscillations exclusively encode anatomical coordinates. In the blind group, central alpha-band activity was lateralized, but did not change across postures. The pattern of beta-band activity was indistinguishable between groups. Because the neural mechanisms for posterior alpha-band generation seem to be linked to developmental vision, we speculate that the lack of this neural mechanism in blind individuals is related to their preferred use of anatomical over external spatial codes in sensory processing. Copyright © 2015 Elsevier Inc. All rights reserved.

Oscillatory Activity in the Infant Brain and the Representation of Small Numbers

PubMed Central

Leung, Sumie; Mareschal, Denis; Rowsell, Renee; Simpson, David; Iaria, Leon; Grbic, Amanda; Kaufman, Jordy

2016-01-01

Gamma-band oscillatory activity (GBA) is an established neural signature of sustained occluded object representation in infants and adults. However, it is not yet known whether the magnitude of GBA in the infant brain reflects the quantity of occluded items held in memory. To examine this, we compared GBA of 6–8 month-old infants during occlusion periods after the representation of two objects vs. that of one object. We found that maintaining a representation of two objects during occlusion resulted in significantly greater GBA relative to maintaining a single object. Further, this enhancement was located in the right occipital region, which is consistent with previous object representation research in adults and infants. We conclude that enhanced GBA reflects neural processes underlying infants’ representation of small numbers. PMID:26903821

Oscillatory Activity in the Infant Brain and the Representation of Small Numbers.

PubMed

Leung, Sumie; Mareschal, Denis; Rowsell, Renee; Simpson, David; Iaria, Leon; Grbic, Amanda; Kaufman, Jordy

2016-01-01

Gamma-band oscillatory activity (GBA) is an established neural signature of sustained occluded object representation in infants and adults. However, it is not yet known whether the magnitude of GBA in the infant brain reflects the quantity of occluded items held in memory. To examine this, we compared GBA of 6-8 month-old infants during occlusion periods after the representation of two objects vs. that of one object. We found that maintaining a representation of two objects during occlusion resulted in significantly greater GBA relative to maintaining a single object. Further, this enhancement was located in the right occipital region, which is consistent with previous object representation research in adults and infants. We conclude that enhanced GBA reflects neural processes underlying infants' representation of small numbers.

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.

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.

On the contribution of motor planning to the retroactive cuing benefit in working memory: Evidence by mu and beta oscillatory activity in the EEG.

PubMed

Schneider, Daniel; Barth, Anna; Wascher, Edmund

2017-11-15

Attention can be allocated toward mental representations in working memory also after the initial encoding of information has been completed. It was shown that focusing on only one item within working memory transfers this representation into a protected state, reducing its susceptibility to interference by incoming signals. The present study investigated the nature of this retroactive cue (retro-cue) benefit by means of oscillatory activity in the EEG. In a working memory task with a retro-cue indicating one, two or three memory representations as relevant and a block-wise distractor display presented after the retro-cue, participants had to remember the orientation of a colored bar. On behavioral level, we found that the interfering effect of the distractor display on memory performance could be prevented when a retro-cue reduced the number of attended representations in working memory. However, only the one-item retro-cue led to an overall increase in task performance compared to a condition without a retro-cue. The neural basis of this special representational status was investigated by means of oscillatory parameters in the EEG and a clustering approach on level of the independent components (ICs) in the signal. The retroactive reduction of attended working memory representations was reflected in a suppression of alpha power over right parietal and parieto-occipital sites. In addition, we found that an IC cluster representing oscillatory activity in the mu/beta range (10-12 Hz and 20-24 Hz) with a source in sensorimotor cortex revealed a power suppression already prior to the memory probe following the one-item retro-cue. This suggests that the retro-cue benefit results in large parts from the possibility to focus attention on one particular item in working memory and initiate motor planning processes already ahead of the probe stimulus indicating the respective response. Copyright © 2017 Elsevier Inc. All rights reserved.

Visual Contrast Sensitivity Improvement by Right Frontal High-Beta Activity Is Mediated by Contrast Gain Mechanisms and Influenced by Fronto-Parietal White Matter Microstructure

PubMed Central

Quentin, Romain; Elkin Frankston, Seth; Vernet, Marine; Toba, Monica N.; Bartolomeo, Paolo; Chanes, Lorena; Valero-Cabré, Antoni

2016-01-01

Behavioral and electrophysiological studies in humans and non-human primates have correlated frontal high-beta activity with the orienting of endogenous attention and shown the ability of the latter function to modulate visual performance. We here combined rhythmic transcranial magnetic stimulation (TMS) and diffusion imaging to study the relation between frontal oscillatory activity and visual performance, and we associated these phenomena to a specific set of white matter pathways that in humans subtend attentional processes. High-beta rhythmic activity on the right frontal eye field (FEF) was induced with TMS and its causal effects on a contrast sensitivity function were recorded to explore its ability to improve visual detection performance across different stimulus contrast levels. Our results show that frequency-specific activity patterns engaged in the right FEF have the ability to induce a leftward shift of the psychometric function. This increase in visual performance across different levels of stimulus contrast is likely mediated by a contrast gain mechanism. Interestingly, microstructural measures of white matter connectivity suggest a strong implication of right fronto-parietal connectivity linking the FEF and the intraparietal sulcus in propagating high-beta rhythmic signals across brain networks and subtending top-down frontal influences on visual performance. PMID:25899709

Motor network disruption in essential tremor: a functional and effective connectivity study.

PubMed

Buijink, Arthur W G; van der Stouwe, A M Madelein; Broersma, Marja; Sharifi, Sarvi; Groot, Paul F C; Speelman, Johannes D; Maurits, Natasha M; van Rootselaar, Anne-Fleur

2015-10-01

Although involvement of the cerebello-thalamo-cortical network has often been suggested in essential tremor, the source of oscillatory activity remains largely unknown. To elucidate mechanisms of tremor generation, it is of crucial importance to study the dynamics within the cerebello-thalamo-cortical network. Using a combination of electromyography and functional magnetic resonance imaging, it is possible to record the peripheral manifestation of tremor simultaneously with brain activity related to tremor generation. Our first aim was to study the intrinsic activity of regions within the cerebello-thalamo-cortical network using dynamic causal modelling to estimate effective connectivity driven by the concurrently recorded tremor signal. Our second aim was to objectify how the functional integrity of the cerebello-thalamo-cortical network is affected in essential tremor. We investigated the functional connectivity between cerebellar and cortical motor regions showing activations during a motor task. Twenty-two essential tremor patients and 22 healthy controls were analysed. For the effective connectivity analysis, a network of tremor-signal related regions was constructed, consisting of the left primary motor cortex, premotor cortex, supplementary motor area, left thalamus, and right cerebellar motor regions lobule V and lobule VIII. A measure of variation in tremor severity over time, derived from the electromyogram, was included as modulatory input on intrinsic connections and on the extrinsic cerebello-thalamic connections, giving a total of 128 models. Bayesian model selection and random effects Bayesian model averaging were used. Separate seed-based functional connectivity analyses for the left primary motor cortex, left supplementary motor area and right cerebellar lobules IV, V, VI and VIII were performed. We report two novel findings that support an important role for the cerebellar system in the pathophysiology of essential tremor. First, in the effective connectivity analysis, tremor variation during the motor task has an excitatory effect on both the extrinsic connection from cerebellar lobule V to the thalamus, and the intrinsic activity of cerebellar lobule V and thalamus. Second, the functional integrity of the motor network is affected in essential tremor, with a decrease in functional connectivity between cortical and cerebellar motor regions. This decrease in functional connectivity, related to the motor task, correlates with an increase in clinical tremor severity. Interestingly, increased functional connectivity between right cerebellar lobules I-IV and the left thalamus correlates with an increase in clinical tremor severity. In conclusion, our findings suggest that cerebello-dentato-thalamic activity and cerebello-cortical connectivity is disturbed in essential tremor, supporting previous evidence of functional cerebellar changes in essential tremor. © The Author (2015). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

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.

Synchronized delta oscillations correlate with the resting-state functional MRI signal

PubMed Central

Lu, Hanbing; Zuo, Yantao; Gu, Hong; Waltz, James A.; Zhan, Wang; Scholl, Clara A.; Rea, William; Yang, Yihong; Stein, Elliot A.

2007-01-01

Synchronized low-frequency spontaneous fluctuations of the functional MRI (fMRI) signal have recently been applied to investigate large-scale neuronal networks of the brain in the absence of specific task instructions. However, the underlying neural mechanisms of these fluctuations remain largely unknown. To this end, electrophysiological recordings and resting-state fMRI measurements were conducted in α-chloralose-anesthetized rats. Using a seed-voxel analysis strategy, region-specific, anesthetic dose-dependent fMRI resting-state functional connectivity was detected in bilateral primary somatosensory cortex (S1FL) of the resting brain. Cortical electroencephalographic signals were also recorded from bilateral S1FL; a visual cortex locus served as a control site. Results demonstrate that, unlike the evoked fMRI response that correlates with power changes in the γ bands, the resting-state fMRI signal correlates with the power coherence in low-frequency bands, particularly the δ band. These data indicate that hemodynamic fMRI signal differentially registers specific electrical oscillatory frequency band activity, suggesting that fMRI may be able to distinguish the ongoing from the evoked activity of the brain. PMID:17991778

Spontaneous sensorimotor cortical activity is suppressed by deep brain stimulation in patients with advanced Parkinson's disease.

PubMed

Luoma, Jarkko; Pekkonen, Eero; Airaksinen, Katja; Helle, Liisa; Nurminen, Jussi; Taulu, Samu; Mäkelä, Jyrki P

2018-06-22

Advanced Parkinson's disease (PD) is characterized by an excessive oscillatory beta band activity in the subthalamic nucleus (STN). Deep brain stimulation (DBS) of STN alleviates motor symptoms in PD and suppresses the STN beta band activity. The effect of DBS on cortical sensorimotor activity is more ambiguous; both increases and decreases of beta band activity have been reported. Non-invasive studies with simultaneous DBS are problematic due to DBS-induced artifacts. We recorded magnetoencephalography (MEG) from 16 advanced PD patients with and without STN DBS during rest and wrist extension. The strong magnetic artifacts related to stimulation were removed by temporal signal space separation. MEG oscillatory activity at 5-25 Hz was suppressed during DBS in a widespread frontoparietal region, including the sensorimotor cortex identified by the cortico-muscular coherence. The strength of suppression did not correlate with clinical improvement. Our results indicate that alpha and beta band oscillations are suppressed at the frontoparietal cortex by STN DBS in PD. Copyright © 2018. Published by Elsevier B.V.

Dynamic Processes in Regulation and Some Implications for Biofeedback and Biobehavioral Interventions

PubMed Central

Lehrer, Paul; Eddie, David

2013-01-01

Systems theory has long been applied in psychology, biology, and sociology. This paper applies newer methods of control systems modeling to the assessment of system stability in health and disease. Control systems can be characterized as open or closed systems with feedback loops. Feedback produces oscillatory activity, and the complexity of naturally occurring oscillatory patterns reflects the multiplicity of feedback mechanisms, such that many mechanisms operate simultaneously to control the system. Unstable systems, often associated with poor health, are characterized by absence of oscillation, random noise, or a very simple pattern of oscillation. This modeling approach can be applied to a diverse range of phenomena, including cardiovascular and brain activity, mood and thermal regulation, and social system stability. External system stressors such as disease, psychological stress, injury, or interpersonal conflict may perturb a system, yet simultaneously stimulate oscillatory processes and exercise control mechanisms. Resonance can occur in systems with negative feedback loops, causing high-amplitude oscillations at a single frequency. Resonance effects can be used to strengthen modulatory oscillations, but may obscure other information and control mechanisms, and weaken system stability. Positive as well as negative feedback loops are important for system function and stability. Examples are presented of oscillatory processes in heart rate variability, and regulation of autonomic, thermal, pancreatic and central nervous system processes, as well as in social/organizational systems such as marriages and business organizations. Resonance in negative feedback loops can help stimulate oscillations and exercise control reflexes, but also can deprive the system of important information. Empirical hypotheses derived from this approach are presented, including that moderate stress may enhance health and functioning. PMID:23572244

Modulation of Oscillatory Power and Connectivity in the Human Posterior Cingulate Cortex Supports the Encoding and Retrieval of Episodic Memories.

PubMed

Lega, Bradley; Germi, James; Rugg, Michael

2017-08-01

Existing data from noninvasive studies have led researchers to posit that the posterior cingulate cortex (PCC) supports mnemonic processes: It exhibits degeneration in memory disorders, and fMRI investigations have demonstrated memory-related activation principally during the retrieval of memory items. Despite these data, the role of the PCC in episodic memory has received only limited treatment using the spatial and temporal precision of intracranial EEG, with previous analyses focused on item retrieval. Using data gathered from 21 human participants who underwent stereo-EEG for seizure localization, we characterized oscillatory patterns in the PCC during the encoding and retrieval of episodic memories. We identified a subsequent memory effect during item encoding characterized by increased gamma band oscillatory power and a low-frequency power desynchronization. Fourteen participants had stereotactic electrodes located simultaneously in the hippocampus and PCC, and with these unique data, we describe connectivity changes between these structures that predict successful item encoding and that precede item retrieval. Oscillatory power during retrieval matched the pattern we observed during encoding, with low-frequency (below 15 Hz) desynchronization and a gamma band (especially high gamma, 70-180 Hz) power increase. Encoding is characterized by synchrony between the hippocampus and PCC, centered at 3 Hz, consistent with other observations of properties of this oscillation akin to those for rodent theta activity. We discuss our findings in light of existing theories of episodic memory processing, including the information via desynchronization hypothesis and retrieved context theory, and examine how our data fit with existing theories for the functional role of the PCC. These include a postulated role for the PCC in modulating internally directed attention and for representing or integrating contextual information for memory items.

mir-125a-5p-mediated Regulation of Lfng is Essential for the Avian Segmentation Clock

PubMed Central

Riley, Maurisa F.; Bochter, Matthew S.; Wahi, Kanu; Nuovo, Gerard J.; Cole, Susan E.

2013-01-01

Summary Somites are embryonic precursors of the axial skeleton and skeletal muscles, and establish the segmental vertebrate body plan. Somitogenesis is controlled in part by a segmentation clock that requires oscillatory expression of genes including Lunatic fringe (Lfng). Oscillatory genes must be tightly regulated both at the transcriptional and post-transcriptional levels for proper clock function. Here we demonstrate that microRNA-mediated regulation of Lfng is essential for proper segmentation during chick somitogenesis. We find that mir-125a-5p targets evolutionarily conserved sequences in the Lfng 3′UTR, and that preventing interactions between mir-125a-5p and Lfng transcripts in vivo causes abnormal segmentation and perturbs clock activity. This provides strong evidence that miRNAs function in the post-transcriptional regulation of oscillatory genes in the segmentation clock. Further, this demonstrates that the relatively subtle effects of miRNAs on target genes can have broad effects in developmental situations that have critical requirements for tight post-transcriptional regulation. PMID:23484856

Cellular and oscillatory substrates of fear extinction learning.

PubMed

Davis, Patrick; Zaki, Yosif; Maguire, Jamie; Reijmers, Leon G

2017-11-01

The mammalian brain contains dedicated circuits for both the learned expression and suppression of fear. These circuits require precise coordination to facilitate the appropriate expression of fear behavior, but the mechanisms underlying this coordination remain unclear. Using a combination of chemogenetics, activity-based neuronal-ensemble labeling and in vivo electrophysiology, we found that fear extinction learning confers on parvalbumin-expressing (PV) interneurons in the basolateral amygdala (BLA) a dedicated role in the selective suppression of a previously encoded fear memory and BLA fear-encoding neurons. In addition, following extinction learning, PV interneurons enable a competing interaction between a 6-12 Hz oscillation and a fear-associated 3-6 Hz oscillation within the BLA. Loss of this competition increases a 3-6 Hz oscillatory signature, with BLA→medial prefrontal cortex directionality signaling the recurrence of fear expression. The discovery of cellular and oscillatory substrates of fear extinction learning that critically depend on BLA PV interneurons could inform therapies aimed at preventing the pathological recurrence of fear following extinction learning.

Cellular and Oscillatory Substrates of Fear Extinction Learning

PubMed Central

Davis, Patrick; Zaki, Yosif; Maguire, Jamie; Reijmers, Leon G.

2018-01-01

The mammalian brain contains dedicated circuits for both the learned expression and suppression of fear. These circuits require precise coordination to facilitate the appropriate expression of fear behavior, but the mechanisms underlying this coordination remain unclear. Using a novel combination of chemogenetics, activity-based neuronal-ensemble labeling, and in vivo electrophysiology, we found that fear extinction learning confers parvalbumin-expressing (PV) interneurons in the basolateral amygdala (BLA) with a dedicated role in the selective suppression of a previously encoded fear memory and BLA fear-encoding neurons. In addition, following extinction learning, PV interneurons enable a competing interaction between a 6–12 Hz oscillation and a fear-associated 3–6 Hz oscillation within the BLA. Loss of this competition increases a 3–6 Hz oscillatory signature, with BLA→mPFC directionality signaling the recurrence of fear expression. The discovery of cellular and oscillatory substrates of fear extinction learning that critically depend on BLA PV-interneurons could inform therapies aimed at preventing the pathological recurrence of fear following extinction learning. PMID:28967909

The nicotinic receptor blocker hexamethonium alters neuronal responses to glutamate in the medial septal area of the brain of the ground squirrel in vitro.

PubMed

Karavaev, E N; Popova, I Yu; Kichigina, V F

2008-03-01

Despite extensive interest in studies of the medial septal area, the nature of the interactions of its various neurochemical systems remains largely unclear. The aim of the present work was to clarify the role of nicotinic receptors in mediating the interaction of the glutamatergic and cholinergic systems in this structure. Extracellular recording of neuron activity in living slices of ground squirrel brain was used to study the influences of L-glutamate (1 microM) during application of the nicotinic receptor blocker hexamethonium (1 mM). The responses of septal neurons to glutamate depended on the type of their initial activity and the presence of pacemaker properties. This study is the first to show that glutamate increases the frequency of volleys in rhythmic neurons in the septum. Hexamethonium induced changes in neuron activity similar to the influences of glutamate. After prior application of hexamethonium, the responses of neurons to glutamate changed: activatory responses were masked and inhibitory responses were enhanced. Cholinergic modulation of the responses of septal neurons to glutamate were shown to occur, as did modulation of the strength of the oscillatory properties of the septal network by nicotinic receptors.

[Hexamethonium, nicotinic receptor blocker, changes the neuronal reactions on glutamate in the medial septal area in vitro].

PubMed

Karavaev, E N; Popova, I Iu; Kichigina, V F

2007-01-01

Despite the great interest in studying the medial septal area, the interactions of its neurochemical systems are not yet clearly understood. The aim of this study was to elucidate the role of nicotinic receptors in the interaction of glutamatergic and cholinergic systems of the medial septal area. The effect of L-glutamate (1 microM) on septal neurons was studied under the application of hexamethonium, nicotinic cholinoreceptor blocker by using the method of extracellular recording of neuronal activity in brain slices of ground squirrels. The response of septal neurons to glutamate depended on the type of their initial activity and on the presence of pacemaker properties. For the first time, the ability of septal neurons to respond to glutamate with an increase in burst frequency was shown. The influence of hexamethonium on the neuronal activity was similar to that of glutamate. After a preliminary application of hexamethonium, the reactions of neurons to glutamate changed. The excitatory reactions were masked, while the inhibitory reactions became stronger. It was found that nicotinic cholinergic receptors modulated the reactions of MS-DB cells to glutamate and the expression of the oscillatory properties of the septal neuronal network.

[Coupling of brain oscillatory systems with cognitive (experience and valence) and physiological (cardiovascular reactivity) components of emotion].

PubMed

Aftanas, L I; Reva, N V; Pavlov, S V; Korenek, V V; Brak, I V

2014-02-01

We investigated the coupling of EEG oscillators with cognitive (experience and valence) and physiological (cardiovascular reactivity) components of emotion. Emotions of anger and joy were evoked in healthy males (n = 49) using a guided imagery method, multichannel EEG and cardiovascular reactivity (Finometer) were simultaneously recorded. Correlational analysis revealed that specially distributed EEG oscillators seem to be selectively involved into cognitive (experience and valence) and physiological (cardiovascular reactivity) components of emotional responding. We showed that low theta (4-6 Hz) activity from medial and lateral frontal cortex of the right hemisphere predominantly correlated with the anger experience, high alpha (10-12 and 12-14 Hz) and gamma (30-45 Hz) activity from central-parieto-occipital regions of the left hemisphere--with cardiovascular reactivity to anger and joy, gamma-activity (30-45 Hz) from the left hemisphere in parietal areas--with cardiovascular reactivity to joy. The findings suggest that specially distributed neuronal networks oscillating at different frequencies may be regarded as a putative neurobiological mechanism coordination dynamical balance between cognitive and physiological components of emotion as well as psycho-neuro-somatic relationships within the mind-brain-body system.

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

Spatio-temporal modelling of the NF-κB intracellular signalling pathway: the roles of diffusion, active transport, and cell geometry.

PubMed

Terry, Alan J; Chaplain, Mark A J

2011-12-07

The nuclear factor kappa B (NF-κB) intracellular signalling pathway is central to many stressful, inflammatory, and innate immune responses. NF-κB proteins themselves are transcription factors for hundreds of genes. Experiments have shown that the NF-κB pathway can exhibit oscillatory dynamics-a negative feedback loop causes oscillatory nuclear-cytoplasmic translocation of NF-κB. Given that cell size and shape are known to influence intracellular signal transduction, we consider a spatio-temporal model of partial differential equations for the NF-κB pathway, where we model molecular movement by diffusion and, for several key species including NF-κB, by active transport as well. Through numerical simulations we find values for model parameters such that sustained oscillatory dynamics occur. Our spatial profiles and animations bear a striking resemblance to experimental images and movie clips employing fluorescent fusion proteins. We discover that oscillations in nuclear NF-κB may occur when active transport is across the nuclear membrane only, or when no species are subject to active transport. However, when active transport is across the nuclear membrane and NF-κB is additionally actively transported through the cytoplasm, oscillations are lost. Hence transport mechanisms in a cell will influence its response to activation of its NF-κB pathway. We also demonstrate that sustained oscillations in nuclear NF-κB are somewhat robust to changes in the shape of the cell, or the shape, location, and size of its nucleus, or the location of ribosomes. Yet if the cell is particularly flat or the nucleus sufficiently small, then oscillations are lost. Thus the geometry of a cell may partly determine its response to NF-κB activation. The NF-κB pathway is known to be constitutively active in several human cancers. Our spatially explicit modelling approach will allow us, in future work, to investigate targeted drug therapy of tumours. Copyright © 2011 Elsevier Ltd. All rights reserved.

The serotonin hallucinogen 5-MeO-DMT alters cortico-thalamic activity in freely moving mice: Regionally-selective involvement of 5-HT1A and 5-HT2A receptors.

PubMed

Riga, Maurizio S; Lladó-Pelfort, Laia; Artigas, Francesc; Celada, Pau

2017-12-06

5-MeO-DMT is a natural hallucinogen acting as serotonin 5-HT 1A /5-HT 2A receptor agonist. Its ability to evoke hallucinations could be used to study the neurobiology of psychotic symptoms and to identify new treatment targets. Moreover, recent studies revealed the therapeutic potential of serotonin hallucinogens in treating mood and anxiety disorders. Our previous results in anesthetized animals show that 5-MeO-DMT alters cortical activity via 5-HT 1A and 5-HT 2A receptors. Here, we examined 5-MeO-DMT effects on oscillatory activity in prefrontal (PFC) and visual (V1) cortices, and in mediodorsal thalamus (MD) of freely-moving wild-type (WT) and 5-HT 2A -R knockout (KO2A) mice. We performed local field potential multi-recordings evaluating the power at different frequency bands and coherence between areas. We also examined the prevention of 5-MeO-DMT effects by the 5-HT 1A -R antagonist WAY-100635. 5-MeO-DMT affected oscillatory activity more in cortical than in thalamic areas. More marked effects were observed in delta power in V1 of KO2A mice. 5-MeO-DMT increased beta band coherence between all examined areas. In KO2A mice, WAY100635 prevented most of 5-MeO-DMT effects on oscillatory activity. The present results indicate that hallucinatory activity of 5-MeO-DMT is likely mediated by simultaneous alteration of prefrontal and visual activities. The prevention of these effects by WAY-100635 in KO2A mice supports the potential usefulness of 5-HT 1A receptor antagonists to treat visual hallucinations. 5-MeO-DMT effects on PFC theta activity and cortico-thalamic coherence may be related to its antidepressant activity. Copyright © 2017. Published by Elsevier Ltd.

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

PubMed Central

Tchumatchenko, Tatjana; Clopath, Claudia

2014-01-01

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

Contraction driven flow in the extended vein networks of Physarum polycephalum

NASA Astrophysics Data System (ADS)

Alim, Karen; Amselem, Gabriel; Peaudecerf, Francois; Pringle, Anne; Brenner, Michael P.

2011-11-01

The true slime mold Physarum polycephalum is a basal organism that forms an extended network of veins to forage for food. P. polycephalum is renown for its adaptive changes of vein structure and morphology in response to food sources. These rearrangements presumably occur to establish an efficient transport and mixing of resources throughout the networks thus presenting a prototype to design transport networks under the constraints of laminar flow. The physical flows of cytoplasmic fluid enclosed by the veins exhibit an oscillatory flow termed ``shuttle streaming.'' The flow exceed by far the volume required for growth at the margins suggesting that the additional energy cost for generating the flow is spent for efficient and/or targeted redistribution of resources. We show that the viscous shuttle flow is driven by the radial contractions of the veins that accompany the streaming. We present a model for the fluid flow and resource dispersion arising due to radial contractions. The transport and mixing properties of the flow are discussed.

Resting-State Oscillatory Activity in Children Born Small for Gestational Age: An MEG Study

PubMed Central

Boersma, Maria; de Bie, Henrica M. A.; Oostrom, Kim J.; van Dijk, Bob W.; Hillebrand, Arjan; van Wijk, Bernadette C. M.; Delemarre-van de Waal, Henriëtte A.; Stam, Cornelis J.

2013-01-01

Growth restriction in utero during a period that is critical for normal growth of the brain, has previously been associated with deviations in cognitive abilities and brain anatomical and functional changes. We measured magnetoencephalography (MEG) in 4- to 7-year-old children to test if children born small for gestational age (SGA) show deviations in resting-state brain oscillatory activity. Children born SGA with postnatally spontaneous catch-up growth [SGA+; six boys, seven girls; mean age 6.3 year (SD = 0.9)] and children born appropriate for gestational age [AGA; seven boys, three girls; mean age 6.0 year (SD = 1.2)] participated in a resting-state MEG study. We calculated absolute and relative power spectra and used non-parametric statistics to test for group differences. SGA+ and AGA born children showed no significant differences in absolute and relative power except for reduced absolute gamma band power in SGA children. At the time of MEG investigation, SGA+ children showed significantly lower head circumference (HC) and a trend toward lower IQ, however there was no association of HC or IQ with absolute or relative power. Except for reduced absolute gamma band power, our findings suggest normal brain activity patterns at school age in a group of children born SGA in which spontaneous catch-up growth of bodily length after birth occurred. Although previous findings suggest that being born SGA alters brain oscillatory activity early in neonatal life, we show that these neonatal alterations do not persist at early school age when spontaneous postnatal catch-up growth occurs after birth. PMID:24068993

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.

Star-type oscillatory networks with generic Kuramoto-type coupling: A model for "Japanese drums synchrony"

NASA Astrophysics Data System (ADS)

Vlasov, Vladimir; Pikovsky, Arkady; Macau, Elbert E. N.

2015-12-01

We analyze star-type networks of phase oscillators by virtue of two methods. For identical oscillators we adopt the Watanabe-Strogatz approach, which gives full analytical description of states, rotating with constant frequency. For nonidentical oscillators, such states can be obtained by virtue of the self-consistent approach in a parametric form. In this case stability analysis cannot be performed, however with the help of direct numerical simulations we show which solutions are stable and which not. We consider this system as a model for a drum orchestra, where we assume that the drummers follow the signal of the leader without listening to each other and the coupling parameters are determined by a geometrical organization of the orchestra.

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.

Micromechanics and poroelasticity of hydrated cellulose networks.

PubMed

Lopez-Sanchez, P; Rincon, Mauricio; Wang, D; Brulhart, S; Stokes, J R; Gidley, M J

2014-06-09

The micromechanics of cellulose hydrogels have been investigated using a new rheological experimental approach, combined with simulation using a poroelastic constitutive model. A series of mechanical compression steps at different strain rates were performed as a function of cellulose hydrogel thickness, combined with small amplitude oscillatory shear after each step to monitor the viscoelasticity of the sample. During compression, bacterial cellulose hydrogels behaved as anisotropic materials with near zero Poisson's ratio. The micromechanics of the hydrogels altered with each compression as water was squeezed out of the structure, and microstructural changes were strain rate-dependent, with increased densification of the cellulose network and increased cellulose fiber aggregation observed for slower compressive strain rates. A transversely isotropic poroelastic model was used to explain the observed micromechanical behavior, showing that the mechanical properties of cellulose networks in aqueous environments are mainly controlled by the rate of water movement within the structure.