Changes in interhemispheric motor connectivity after muscle fatigue

NASA Astrophysics Data System (ADS)

Peltier, Scott; LaConte, Stephen M.; Niyazov, Dmitriy; Liu, Jing; Sahgal, Vinod; Yue, Guang; Hu, Xiaoping

2005-04-01

Synchronized oscillations in resting state timecourses have been detected in recent fMRI studies. These oscillations are low frequency in nature (< 0.08 Hz), and seem to be a property of symmetric cortices. These fluctuations are important as a potential signal of interest, which could indicate connectivity between functionally related areas of the brain. It has also been shown that the synchronized oscillations decrease in some spontaneous pathological states. Thus, detection of these functional connectivity patterns may help to serve as a gauge of normal brain activity. The cognitive effects of muscle fatigue are not well characterized. Sustained fatigue has the potential to dynamically alter activity in brain networks. In this work, we examined the interhemispheric correlations in the left and right primary motor cortices and how they change with muscle fatigue. Resting-state functional MRI imaging was done before and after a repetitive unilateral fatigue task. We find that the number of significant correlations in the bilateral motor network decreases with fatigue. These results suggest that resting-state interhemispheric motor cortex functional connectivity is affected by muscle fatigue.

Alpha oscillations and their impairment in affective and post-traumatic stress disorders.

PubMed

Eidelman-Rothman, Moranne; Levy, Jonathan; Feldman, Ruth

2016-09-01

Affective and anxiety disorders are debilitating conditions characterized by impairments in cognitive and social functioning. Elucidating their neural underpinnings may assist in improving diagnosis and developing targeted interventions. Neural oscillations are fundamental for brain functioning. Specifically, oscillations in the alpha frequency range (alpha rhythms) are prevalent in the awake, conscious brain and play an important role in supporting perceptual, cognitive, and social processes. We review studies utilizing various alpha power measurements to assess abnormalities in brain functioning in affective and anxiety disorders as well as obsessive compulsive and post-traumatic stress disorders. Despite some inconsistencies, studies demonstrate associations between aberrant alpha patterns and these disorders both in response to specific cognitive and emotional tasks and during a resting state. We conclude by discussing methodological considerations and future directions, and underscore the need for much further research on the role of alpha functionality in social contexts. As social dysfunction accompanies most psychiatric conditions, research on alpha's involvement in social processes may provide a unique window into the neural mechanisms underlying these disorders. Copyright © 2016 Elsevier Ltd. All rights reserved.

Breakdown of long-range temporal correlations in brain oscillations during general anesthesia.

PubMed

Krzemiński, Dominik; Kamiński, Maciej; Marchewka, Artur; Bola, Michał

2017-10-01

Consciousness has been hypothesized to emerge from complex neuronal dynamics, which prevails when brain operates in a critical state. Evidence supporting this hypothesis comes mainly from studies investigating neuronal activity on a short time-scale of seconds. However, a key aspect of criticality is presence of scale-free temporal dependencies occurring across a wide range of time-scales. Indeed, robust long-range temporal correlations (LRTCs) are found in neuronal oscillations during conscious states, but it is not known how LRTCs are affected by loss of consciousness. To further test a relation between critical dynamics and consciousness, we investigated LRTCs in electrocorticography signals recorded from four macaque monkeys during resting wakefulness and general anesthesia induced by various anesthetics (ketamine, medetomidine, or propofol). Detrended Fluctuation Analysis was used to estimate LRTCs in amplitude fluctuations (envelopes) of band-pass filtered signals. We demonstrate two main findings. First, during conscious states all lateral cortical regions are characterized by significant LRTCs of alpha-band activity (7-14 Hz). LRTCs are stronger in the eyes-open than eyes-closed state, but in both states they form a spatial gradient, with anterior brain regions exhibiting stronger LRTCs than posterior regions. Second, we observed a substantial decrease of LRTCs during loss of consciousness, the magnitude of which was associated with the baseline (i.e. pre-anesthesia) state of the brain. Specifically, brain regions characterized by strongest LRTCs during a wakeful baseline exhibited greatest decreases during anesthesia (i.e. "the rich got poorer"), which consequently disturbed the posterior-anterior gradient. Therefore, our results suggest that general anesthesia affects mainly brain areas characterized by strongest LRTCs during wakefulness, which might account for lack of capacities for extensive temporal integration during loss of consciousness. Copyright © 2017 Elsevier Inc. All rights reserved.

Three types of ependymal cells with intracellular calcium oscillation are characterized by distinct cilia beating properties.

PubMed

Liu, Tongyu; Jin, Xingjian; Prasad, Rahul M; Sari, Youssef; Nauli, Surya M

2014-09-01

Ependymal cells are multiciliated epithelial cells that line the ventricles in the adult brain. Abnormal function or structure of ependymal cilia has been associated with various neurological deficits. For the first time, we report three distinct ependymal cell types, I, II, and III, based on their unique ciliary beating frequency and beating angle. These ependymal cells have specific localizations within the third ventricle of the mouse brain. Furthermore, neither ependymal cell types nor their localizations are altered by aging. Our high-speed fluorescence imaging analysis reveals that these ependymal cells have an intracellular pacing calcium oscillation property. Our study further shows that alcohol can significantly repress the amplitude of calcium oscillation and the frequency of ciliary beating, resulting in an overall decrease in volume replacement by the cilia. Furthermore, the pharmacological agent cilostazol could differentially increase cilia beating frequency in type II, but not in type I or type III, ependymal cells. In summary, we provide the first evidence of three distinct types of ependymal cells with calcium oscillation properties. © 2014 Wiley Periodicals, Inc.

The human brain pacemaker: Synchronized infra-slow neurovascular coupling in patients undergoing non-pulsatile cardiopulmonary bypass.

PubMed

Zanatta, Paolo; Toffolo, Gianna Maria; Sartori, Elisa; Bet, Anna; Baldanzi, Fabrizio; Agarwal, Nivedita; Golanov, Eugene

2013-05-15

In non-pulsatile cardiopulmonary bypass surgery, middle cerebral artery blood flow velocity (BFV) is characterized by infra-slow oscillations of approximately 0.06Hz, which are paralleled by changes in total EEG power variability (EEG-PV), measured in 2s intervals. Since the origin of these BFV oscillations is not known, we explored their possible causative relationships with oscillations in EEG-PV at around 0.06Hz. We monitored 28 patients undergoing non-pulsatile cardiopulmonary bypass using transcranial Doppler sonography and scalp electroencephalography at two levels of anesthesia, deep (prevalence of burst suppression rhythm) and moderate (prevalence of theta rhythm). Under deep anesthesia, the EEG bursts suppression pattern was highly correlative with BFV oscillations. Hence, a detailed quantitative picture of the coupling between electrical brain activity and BFV was derived, both in deep and moderate anesthesia, via linear and non linear processing of EEG-PV and BFV signals, resorting to widely used measures of signal coupling such as frequency of oscillations, coherence, Granger causality and cross-approximate entropy. Results strongly suggest the existence of coupling between EEG-PV and BFV. In moderate anesthesia EEG-PV mean dominant frequency is similar to frequency of BFV oscillations (0.065±0.010Hz vs 0.045±0.019Hz); coherence between the two signals was significant in about 55% of subjects, and the Granger causality suggested an EEG-PV→BFV causal effect direction. The strength of the coupling increased with deepening anesthesia, as EEG-PV oscillations mean dominant frequency virtually coincided with the BFV peak frequency (0.062±0.017Hz vs 0.060±0.024Hz), and coherence became significant in a larger number (65%) of subjects. Cross-approximate entropy decreased significantly from moderate to deep anesthesia, indicating a higher level of synchrony between the two signals. Presence of a subcortical brain pacemaker that drives vascular infra-slow oscillations in the brain is proposed. These findings allow to suggest an original hypothesis explaining the mechanism underlying infra-slow neurovascular coupling. Copyright © 2013 Elsevier Inc. All rights reserved.

Self-regulation of brain oscillations as a treatment for aberrant brain connections in children with autism.

PubMed

Pineda, J A; Juavinett, A; Datko, M

2012-12-01

Autism is a highly varied developmental disorder typically characterized by deficits in reciprocal social interaction, difficulties with verbal and nonverbal communication, and restricted interests and repetitive behaviors. Although a wide range of behavioral, pharmacological, and alternative medicine strategies have been reported to ameliorate specific symptoms for some individuals, there is at present no cure for the condition. Nonetheless, among the many incompatible observations about aspects of the development, anatomy, and functionality of the autistic brain, it is widely agreed that it is characterized by widespread aberrant connectivity. Such disordered connectivity, be it increased, decreased, or otherwise compromised, may complicate healthy synchronization and communication among and within different neural circuits, thereby producing abnormal processing of sensory inputs necessary for normal social life. It is widely accepted that the innate properties of brain electrical activity produce pacemaker elements and linked networks that oscillate synchronously or asynchronously, likely reflecting a type of functional connectivity. Using phase coherence in multiple frequency EEG bands as a measure of functional connectivity, studies have shown evidence for both global hypoconnectivity and local hyperconnectivity in individuals with ASD. However, the nature of the brain's experience-dependent structural plasticity suggests that these abnormal patterns may be reversed with the proper type of treatment. Indeed, neurofeedback (NF) training, an intervention based on operant conditioning that results in self-regulation of brain electrical oscillations, has shown promise in addressing marked abnormalities in functional and structural connectivity. It is hypothesized that neurofeedback produces positive behavioral changes in ASD children by normalizing the aberrant connections within and between neural circuits. NF exploits the brain's plasticity to normalize aberrant connectivity patterns apparent in the autistic brain. By grounding this training in known anatomical (e.g., mirror neuron system) and functional markers (e.g., mu rhythms) of autism, NF training holds promise to support current treatments for this complex disorder. The proposed hypothesis specifically states that neurofeedback-induced alpha mu (8-12Hz) rhythm suppression or desynchronization, a marker of cortical activation, should induce neuroplastic changes and lead to normalization in relevant mirroring networks that have been associated with higher-order social cognition. Copyright © 2012 Elsevier Ltd. All rights reserved.

Cross-frequency coupling of brain oscillations in studying motivation and emotion.

PubMed

Schutter, Dennis J L G; Knyazev, Gennady G

2012-03-01

Research has shown that brain functions are realized by simultaneous oscillations in various frequency bands. In addition to examining oscillations in pre-specified bands, interactions and relations between the different frequency bandwidths is another important aspect that needs to be considered in unraveling the workings of the human brain and its functions. In this review we provide evidence that studying interdependencies between brain oscillations may be a valuable approach to study the electrophysiological processes associated with motivation and emotional states. Studies will be presented showing that amplitude-amplitude coupling between delta-alpha and delta-beta oscillations varies as a function of state anxiety and approach-avoidance-related motivation, and that changes in the association between delta-beta oscillations can be observed following successful psychotherapy. Together these studies suggest that cross-frequency coupling of brain oscillations may contribute to expanding our understanding of the neural processes underlying motivation and emotion.

Perturbation of Brain Oscillations after Ischemic Stroke: A Potential Biomarker for Post-Stroke Function and Therapy

PubMed Central

Rabiller, Gratianne; He, Ji-Wei; Nishijima, Yasuo; Wong, Aaron; Liu, Jialing

2015-01-01

Brain waves resonate from the generators of electrical current and propagate across brain regions with oscillation frequencies ranging from 0.05 to 500 Hz. The commonly observed oscillatory waves recorded by an electroencephalogram (EEG) in normal adult humans can be grouped into five main categories according to the frequency and amplitude, namely δ (1–4 Hz, 20–200 μV), θ (4–8 Hz, 10 μV), α (8–12 Hz, 20–200 μV), β (12–30 Hz, 5–10 μV), and γ (30–80 Hz, low amplitude). Emerging evidence from experimental and human studies suggests that groups of function and behavior seem to be specifically associated with the presence of each oscillation band, although the complex relationship between oscillation frequency and function, as well as the interaction between brain oscillations, are far from clear. Changes of brain oscillation patterns have long been implicated in the diseases of the central nervous system including ischemic stroke, in which the reduction of cerebral blood flow as well as the progression of tissue damage have direct spatiotemporal effects on the power of several oscillatory bands and their interactions. This review summarizes the current knowledge in behavior and function associated with each brain oscillation, and also in the specific changes in brain electrical activities that correspond to the molecular events and functional alterations observed after experimental and human stroke. We provide the basis of the generations of brain oscillations and potential cellular and molecular mechanisms underlying stroke-induced perturbation. We will also discuss the implications of using brain oscillation patterns as biomarkers for the prediction of stroke outcome and therapeutic efficacy. PMID:26516838

Using the virtual brain to reveal the role of oscillations and plasticity in shaping brain's dynamical landscape.

PubMed

Roy, Dipanjan; Sigala, Rodrigo; Breakspear, Michael; McIntosh, Anthony Randal; Jirsa, Viktor K; Deco, Gustavo; Ritter, Petra

2014-12-01

Spontaneous brain activity, that is, activity in the absence of controlled stimulus input or an explicit active task, is topologically organized in multiple functional networks (FNs) maintaining a high degree of coherence. These "resting state networks" are constrained by the underlying anatomical connectivity between brain areas. They are also influenced by the history of task-related activation. The precise rules that link plastic changes and ongoing dynamics of resting-state functional connectivity (rs-FC) remain unclear. Using the framework of the open source neuroinformatics platform "The Virtual Brain," we identify potential computational mechanisms that alter the dynamical landscape, leading to reconfigurations of FNs. Using a spiking neuron model, we first demonstrate that network activity in the absence of plasticity is characterized by irregular oscillations between low-amplitude asynchronous states and high-amplitude synchronous states. We then demonstrate the capability of spike-timing-dependent plasticity (STDP) combined with intrinsic alpha (8-12 Hz) oscillations to efficiently influence learning. Further, we show how alpha-state-dependent STDP alters the local area dynamics from an irregular to a highly periodic alpha-like state. This is an important finding, as the cortical input from the thalamus is at the rate of alpha. We demonstrate how resulting rhythmic cortical output in this frequency range acts as a neuronal tuner and, hence, leads to synchronization or de-synchronization between brain areas. Finally, we demonstrate that locally restricted structural connectivity changes influence local as well as global dynamics and lead to altered rs-FC.

Cerebral energy metabolism and the brain's functional network architecture: an integrative review.

PubMed

Lord, Louis-David; Expert, Paul; Huckins, Jeremy F; Turkheimer, Federico E

2013-09-01

Recent functional magnetic resonance imaging (fMRI) studies have emphasized the contributions of synchronized activity in distributed brain networks to cognitive processes in both health and disease. The brain's 'functional connectivity' is typically estimated from correlations in the activity time series of anatomically remote areas, and postulated to reflect information flow between neuronal populations. Although the topological properties of functional brain networks have been studied extensively, considerably less is known regarding the neurophysiological and biochemical factors underlying the temporal coordination of large neuronal ensembles. In this review, we highlight the critical contributions of high-frequency electrical oscillations in the γ-band (30 to 100 Hz) to the emergence of functional brain networks. After describing the neurobiological substrates of γ-band dynamics, we specifically discuss the elevated energy requirements of high-frequency neural oscillations, which represent a mechanistic link between the functional connectivity of brain regions and their respective metabolic demands. Experimental evidence is presented for the high oxygen and glucose consumption, and strong mitochondrial performance required to support rhythmic cortical activity in the γ-band. Finally, the implications of mitochondrial impairments and deficits in glucose metabolism for cognition and behavior are discussed in the context of neuropsychiatric and neurodegenerative syndromes characterized by large-scale changes in the organization of functional brain networks.

Spikes, Local Field Potentials, and Electrocorticogram Characterization during Motor Learning in Rats for Brain Machine Interface Tasks.

PubMed

Marzullo, T C; Dudley, J R; Miller, C R; Trejo, L; Kipke, D R

2005-01-01

Brain machine interface development typically falls into two arenas, invasive extracellular recording and non-invasive electroencephalogram recording methods. The relationship between action potentials and field potentials is not well understood, and investigation of interrelationships may improve design of neuroprosthetic control systems. Rats were trained on a motor learning task whereby they had to insert their noses into an aperture while simultaneously pressing down on levers with their forepaws; spikes, local field potentials (LFPs), and electrocorticograms (ECoGs) over the motor cortex were recorded and characterized. Preliminary results suggest that the LFP activity in lower cortical layers oscillates with the ECoG.

Common oscillatory mechanisms across multiple memory systems

NASA Astrophysics Data System (ADS)

Headley, Drew B.; Paré, Denis

2017-01-01

The cortex, hippocampus, and striatum support dissociable forms of memory. While each of these regions contains specialized circuitry supporting their respective functions, all structure their activities across time with delta, theta, and gamma rhythms. We review how these oscillations are generated and how they coordinate distinct memory systems during encoding, consolidation, and retrieval. First, gamma oscillations occur in all regions and coordinate local spiking, compressing it into short population bursts. Second, gamma oscillations are modulated by delta and theta oscillations. Third, oscillatory dynamics in these memory systems can operate in either a "slow" or "fast" mode. The slow mode happens during slow-wave sleep and is characterized by large irregular activity in the hippocampus and delta oscillations in cortical and striatal circuits. The fast mode occurs during active waking and rapid eye movement (REM) sleep and is characterized by theta oscillations in the hippocampus and its targets, along with gamma oscillations in the rest of cortex. In waking, the fast mode is associated with the efficacious encoding and retrieval of declarative and procedural memories. Theta and gamma oscillations have similar relationships with encoding and retrieval across multiple forms of memory and brain regions, despite regional differences in microcircuitry and information content. Differences in the oscillatory coordination of memory systems during sleep might explain why the consolidation of some forms of memory is sensitive to slow-wave sleep, while others depend on REM. In particular, theta oscillations appear to support the consolidation of certain types of procedural memories during REM, while delta oscillations during slow-wave sleep seem to promote declarative and procedural memories.

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.

Spectral fingerprints of large-scale neuronal interactions.

PubMed

Siegel, Markus; Donner, Tobias H; Engel, Andreas K

2012-01-11

Cognition results from interactions among functionally specialized but widely distributed brain regions; however, neuroscience has so far largely focused on characterizing the function of individual brain regions and neurons therein. Here we discuss recent studies that have instead investigated the interactions between brain regions during cognitive processes by assessing correlations between neuronal oscillations in different regions of the primate cerebral cortex. These studies have opened a new window onto the large-scale circuit mechanisms underlying sensorimotor decision-making and top-down attention. We propose that frequency-specific neuronal correlations in large-scale cortical networks may be 'fingerprints' of canonical neuronal computations underlying cognitive processes.

Pigment-Dispersing Factor-expressing neurons convey circadian information in the honey bee brain

PubMed Central

Beer, Katharina; Kolbe, Esther; Kahana, Noa B.; Yayon, Nadav; Weiss, Ron; Menegazzi, Pamela; Bloch, Guy

2018-01-01

Pigment-Dispersing Factor (PDF) is an important neuropeptide in the brain circadian network of Drosophila and other insects, but its role in bees in which the circadian clock influences complex behaviour is not well understood. We combined high-resolution neuroanatomical characterizations, quantification of PDF levels over the day and brain injections of synthetic PDF peptide to study the role of PDF in the honey bee Apis mellifera. We show that PDF co-localizes with the clock protein Period (PER) in a cluster of laterally located neurons and that the widespread arborizations of these PER/PDF neurons are in close vicinity to other PER-positive cells (neurons and glia). PDF-immunostaining intensity oscillates in a diurnal and circadian manner with possible influences for age or worker task on synchrony of oscillations in different brain areas. Finally, PDF injection into the area between optic lobes and the central brain at the end of the subjective day produced a consistent trend of phase-delayed circadian rhythms in locomotor activity. Altogether, these results are consistent with the hypothesis that PDF is a neuromodulator that conveys circadian information from pacemaker cells to brain centres involved in diverse functions including locomotion, time memory and sun-compass orientation. PMID:29321240

Information-geometric measures estimate neural interactions during oscillatory brain states

PubMed Central

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

2014-01-01

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

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

PubMed

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

2014-01-01

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

Biological timing and the clock metaphor: oscillatory and hourglass mechanisms.

PubMed

Rensing, L; Meyer-Grahle, U; Ruoff, P

2001-05-01

Living organisms have developed a multitude of timing mechanisms--"biological clocks." Their mechanisms are based on either oscillations (oscillatory clocks) or unidirectional processes (hourglass clocks). Oscillatory clocks comprise circatidal, circalunidian, circadian, circalunar, and circannual oscillations--which keep time with environmental periodicities--as well as ultradian oscillations, ovarian cycles, and oscillations in development and in the brain, which keep time with biological timescales. These clocks mainly determine time points at specific phases of their oscillations. Hourglass clocks are predominantly found in development and aging and also in the brain. They determine time intervals (duration). More complex timing systems combine oscillatory and hourglass mechanisms, such as the case for cell cycle, sleep initiation, or brain clocks, whereas others combine external and internal periodicities (photoperiodism, seasonal reproduction). A definition of a biological clock may be derived from its control of functions external to its own processes and its use in determining temporal order (sequences of events) or durations. Biological and chemical oscillators are characterized by positive and negative feedback (or feedforward) mechanisms. During evolution, living organisms made use of the many existing oscillations for signal transmission, movement, and pump mechanisms, as well as for clocks. Some clocks, such as the circadian clock, that time with environmental periodicities are usually compensated (stabilized) against temperature, whereas other clocks, such as the cell cycle, that keep time with an organismic timescale are not compensated. This difference may be related to the predominance of negative feedback in the first class of clocks and a predominance of positive feedback (autocatalytic amplification) in the second class. The present knowledge of a compensated clock (the circadian oscillator) and an uncompensated clock (the cell cycle), as well as relevant models, are briefly re viewed. Hourglass clocks are based on linear or exponential unidirectional processes that trigger events mainly in the course of development and aging. An important hourglass mechanism within the aging process is the limitation of cell division capacity by the length of telomeres. The mechanism of this clock is briefly reviewed. In all clock mechanisms, thresholds at which "dependent variables" are triggered play an important role.

High-frequency oscillations in human and monkey neocortex during the wake–sleep cycle

PubMed Central

Le Van Quyen, Michel; Muller, Lyle E.; Telenczuk, Bartosz; Halgren, Eric; Cash, Sydney; Hatsopoulos, Nicholas G.; Dehghani, Nima; Destexhe, Alain

2016-01-01

Beta (β)- and gamma (γ)-oscillations are present in different cortical areas and are thought to be inhibition-driven, but it is not known if these properties also apply to γ-oscillations in humans. Here, we analyze such oscillations in high-density microelectrode array recordings in human and monkey during the wake–sleep cycle. In these recordings, units were classified as excitatory and inhibitory cells. We find that γ-oscillations in human and β-oscillations in monkey are characterized by a strong implication of inhibitory neurons, both in terms of their firing rate and their phasic firing with the oscillation cycle. The β- and γ-waves systematically propagate across the array, with similar velocities, during both wake and sleep. However, only in slow-wave sleep (SWS) β- and γ-oscillations are associated with highly coherent and functional interactions across several millimeters of the neocortex. This interaction is specifically pronounced between inhibitory cells. These results suggest that inhibitory cells are dominantly involved in the genesis of β- and γ-oscillations, as well as in the organization of their large-scale coherence in the awake and sleeping brain. The highest oscillation coherence found during SWS suggests that fast oscillations implement a highly coherent reactivation of wake patterns that may support memory consolidation during SWS. PMID:27482084

High-frequency oscillations in human and monkey neocortex during the wake-sleep cycle.

PubMed

Le Van Quyen, Michel; Muller, Lyle E; Telenczuk, Bartosz; Halgren, Eric; Cash, Sydney; Hatsopoulos, Nicholas G; Dehghani, Nima; Destexhe, Alain

2016-08-16

Beta (β)- and gamma (γ)-oscillations are present in different cortical areas and are thought to be inhibition-driven, but it is not known if these properties also apply to γ-oscillations in humans. Here, we analyze such oscillations in high-density microelectrode array recordings in human and monkey during the wake-sleep cycle. In these recordings, units were classified as excitatory and inhibitory cells. We find that γ-oscillations in human and β-oscillations in monkey are characterized by a strong implication of inhibitory neurons, both in terms of their firing rate and their phasic firing with the oscillation cycle. The β- and γ-waves systematically propagate across the array, with similar velocities, during both wake and sleep. However, only in slow-wave sleep (SWS) β- and γ-oscillations are associated with highly coherent and functional interactions across several millimeters of the neocortex. This interaction is specifically pronounced between inhibitory cells. These results suggest that inhibitory cells are dominantly involved in the genesis of β- and γ-oscillations, as well as in the organization of their large-scale coherence in the awake and sleeping brain. The highest oscillation coherence found during SWS suggests that fast oscillations implement a highly coherent reactivation of wake patterns that may support memory consolidation during SWS.

Functional connectivity changes in adults with developmental stuttering: a preliminary study using quantitative electro-encephalography

PubMed Central

Joos, Kathleen; De Ridder, Dirk; Boey, Ronny A.; Vanneste, Sven

2014-01-01

Introduction: Stuttering is defined as speech characterized by verbal dysfluencies, but should not be seen as an isolated speech disorder, but as a generalized sensorimotor timing deficit due to impaired communication between speech related brain areas. Therefore we focused on resting state brain activity and functional connectivity. Method: We included 11 patients with developmental stuttering and 11 age matched controls. To objectify stuttering severity and the impact on quality of life (QoL), we used the Dutch validated Test for Stuttering Severity-Readers (TSS-R) and the Overall Assessment of the Speaker’s Experience of Stuttering (OASES), respectively. Furthermore, we used standardized low resolution brain electromagnetic tomography (sLORETA) analyses to look at resting state activity and functional connectivity differences and their correlations with the TSS-R and OASES. Results: No significant results could be obtained when looking at neural activity, however significant alterations in resting state functional connectivity could be demonstrated between persons who stutter (PWS) and fluently speaking controls, predominantly interhemispheric, i.e., a decreased functional connectivity for high frequency oscillations (beta and gamma) between motor speech areas (BA44 and 45) and the contralateral premotor (BA6) and motor (BA4) areas. Moreover, a positive correlation was found between functional connectivity at low frequency oscillations (theta and alpha) and stuttering severity, while a mixed increased and decreased functional connectivity at low and high frequency oscillations correlated with QoL. Discussion: PWS are characterized by decreased high frequency interhemispheric functional connectivity between motor speech, premotor and motor areas in the resting state, while higher functional connectivity in the low frequency bands indicates more severe speech disturbances, suggesting that increased interhemispheric and right sided functional connectivity is maladaptive. PMID:25352797

Probing phase- and frequency-dependent characteristics of cortical interneurons using combined transcranial alternating current stimulation and transcranial magnetic stimulation.

PubMed

Hussain, Sara J; Thirugnanasambandam, Nivethida

2017-06-01

Paired-pulse transcranial magnetic stimulation (TMS) and peripheral stimulation combined with TMS can be used to study cortical interneuronal circuitry. By combining these procedures with concurrent transcranial alternating current stimulation (tACS), Guerra and colleagues recently showed that different cortical interneuronal populations are differentially modulated by the phase and frequency of tACS-imposed oscillations (Guerra A, Pogosyan A, Nowak M, Tan H, Ferreri F, Di Lazzaro V, Brown P. Cerebral Cortex 26: 3977-2990, 2016). This work suggests that different cortical interneuronal populations can be characterized by their phase and frequency dependency. Here we discuss how combining TMS and tACS can reveal the frequency at which cortical interneuronal populations oscillate, the neuronal origins of behaviorally relevant cortical oscillations, and how entraining cortical oscillations could potentially treat brain disorders. Copyright © 2017 the American Physiological Society.

Brain Oscillations, Hypnosis, and Hypnotizability.

PubMed

Jensen, Mark P; Adachi, Tomonori; Hakimian, Shahin

2015-01-01

This article summarizes the state-of-science knowledge regarding the associations between hypnosis and brain oscillations. Brain oscillations represent the combined electrical activity of neuronal assemblies, usually measured as specific frequencies representing slower (delta, theta, alpha) and faster (beta, gamma) oscillations. Hypnosis has been most closely linked to power in the theta band and changes in gamma activity. These oscillations are thought to play a critical role in both the recording and recall of declarative memory and emotional limbic circuits. The authors propose that this role may be the mechanistic link between theta (and perhaps gamma) oscillations and hypnosis, specifically, that the increases in theta oscillations and changes in gamma activity observed with hypnosis may underlie some hypnotic responses. If these hypotheses are supported, they have important implications for both understanding the effects of hypnosis and for enhancing response to hypnotic treatments.

Hypoactivation of reward motivational system in patients with newly diagnosed hypertension grade I-II.

PubMed

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

2014-08-01

In patients with newly diagnosed untreated grade I-II hypertension, EEG oscillations were recorded under conditions activation of the two basic motivational systems, defensive motivational system and positive reinforcement system, evoked by recall of personally meaningful emotional events. The 64-channel EEG and cardiovascular reactivity (beat-by-beat technology) were simultaneously recorded. At rest, hypertensive patients had significantly reduced platelet serotonin concentrations in comparison with healthy individuals. The patients experiencing emotional activation were characterized by significantly lower intensity of positive emotions associated with more pronounced suppression of EEG activity in the delta (2-4 Hz) and theta (ranges of frequency 4-6 and 6-8 Hz) oscillators in the parieto-occipital cortex (zones P and PO) in both hemispheres of the brain. The findings attest to insufficient function of the brain serotonin system and hypoactivation of the reward/reinforcement system in patients with primary hypertension.

Brain Oscillations, Hypnosis, and Hypnotizability

PubMed Central

Jensen, Mark P.; Adachi, Tomonori; Hakimian, Shahin

2014-01-01

In this article, we summarize the state-of-science knowledge regarding the associations between hypnosis and brain oscillations. Brain oscillations represent the combined electrical activity of neuronal assemblies, and are usually measured as specific frequencies representing slower (delta, theta, alpha) and faster (beta, gamma) oscillations. Hypnosis has been most closely linked to power in the theta band and changes in gamma activity. These oscillations are thought to play a critical role in both the recording and recall of declarative memory and emotional limbic circuits. Here we propose that it is this role that may be the mechanistic link between theta (and perhaps gamma) oscillations and hypnosis; specifically that theta oscillations may facilitate, and that changes in gamma activity observed with hypnosis may underlie, some hypnotic responses. If these hypotheses are supported, they have important implications for both understanding the effects of hypnosis, and for enhancing response to hypnotic treatments. PMID:25792761

Hypothesis-driven methods to augment human cognition by optimizing cortical oscillations

PubMed Central

Horschig, Jörn M.; Zumer, Johanna M.; Bahramisharif, Ali

2014-01-01

Cortical oscillations have been shown to represent fundamental functions of a working brain, e.g., communication, stimulus binding, error monitoring, and inhibition, and are directly linked to behavior. Recent studies intervening with these oscillations have demonstrated effective modulation of both the oscillations and behavior. In this review, we collect evidence in favor of how hypothesis-driven methods can be used to augment cognition by optimizing cortical oscillations. We elaborate their potential usefulness for three target groups: healthy elderly, patients with attention deficit/hyperactivity disorder, and healthy young adults. We discuss the relevance of neuronal oscillations in each group and show how each of them can benefit from the manipulation of functionally-related oscillations. Further, we describe methods for manipulation of neuronal oscillations including direct brain stimulation as well as indirect task alterations. We also discuss practical considerations about the proposed techniques. In conclusion, we propose that insights from neuroscience should guide techniques to augment human cognition, which in turn can provide a better understanding of how the human brain works. PMID:25018706

Brain Oscillations during Semantic Evaluation of Speech

ERIC Educational Resources Information Center

Shahin, Antoine J.; Picton, Terence W.; Miller, Lee M.

2009-01-01

Changes in oscillatory brain activity have been related to perceptual and cognitive processes such as selective attention and memory matching. Here we examined brain oscillations, measured with electroencephalography (EEG), during a semantic speech processing task that required both lexically mediated memory matching and selective attention.…

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.

Genetic influences on phase synchrony of brain oscillations supporting response inhibition.

PubMed

Müller, Viktor; Anokhin, Andrey P; Lindenberger, Ulman

2017-05-01

Phase synchronization of neuronal oscillations is a fundamental mechanism underlying cognitive processing and behavior, including context-dependent response production and inhibition. Abnormalities in neural synchrony can lead to abnormal information processing and contribute to cognitive and behavioral deficits in neuropsychiatric disorders. However, little is known about genetic and environmental contributions to individual differences in cortical oscillatory dynamics underlying response inhibition. This study examined heritability of event-related phase synchronization of brain oscillations in 302 young female twins including 94 MZ and 57 DZ pairs performing a cued Go/No-Go version of the Continuous Performance Test (CPT). We used the Phase Locking Index (PLI) to assess inter-trial phase clustering (synchrony) in several frequency bands in two time intervals after stimulus onset (0-300 and 301-600ms). Response inhibition (i.e., successful response suppression in No-Go trials) was characterized by a transient increase in phase synchronization of delta- and theta-band oscillations in the fronto-central midline region. Genetic analysis showed significant heritability of the phase locking measures related to response inhibition, with 30 to 49% of inter-individual variability being accounted for by genetic factors. This is the first study providing evidence for heritability of task-related neural synchrony. The present results suggest that PLI can serve as an indicator of genetically transmitted individual differences in neural substrates of response inhibition. Copyright © 2016 Elsevier B.V. All rights reserved.

Advances in Electrophysiological Research

PubMed Central

Kamarajan, Chella; Porjesz, Bernice

2015-01-01

Electrophysiological measures of brain function are effective tools to understand neurocognitive phenomena and sensitive indicators of pathophysiological processes associated with various clinical conditions, including alcoholism. Individuals with alcohol use disorder (AUD) and their high-risk offspring have consistently shown dysfunction in several electrophysiological measures in resting state (i.e., electroencephalogram) and during cognitive tasks (i.e., event-related potentials and event-related oscillations). Researchers have recently developed sophisticated signal-processing techniques to characterize different aspects of brain dynamics, which can aid in identifying the neural mechanisms underlying alcoholism and other related complex disorders. These quantitative measures of brain function also have been successfully used as endophenotypes to identify and help understand genes associated with AUD and related disorders. Translational research also is examining how brain electrophysiological measures potentially can be applied to diagnosis, prevention, and treatment. PMID:26259089

Traveling Slow Oscillations During Sleep: A Marker of Brain Connectivity in Childhood.

PubMed

Kurth, Salome; Riedner, Brady A; Dean, Douglas C; O'Muircheartaigh, Jonathan; Huber, Reto; Jenni, Oskar G; Deoni, Sean C L; LeBourgeois, Monique K

2017-09-01

Slow oscillations, a defining characteristic of the nonrapid eye movement sleep electroencephalogram (EEG), proliferate across the scalp in highly reproducible patterns. In adults, the propagation of slow oscillations is a recognized fingerprint of brain connectivity and excitability. In this study, we (1) describe for the first time maturational features of sleep slow oscillation propagation in children (n = 23; 2-13 years) using high-density (hd) EEG and (2) examine associations between sleep slow oscillatory propagation characteristics (ie, distance, traveling speed, cortical involvement) and white matter myelin microstructure as measured with multicomponent Driven Equilibrium Single Pulse Observation of T1 and T2-magnetic resonance imaging (mcDESPOT-MRI). Results showed that with increasing age, slow oscillations propagated across longer distances (average growth of 0.2 cm per year; R(21) = 0.50, p < .05), while traveling speed and cortical involvement (ie, slow oscillation expanse) remained unchanged across childhood. Cortical involvement (R(20) = 0.44) and slow oscillation speed (R(20) = -0.47; both p < .05, corrected for age) were associated with myelin content in the superior longitudinal fascicle, the largest anterior-posterior, intrahemispheric white matter connectivity tract. Furthermore, slow oscillation distance was moderately associated with whole-brain (R(21) = 0.46, p < .05) and interhemispheric myelin content, the latter represented by callosal myelin water fraction (R(21) = 0.54, p < .01, uncorrected). Thus, we demonstrate age-related changes in slow oscillation propagation distance, as well as regional associations between brain activity during sleep and the anatomical connectivity of white matter microstructure. Our findings make an important contribution to knowledge of the brain connectome using a noninvasive and novel analytic approach. These data also have implications for understanding the emergence of neurodevelopmental disorders and the role of sleep in brain maturation trajectories. © Sleep Research Society 2017. Published by Oxford University Press on behalf of the Sleep Research Society. All rights reserved. For permissions, please e-mail journals.permissions@oup.com.

CLOCK expression identifies developing circadian oscillator neurons in the brains of Drosophila embryos.

PubMed

Houl, Jerry H; Ng, Fanny; Taylor, Pete; Hardin, Paul E

2008-12-18

The Drosophila circadian oscillator is composed of transcriptional feedback loops in which CLOCK-CYCLE (CLK-CYC) heterodimers activate their feedback regulators period (per) and timeless (tim) via E-box mediated transcription. These feedback loop oscillators are present in distinct clusters of dorsal and lateral neurons in the adult brain, but how this pattern of expression is established during development is not known. Since CLK is required to initiate feedback loop function, defining the pattern of CLK expression in embryos and larvae will shed light on oscillator neuron development. A novel CLK antiserum is used to show that CLK expression in the larval CNS and adult brain is limited to circadian oscillator cells. CLK is initially expressed in presumptive small ventral lateral neurons (s-LNvs), dorsal neurons 2 s (DN2s), and dorsal neuron 1 s (DN1s) at embryonic stage (ES) 16, and this CLK expression pattern persists through larval development. PER then accumulates in all CLK-expressing cells except presumptive DN2s during late ES 16 and ES 17, consistent with the delayed accumulation of PER in adult oscillator neurons and antiphase cycling of PER in larval DN2s. PER is also expressed in non-CLK-expressing cells in the embryonic CNS starting at ES 12. Although PER expression in CLK-negative cells continues in ClkJrk embryos, PER expression in cells that co-express PER and CLK is eliminated. These data demonstrate that brain oscillator neurons begin development during embryogenesis, that PER expression in non-oscillator cells is CLK-independent, and that oscillator phase is an intrinsic characteristic of brain oscillator neurons. These results define the temporal and spatial coordinates of factors that initiate Clk expression, imply that circadian photoreceptors are not activated until the end of embryogenesis, and suggest that PER functions in a different capacity before oscillator cell development is initiated.

Effects of non-pharmacological pain treatments on brain states

PubMed Central

Jensen, Mark P.; Sherlin, Leslie H.; Askew, Robert L.; Fregni, Felipe; Witkop, Gregory; Gianas, Ann; Howe, Jon D.; Hakimian, Shahin

2013-01-01

Objective To (1) evaluate the effects of a single session of four non-pharmacological pain interventions, relative to a sham tDCS procedure, on pain and electroencephalogram- (EEG-) assessed brain oscillations, and (2) determine the extent to which procedure-related changes in pain intensity are associated with changes in brain oscillations. Methods 30 individuals with spinal cord injury and chronic pain were given an EEG and administered measures of pain before and after five procedures (hypnosis, meditation, transcranial direct current stimulation [tDCS], and neurofeedback) and a control sham tDCS procedure. Results Each procedure was associated with a different pattern of changes in brain activity, and all active procedures were significantly different from the control procedure in at least three bandwidths. Very weak and mostly non-significant associations were found between changes in EEG-assessed brain activity and pain. Conclusions Different non-pharmacological pain treatments have distinctive effects on brain oscillation patterns. However, changes in EEG-assessed brain oscillations are not significantly associated with changes in pain, and therefore such changes do not appear useful for explaining the benefits of these treatments. Significance The results provide new findings regarding the unique effects of four non-pharmacological treatments on pain and brain activity. PMID:23706958

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

PubMed Central

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

2010-01-01

Cerebral cortical brain networks possess a number of conspicuous features of structure and dynamics. First, these networks have an intricate, non-random organization. In particular, they are structured in a hierarchical modular fashion, from large-scale regions of the whole brain, via cortical areas and area subcompartments organized as structural and functional maps to cortical columns, and finally circuits made up of individual neurons. Second, the networks display self-organized sustained activity, which is persistent in the absence of external stimuli. At the systems level, such activity is characterized by complex rhythmical oscillations over a broadband background, while at the cellular level, neuronal discharges have been observed to display avalanches, indicating that cortical networks are at the state of self-organized criticality (SOC). We explored the relationship between hierarchical neural network organization and sustained dynamics using large-scale network modeling. Previously, it was shown that sparse random networks with balanced excitation and inhibition can sustain neural activity without external stimulation. We found that a hierarchical modular architecture can generate sustained activity better than random networks. Moreover, the system can simultaneously support rhythmical oscillations and SOC, which are not present in the respective random networks. The mechanism underlying the sustained activity is that each dense module cannot sustain activity on its own, but displays SOC in the presence of weak perturbations. Therefore, the hierarchical modular networks provide the coupling among subsystems with SOC. These results imply that the hierarchical modular architecture of cortical networks plays an important role in shaping the ongoing spontaneous activity of the brain, potentially allowing the system to take advantage of both the sensitivity of critical states and the predictability and timing of oscillations for efficient information processing. PMID:21852971

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

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.

Harmonic Brain Modes: A Unifying Framework for Linking Space and Time in Brain Dynamics.

PubMed

Atasoy, Selen; Deco, Gustavo; Kringelbach, Morten L; Pearson, Joel

2018-06-01

A fundamental characteristic of spontaneous brain activity is coherent oscillations covering a wide range of frequencies. Interestingly, these temporal oscillations are highly correlated among spatially distributed cortical areas forming structured correlation patterns known as the resting state networks, although the brain is never truly at "rest." Here, we introduce the concept of harmonic brain modes-fundamental building blocks of complex spatiotemporal patterns of neural activity. We define these elementary harmonic brain modes as harmonic modes of structural connectivity; that is, connectome harmonics, yielding fully synchronous neural activity patterns with different frequency oscillations emerging on and constrained by the particular structure of the brain. Hence, this particular definition implicitly links the hitherto poorly understood dimensions of space and time in brain dynamics and its underlying anatomy. Further we show how harmonic brain modes can explain the relationship between neurophysiological, temporal, and network-level changes in the brain across different mental states ( wakefulness, sleep, anesthesia, psychedelic). Notably, when decoded as activation of connectome harmonics, spatial and temporal characteristics of neural activity naturally emerge from the interplay between excitation and inhibition and this critical relation fits the spatial, temporal, and neurophysiological changes associated with different mental states. Thus, the introduced framework of harmonic brain modes not only establishes a relation between the spatial structure of correlation patterns and temporal oscillations (linking space and time in brain dynamics), but also enables a new dimension of tools for understanding fundamental principles underlying brain dynamics in different states of consciousness.

Regulating Cortical Oscillations in an Inhibition-Stabilized Network.

PubMed

Jadi, Monika P; Sejnowski, Terrence J

2014-04-21

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

Communication between Brain Areas Based on Nested Oscillations

PubMed Central

Kastner, Sabine

2017-01-01

Abstract Unraveling how brain regions communicate is crucial for understanding how the brain processes external and internal information. Neuronal oscillations within and across brain regions have been proposed to play a crucial role in this process. Two main hypotheses have been suggested for routing of information based on oscillations, namely communication through coherence and gating by inhibition. Here, we propose a framework unifying these two hypotheses that is based on recent empirical findings. We discuss a theory in which communication between two regions is established by phase synchronization of oscillations at lower frequencies (<25 Hz), which serve as temporal reference frame for information carried by high-frequency activity (>40 Hz). Our framework, consistent with numerous recent empirical findings, posits that cross-frequency interactions are essential for understanding how large-scale cognitive and perceptual networks operate. PMID:28374013

Brain and muscle oxygenation monitoring using near-infrared spectroscopy (NIRS) during all-night sleep

NASA Astrophysics Data System (ADS)

Zhang, Zhongxing; Khatami, Ramin

2013-03-01

The hemodynamic changes during natural human sleep are still not well understood. NIRS is ideally suited for monitoring the hemodynamic changes during sleep due to the properties of local measurement, totally safe application and good tolerance to motion. Several studies have been conducted using NIRS in both normal subjects and patients with various sleep disorders during sleep to characterize the hemodynamic changing patterns during different sleep stages and during different symptoms such as obstructive apneas. Here we assessed brain and muscle oxygenation changes in 7 healthy adults during all-night sleep with combined polysomnography measurement to test the notion if hemodynamic changes in sleep are indeed brain specific. We found that muscle and brain showed similar hemodynamic changes during sleep initiation. A decrease in HbO2 and tissue oxygenation index (TOI) while an increase in HHb was observed immediately after sleep onset, and an opposite trend was found after transition with progression to deeper slow-wave sleep (SWS) stage. Spontaneous low frequency oscillations (LFO) and very low frequency oscillations (VLFO) were smaller (Levene's test, p<0.05) during SWS compared to light sleep (LS) and rapid-eye-movement (REM) sleep in both brain and muscle. Spectral analysis of the NIRS signals measured from brain and muscle also showed reductions in VLFO and LFO powers during SWS with respect to LS and REM sleep. These results indicate a systemic attenuation rather than local cerebral reduction of spontaneous hemodynamic activity in SWS. A systemic physiological mechanism may exist to regulate the hemodynamic changes in brain and muscle during sleep.

Prestimulus neural oscillations inhibit visual perception via modulation of response gain.

PubMed

Chaumon, Maximilien; Busch, Niko A

2014-11-01

The ongoing state of the brain radically affects how it processes sensory information. How does this ongoing brain activity interact with the processing of external stimuli? Spontaneous oscillations in the alpha range are thought to inhibit sensory processing, but little is known about the psychophysical mechanisms of this inhibition. We recorded ongoing brain activity with EEG while human observers performed a visual detection task with stimuli of different contrast intensities. To move beyond qualitative description, we formally compared psychometric functions obtained under different levels of ongoing alpha power and evaluated the inhibitory effect of ongoing alpha oscillations in terms of contrast or response gain models. This procedure opens the way to understanding the actual functional mechanisms by which ongoing brain activity affects visual performance. We found that strong prestimulus occipital alpha oscillations-but not more anterior mu oscillations-reduce performance most strongly for stimuli of the highest intensities tested. This inhibitory effect is best explained by a divisive reduction of response gain. Ongoing occipital alpha oscillations thus reflect changes in the visual system's input/output transformation that are independent of the sensory input to the system. They selectively scale the system's response, rather than change its sensitivity to sensory information.

Memory as the "whole brain work": a large-scale model based on "oscillations in super-synergy".

PubMed

Başar, Erol

2005-01-01

According to recent trends, memory depends on several brain structures working in concert across many levels of neural organization; "memory is a constant work-in progress." The proposition of a brain theory based on super-synergy in neural populations is most pertinent for the understanding of this constant work in progress. This report introduces a new model on memory basing on the processes of EEG oscillations and Brain Dynamics. This model is shaped by the following conceptual and experimental steps: 1. The machineries of super-synergy in the whole brain are responsible for formation of sensory-cognitive percepts. 2. The expression "dynamic memory" is used for memory processes that evoke relevant changes in alpha, gamma, theta and delta activities. The concerted action of distributed multiple oscillatory processes provides a major key for understanding of distributed memory. It comprehends also the phyletic memory and reflexes. 3. The evolving memory, which incorporates reciprocal actions or reverberations in the APLR alliance and during working memory processes, is especially emphasized. 4. A new model related to "hierarchy of memories as a continuum" is introduced. 5. The notions of "longer activated memory" and "persistent memory" are proposed instead of long-term memory. 6. The new analysis to recognize faces emphasizes the importance of EEG oscillations in neurophysiology and Gestalt analysis. 7. The proposed basic framework called "Memory in the Whole Brain Work" emphasizes that memory and all brain functions are inseparable and are acting as a "whole" in the whole brain. 8. The role of genetic factors is fundamental in living system settings and oscillations and accordingly in memory, according to recent publications. 9. A link from the "whole brain" to "whole body," and incorporation of vegetative and neurological system, is proposed, EEG oscillations and ultraslow oscillations being a control parameter.

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.

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

The up and down of sleep: From molecules to electrophysiology.

PubMed

Navarro-Lobato, Irene; Genzel, Lisa

2018-03-12

Alternations of up and down can be seen across many different levels during sleep. Neural firing-rates, synaptic markers, molecular pathways, and gene expression all show differential up and down regulation across brain areas and sleep stages. And also the hallmarks of sleep - sleep stage specific oscillations - are characterized themselves by up and down as seen within the slow oscillation or theta cycles. In this review, we summarize the up and down of sleep covering molecules to electrophysiology and present different theories how this up and down could be regulated by the up and down of sleep oscillations. Further, we propose a tentative theory how this differential up and down could contribute to various outcomes of sleep related memory consolidation: enhancement of hippocampal representations of very novel memories and cortical consolidation of memories congruent with previous knowledge-networks. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Dual-labeling method for electron microscopy to characterize synaptic connectivity using genetically encoded fluorescent reporters in Drosophila

PubMed Central

Tanaka, Nobuaki K.; Dye, Louis; Stopfer, Mark

2010-01-01

Light and electron microscopy (LM and EM) both offer important advantages for characterizing neuronal circuitry in intact brains: LM can reveal the general patterns neurons trace between brain areas, and EM can confirm synaptic connections between identified neurons within a small area. In a few species, genetic labeling with fluorescent proteins has been used with LM to visualize many kinds of neurons and to analyze their morphologies and projection patterns. However, combining these large-scale patterns with the fine detail available in EM analysis has been a technical challenge. To analyze the synaptic connectivity of neurons expressing fluorescent markers with EM, we developed a dual-labeling method for use with pre-embedded brains. In Drosophila expressing genetic labels and also injected with markers we visualized synaptic connections among two populations of neurons in the AL, one of which has been shown to mediate a specific function, odor evoked neural oscillation. PMID:21074556

Effective Desynchronization by Nonlinear Delayed Feedback

NASA Astrophysics Data System (ADS)

Popovych, Oleksandr V.; Hauptmann, Christian; Tass, Peter A.

2005-04-01

We show that nonlinear delayed feedback opens up novel means for the control of synchronization. In particular, we propose a demand-controlled method for powerful desynchronization, which does not require any time-consuming calibration. Our technique distinguishes itself by its robustness against variations of system parameters, even in strongly coupled ensembles of oscillators. We suggest our method for mild and effective deep brain stimulation in neurological diseases characterized by pathological cerebral synchronization.

Multichannel brain recordings in behaving Drosophila reveal oscillatory activity and local coherence in response to sensory stimulation and circuit activation

PubMed Central

Paulk, Angelique C.; Zhou, Yanqiong; Stratton, Peter; Liu, Li

2013-01-01

Neural networks in vertebrates exhibit endogenous oscillations that have been associated with functions ranging from sensory processing to locomotion. It remains unclear whether oscillations may play a similar role in the insect brain. We describe a novel “whole brain” readout for Drosophila melanogaster using a simple multichannel recording preparation to study electrical activity across the brain of flies exposed to different sensory stimuli. We recorded local field potential (LFP) activity from >2,000 registered recording sites across the fly brain in >200 wild-type and transgenic animals to uncover specific LFP frequency bands that correlate with: 1) brain region; 2) sensory modality (olfactory, visual, or mechanosensory); and 3) activity in specific neural circuits. We found endogenous and stimulus-specific oscillations throughout the fly brain. Central (higher-order) brain regions exhibited sensory modality-specific increases in power within narrow frequency bands. Conversely, in sensory brain regions such as the optic or antennal lobes, LFP coherence, rather than power, best defined sensory responses across modalities. By transiently activating specific circuits via expression of TrpA1, we found that several circuits in the fly brain modulate LFP power and coherence across brain regions and frequency domains. However, activation of a neuromodulatory octopaminergic circuit specifically increased neuronal coherence in the optic lobes during visual stimulation while decreasing coherence in central brain regions. Our multichannel recording and brain registration approach provides an effective way to track activity simultaneously across the fly brain in vivo, allowing investigation of functional roles for oscillations in processing sensory stimuli and modulating behavior. PMID:23864378

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.

Gradual emergence of spontaneous correlated brain activity during fading of general anesthesia in rats: Evidences from fMRI and local field potentials

PubMed Central

Bettinardi, Ruggero G.; Tort-Colet, Núria; Ruiz-Mejias, Marcel; Sanchez-Vives, Maria V.; Deco, Gustavo

2015-01-01

Intrinsic brain activity is characterized by the presence of highly structured networks of correlated fluctuations between different regions of the brain. Such networks encompass different functions, whose properties are known to be modulated by the ongoing global brain state and are altered in several neurobiological disorders. In the present study, we induced a deep state of anesthesia in rats by means of a ketamine/medetomidine peritoneal injection, and analyzed the time course of the correlation between the brain activity in different areas while anesthesia spontaneously decreased over time. We compared results separately obtained from fMRI and local field potentials (LFPs) under the same anesthesia protocol, finding that while most profound phases of anesthesia can be described by overall sparse connectivity, stereotypical activity and poor functional integration, during lighter states different frequency-specific functional networks emerge, endowing the gradual restoration of structured large-scale activity seen during rest. Noteworthy, our in vivo results show that those areas belonging to the same functional network (the default-mode) exhibited sustained correlated oscillations around 10 Hz throughout the protocol, suggesting the presence of a specific functional backbone that is preserved even during deeper phases of anesthesia. Finally, the overall pattern of results obtained from both imaging and in vivo-recordings suggests that the progressive emergence from deep anesthesia is reflected by a corresponding gradual increase of organized correlated oscillations across the cortex. PMID:25804643

The CLAIR model: Extension of Brodmann areas based on brain oscillations and connectivity.

PubMed

Başar, Erol; Düzgün, Aysel

2016-05-01

Since the beginning of the last century, the localization of brain function has been represented by Brodmann areas, maps of the anatomic organization of the brain. They are used to broadly represent cortical structures with their given sensory-cognitive functions. In recent decades, the analysis of brain oscillations has become important in the correlation of brain functions. Moreover, spectral connectivity can provide further information on the dynamic connectivity between various structures. In addition, brain responses are dynamic in nature and structural localization is almost impossible, according to Luria (1966). Therefore, brain functions are very difficult to localize; hence, a combined analysis of oscillation and event-related coherences is required. In this study, a model termed as "CLAIR" is described to enrich and possibly replace the concept of the Brodmann areas. A CLAIR model with optimum function may take several years to develop, but this study sets out to lay its foundation. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

Altered cortical beta-band oscillations reflect motor system degeneration in amyotrophic lateral sclerosis.

PubMed

Proudfoot, Malcolm; Rohenkohl, Gustavo; Quinn, Andrew; Colclough, Giles L; Wuu, Joanne; Talbot, Kevin; Woolrich, Mark W; Benatar, Michael; Nobre, Anna C; Turner, Martin R

2017-01-01

Continuous rhythmic neuronal oscillations underpin local and regional cortical communication. The impact of the motor system neurodegenerative syndrome amyotrophic lateral sclerosis (ALS) on the neuronal oscillations subserving movement might therefore serve as a sensitive marker of disease activity. Movement preparation and execution are consistently associated with modulations to neuronal oscillation beta (15-30 Hz) power. Cortical beta-band oscillations were measured using magnetoencephalography (MEG) during preparation for, execution, and completion of a visually cued, lateralized motor task that included movement inhibition trials. Eleven "classical" ALS patients, 9 with the primary lateral sclerosis (PLS) phenotype, and 12 asymptomatic carriers of ALS-associated gene mutations were compared with age-similar healthy control groups. Augmented beta desynchronization was observed in both contra- and ipsilateral motor cortices of ALS patients during motor preparation. Movement execution coincided with excess beta desynchronization in asymptomatic mutation carriers. Movement completion was followed by a slowed rebound of beta power in all symptomatic patients, further reflected in delayed hemispheric lateralization for beta rebound in the PLS group. This may correspond to the particular involvement of interhemispheric fibers of the corpus callosum previously demonstrated in diffusion tensor imaging studies. We conclude that the ALS spectrum is characterized by intensified cortical beta desynchronization followed by delayed rebound, concordant with a broader concept of cortical hyperexcitability, possibly through loss of inhibitory interneuronal influences. MEG may potentially detect cortical dysfunction prior to the development of overt symptoms, and thus be able to contribute to the assessment of future neuroprotective strategies. Hum Brain Mapp 38:237-254, 2017. © 2016 Wiley Periodicals, Inc. © 2016 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

Characterization of basal gene expression trends over a diurnal cycle in Xiphophorus maculatus skin, brain and liver.

PubMed

Lu, Yuan; Reyes, Jose; Walter, Sean; Gonzalez, Trevor; Medrano, Geraldo; Boswell, Mikki; Boswell, William; Savage, Markita; Walter, Ronald

2018-06-01

Evolutionarily conserved diurnal circadian mechanisms maintain oscillating patterns of gene expression based on the day-night cycle. Xiphophorus fish have been used to evaluate transcriptional responses after exposure to various light sources and it was determined that each source incites distinct genetic responses in skin tissue. However, basal expression levels of genes that show oscillating expression patterns in day-night cycle, may affect the outcomes of such experiments, since basal gene expression levels at each point in the circadian path may influence the profile of identified light responsive genes. Lack of knowledge regarding diurnal fluctuations in basal gene expression patterns may confound the understanding of genetic responses to external stimuli (e.g., light) since the dynamic nature of gene expression implies animals subjected to stimuli at different times may be at very different stages within the continuum of genetic homeostasis. We assessed basal gene expression changes over a 24-hour period in 200 select Xiphophorus gene targets known to transcriptionally respond to various types of light exposure. We identified 22 genes in skin, 36 genes in brain and 28 genes in liver that exhibit basal oscillation of expression patterns. These genes, including known circadian regulators, produced the expected expression patterns over a 24-hour cycle when compared to circadian regulatory genes identified in other species, especially human and other vertebrate animal models. Our results suggest the regulatory network governing diurnal oscillating gene expression is similar between Xiphophorus and other vertebrates for the three Xiphophorus organs tested. In addition, we were able to categorize light responsive gene sets in Xiphophorus that do, and do not, exhibit circadian based oscillating expression patterns. Copyright © 2017 Elsevier Inc. All rights reserved.

Uncovering genes for cognitive (dys)function and predisposition for alcoholism spectrum disorders: A review of human brain oscillations as effective endophenotypes

PubMed Central

Rangaswamy, Madhavi; Porjesz, Bernice

2010-01-01

Brain oscillations provide a rich source of potentially useful endophenotypes (intermediate phenotypes) for psychiatric genetics, as they represent important correlates of human information processing and are associated with fundamental processes from perception to cognition. These oscillations are highly heritable, are modulated by genes controlling neurotransmitters in the brain, and provide links to associative and integrative brain functions. These endophenotypes represent traits that are less complex and more proximal to gene function than either diagnostic labels or traditional cognitive measures, providing a powerful strategy in searching for genes in psychiatric disorders. These intermediate phenotypes identify both affected and unaffected members of an affected family, including offspring at risk, providing a more direct connection with underlying biological vulnerability. Our group has utilized heritable neurophysiological features (i.e., brain oscillations) as endophenotypes, making it possible to identify susceptibility genes that may be difficult to detect with diagnosis alone. We have discussed our findings of significant linkage and association between brain oscillations and genes in GABAergic, cholinergic and glutamatergic systems (GABRA2, CHRM2, and GRM8). We have also shown that some oscillatory indices from both resting and active cognitive states have revealed a common subset of genetic foci that are shared with the diagnosis of alcoholism and related disorders. Implications of our findings have been discussed in the context of physiological and pharmacological studies on receptor function. These findings underscore the utility of quantitative neurophysiological endophenotypes in the study of the genetics of brain function and the genetic diathesis underlying complex psychiatric disorders. PMID:18634760

Uncovering genes for cognitive (dys)function and predisposition for alcoholism spectrum disorders: a review of human brain oscillations as effective endophenotypes.

PubMed

Rangaswamy, Madhavi; Porjesz, Bernice

2008-10-15

Brain oscillations provide a rich source of potentially useful endophenotypes (intermediate phenotypes) for psychiatric genetics, as they represent important correlates of human information processing and are associated with fundamental processes from perception to cognition. These oscillations are highly heritable, are modulated by genes controlling neurotransmitters in the brain, and provide links to associative and integrative brain functions. These endophenotypes represent traits that are less complex and more proximal to gene function than either diagnostic labels or traditional cognitive measures, providing a powerful strategy in searching for genes in psychiatric disorders. These intermediate phenotypes identify both affected and unaffected members of an affected family, including offspring at risk, providing a more direct connection with underlying biological vulnerability. Our group has utilized heritable neurophysiological features (i.e., brain oscillations) as endophenotypes, making it possible to identify susceptibility genes that may be difficult to detect with diagnosis alone. We have discussed our findings of significant linkage and association between brain oscillations and genes in GABAergic, cholinergic and glutamatergic systems (GABRA2, CHRM2, and GRM8). We have also shown that some oscillatory indices from both resting and active cognitive states have revealed a common subset of genetic foci that are shared with the diagnosis of alcoholism and related disorders. Implications of our findings have been discussed in the context of physiological and pharmacological studies on receptor function. These findings underscore the utility of quantitative neurophysiological endophenotypes in the study of the genetics of brain function and the genetic diathesis underlying complex psychiatric disorders.

Tuning pathological brain oscillations with neurofeedback: a systems neuroscience framework

PubMed Central

Ros, Tomas; J. Baars, Bernard; Lanius, Ruth A.; Vuilleumier, Patrik

2014-01-01

Neurofeedback (NFB) is emerging as a promising technique that enables self-regulation of ongoing brain oscillations. However, despite a rise in empirical evidence attesting to its clinical benefits, a solid theoretical basis is still lacking on the manner in which NFB is able to achieve these outcomes. The present work attempts to bring together various concepts from neurobiology, engineering, and dynamical systems so as to propose a contemporary theoretical framework for the mechanistic effects of NFB. The objective is to provide a firmly neurophysiological account of NFB, which goes beyond traditional behaviorist interpretations that attempt to explain psychological processes solely from a descriptive standpoint whilst treating the brain as a “black box”. To this end, we interlink evidence from experimental findings that encompass a broad range of intrinsic brain phenomena: starting from “bottom-up” mechanisms of neural synchronization, followed by “top-down” regulation of internal brain states, moving to dynamical systems plus control-theoretic principles, and concluding with activity-dependent as well as homeostatic forms of brain plasticity. In support of our framework, we examine the effects of NFB in several brain disorders, including attention-deficit hyperactivity (ADHD) and post-traumatic stress disorder (PTSD). In sum, it is argued that pathological oscillations emerge from an abnormal formation of brain-state attractor landscape(s). The central thesis put forward is that NFB tunes brain oscillations toward a homeostatic set-point which affords an optimal balance between network flexibility and stability (i.e., self-organised criticality (SOC)). PMID:25566028

The Impact of Cortical Deafferentation on the Neocortical Slow Oscillation

PubMed Central

Lemieux, Maxime; Chen, Jen-Yung; Lonjers, Peter; Bazhenov, Maxim

2014-01-01

Slow oscillation is the main brain rhythm observed during deep sleep in mammals. Although several studies have demonstrated its neocortical origin, the extent of the thalamic contribution is still a matter of discussion. Using electrophysiological recordings in vivo on cats and computational modeling, we found that the local thalamic inactivation or the complete isolation of the neocortical slabs maintained within the brain dramatically reduced the expression of slow and fast oscillations in affected cortical areas. The slow oscillation began to recover 12 h after thalamic inactivation. The slow oscillation, but not faster activities, nearly recovered after 30 h and persisted for weeks in the isolated slabs. We also observed an increase of the membrane potential fluctuations recorded in vivo several hours after thalamic inactivation. Mimicking this enhancement in a network computational model with an increased postsynaptic activity of long-range intracortical afferents or scaling K+ leak current, but not several other Na+ and K+ intrinsic currents was sufficient for recovering the slow oscillation. We conclude that, in the intact brain, the thalamus contributes to the generation of cortical active states of the slow oscillation and mediates its large-scale synchronization. Our study also suggests that the deafferentation-induced alterations of the sleep slow oscillation can be counteracted by compensatory intracortical mechanisms and that the sleep slow oscillation is a fundamental and intrinsic state of the neocortex. PMID:24741059

Gamma oscillations: precise temporal coordination without a metronome.

PubMed

Nikolić, Danko; Fries, Pascal; Singer, Wolf

2013-02-01

Gamma oscillations in the brain should not be conceptualized as a sine wave with constant oscillation frequency. Rather, these oscillations serve to concentrate neuronal discharges to particular phases of the oscillation cycle and thereby provide the substrate for various, functionally relevant synchronization phenomena. Copyright © 2012 Elsevier Ltd. All rights reserved.

High frequency oscillations are associated with cognitive processing in human recognition memory.

PubMed

Kucewicz, Michal T; Cimbalnik, Jan; Matsumoto, Joseph Y; Brinkmann, Benjamin H; Bower, Mark R; Vasoli, Vincent; Sulc, Vlastimil; Meyer, Fred; Marsh, W R; Stead, S M; Worrell, Gregory A

2014-08-01

High frequency oscillations are associated with normal brain function, but also increasingly recognized as potential biomarkers of the epileptogenic brain. Their role in human cognition has been predominantly studied in classical gamma frequencies (30-100 Hz), which reflect neuronal network coordination involved in attention, learning and memory. Invasive brain recordings in animals and humans demonstrate that physiological oscillations extend beyond the gamma frequency range, but their function in human cognitive processing has not been fully elucidated. Here we investigate high frequency oscillations spanning the high gamma (50-125 Hz), ripple (125-250 Hz) and fast ripple (250-500 Hz) frequency bands using intracranial recordings from 12 patients (five males and seven females, age 21-63 years) during memory encoding and recall of a series of affectively charged images. Presentation of the images induced high frequency oscillations in all three studied bands within the primary visual, limbic and higher order cortical regions in a sequence consistent with the visual processing stream. These induced oscillations were detected on individual electrodes localized in the amygdala, hippocampus and specific neocortical areas, revealing discrete oscillations of characteristic frequency, duration and latency from image presentation. Memory encoding and recall significantly modulated the number of induced high gamma, ripple and fast ripple detections in the studied structures, which was greater in the primary sensory areas during the encoding (Wilcoxon rank sum test, P = 0.002) and in the higher-order cortical association areas during the recall (Wilcoxon rank sum test, P = 0.001) of memorized images. Furthermore, the induced high gamma, ripple and fast ripple responses discriminated the encoded and the affectively charged images. In summary, our results show that high frequency oscillations, spanning a wide range of frequencies, are associated with memory processing and generated along distributed cortical and limbic brain regions. These findings support an important role for fast network synchronization in human cognition and extend our understanding of normal physiological brain activity during memory processing. © The Author (2014). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

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.

The dark side of high-frequency oscillations in the developing brain.

PubMed

Le Van Quyen, Michel; Khalilov, Ilgam; Ben-Ari, Yehezkel

2006-07-01

Adult brain networks generate a wide range of oscillations. Some of these are behaviourally relevant, whereas others occur during seizures and other pathological conditions. This raises the question of how physiological oscillations differ from pathogenic ones. In this review, this issue is discussed from a developmental standpoint. Indeed, both epileptic and physiological high-frequency oscillations (HFOs) appear progressively during maturation, and it is therefore possible to determine how this program corresponds to maturation of the neuronal populations that generate these oscillations. We review here important differences in the development of neuronal populations that might contribute to their different oscillatory properties. In particular, at an early stage, the density of glutamatergic synapses is too low for physiological HFOs but an additional drive can be provided by excitatory GABA, triggering epileptic HFOs and the cascades involved in long-lasting epileptogenic transformations. This review is part of the INMED/TINS special issue "Nature and nurture in brain development and neurological disorders", based on presentations at the annual INMED/TINS symposium (http://inmednet.com/).

Low-Frequency Oscillations and Control of the Motor Output

PubMed Central

Lodha, Neha; Christou, Evangelos A.

2017-01-01

A less precise force output impairs our ability to perform movements, learn new motor tasks, and use tools. Here we show that low-frequency oscillations in force are detrimental to force precision. We summarize the recent evidence that low-frequency oscillations in force output represent oscillations of the spinal motor neuron pool from the voluntary drive, and can be modulated by shifting power to higher frequencies. Further, force oscillations below 0.5 Hz impair force precision with increased voluntary drive, aging, and neurological disease. We argue that the low-frequency oscillations are (1) embedded in the descending drive as shown by the activation of multiple spinal motor neurons, (2) are altered with force intensity and brain pathology, and (3) can be modulated by visual feedback and motor training to enhance force precision. Thus, low-frequency oscillations in force provide insight into how the human brain regulates force precision. PMID:28261107

Interacting Turing-Hopf Instabilities Drive Symmetry-Breaking Transitions in a Mean-Field Model of the Cortex: A Mechanism for the Slow Oscillation

NASA Astrophysics Data System (ADS)

Steyn-Ross, Moira L.; Steyn-Ross, D. A.; Sleigh, J. W.

2013-04-01

Electrical recordings of brain activity during the transition from wake to anesthetic coma show temporal and spectral alterations that are correlated with gross changes in the underlying brain state. Entry into anesthetic unconsciousness is signposted by the emergence of large, slow oscillations of electrical activity (≲1Hz) similar to the slow waves observed in natural sleep. Here we present a two-dimensional mean-field model of the cortex in which slow spatiotemporal oscillations arise spontaneously through a Turing (spatial) symmetry-breaking bifurcation that is modulated by a Hopf (temporal) instability. In our model, populations of neurons are densely interlinked by chemical synapses, and by interneuronal gap junctions represented as an inhibitory diffusive coupling. To demonstrate cortical behavior over a wide range of distinct brain states, we explore model dynamics in the vicinity of a general-anesthetic-induced transition from “wake” to “coma.” In this region, the system is poised at a codimension-2 point where competing Turing and Hopf instabilities coexist. We model anesthesia as a moderate reduction in inhibitory diffusion, paired with an increase in inhibitory postsynaptic response, producing a coma state that is characterized by emergent low-frequency oscillations whose dynamics is chaotic in time and space. The effect of long-range axonal white-matter connectivity is probed with the inclusion of a single idealized point-to-point connection. We find that the additional excitation from the long-range connection can provoke seizurelike bursts of cortical activity when inhibitory diffusion is weak, but has little impact on an active cortex. Our proposed dynamic mechanism for the origin of anesthetic slow waves complements—and contrasts with—conventional explanations that require cyclic modulation of ion-channel conductances. We postulate that a similar bifurcation mechanism might underpin the slow waves of natural sleep and comment on the possible consequences of chaotic dynamics for memory processing and learning.

Wavelet analysis can sensitively describe dynamics of ethanol evoked local field potentials of the slug (Limax marginatus) brain.

PubMed

Schütt, Atsuko; Ito, Iori; Rosso, Osvaldo A; Figliola, Alejandra

2003-10-30

Odorants evoke characteristic, but complex, local field potentials (LFPs) in the molluscan brain. Wavelet tools in combination with Fourier analysis can detect and characterize hitherto unknown discrete, slow potentials underlying the conspicuous oscillations. Ethanol was one of the odorants that we have extensively studied (J. Neurosci. Methods, 119 (2002) 89). To detect new features and to elucidate their functions, we tested the wavelet tools on the ethanol-evoked LFP responses of the slug (Limax) procerebrum. Recordings were made in vitro from the neuropile and the cell layer. The present study led to the following findings: (i) Mutual exclusion. Energy concentrated mainly in two ranges, (a) 0.1-0.4 Hz and (b) 1.56-12.5 Hz, and the sum of energy remained constant throughout experiments regardless of the condition. A redistribution of relative energy within this sum seemed to occur in the course of main, possible interactions between the two components excluding each other ('mutual exclusion'). (ii) Transient signal ordering and disordering. Ethanol stimulation alternatingly evoked periods of strongly time evolving oscillation dominated by the energy of 1.56-12.5 Hz (increase of entropy=disordered or complexly ordered state) and those of near-silence were predominated by the energy of 0.1-0.4 Hz (decrease of entropy=ordered state). (iii) About 0.1 Hz slow wave oscillation. It was robust. The dominant energy oscillation and the resulting large entropy fluctuation were negatively correlated to each other, and revealed strong frequency-tuning or synchronization at this frequency. Our findings suggest that discrete slow waves play functionally important roles in the invertebrate brain, as widely known in vertebrate EEG. Wavelet tools allow an easy interpretation of several minutes of frequency variations in a single display and give precise information on stimulus-evoked complex change of the neural system describing the new state 'more ordered' or 'non-ordered or more complexly ordered'.

Connexin channels provide a target to manipulate brain endothelial calcium dynamics and blood–brain barrier permeability

PubMed Central

De Bock, Marijke; Culot, Maxime; Wang, Nan; Bol, Mélissa; Decrock, Elke; De Vuyst, Elke; da Costa, Anaelle; Dauwe, Ine; Vinken, Mathieu; Simon, Alexander M; Rogiers, Vera; De Ley, Gaspard; Evans, William Howard; Bultynck, Geert; Dupont, Geneviève; Cecchelli, Romeo; Leybaert, Luc

2011-01-01

The cytoplasmic Ca2+ concentration ([Ca2+]i) is an important factor determining the functional state of blood–brain barrier (BBB) endothelial cells but little is known on the effect of dynamic [Ca2+]i changes on BBB function. We applied different agonists that trigger [Ca2+]i oscillations and determined the involvement of connexin channels and subsequent effects on endothelial permeability in immortalized and primary brain endothelial cells. The inflammatory peptide bradykinin (BK) triggered [Ca2+]i oscillations and increased endothelial permeability. The latter was prevented by buffering [Ca2+]i with BAPTA, indicating that [Ca2+]i oscillations are crucial in the permeability changes. Bradykinin-triggered [Ca2+]i oscillations were inhibited by interfering with connexin channels, making use of carbenoxolone, Gap27, a peptide blocker of connexin channels, and Cx37/43 knockdown. Gap27 inhibition of the oscillations was rapid (within minutes) and work with connexin hemichannel-permeable dyes indicated hemichannel opening and purinergic signaling in response to stimulation with BK. Moreover, Gap27 inhibited the BK-triggered endothelial permeability increase in in vitro and in vivo experiments. By contrast, [Ca2+]i oscillations provoked by exposure to adenosine 5′ triphosphate (ATP) were not affected by carbenoxolone or Gap27 and ATP did not disturb endothelial permeability. We conclude that interfering with endothelial connexin hemichannels is a novel approach to limiting BBB-permeability alterations. PMID:21654699

The brain’s resting state activity is shaped by synchronized cross frequency coupling of neural oscillations (Author’s Manuscript)

DTIC Science & Technology

2015-02-11

uncovered. Using magnetoencephalography ( MEG ) imaging during rest in 12 healthy subjects we analyse the resting state networks and their underlying...across the whole brain of the resting state is generated. Human magnetoencephalography ( MEG ) of the whole brain emphasized the contribution of...frequency oscillations coordinate long-range communication (Stein, Chiang, and König, 2000). However, these MEG findings do not align entirely with

Unusual developmental pattern of brain lateralization in young boys with autism spectrum disorder: Power analysis with child-sized magnetoencephalography.

PubMed

Hiraishi, Hirotoshi; Kikuchi, Mitsuru; Yoshimura, Yuko; Kitagawa, Sachiko; Hasegawa, Chiaki; Munesue, Toshio; Takesaki, Natsumi; Ono, Yasuki; Takahashi, Tsutomu; Suzuki, Michio; Higashida, Haruhiro; Asada, Minoru; Minabe, Yoshio

2015-03-01

Autism spectrum disorder (ASD) is often described as comprising an unusual brain growth pattern and aberrant brain lateralization. Although it is important to study the pathophysiology of the developing ASD cortex, examples of physiological brain lateralization in young children with ASD have yet to be well examined. Thirty-eight boys with ASD (aged 3-7 years) and 38 typically developing (TD) boys (aged 3-8 years) concentrated on video programs and their brain activities were measured non-invasively. We employed a customized child-sized magnetoencephalography system in which the sensors were located as close to the brain as possible for optimal recording in young children. To produce a credible laterality index of the brain oscillations, we defined two clusters of sensors corresponding to the right and left hemispheres. We focused on the laterality index ([left - right]/[left+right]) of the relative power band in seven frequency bands. The TD group displayed significantly rightward lateralized brain oscillations in the theta-1 frequency bands compared to the ASD group. This is the first study to demonstrate unusual brain lateralization of brain oscillations measured by magnetoencephalography in young children with ASD. © 2014 The Authors. Psychiatry and Clinical Neurosciences © 2014 Japanese Society of Psychiatry and Neurology.

Atypical Laterality of Resting Gamma Oscillations in Autism Spectrum Disorders

ERIC Educational Resources Information Center

Maxwell, Christina R.; Villalobos, Michele E.; Schultz, Robert T.; Herpertz-Dahlmann, Beate; Konrad, Kerstin; Kohls, Gregor

2015-01-01

Abnormal brain oscillatory activity has been found in autism spectrum disorders (ASD) and proposed as a potential biomarker. While several studies have investigated gamma oscillations in ASD, none have examined resting gamma power across multiple brain regions. This study investigated resting gamma power using EEG in 15 boys with ASD and 18 age…

Brain Oscillations Forever--Neurophysiology in Future Research of Child Psychiatric Problems

ERIC Educational Resources Information Center

Rothenberger, Aribert

2009-01-01

For decades neurophysiology has successfully contributed to research and clinical care in child psychiatry. Recently, methodological progress has led to a revival of interest in brain oscillations (i.e., a band of periodic neuronal frequencies with a wave-duration from milliseconds to several seconds which may code and decode information). These…

Cortical Local Field Potential Power Is Associated with Behavioral Detection of Near-threshold Stimuli in the Rat Whisker System: Dissociation between Orbitofrontal and Somatosensory Cortices.

PubMed

Rickard, Rachel E; Young, Andrew M J; Gerdjikov, Todor V

2018-01-01

There is growing evidence that ongoing brain oscillations may represent a key regulator of attentional processes and as such may contribute to behavioral performance in psychophysical tasks. OFC appears to be involved in the top-down modulation of sensory processing; however, the specific contribution of ongoing OFC oscillations to perception has not been characterized. Here we used the rat whiskers as a model system to further characterize the relationship between cortical state and tactile detection. Head-fixed rats were trained to report the presence of a vibrotactile stimulus (frequency = 60 Hz, duration = 2 sec, deflection amplitude = 0.01-0.5 mm) applied to a single vibrissa. We calculated power spectra of local field potentials preceding the onset of near-threshold stimuli from microelectrodes chronically implanted in OFC and somatosensory cortex. We found a dissociation between slow oscillation power in the two regions in relation to detection probability: Higher OFC but not somatosensory delta power was associated with increased detection probability. Furthermore, coherence between OFC and barrel cortex was reduced preceding successful detection. Consistent with the role of OFC in attention, our results identify a cortical network whose activity is differentially modulated before successful tactile detection.

Experimental Evidence for Phase Synchronization Transitions in the Human Cardiorespiratory System

NASA Astrophysics Data System (ADS)

Bartsch, Ronny; Kantelhardt, Jan W.; Penzel, Thomas; Havlin, Shlomo

2007-02-01

Transitions in the dynamics of complex systems can be characterized by changes in the synchronization behavior of their components. Taking the human cardiorespiratory system as an example and using an automated procedure for screening the synchrograms of 112 healthy subjects we study the frequency and the distribution of synchronization episodes under different physiological conditions that occur during sleep. We find that phase synchronization between heartbeat and breathing is significantly enhanced during non-rapid-eye-movement (non-REM) sleep (deep sleep and light sleep) and reduced during REM sleep. Our results suggest that the synchronization is mainly due to a weak influence of the breathing oscillator upon the heartbeat oscillator, which is disturbed in the presence of long-term correlated noise, superimposed by the activity of higher brain regions during REM sleep.

A Prospective Study of Age-dependent Changes in Propofol-induced Electroencephalogram Oscillations in Children.

PubMed

Lee, Johanna M; Akeju, Oluwaseun; Terzakis, Kristina; Pavone, Kara J; Deng, Hao; Houle, Timothy T; Firth, Paul G; Shank, Erik S; Brown, Emery N; Purdon, Patrick L

2017-08-01

In adults, frontal electroencephalogram patterns observed during propofol-induced unconsciousness consist of slow oscillations (0.1 to 1 Hz) and coherent alpha oscillations (8 to 13 Hz). Given that the nervous system undergoes significant changes during development, anesthesia-induced electroencephalogram oscillations in children may differ from those observed in adults. Therefore, we investigated age-related changes in frontal electroencephalogram power spectra and coherence during propofol-induced unconsciousness. We analyzed electroencephalogram data recorded during propofol-induced unconsciousness in patients between 0 and 21 yr of age (n = 97), using multitaper spectral and coherence methods. We characterized power and coherence as a function of age using multiple linear regression analysis and within four age groups: 4 months to 1 yr old (n = 4), greater than 1 to 7 yr old (n = 16), greater than 7 to 14 yr old (n = 30), and greater than 14 to 21 yr old (n = 47). Total electroencephalogram power (0.1 to 40 Hz) peaked at approximately 8 yr old and subsequently declined with increasing age. For patients greater than 1 yr old, the propofol-induced electroencephalogram structure was qualitatively similar regardless of age, featuring slow and coherent alpha oscillations. For patients under 1 yr of age, frontal alpha oscillations were not coherent. Neurodevelopmental processes that occur throughout childhood, including thalamocortical development, may underlie age-dependent changes in electroencephalogram power and coherence during anesthesia. These age-dependent anesthesia-induced electroencephalogram oscillations suggest a more principled approach to monitoring brain states in pediatric patients.

Extra-hypothalamic brain clocks in songbirds: Photoperiodic state dependent clock gene oscillations in night-migratory blackheaded buntings, Emberiza melanocephala.

PubMed

Singh, Devraj; Kumar, Vinod

2017-04-01

The avian circadian pacemaker system is comprised of independent clocks in the retina, pineal and hypothalamus, as shown by daily and circadian oscillations of core clock genes (Per2, Cry1, Bmal1 and Clock) in several birds including migratory blackheaded buntings (Emberiza melanocephala). This study investigated the extra-hypothalamic brain circadian clocks in blackheaded buntings, and measured Per2, Cry1, Cry2, Bmal1 and Clock mRNA expressions at 4h intervals over 24h beginning 1h after light-on in the left and right telencephalon, optic tectum and cerebellum, the brain regions involved in several physiological and cognitive functions. Because of seasonal alterations in the circadian clock dependent brain functions, we measured daily clock gene oscillations in buntings photoperiod-induced with the non-migratory state under short days (SDnM), and the pre-migratory (LDpM), migratory (LDM) and post-migratory (refractory, LDR) states under long days. Daily Per2 oscillations were not altered with changes in the photoperiodic states, except for about 2-3h phase difference in the optic tectum between the SDnM and LDpM states. However, there were about 3-5h differences in the phase and 2 to 4 fold change in the amplitude of daily Bmal1 and Cry1 mRNA oscillations between the photoperiod-induced states. Further, Cry2 and Clock genes lacked a significant oscillation, except in Cb (Cry2) and TeO and Rt (Clock) under LDR state. Overall, these results show the presence of circadian clocks in extra-hypothalamic brain regions of blackheaded buntings, and suggest tissue-dependent alterations in the waveforms of mRNA oscillations with transitions in the photoperiod-induced seasonal states in a long-day species. Copyright © 2017 Elsevier B.V. All rights reserved.

Alpha-Band Rhythms in Visual Task Performance: Phase-Locking by Rhythmic Sensory Stimulation

PubMed Central

de Graaf, Tom A.; Gross, Joachim; Paterson, Gavin; Rusch, Tessa; Sack, Alexander T.; Thut, Gregor

2013-01-01

Oscillations are an important aspect of neuronal activity. Interestingly, oscillatory patterns are also observed in behaviour, such as in visual performance measures after the presentation of a brief sensory event in the visual or another modality. These oscillations in visual performance cycle at the typical frequencies of brain rhythms, suggesting that perception may be closely linked to brain oscillations. We here investigated this link for a prominent rhythm of the visual system (the alpha-rhythm, 8–12 Hz) by applying rhythmic visual stimulation at alpha-frequency (10.6 Hz), known to lead to a resonance response in visual areas, and testing its effects on subsequent visual target discrimination. Our data show that rhythmic visual stimulation at 10.6 Hz: 1) has specific behavioral consequences, relative to stimulation at control frequencies (3.9 Hz, 7.1 Hz, 14.2 Hz), and 2) leads to alpha-band oscillations in visual performance measures, that 3) correlate in precise frequency across individuals with resting alpha-rhythms recorded over parieto-occipital areas. The most parsimonious explanation for these three findings is entrainment (phase-locking) of ongoing perceptually relevant alpha-band brain oscillations by rhythmic sensory events. These findings are in line with occipital alpha-oscillations underlying periodicity in visual performance, and suggest that rhythmic stimulation at frequencies of intrinsic brain-rhythms can be used to reveal influences of these rhythms on task performance to study their functional roles. PMID:23555873

Shunting inhibition improves robustness of gamma oscillations in hippocampal interneuron networks by homogenizing firing rates.

PubMed

Vida, Imre; Bartos, Marlene; Jonas, Peter

2006-01-05

Networks of GABAergic neurons are key elements in the generation of gamma oscillations in the brain. Computational studies suggested that the emergence of coherent oscillations requires hyperpolarizing inhibition. Here, we show that GABA(A) receptor-mediated inhibition in mature interneurons of the hippocampal dentate gyrus is shunting rather than hyperpolarizing. Unexpectedly, when shunting inhibition is incorporated into a structured interneuron network model with fast and strong synapses, coherent oscillations emerge. In comparison to hyperpolarizing inhibition, networks with shunting inhibition show several advantages. First, oscillations are generated with smaller tonic excitatory drive. Second, network frequencies are tuned to the gamma band. Finally, robustness against heterogeneity in the excitatory drive is markedly improved. In single interneurons, shunting inhibition shortens the interspike interval for low levels of drive but prolongs it for high levels, leading to homogenization of neuronal firing rates. Thus, shunting inhibition may confer increased robustness to gamma oscillations in the brain.

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

Friends, not foes: Magnetoencephalography as a tool to uncover brain dynamics during transcranial alternating current stimulation.

PubMed

Neuling, Toralf; Ruhnau, Philipp; Fuscà, Marco; Demarchi, Gianpaolo; Herrmann, Christoph S; Weisz, Nathan

2015-09-01

Brain oscillations are supposedly crucial for normal cognitive functioning and alterations are associated with cognitive dysfunctions. To demonstrate their causal role on behavior, entrainment approaches in particular aim at driving endogenous oscillations via rhythmic stimulation. Within this context, transcranial electrical stimulation, especially transcranial alternating current stimulation (tACS), has received renewed attention. This is likely due to the possibility of defining oscillatory stimulation properties precisely. Also, measurements comparing pre-tACS with post-tACS electroencephalography (EEG) have shown impressive modulations. However, the period during tACS has remained a blackbox until now, due to the enormous stimulation artifact. By means of application of beamforming to magnetoencephalography (MEG) data, we successfully recovered modulations of the amplitude of brain oscillations during weak and strong tACS. Additionally, we demonstrate that also evoked responses to visual and auditory stimuli can be recovered during tACS. The main contribution of the present study is to provide critical evidence that during ongoing tACS, subtle modulations of oscillatory brain activity can be reconstructed even at the stimulation frequency. Future tACS experiments will be able to deliver direct physiological insights in order to further the understanding of the contribution of brain oscillations to cognition and behavior. Copyright © 2015. Published by Elsevier Inc.

Friends, not foes: Magnetoencephalography as a tool to uncover brain dynamics during transcranial alternating current stimulation

PubMed Central

Neuling, Toralf; Ruhnau, Philipp; Fuscà, Marco; Demarchi, Gianpaolo; Herrmann, Christoph S.; Weisz, Nathan

2015-01-01

Brain oscillations are supposedly crucial for normal cognitive functioning and alterations are associated with cognitive dysfunctions. To demonstrate their causal role on behavior, entrainment approaches in particular aim at driving endogenous oscillations via rhythmic stimulation. Within this context, transcranial electrical stimulation, especially transcranial alternating current stimulation (tACS), has received renewed attention. This is likely due to the possibility of defining oscillatory stimulation properties precisely. Also, measurements comparing pre-tACS with post-tACS electroencephalography (EEG) have shown impressive modulations. However, the period during tACS has remained a blackbox until now, due to the enormous stimulation artifact. By means of application of beamforming to magnetoencephalography (MEG) data, we successfully recovered modulations of the amplitude of brain oscillations during weak and strong tACS. Additionally, we demonstrate that also evoked responses to visual and auditory stimuli can be recovered during tACS. The main contribution of the present study is to provide critical evidence that during ongoing tACS, subtle modulations of oscillatory brain activity can be reconstructed even at the stimulation frequency. Future tACS experiments will be able to deliver direct physiological insights in order to further the understanding of the contribution of brain oscillations to cognition and behavior. PMID:26080310

Brain rhythms and neural syntax: implications for efficient coding of cognitive content and neuropsychiatric disease.

PubMed Central

Buzsáki, György; Watson, Brendon O.

2012-01-01

The perpetual activity of the cerebral cortex is largely supported by the variety of oscillations the brain generates, spanning a number of frequencies and anatomical locations, as well as behavioral correlates. First, we review findings from animal studies showing that most forms of brain rhythms are inhibition-based, producing rhythmic volleys of inhibitory inputs to principal cell populations, thereby providing alternating temporal windows of relatively reduced and enhanced excitability in neuronal networks. These inhibition-based mechanisms offer natural temporal frames to group or “chunk” neuronal activity into cell assemblies and sequences of assemblies, with more complex multi-oscillation interactions creating syntactical rules for the effective exchange of information among cortical networks. We then review recent studies in human psychiatric patients demonstrating a variety alterations in neural oscillations across all major psychiatric diseases, and suggest possible future research directions and treatment approaches based on the fundamental properties of brain rhythms. PMID:23393413

Analysis of the characteristics of the synchronous clusters in the adaptive Kuramoto network and neural network of the epileptic brain

NASA Astrophysics Data System (ADS)

Hramov, Alexander E.; Kharchenko, Alexander A.; Makarov, Vladimir V.; Khramova, Marina V.; Koronovskii, Alexey A.; Pavlov, Alexey N.; Dana, Syamal K.

2016-04-01

In the paper we study the mechanisms of phase synchronization in the adaptive model network of Kuramoto oscillators and the neural network of brain by consideration of the integral characteristics of the observed networks signals. As the integral characteristics of the model network we consider the summary signal produced by the oscillators. Similar to the model situation we study the ECoG signal as the integral characteristic of neural network of the brain. We show that the establishment of the phase synchronization results in the increase of the peak, corresponding to synchronized oscillators, on the wavelet energy spectrum of the integral signals. The observed correlation between the phase relations of the elements and the integral characteristics of the whole network open the way to detect the size of synchronous clusters in the neural networks of the epileptic brain before and during seizure.

In vivo imaging of spontaneous low-frequency oscillations in cerebral hemodynamics with a digital red-green-blue camera

NASA Astrophysics Data System (ADS)

Mustari, Afrina; Nakamura, Naoki; Nishidate, Izumi; Kawauchi, Satoko; Sato, Shunichi; Sato, Manabu; Kokobo, Yasuaki

2017-04-01

Nervous system relies on a continuous and adequate supply of blood flow, bringing the nutrients that it needs and removing the waste products of metabolism. Failure of these mechanisms is found in a number of devastating cerebral diseases, including stroke, vascular dementia, brain injury and trauma. Vasomotion which is the spontaneous low-frequency oscillation derived by the contraction and relaxation of arterioles and appears to be an intrinsic property of the cerebral vasculature, is important for monitoring the cerebral flow, tissue metabolism and health status of brain tissue. In the present study, we investigated a method to visualize the spontaneous low-frequency oscillation of cerebral blood volume based on the sequential RGB images of exposed brain.

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

PubMed

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

2017-11-01

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

Cross-entropy optimization for neuromodulation.

PubMed

Brar, Harleen K; Yunpeng Pan; Mahmoudi, Babak; Theodorou, Evangelos A

2016-08-01

This study presents a reinforcement learning approach for the optimization of the proportional-integral gains of the feedback controller represented in a computational model of epilepsy. The chaotic oscillator model provides a feedback control systems view of the dynamics of an epileptic brain with an internal feedback controller representative of the natural seizure suppression mechanism within the brain circuitry. Normal and pathological brain activity is simulated in this model by adjusting the feedback gain values of the internal controller. With insufficient gains, the internal controller cannot provide enough feedback to the brain dynamics causing an increase in correlation between different brain sites. This increase in synchronization results in the destabilization of the brain dynamics, which is representative of an epileptic seizure. To provide compensation for an insufficient internal controller an external controller is designed using proportional-integral feedback control strategy. A cross-entropy optimization algorithm is applied to the chaotic oscillator network model to learn the optimal feedback gains for the external controller instead of hand-tuning the gains to provide sufficient control to the pathological brain and prevent seizure generation. The correlation between the dynamics of neural activity within different brain sites is calculated for experimental data to show similar dynamics of epileptic neural activity as simulated by the network of chaotic oscillators.

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.

Gamma oscillations precede interictal epileptiform spikes in the seizure onset zone

PubMed Central

Ren, Liankun; Kucewicz, Michal T.; Cimbalnik, Jan; Matsumoto, Joseph Y.; Brinkmann, Benjamin H.; Hu, Wei; Marsh, W. Richard; Meyer, Fredric B.; Stead, S. Matthew

2015-01-01

Objective: To investigate the generation, spectral characteristics, and potential clinical significance of brain activity preceding interictal epileptiform spike discharges (IEDs) recorded with intracranial EEG. Methods: Seventeen adult patients with drug-resistant temporal lobe epilepsy were implanted with intracranial electrodes as part of their evaluation for epilepsy surgery. IEDs detected on clinical macro- and research microelectrodes were analyzed using time-frequency spectral analysis. Results: Gamma frequency oscillations (30–100 Hz) often preceded IEDs in spatially confined brain areas. The gamma-IEDs were consistently observed 35 to 190 milliseconds before the epileptiform spike waveforms on individual macro- and microelectrodes. The gamma oscillations associated with IEDs had longer duration (p < 0.001) and slightly higher frequency (p = 0.045) when recorded on microelectrodes compared with clinical macroelectrodes. Although gamma-IEDs comprised only a subset of IEDs, they were strongly associated with electrodes in the seizure onset zone (SOZ) compared with the surrounding brain regions (p = 0.004), in sharp contrast to IEDs without preceding gamma oscillations that were often also detected outside of the SOZ. Similar to prior studies, isolated pathologic high-frequency oscillations in the gamma (30–100 Hz) and higher (100–600 Hz) frequency range, not associated with an IED, were also found to be associated with SOZ. Conclusions: The occurrence of locally generated gamma oscillations preceding IEDs suggests a mechanistic role for gamma in pathologic network activity generating IEDs. The results show a strong association between SOZ and gamma-IEDs. The potential clinical application of gamma-IEDs for mapping pathologic brain regions is intriguing, but will require future prospective studies. PMID:25589669

Finding brain oscillations with power dependencies in neuroimaging data.

PubMed

Dähne, Sven; Nikulin, Vadim V; Ramírez, David; Schreier, Peter J; Müller, Klaus-Robert; Haufe, Stefan

2014-08-01

Phase synchronization among neuronal oscillations within the same frequency band has been hypothesized to be a major mechanism for communication between different brain areas. On the other hand, cross-frequency communications are more flexible allowing interactions between oscillations with different frequencies. Among such cross-frequency interactions amplitude-to-amplitude interactions are of a special interest as they show how the strength of spatial synchronization in different neuronal populations relates to each other during a given task. While, previously, amplitude-to-amplitude correlations were studied primarily on the sensor level, we present a source separation approach using spatial filters which maximize the correlation between the envelopes of brain oscillations recorded with electro-/magnetoencephalography (EEG/MEG) or intracranial multichannel recordings. Our approach, which is called canonical source power correlation analysis (cSPoC), is thereby capable of extracting genuine brain oscillations solely based on their assumed coupling behavior even when the signal-to-noise ratio of the signals is low. In addition to using cSPoC for the analysis of cross-frequency interactions in the same subject, we show that it can also be utilized for studying amplitude dynamics of neuronal oscillations across subjects. We assess the performance of cSPoC in simulations as well as in three distinctively different analysis scenarios of real EEG data, each involving several subjects. In the simulations, cSPoC outperforms unsupervised state-of-the-art approaches. In the analysis of real EEG recordings, we demonstrate excellent unsupervised discovery of meaningful power-to-power couplings, within as well as across subjects and frequency bands. Copyright © 2014 Elsevier Inc. All rights reserved.

Neural mechanisms of mental schema: a triplet of delta, low beta/spindle and ripple oscillations.

PubMed

Ohki, Takefumi; Takei, Yuichi

2018-02-06

Schemas are higher-level knowledge structures that integrate and organise lower-level representations. As internal templates, schemas are formed according to how events are perceived, interpreted and remembered. Although these higher-level units are assumed to play a fundamental role in our daily life from an early age, the neuronal basis and mechanisms of schema formation and use remain largely unknown. It is important to elucidate how the brain constructs and maintains these higher-level units. In order to examine the possible neural underpinnings of schema, we recapitulate previous work and discuss their findings related to schemas as the brain template. We specifically focused on low beta/spindle oscillations, which are assumed to be the key components of schemas, and propose that the brain template is implemented with a triplet of neural oscillations, that is delta, low beta/spindle and ripple oscillations. © 2018 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

Python Executable Script for Estimating Two Effective Parameters to Individualize Brain-Computer Interfaces: Individual Alpha Frequency and Neurophysiological Predictor.

PubMed

Alonso-Valerdi, Luz María

2016-01-01

A brain-computer interface (BCI) aims to establish communication between the human brain and a computing system so as to enable the interaction between an individual and his environment without using the brain output pathways. Individuals control a BCI system by modulating their brain signals through mental tasks (e.g., motor imagery or mental calculation) or sensory stimulation (e.g., auditory, visual, or tactile). As users modulate their brain signals at different frequencies and at different levels, the appropriate characterization of those signals is necessary. The modulation of brain signals through mental tasks is furthermore a skill that requires training. Unfortunately, not all the users acquire such skill. A practical solution to this problem is to assess the user probability of controlling a BCI system. Another possible solution is to set the bandwidth of the brain oscillations, which is highly sensitive to the users' age, sex and anatomy. With this in mind, NeuroIndex, a Python executable script, estimates a neurophysiological prediction index and the individual alpha frequency (IAF) of the user in question. These two parameters are useful to characterize the user EEG signals, and decide how to go through the complex process of adapting the human brain and the computing system on the basis of previously proposed methods. NeuroIndeX is not only the implementation of those methods, but it also complements the methods each other and provides an alternative way to obtain the prediction parameter. However, an important limitation of this application is its dependency on the IAF value, and some results should be interpreted with caution. The script along with some electroencephalographic datasets are available on a GitHub repository in order to corroborate the functionality and usability of this application.

Python Executable Script for Estimating Two Effective Parameters to Individualize Brain-Computer Interfaces: Individual Alpha Frequency and Neurophysiological Predictor

PubMed Central

Alonso-Valerdi, Luz María

2016-01-01

A brain-computer interface (BCI) aims to establish communication between the human brain and a computing system so as to enable the interaction between an individual and his environment without using the brain output pathways. Individuals control a BCI system by modulating their brain signals through mental tasks (e.g., motor imagery or mental calculation) or sensory stimulation (e.g., auditory, visual, or tactile). As users modulate their brain signals at different frequencies and at different levels, the appropriate characterization of those signals is necessary. The modulation of brain signals through mental tasks is furthermore a skill that requires training. Unfortunately, not all the users acquire such skill. A practical solution to this problem is to assess the user probability of controlling a BCI system. Another possible solution is to set the bandwidth of the brain oscillations, which is highly sensitive to the users' age, sex and anatomy. With this in mind, NeuroIndex, a Python executable script, estimates a neurophysiological prediction index and the individual alpha frequency (IAF) of the user in question. These two parameters are useful to characterize the user EEG signals, and decide how to go through the complex process of adapting the human brain and the computing system on the basis of previously proposed methods. NeuroIndeX is not only the implementation of those methods, but it also complements the methods each other and provides an alternative way to obtain the prediction parameter. However, an important limitation of this application is its dependency on the IAF value, and some results should be interpreted with caution. The script along with some electroencephalographic datasets are available on a GitHub repository in order to corroborate the functionality and usability of this application. PMID:27445783

A transition in brain state during propofol-induced unconsciousness.

PubMed

Mukamel, Eran A; Pirondini, Elvira; Babadi, Behtash; Wong, Kin Foon Kevin; Pierce, Eric T; Harrell, P Grace; Walsh, John L; Salazar-Gomez, Andres F; Cash, Sydney S; Eskandar, Emad N; Weiner, Veronica S; Brown, Emery N; Purdon, Patrick L

2014-01-15

Rhythmic oscillations shape cortical dynamics during active behavior, sleep, and general anesthesia. Cross-frequency phase-amplitude coupling is a prominent feature of cortical oscillations, but its role in organizing conscious and unconscious brain states is poorly understood. Using high-density EEG and intracranial electrocorticography during gradual induction of propofol general anesthesia in humans, we discovered a rapid drug-induced transition between distinct states with opposite phase-amplitude coupling and different cortical source distributions. One state occurs during unconsciousness and may be similar to sleep slow oscillations. A second state occurs at the loss or recovery of consciousness and resembles an enhanced slow cortical potential. These results provide objective electrophysiological landmarks of distinct unconscious brain states, and could be used to help improve EEG-based monitoring for general anesthesia.

Sound Asleep: Processing and Retention of Slow Oscillation Phase-Targeted Stimuli

PubMed Central

Cox, Roy; Korjoukov, Ilia; de Boer, Marieke; Talamini, Lucia M.

2014-01-01

The sleeping brain retains some residual information processing capacity. Although direct evidence is scarce, a substantial literature suggests the phase of slow oscillations during deep sleep to be an important determinant for stimulus processing. Here, we introduce an algorithm for predicting slow oscillations in real-time. Using this approach to present stimuli directed at both oscillatory up and down states, we show neural stimulus processing depends importantly on the slow oscillation phase. During ensuing wakefulness, however, we did not observe differential brain or behavioral responses to these stimulus categories, suggesting no enduring memories were formed. We speculate that while simpler forms of learning may occur during sleep, neocortically based memories are not readily established during deep sleep. PMID:24999803

Sound asleep: processing and retention of slow oscillation phase-targeted stimuli.

PubMed

Cox, Roy; Korjoukov, Ilia; de Boer, Marieke; Talamini, Lucia M

2014-01-01

The sleeping brain retains some residual information processing capacity. Although direct evidence is scarce, a substantial literature suggests the phase of slow oscillations during deep sleep to be an important determinant for stimulus processing. Here, we introduce an algorithm for predicting slow oscillations in real-time. Using this approach to present stimuli directed at both oscillatory up and down states, we show neural stimulus processing depends importantly on the slow oscillation phase. During ensuing wakefulness, however, we did not observe differential brain or behavioral responses to these stimulus categories, suggesting no enduring memories were formed. We speculate that while simpler forms of learning may occur during sleep, neocortically based memories are not readily established during deep sleep.

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

Human Genomic Signatures of Brain Oscillations During Memory Encoding.

PubMed

Berto, Stefano; Wang, Guang-Zhong; Germi, James; Lega, Bradley C; Konopka, Genevieve

2018-05-01

Memory encoding is an essential step for all learning. However, the genetic and molecular mechanisms underlying human memory encoding remain poorly understood, and how this molecular framework permits the emergence of specific patterns of brain oscillations observed during mnemonic processing is unknown. Here, we directly compare intracranial electroencephalography recordings from the neocortex in individuals performing an episodic memory task with human gene expression from the same areas. We identify genes correlated with oscillatory memory effects across 6 frequency bands. These genes are enriched for autism-related genes and have preferential expression in neurons, in particular genes encoding synaptic proteins and ion channels, supporting the idea that the genes regulating voltage gradients are involved in the modulation of oscillatory patterns during successful memory encoding across brain areas. Memory-related genes are distinct from those correlated with other forms of cognitive processing and resting state fMRI. These data are the first to identify correlations between gene expression and active human brain states as well as provide a molecular window into memory encoding oscillations in the human brain.

Gamma Oscillations and Visual Binding

NASA Astrophysics Data System (ADS)

Robinson, Peter A.; Kim, Jong Won

2006-03-01

At the root of visual perception is the mechanism the brain uses to analyze features in a scene and bind related ones together. Experiments show this process is linked to oscillations of brain activity in the 30-100 Hz gamma band. Oscillations at different sites have correlation functions (CFs) that often peak at zero lag, implying simultaneous firing, even when conduction delays are large. CFs are strongest between cells stimulated by related features. Gamma oscillations are studied here by modeling mm-scale patchy interconnections in the visual cortex. Resulting predictions for gamma responses to stimuli account for numerous experimental findings, including why oscillations and zero-lag synchrony are associated, observed connections with feature preferences, the shape of the zero-lag peak, and variations of CFs with attention. Gamma waves are found to obey the Schroedinger equation, opening the possibility of cortical analogs of quantum phenomena. Gamma instabilities are tied to observations of gamma activity linked to seizures and hallucinations.

Common medial frontal mechanisms of adaptive control in humans and rodents

PubMed Central

Frank, Michael J.; Laubach, Mark

2013-01-01

In this report, we describe how common brain networks within the medial frontal cortex facilitate adaptive behavioral control in rodents and humans. We demonstrate that low frequency oscillations below 12 Hz are dramatically modulated after errors in humans over mid-frontal cortex and in rats within prelimbic and anterior cingulate regions of medial frontal cortex. These oscillations were phase-locked between medial frontal cortex and motor areas in both rats and humans. In rats, single neurons that encoded prior behavioral outcomes were phase-coherent with low-frequency field oscillations particularly after errors. Inactivating medial frontal regions in rats led to impaired behavioral adjustments after errors, eliminated the differential expression of low frequency oscillations after errors, and increased low-frequency spike-field coupling within motor cortex. Our results describe a novel mechanism for behavioral adaptation via low-frequency oscillations and elucidate how medial frontal networks synchronize brain activity to guide performance. PMID:24141310

Dynamic Interaction of Spindles and Gamma Activity during Cortical Slow Oscillations and Its Modulation by Subcortical Afferents

PubMed Central

Valencia, Miguel; Artieda, Julio; Bolam, J. Paul; Mena-Segovia, Juan

2013-01-01

Slow oscillations are a hallmark of slow wave sleep. They provide a temporal framework for a variety of phasic events to occur and interact during sleep, including the expression of high-frequency oscillations and the discharge of neurons across the entire brain. Evidence shows that the emergence of distinct high-frequency oscillations during slow oscillations facilitates the communication among brain regions whose activity was correlated during the preceding waking period. While the frequencies of oscillations involved in such interactions have been identified, their dynamics and the correlations between them require further investigation. Here we analyzed the structure and dynamics of these signals in anesthetized rats. We show that spindles and gamma oscillations coexist but have distinct temporal dynamics across the slow oscillation cycle. Furthermore, we observed that spindles and gamma are functionally coupled to the slow oscillations and between each other. Following the activation of ascending pathways from the brainstem by means of a carbachol injection in the pedunculopontine nucleus, we were able to modify the gain in the gamma oscillations that are independent of the spindles while the spindle amplitude was reduced. Furthermore, carbachol produced a decoupling of the gamma oscillations that are dependent on the spindles but with no effect on their amplitude. None of the changes in the high-frequency oscillations affected the onset or shape of the slow oscillations, suggesting that slow oscillations occur independently of the phasic events that coexist with them. Our results provide novel insights into the regulation, dynamics and homeostasis of cortical slow oscillations. PMID:23844020

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

PubMed Central

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

2010-01-01

The transition from wakefulness to sleep is marked by pronounced changes in brain activity. The brain rhythms that characterize the two main types of mammalian sleep, slow-wave sleep (SWS) and rapid eye movement (REM) sleep, are thought to be involved in the functions of sleep. In particular, recent theories suggest that the synchronous slow-oscillation of neocortical neuronal membrane potentials, the defining feature of SWS, is involved in processing information acquired during wakefulness. According to the Standard Model of memory consolidation, during wakefulness the hippocampus receives input from neocortical regions involved in the initial encoding of an experience and binds this information into a coherent memory trace that is then transferred to the neocortex during SWS where it is stored and integrated within preexisting memory traces. Evidence suggests that this process selectively involves direct connections from the hippocampus to the prefrontal cortex (PFC), a multimodal, high-order association region implicated in coordinating the storage and recall of remote memories in the neocortex. The slow-oscillation is thought to orchestrate the transfer of information from the hippocampus by temporally coupling hippocampal sharp-wave/ripples (SWRs) and thalamocortical spindles. SWRs are synchronous bursts of hippocampal activity, during which waking neuronal firing patterns are reactivated in the hippocampus and neocortex in a coordinated manner. Thalamocortical spindles are brief 7–14 Hz oscillations that may facilitate the encoding of information reactivated during SWRs. By temporally coupling the readout of information from the hippocampus with conditions conducive to encoding in the neocortex, the slow-oscillation is thought to mediate the transfer of information from the hippocampus to the neocortex. Although several lines of evidence are consistent with this function for mammalian SWS, it is unclear whether SWS serves a similar function in birds, the only taxonomic group other than mammals to exhibit SWS and REM sleep. Based on our review of research on avian sleep, neuroanatomy, and memory, although involved in some forms of memory consolidation, avian sleep does not appear to be involved in transferring hippocampal memories to other brain regions. Despite exhibiting the slow-oscillation, SWRs and spindles have not been found in birds. Moreover, although birds independently evolved a brain region – the caudolateral nidopallium (NCL) – involved in performing high-order cognitive functions similar to those performed by the PFC, direct connections between the NCL and hippocampus have not been found in birds, and evidence for the transfer of information from the hippocampus to the NCL or other extra-hippocampal regions is lacking. Although based on the absence of evidence for various traits, collectively, these findings suggest that unlike mammalian SWS, avian SWS may not be involved in transferring memories from the hippocampus. Furthermore, it suggests that the slow-oscillation, the defining feature of mammalian and avian SWS, may serve a more general function independent of that related to coordinating the transfer of information from the hippocampus to the PFC in mammals. Given that SWS is homeostatically regulated (a process intimately related to the slow-oscillation) in mammals and birds, functional hypotheses linked to this process may apply to both taxonomic groups. PMID:21070585

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

PubMed

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

2011-08-01

The transition from wakefulness to sleep is marked by pronounced changes in brain activity. The brain rhythms that characterize the two main types of mammalian sleep, slow-wave sleep (SWS) and rapid eye movement (REM) sleep, are thought to be involved in the functions of sleep. In particular, recent theories suggest that the synchronous slow-oscillation of neocortical neuronal membrane potentials, the defining feature of SWS, is involved in processing information acquired during wakefulness. According to the Standard Model of memory consolidation, during wakefulness the hippocampus receives input from neocortical regions involved in the initial encoding of an experience and binds this information into a coherent memory trace that is then transferred to the neocortex during SWS where it is stored and integrated within preexisting memory traces. Evidence suggests that this process selectively involves direct connections from the hippocampus to the prefrontal cortex (PFC), a multimodal, high-order association region implicated in coordinating the storage and recall of remote memories in the neocortex. The slow-oscillation is thought to orchestrate the transfer of information from the hippocampus by temporally coupling hippocampal sharp-wave/ripples (SWRs) and thalamocortical spindles. SWRs are synchronous bursts of hippocampal activity, during which waking neuronal firing patterns are reactivated in the hippocampus and neocortex in a coordinated manner. Thalamocortical spindles are brief 7-14 Hz oscillations that may facilitate the encoding of information reactivated during SWRs. By temporally coupling the readout of information from the hippocampus with conditions conducive to encoding in the neocortex, the slow-oscillation is thought to mediate the transfer of information from the hippocampus to the neocortex. Although several lines of evidence are consistent with this function for mammalian SWS, it is unclear whether SWS serves a similar function in birds, the only taxonomic group other than mammals to exhibit SWS and REM sleep. Based on our review of research on avian sleep, neuroanatomy, and memory, although involved in some forms of memory consolidation, avian sleep does not appear to be involved in transferring hippocampal memories to other brain regions. Despite exhibiting the slow-oscillation, SWRs and spindles have not been found in birds. Moreover, although birds independently evolved a brain region--the caudolateral nidopallium (NCL)--involved in performing high-order cognitive functions similar to those performed by the PFC, direct connections between the NCL and hippocampus have not been found in birds, and evidence for the transfer of information from the hippocampus to the NCL or other extra-hippocampal regions is lacking. Although based on the absence of evidence for various traits, collectively, these findings suggest that unlike mammalian SWS, avian SWS may not be involved in transferring memories from the hippocampus. Furthermore, it suggests that the slow-oscillation, the defining feature of mammalian and avian SWS, may serve a more general function independent of that related to coordinating the transfer of information from the hippocampus to the PFC in mammals. Given that SWS is homeostatically regulated (a process intimately related to the slow-oscillation) in mammals and birds, functional hypotheses linked to this process may apply to both taxonomic groups. © 2010 The Authors. Biological Reviews © 2010 Cambridge Philosophical Society.

Guiding transcranial brain stimulation by EEG/MEG to interact with ongoing brain activity and associated functions: A position paper

PubMed Central

Thut, Gregor; Bergmann, Til Ole; Fröhlich, Flavio; Soekadar, Surjo R.; Brittain, John-Stuart; Valero-Cabré, Antoni; Sack, Alexander; Miniussi, Carlo; Antal, Andrea; Siebner, Hartwig Roman; Ziemann, Ulf; Herrmann, Christoph S.

2017-01-01

Non-invasive transcranial brain stimulation (NTBS) techniques have a wide range of applications but also suffer from a number of limitations mainly related to poor specificity of intervention and variable effect size. These limitations motivated recent efforts to focus on the temporal dimension of NTBS with respect to the ongoing brain activity. Temporal patterns of ongoing neuronal activity, in particular brain oscillations and their fluctuations, can be traced with electro- or magnetoencephalography (EEG/MEG), to guide the timing as well as the stimulation settings of NTBS. These novel, online and offline EEG/MEG-guided NTBS-approaches are tailored to specifically interact with the underlying brain activity. Online EEG/MEG has been used to guide the timing of NTBS (i.e., when to stimulate): by taking into account instantaneous phase or power of oscillatory brain activity, NTBS can be aligned to fluctuations in excitability states. Moreover, offline EEG/MEG recordings prior to interventions can inform researchers and clinicians how to stimulate: by frequency-tuning NTBS to the oscillation of interest, intrinsic brain oscillations can be up- or down-regulated. In this paper, we provide an overview of existing approaches and ideas of EEG/MEG-guided interventions, and their promises and caveats. We point out potential future lines of research to address challenges. PMID:28233641

Volitional enhancement of firing synchrony and oscillation by neuronal operant conditioning: interaction with neurorehabilitation and brain-machine interface

PubMed Central

Sakurai, Yoshio; Song, Kichan; Tachibana, Shota; Takahashi, Susumu

2014-01-01

In this review, we focus on neuronal operant conditioning in which increments in neuronal activities are directly rewarded without behaviors. We discuss the potential of this approach to elucidate neuronal plasticity for enhancing specific brain functions and its interaction with the progress in neurorehabilitation and brain-machine interfaces. The key to-be-conditioned activities that this paper emphasizes are synchronous and oscillatory firings of multiple neurons that reflect activities of cell assemblies. First, we introduce certain well-known studies on neuronal operant conditioning in which conditioned enhancements of neuronal firing were reported in animals and humans. These studies demonstrated the feasibility of volitional control over neuronal activity. Second, we refer to the recent studies on operant conditioning of synchrony and oscillation of neuronal activities. In particular, we introduce a recent study showing volitional enhancement of oscillatory activity in monkey motor cortex and our study showing selective enhancement of firing synchrony of neighboring neurons in rat hippocampus. Third, we discuss the reasons for emphasizing firing synchrony and oscillation in neuronal operant conditioning, the main reason being that they reflect the activities of cell assemblies, which have been suggested to be basic neuronal codes representing information in the brain. Finally, we discuss the interaction of neuronal operant conditioning with neurorehabilitation and brain-machine interface (BMI). We argue that synchrony and oscillation of neuronal firing are the key activities required for developing both reliable neurorehabilitation and high-performance BMI. Further, we conclude that research of neuronal operant conditioning, neurorehabilitation, BMI, and system neuroscience will produce findings applicable to these interrelated fields, and neuronal synchrony and oscillation can be a common important bridge among all of them. PMID:24567704

Volitional enhancement of firing synchrony and oscillation by neuronal operant conditioning: interaction with neurorehabilitation and brain-machine interface.

PubMed

Sakurai, Yoshio; Song, Kichan; Tachibana, Shota; Takahashi, Susumu

2014-01-01

In this review, we focus on neuronal operant conditioning in which increments in neuronal activities are directly rewarded without behaviors. We discuss the potential of this approach to elucidate neuronal plasticity for enhancing specific brain functions and its interaction with the progress in neurorehabilitation and brain-machine interfaces. The key to-be-conditioned activities that this paper emphasizes are synchronous and oscillatory firings of multiple neurons that reflect activities of cell assemblies. First, we introduce certain well-known studies on neuronal operant conditioning in which conditioned enhancements of neuronal firing were reported in animals and humans. These studies demonstrated the feasibility of volitional control over neuronal activity. Second, we refer to the recent studies on operant conditioning of synchrony and oscillation of neuronal activities. In particular, we introduce a recent study showing volitional enhancement of oscillatory activity in monkey motor cortex and our study showing selective enhancement of firing synchrony of neighboring neurons in rat hippocampus. Third, we discuss the reasons for emphasizing firing synchrony and oscillation in neuronal operant conditioning, the main reason being that they reflect the activities of cell assemblies, which have been suggested to be basic neuronal codes representing information in the brain. Finally, we discuss the interaction of neuronal operant conditioning with neurorehabilitation and brain-machine interface (BMI). We argue that synchrony and oscillation of neuronal firing are the key activities required for developing both reliable neurorehabilitation and high-performance BMI. Further, we conclude that research of neuronal operant conditioning, neurorehabilitation, BMI, and system neuroscience will produce findings applicable to these interrelated fields, and neuronal synchrony and oscillation can be a common important bridge among all of them.

Carbachol-induced network oscillations in an in vitro limbic system brain slice.

PubMed

Lévesque, Maxime; Cataldi, Mauro; Chen, Li-Yuan; Hamidi, Shabnam; Avoli, Massimo

2017-04-21

We employed simultaneous field potential recordings from CA3, subiculum and entorhinal cortex in an in vitro brain slice preparation to understand the involvement of these limbic areas in the generation of the field potential oscillations that are induced by bath application of the muscarinic receptor agonist carbachol. Regularly spaced oscillations that mainly presented at theta frequency range (5-12Hz) occurred synchronously in all three structures in the presence of carbachol. These oscillations, which disappeared when slices were perfused with pirenzepine or with glutamatergic receptor antagonists, were categorized as short (<4s) and long (>4s) with short events oscillating at higher frequencies than long events. Field oscillations were highly synchronized between regions and latency analysis revealed that they often initiated in the entorhinal cortex later than in the other two structures. Blocking GABA A receptors modified the activity patterns of both short and long oscillations and decreased their coherence in the theta frequency range. Finally, blocking KCC2 activity disclosed a pattern of recurrent short oscillations. Our results suggest that in the presence of carbachol both subiculum and CA3 most often drive theta generators in the entorhinal cortex and that these oscillations are influenced but not abolished by altering GABA A receptor signaling. Copyright © 2017 IBRO. Published by Elsevier Ltd. All rights reserved.

The θ-γ neural code.

PubMed

Lisman, John E; Jensen, Ole

2013-03-20

Theta and gamma frequency oscillations occur in the same brain regions and interact with each other, a process called cross-frequency coupling. Here, we review evidence for the following hypothesis: that the dual oscillations form a code for representing multiple items in an ordered way. This form of coding has been most clearly demonstrated in the hippocampus, where different spatial information is represented in different gamma subcycles of a theta cycle. Other experiments have tested the functional importance of oscillations and their coupling. These involve correlation of oscillatory properties with memory states, correlation with memory performance, and effects of disrupting oscillations on memory. Recent work suggests that this coding scheme coordinates communication between brain regions and is involved in sensory as well as memory processes. Copyright © 2013 Elsevier Inc. All rights reserved.

Interpersonal synchrony enhanced through 20 Hz phase-coupled dual brain stimulation

PubMed Central

Knoblich, Günther; Dunne, Laura; Keller, Peter E.

2017-01-01

Abstract Synchronous movement is a key component of social behavior in several species including humans. Recent theories have suggested a link between interpersonal synchrony of brain oscillations and interpersonal movement synchrony. The present study investigated this link. Using transcranial alternating current stimulation (tACS) applied over the left motor cortex, we induced beta band (20 Hz) oscillations in pairs of individuals who both performed a finger-tapping task with the right hand. In-phase or anti-phase oscillations were delivered during a preparatory period prior to movement and while the tapping task was performed. In-phase 20 Hz stimulation enhanced interpersonal movement synchrony, compared with anti-phase or sham stimulation, particularly for the initial taps following the preparatory period. This was confirmed in an analysis comparing real vs pseudo pair surrogate data. No enhancement was observed for stimulation frequencies of 2 Hz (matching the target movement frequency) or 10 Hz (alpha band). Thus, phase-coupling of beta band neural oscillations across two individuals’ (resting) motor cortices supports the interpersonal alignment of sensorimotor processes that regulate rhythmic action initiation, thereby facilitating the establishment of synchronous movement. Phase-locked dual brain stimulation provides a promising method to study causal effects of interpersonal brain synchrony on social, sensorimotor and cognitive processes. PMID:28119510

Interpersonal synchrony enhanced through 20 Hz phase-coupled dual brain stimulation.

PubMed

Novembre, Giacomo; Knoblich, Günther; Dunne, Laura; Keller, Peter E

2017-01-24

Synchronous movement is a key component of social behaviour in several species including humans. Recent theories have suggested a link between interpersonal synchrony of brain oscillations and interpersonal movement synchrony. The present study investigated this link. Using transcranial alternating current stimulation (tACS) applied over the left motor cortex, we induced beta band (20 Hz) oscillations in pairs of individuals who both performed a finger-tapping task with the right hand. In-phase or anti-phase oscillations were delivered during a preparatory period prior to movement and while the tapping task was performed. In-phase 20 Hz stimulation enhanced interpersonal movement synchrony, compared to anti-phase or sham stimulation, particularly for the initial taps following the preparatory period. This was confirmed in an analysis comparing real vs. pseudo pair surrogate data. No enhancement was observed for stimulation frequencies of 2 Hz (matching the target movement frequency) or 10 Hz (alpha band). Thus, phase-coupling of beta band neural oscillations across two individuals' (resting) motor cortices supports the interpersonal alignment of sensorimotor processes that regulate rhythmic action initiation, thereby facilitating the establishment of synchronous movement. Phase-locked dual brain stimulation provides a promising method to study causal effects of interpersonal brain synchrony on social, sensorimotor and cognitive processes. © The Author (2017). Published by Oxford University Press.

Decrease in early right alpha band phase synchronization and late gamma band oscillations in processing syntax in music.

PubMed

Ruiz, María Herrojo; Koelsch, Stefan; Bhattacharya, Joydeep

2009-04-01

The present study investigated the neural correlates associated with the processing of music-syntactical irregularities as compared with regular syntactic structures in music. Previous studies reported an early ( approximately 200 ms) right anterior negative component (ERAN) by traditional event-related-potential analysis during music-syntactical irregularities, yet little is known about the underlying oscillatory and synchronization properties of brain responses which are supposed to play a crucial role in general cognition including music perception. First we showed that the ERAN was primarily represented by low frequency (<8 Hz) brain oscillations. Further, we found that music-syntactical irregularities as compared with music-syntactical regularities, were associated with (i) an early decrease in the alpha band (9-10 Hz) phase synchronization between right fronto-central and left temporal brain regions, and (ii) a late ( approximately 500 ms) decrease in gamma band (38-50 Hz) oscillations over fronto-central brain regions. These results indicate a weaker degree of long-range integration when the musical expectancy is violated. In summary, our results reveal neural mechanisms of music-syntactic processing that operate at different levels of cortical integration, ranging from early decrease in long-range alpha phase synchronization to late local gamma oscillations. 2008 Wiley-Liss, Inc.

The effect of aging on EEG brain oscillations related to sensory and sensorimotor functions.

PubMed

Dushanova, Juliana; Christov, Mario

2014-03-01

The question of the present study is whether the brain as a system with gradually decreasing resources maximizes its performance by reorganizing neural networks for greater efficiency. Auditory event-related low frequency oscillations (delta δ - [2, 4]Hz; theta θ - [4.5, 7]Hz; alpha α - [7.5, 12]Hz) were examined during an auditory discrimination motor task (low-frequency tone - right hand movement, high-frequency tone - left hand movement) between two groups with mean age 26.3 and 55 years. The amplitudes of the phase-locked δ, θ and α activity were more pronounced with a progressive increase in age during the sensory processing, independent of tone type. The difference between the groups with respect to scalp distribution was tone-independent for delta/theta oscillations, but not for the alpha activity. Age-related and tone-dependent changes in α band activity were focused at frontal and sensorimotor areas. Neither functional brain specificity was observed for the amplitudes of the low-frequency (δ, θ, α) oscillations during the cognitive processing, which diminished with increasing age. The cognitive brain oscillatory specificity diminished with increasing age. Copyright © 2014 Medical University of Bialystok. Published by Elsevier Urban & Partner Sp. z o.o. All rights reserved.

Populations of striatal medium spiny neurons encode vibrotactile frequency in rats: modulation by slow wave oscillations

PubMed Central

Hawking, Thomas G.

2013-01-01

Dorsolateral striatum (DLS) is implicated in tactile perception and receives strong projections from somatosensory cortex. However, the sensory representations encoded by striatal projection neurons are not well understood. Here we characterized the contribution of DLS to the encoding of vibrotactile information in rats by assessing striatal responses to precise frequency stimuli delivered to a single vibrissa. We applied stimuli in a frequency range (45–90 Hz) that evokes discriminable percepts and carries most of the power of vibrissa vibration elicited by a range of complex fine textures. Both medium spiny neurons and evoked potentials showed tactile responses that were modulated by slow wave oscillations. Furthermore, medium spiny neuron population responses represented stimulus frequency on par with previously reported behavioral benchmarks. Our results suggest that striatum encodes frequency information of vibrotactile stimuli which is dynamically modulated by ongoing brain state. PMID:23114217

Abnormal salience signaling in schizophrenia: The role of integrative beta oscillations.

PubMed

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

2016-04-01

Aberrant salience attribution and cerebral dysconnectivity both have strong evidential support as core dysfunctions in schizophrenia. Aberrant salience arising from an excess of dopamine activity has been implicated in delusions and hallucinations, exaggerating the significance of everyday occurrences and thus leading to perceptual distortions and delusional causal inferences. Meanwhile, abnormalities in key nodes of a salience brain network have been implicated in other characteristic symptoms, including the disorganization and impoverishment of mental activity. A substantial body of literature reports disruption to brain network connectivity in schizophrenia. Electrical oscillations likely play a key role in the coordination of brain activity at spatially remote sites, and evidence implicates beta band oscillations in long-range integrative processes. We used magnetoencephalography and a task designed to disambiguate responses to relevant from irrelevant stimuli to investigate beta oscillations in nodes of a network implicated in salience detection and previously shown to be structurally and functionally abnormal in schizophrenia. Healthy participants, as expected, produced an enhanced beta synchronization to behaviorally relevant, as compared to irrelevant, stimuli, while patients with schizophrenia showed the reverse pattern: a greater beta synchronization in response to irrelevant than to relevant stimuli. These findings not only support both the aberrant salience and disconnectivity hypotheses, but indicate a common mechanism that allows us to integrate them into a single framework for understanding schizophrenia in terms of disrupted recruitment of contextually appropriate brain networks. © 2016 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

Abnormal salience signaling in schizophrenia: The role of integrative beta oscillations

PubMed Central

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

2016-01-01

Abstract Aberrant salience attribution and cerebral dysconnectivity both have strong evidential support as core dysfunctions in schizophrenia. Aberrant salience arising from an excess of dopamine activity has been implicated in delusions and hallucinations, exaggerating the significance of everyday occurrences and thus leading to perceptual distortions and delusional causal inferences. Meanwhile, abnormalities in key nodes of a salience brain network have been implicated in other characteristic symptoms, including the disorganization and impoverishment of mental activity. A substantial body of literature reports disruption to brain network connectivity in schizophrenia. Electrical oscillations likely play a key role in the coordination of brain activity at spatially remote sites, and evidence implicates beta band oscillations in long‐range integrative processes. We used magnetoencephalography and a task designed to disambiguate responses to relevant from irrelevant stimuli to investigate beta oscillations in nodes of a network implicated in salience detection and previously shown to be structurally and functionally abnormal in schizophrenia. Healthy participants, as expected, produced an enhanced beta synchronization to behaviorally relevant, as compared to irrelevant, stimuli, while patients with schizophrenia showed the reverse pattern: a greater beta synchronization in response to irrelevant than to relevant stimuli. These findings not only support both the aberrant salience and disconnectivity hypotheses, but indicate a common mechanism that allows us to integrate them into a single framework for understanding schizophrenia in terms of disrupted recruitment of contextually appropriate brain networks. Hum Brain Mapp 37:1361‐1374, 2016. © 2016 Wiley Periodicals, Inc. PMID:26853904

Baseline Brain Activity Predicts Response to Neuromodulatory Pain Treatment

PubMed Central

Jensen, Mark P.; Sherlin, Leslie H.; Fregni, Felipe; Gianas, Ann; Howe, Jon D.; Hakimian, Shahin

2015-01-01

Objectives The objective of this study was to examine the associations between baseline electroencephalogram (EEG)-assessed brain oscillations and subsequent response to four neuromodulatory treatments. Based on available research, we hypothesized that baseline theta oscillations would prospectively predict response to hypnotic analgesia. Analyses involving other oscillations and the other treatments (meditation, neurofeedback, and both active and sham transcranial direct current stimulation) were viewed as exploratory, given the lack of previous research examining brain oscillations as predictors of response to these other treatments. Design Randomized controlled study of single sessions of four neuromodulatory pain treatments and a control procedure. Methods Thirty individuals with spinal cord injury and chronic pain had their EEG recorded before each session of four active treatments (hypnosis, meditation, EEG biofeedback, transcranial direct current stimulation) and a control procedure (sham transcranial direct stimulation). Results As hypothesized, more presession theta power was associated with greater response to hypnotic analgesia. In exploratory analyses, we found that less baseline alpha power predicted pain reduction with meditation. Conclusions The findings support the idea that different patients respond to different pain treatments and that between-person treatment response differences are related to brain states as measured by EEG. The results have implications for the possibility of enhancing pain treatment response by either 1) better patient/treatment matching or 2) influencing brain activity before treatment is initiated in order to prepare patients to respond. Research is needed to replicate and confirm the findings in additional samples of individuals with chronic pain. PMID:25287554

Brain Oscillations in Sport: Toward EEG Biomarkers of Performance.

PubMed

Cheron, Guy; Petit, Géraldine; Cheron, Julian; Leroy, Axelle; Cebolla, Anita; Cevallos, Carlos; Petieau, Mathieu; Hoellinger, Thomas; Zarka, David; Clarinval, Anne-Marie; Dan, Bernard

2016-01-01

Brain dynamics is at the basis of top performance accomplishment in sports. The search for neural biomarkers of performance remains a challenge in movement science and sport psychology. The non-invasive nature of high-density electroencephalography (EEG) recording has made it a most promising avenue for providing quantitative feedback to practitioners and coaches. Here, we review the current relevance of the main types of EEG oscillations in order to trace a perspective for future practical applications of EEG and event-related potentials (ERP) in sport. In this context, the hypotheses of unified brain rhythms and continuity between wake and sleep states should provide a functional template for EEG biomarkers in sport. The oscillations in the thalamo-cortical and hippocampal circuitry including the physiology of the place cells and the grid cells provide a frame of reference for the analysis of delta, theta, beta, alpha (incl.mu), and gamma oscillations recorded in the space field of human performance. Based on recent neuronal models facilitating the distinction between the different dynamic regimes (selective gating and binding) in these different oscillations we suggest an integrated approach articulating together the classical biomechanical factors (3D movements and EMG) and the high-density EEG and ERP signals to allow finer mathematical analysis to optimize sport performance, such as microstates, coherency/directionality analysis and neural generators.

Brain Oscillations in Sport: Toward EEG Biomarkers of Performance

PubMed Central

Cheron, Guy; Petit, Géraldine; Cheron, Julian; Leroy, Axelle; Cebolla, Anita; Cevallos, Carlos; Petieau, Mathieu; Hoellinger, Thomas; Zarka, David; Clarinval, Anne-Marie; Dan, Bernard

2016-01-01

Brain dynamics is at the basis of top performance accomplishment in sports. The search for neural biomarkers of performance remains a challenge in movement science and sport psychology. The non-invasive nature of high-density electroencephalography (EEG) recording has made it a most promising avenue for providing quantitative feedback to practitioners and coaches. Here, we review the current relevance of the main types of EEG oscillations in order to trace a perspective for future practical applications of EEG and event-related potentials (ERP) in sport. In this context, the hypotheses of unified brain rhythms and continuity between wake and sleep states should provide a functional template for EEG biomarkers in sport. The oscillations in the thalamo-cortical and hippocampal circuitry including the physiology of the place cells and the grid cells provide a frame of reference for the analysis of delta, theta, beta, alpha (incl.mu), and gamma oscillations recorded in the space field of human performance. Based on recent neuronal models facilitating the distinction between the different dynamic regimes (selective gating and binding) in these different oscillations we suggest an integrated approach articulating together the classical biomechanical factors (3D movements and EMG) and the high-density EEG and ERP signals to allow finer mathematical analysis to optimize sport performance, such as microstates, coherency/directionality analysis and neural generators. PMID:26955362

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.

Annotation: Tourette Syndrome--A Relentless Drumbeat--Driven by Misguided Brain Oscillations

ERIC Educational Resources Information Center

Leckman, James F.; Vaccarino, Flora M.; Kalanithi, Paul S. A.; Rothenberger, Aribert

2006-01-01

Objective: This annotation reviews recent evidence that points to the likely role of aberrant neural oscillations in the pathogenesis of Tourette syndrome (TS). Methods: The available anatomic and electrophysiological findings in TS are reviewed in the context of an emerging picture of the crucial role that neural oscillations play in maintaining…

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.

Measuring small compartment dimensions by probing diffusion dynamics via Non-uniform Oscillating-Gradient Spin-Echo (NOGSE) NMR.

PubMed

Shemesh, Noam; Alvarez, Gonzalo A; Frydman, Lucio

2013-12-01

Noninvasive measurements of microstructure in materials, cells, and in biological tissues, constitute a unique capability of gradient-assisted NMR. Diffusion-diffraction MR approaches pioneered by Callaghan demonstrated this ability; Oscillating-Gradient Spin-Echo (OGSE) methodologies tackle the demanding gradient amplitudes required for observing diffraction patterns by utilizing constant-frequency oscillating gradient pairs that probe the diffusion spectrum, D(ω). Here we present a new class of diffusion MR experiments, termed Non-uniform Oscillating-Gradient Spin-Echo (NOGSE), which dynamically probe multiple frequencies of the diffusion spectral density at once, thus affording direct microstructural information on the compartment's dimension. The NOGSE methodology applies N constant-amplitude gradient oscillations; N-1 of these oscillations are spaced by a characteristic time x, followed by a single gradient oscillation characterized by a time y, such that the diffusion dynamics is probed while keeping (N-1)x+y≡TNOGSE constant. These constant-time, fixed-gradient-amplitude, multi-frequency attributes render NOGSE particularly useful for probing small compartment dimensions with relatively weak gradients - alleviating difficulties associated with probing D(ω) frequency-by-frequency or with varying relaxation weightings, as in other diffusion-monitoring experiments. Analytical descriptions of the NOGSE signal are given, and the sequence's ability to extract small compartment sizes with a sensitivity towards length to the sixth power, is demonstrated using a microstructural phantom. Excellent agreement between theory and experiments was evidenced even upon applying weak gradient amplitudes. An MR imaging version of NOGSE was also implemented in ex vivo pig spinal cords and mouse brains, affording maps based on compartment sizes. The effects of size distributions on NOGSE are also briefly analyzed. Copyright © 2013 Elsevier Inc. All rights reserved.

Transcranial Electrical Currents to Probe EEG Brain Rhythms and Memory Consolidation during Sleep in Humans

PubMed Central

Marshall, Lisa; Kirov, Roumen; Brade, Julian; Mölle, Matthias; Born, Jan

2011-01-01

Previously the application of a weak electric anodal current oscillating with a frequency of the sleep slow oscillation (∼0.75 Hz) during non-rapid eye movement sleep (NonREM) sleep boosted endogenous slow oscillation activity and enhanced sleep-associated memory consolidation. The slow oscillations occurring during NonREM sleep and theta oscillations present during REM sleep have been considered of critical relevance for memory formation. Here transcranial direct current stimulation (tDCS) oscillating at 5 Hz, i.e., within the theta frequency range (theta-tDCS) is applied during NonREM and REM sleep. Theta-tDCS during NonREM sleep produced a global decrease in slow oscillatory activity conjoint with a local reduction of frontal slow EEG spindle power (8–12 Hz) and a decrement in consolidation of declarative memory, underlining the relevance of these cortical oscillations for sleep-dependent memory consolidation. In contrast, during REM sleep theta-tDCS appears to increase global gamma (25–45 Hz) activity, indicating a clear brain state-dependency of theta-tDCS. More generally, results demonstrate the suitability of oscillating-tDCS as a tool to analyze functions of endogenous EEG rhythms and underlying endogenous electric fields as well as the interactions between EEG rhythms of different frequencies. PMID:21340034

Noninvasive Assessment of Attention State from Correlated Oscillations in Brain and Muscle

DTIC Science & Technology

2010-11-29

rhythms depend in part on activity in the thalamus. EMG is a composite of muscle fiber action potentials occurring in the muscle . The action...the subjects were asked to perform the isometric MVCs with the first dorsal interosseus muscle of the right hand. The MVC was determined using a...REPORT Noninvasive assessment of attention state from correlated oscillations in brain and muscle 14. ABSTRACT 16. SECURITY CLASSIFICATION OF: In motor

Regional Slow Waves and Spindles in Human Sleep

PubMed Central

Nir, Yuval; Staba, Richard J.; Andrillon, Thomas; Vyazovskiy, Vladyslav V.; Cirelli, Chiara; Fried, Itzhak; Tononi, Giulio

2011-01-01

SUMMARY The most prominent EEG events in sleep are slow waves, reflecting a slow (<1 Hz) oscillation between up and down states in cortical neurons. It is unknown whether slow oscillations are synchronous across the majority or the minority of brain regions—are they a global or local phenomenon? To examine this, we recorded simultaneously scalp EEG, intracerebral EEG, and unit firing in multiple brain regions of neurosurgical patients. We find that most sleep slow waves and the underlying active and inactive neuronal states occur locally. Thus, especially in late sleep, some regions can be active while others are silent. We also find that slow waves can propagate, usually from medial prefrontal cortex to the medial temporal lobe and hippocampus. Sleep spindles, the other hallmark of NREM sleep EEG, are likewise predominantly local. Thus, intracerebral communication during sleep is constrained because slow and spindle oscillations often occur out-of-phase in different brain regions. PMID:21482364

The Involvement of Endogenous Neural Oscillations in the Processing of Rhythmic Input: More Than a Regular Repetition of Evoked Neural Responses

PubMed Central

Zoefel, Benedikt; ten Oever, Sanne; Sack, Alexander T.

2018-01-01

It is undisputed that presenting a rhythmic stimulus leads to a measurable brain response that follows the rhythmic structure of this stimulus. What is still debated, however, is the question whether this brain response exclusively reflects a regular repetition of evoked responses, or whether it also includes entrained oscillatory activity. Here we systematically present evidence in favor of an involvement of entrained neural oscillations in the processing of rhythmic input while critically pointing out which questions still need to be addressed before this evidence could be considered conclusive. In this context, we also explicitly discuss the potential functional role of such entrained oscillations, suggesting that these stimulus-aligned oscillations reflect, and serve as, predictive processes, an idea often only implicitly assumed in the literature. PMID:29563860

The dynamics of human cognition: Increasing global integration coupled with decreasing segregation found using iEEG.

PubMed

Cruzat, Josephine; Deco, Gustavo; Tauste-Campo, Adrià; Principe, Alessandro; Costa, Albert; Kringelbach, Morten L; Rocamora, Rodrigo

2018-05-15

Cognitive processing requires the ability to flexibly integrate and process information across large brain networks. How do brain networks dynamically reorganize to allow broad communication between many different brain regions in order to integrate information? We record neural activity from 12 epileptic patients using intracranial EEG while performing three cognitive tasks. We assess how the functional connectivity between different brain areas changes to facilitate communication across them. At the topological level, this facilitation is characterized by measures of integration and segregation. Across all patients, we found significant increases in integration and decreases in segregation during cognitive processing, especially in the gamma band (50-90 Hz). We also found higher levels of global synchronization and functional connectivity during task execution, again particularly in the gamma band. More importantly, functional connectivity modulations were not caused by changes in the level of the underlying oscillations. Instead, these modulations were caused by a rearrangement of the mutual synchronization between the different nodes as proposed by the "Communication Through Coherence" Theory. Copyright © 2018 Elsevier Inc. All rights reserved.

Cholinergic enhancement of visual attention and neural oscillations in the human brain.

PubMed

Bauer, Markus; Kluge, Christian; Bach, Dominik; Bradbury, David; Heinze, Hans Jochen; Dolan, Raymond J; Driver, Jon

2012-03-06

Cognitive processes such as visual perception and selective attention induce specific patterns of brain oscillations. The neurochemical bases of these spectral changes in neural activity are largely unknown, but neuromodulators are thought to regulate processing. The cholinergic system is linked to attentional function in vivo, whereas separate in vitro studies show that cholinergic agonists induce high-frequency oscillations in slice preparations. This has led to theoretical proposals that cholinergic enhancement of visual attention might operate via gamma oscillations in visual cortex, although low-frequency alpha/beta modulation may also play a key role. Here we used MEG to record cortical oscillations in the context of administration of a cholinergic agonist (physostigmine) during a spatial visual attention task in humans. This cholinergic agonist enhanced spatial attention effects on low-frequency alpha/beta oscillations in visual cortex, an effect correlating with a drug-induced speeding of performance. By contrast, the cholinergic agonist did not alter high-frequency gamma oscillations in visual cortex. Thus, our findings show that cholinergic neuromodulation enhances attentional selection via an impact on oscillatory synchrony in visual cortex, for low rather than high frequencies. We discuss this dissociation between high- and low-frequency oscillations in relation to proposals that lower-frequency oscillations are generated by feedback pathways within visual cortex. Copyright © 2012 Elsevier Ltd. All rights reserved.

Differing Patterns of Altered Slow-5 Oscillations in Healthy Aging and Ischemic Stroke.

PubMed

La, Christian; Mossahebi, Pouria; Nair, Veena A; Young, Brittany M; Stamm, Julie; Birn, Rasmus; Meyerand, Mary E; Prabhakaran, Vivek

2016-01-01

The 'default-mode' network (DMN) has been investigated in the presence of various disorders, such as Alzheimer's disease and Autism spectrum disorders. More recently, this investigation has expanded to include patients with ischemic injury. Here, we characterized the effects of ischemic injury in terms of its spectral distribution of resting-state low-frequency oscillations and further investigated whether those specific disruptions were unique to the DMN, or rather more general, affecting the global cortical system. With 43 young healthy adults, 42 older healthy adults, 14 stroke patients in their early stage (<7 days after stroke onset), and 16 stroke patients in their later stage (between 1 to 6 months after stroke onset), this study showed that patterns of cortical system disruption may differ between healthy aging and following the event of an ischemic stroke. The stroke group in the later stage demonstrated a global reduction in the amplitude of the slow-5 oscillations (0.01-0.027 Hz) in the DMN as well as in the primary visual and sensorimotor networks, two 'task-positive' networks. In comparison to the young healthy group, the older healthy subjects presented a decrease in the amplitude of the slow-5 oscillations specific to the components of the DMN, while exhibiting an increase in oscillation power in the task-positive networks. These two processes of a decrease DMN and an increase in 'task-positive' slow-5 oscillations may potentially be related, with a deficit in DMN inhibition, leading to an elevation of oscillations in non-DMN systems. These findings also suggest that disruptions of the slow-5 oscillations in healthy aging may be more specific to the DMN while the disruptions of those oscillations following a stroke through remote (diaschisis) effects may be more widespread, highlighting a non-specificity of disruption on the DMN in stroke population. The mechanisms underlying those differing modes of network disruption need to be further explored to better inform our understanding of brain function in healthy individuals and following injury.

Speech Rhythms and Multiplexed Oscillatory Sensory Coding in the Human Brain

PubMed Central

Gross, Joachim; Hoogenboom, Nienke; Thut, Gregor; Schyns, Philippe; Panzeri, Stefano; Belin, Pascal; Garrod, Simon

2013-01-01

Cortical oscillations are likely candidates for segmentation and coding of continuous speech. Here, we monitored continuous speech processing with magnetoencephalography (MEG) to unravel the principles of speech segmentation and coding. We demonstrate that speech entrains the phase of low-frequency (delta, theta) and the amplitude of high-frequency (gamma) oscillations in the auditory cortex. Phase entrainment is stronger in the right and amplitude entrainment is stronger in the left auditory cortex. Furthermore, edges in the speech envelope phase reset auditory cortex oscillations thereby enhancing their entrainment to speech. This mechanism adapts to the changing physical features of the speech envelope and enables efficient, stimulus-specific speech sampling. Finally, we show that within the auditory cortex, coupling between delta, theta, and gamma oscillations increases following speech edges. Importantly, all couplings (i.e., brain-speech and also within the cortex) attenuate for backward-presented speech, suggesting top-down control. We conclude that segmentation and coding of speech relies on a nested hierarchy of entrained cortical oscillations. PMID:24391472

EEG Spectral Generators Involved in Motor Imagery: A swLORETA Study

PubMed Central

Cebolla, Ana-Maria; Palmero-Soler, Ernesto; Leroy, Axelle; Cheron, Guy

2017-01-01

In order to characterize the neural generators of the brain oscillations related to motor imagery (MI), we investigated the cortical, subcortical, and cerebellar localizations of their respective electroencephalogram (EEG) spectral power and phase locking modulations. The MI task consisted in throwing a ball with the dominant upper limb while in a standing posture, within an ecological virtual reality (VR) environment (tennis court). The MI was triggered by the visual cues common to the control condition, during which the participant remained mentally passive. As previously developed, our paradigm considers the confounding problem that the reference condition allows two complementary analyses: one which uses the baseline before the occurrence of the visual cues in the MI and control resting conditions respectively; and the other which compares the analog periods between the MI and the control resting-state conditions. We demonstrate that MI activates specific, complex brain networks for the power and phase modulations of the EEG oscillations. An early (225 ms) delta phase-locking related to MI was generated in the thalamus and cerebellum and was followed (480 ms) by phase-locking in theta and alpha oscillations, generated in specific cortical areas and the cerebellum. Phase-locking preceded the power modulations (mainly alpha–beta ERD), whose cortical generators were situated in the frontal BA45, BA11, BA10, central BA6, lateral BA13, and posterior cortex BA2. Cerebellar-thalamic involvement through phase-locking is discussed as an underlying mechanism for recruiting at later stages the cortical areas involved in a cognitive role during MI. PMID:29312028

Out-of-synchrony speech entrainment in developmental dyslexia.

PubMed

Molinaro, Nicola; Lizarazu, Mikel; Lallier, Marie; Bourguignon, Mathieu; Carreiras, Manuel

2016-08-01

Developmental dyslexia is a reading disorder often characterized by reduced awareness of speech units. Whether the neural source of this phonological disorder in dyslexic readers results from the malfunctioning of the primary auditory system or damaged feedback communication between higher-order phonological regions (i.e., left inferior frontal regions) and the auditory cortex is still under dispute. Here we recorded magnetoencephalographic (MEG) signals from 20 dyslexic readers and 20 age-matched controls while they were listening to ∼10-s-long spoken sentences. Compared to controls, dyslexic readers had (1) an impaired neural entrainment to speech in the delta band (0.5-1 Hz); (2) a reduced delta synchronization in both the right auditory cortex and the left inferior frontal gyrus; and (3) an impaired feedforward functional coupling between neural oscillations in the right auditory cortex and the left inferior frontal regions. This shows that during speech listening, individuals with developmental dyslexia present reduced neural synchrony to low-frequency speech oscillations in primary auditory regions that hinders higher-order speech processing steps. The present findings, thus, strengthen proposals assuming that improper low-frequency acoustic entrainment affects speech sampling. This low speech-brain synchronization has the strong potential to cause severe consequences for both phonological and reading skills. Interestingly, the reduced speech-brain synchronization in dyslexic readers compared to normal readers (and its higher-order consequences across the speech processing network) appears preserved through the development from childhood to adulthood. Thus, the evaluation of speech-brain synchronization could possibly serve as a diagnostic tool for early detection of children at risk of dyslexia. Hum Brain Mapp 37:2767-2783, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Positive effects of neurofeedback on autism symptoms correlate with brain activation during imitation and observation.

PubMed

Datko, Michael; Pineda, Jaime A; Müller, Ralph-Axel

2018-03-01

Autism has been characterized by atypical task-related brain activation and functional connections, coinciding with deficits in sociocommunicative abilities. However, evidence of the brain's experience-dependent plasticity suggests that abnormal activity patterns may be reversed with treatment. In particular, neurofeedback training (NFT), an intervention based on operant conditioning resulting in self-regulation of brain electrical oscillations, has shown increasing promise in addressing abnormalities in brain function and behavior. We examined the effects of ≥ 20 h of sensorimotor mu-rhythm-based NFT in children with high-functioning autism spectrum disorders (ASD) and a matched control group of typically developing children (ages 8-17). During a functional magnetic resonance imaging imitation and observation task, the ASD group showed increased activation in regions of the human mirror neuron system following the NFT, as part of a significant interaction between group (ASD vs. controls) and training (pre- vs. post-training). These changes were positively correlated with behavioral improvements in the ASD participants, indicating that mu-rhythm NFT may be beneficial to individuals with ASD. © 2017 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

Measurement of the Dynamic Shear Modulus of Mouse Brain Tissue In Vivo By Magnetic Resonance Elastography

PubMed Central

Atay, Stefan M.; Kroenke, Christopher D.; Sabet, Arash; Bayly, Philip V.

2008-01-01

In this study, the magnetic resonance elastography (MRE) technique was used to estimate the dynamic shear modulus of mouse brain tissue in vivo. The technique allows visualization and measurement of mechanical shear waves excited by lateral vibration of the skull. Quantitative measurements of displacement in three dimensions (3-D) during vibration at 1200 Hz were obtained by applying oscillatory magnetic field gradients at the same frequency during an MR imaging sequence. Contrast in the resulting phase images of the mouse brain is proportional to displacement. To obtain estimates of shear modulus, measured displacement fields were fitted to the shear wave equation. Validation of the procedure was performed on gel characterized by independent rheometry tests and on data from finite element simulations. Brain tissue is, in reality, viscoelastic and nonlinear. The current estimates of dynamic shear modulus are strictly relevant only to small oscillations at a specific frequency, but these estimates may be obtained at high frequencies (and thus high deformation rates), non-invasively throughout the brain. These data complement measurements of nonlinear viscoelastic properties obtained by others at slower rates, either ex vivo or invasively. PMID:18412500

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

The Fate of Incoming Stimuli during NREM Sleep is Determined by Spindles and the Phase of the Slow Oscillation.

PubMed

Schabus, Manuel; Dang-Vu, Thien Thanh; Heib, Dominik Philip Johannes; Boly, Mélanie; Desseilles, Martin; Vandewalle, Gilles; Schmidt, Christina; Albouy, Geneviève; Darsaud, Annabelle; Gais, Steffen; Degueldre, Christian; Balteau, Evelyne; Phillips, Christophe; Luxen, André; Maquet, Pierre

2012-01-01

The present study aimed at identifying the neurophysiological responses associated with auditory stimulation during non-rapid eye movement (NREM) sleep using simultaneous electroencephalography (EEG)/functional magnetic resonance imaging (fMRI) recordings. It was reported earlier that auditory stimuli produce bilateral activation in auditory cortex, thalamus, and caudate during both wakefulness and NREM sleep. However, due to the spontaneous membrane potential fluctuations cortical responses may be highly variable during NREM. Here we now examine the modulation of cerebral responses to tones depending on the presence or absence of sleep spindles and the phase of the slow oscillation. Thirteen healthy young subjects were scanned successfully during stage 2-4 NREM sleep in the first half of the night in a 3 T scanner. Subjects were not sleep-deprived and sounds were post hoc classified according to (i) the presence of sleep spindles or (ii) the phase of the slow oscillation during (±300 ms) tone delivery. These detected sounds were then entered as regressors of interest in fMRI analyses. Interestingly wake-like responses - although somewhat altered in size and location - persisted during NREM sleep, except during present spindles (as previously published in Dang-Vu et al., 2011) and the negative going phase of the slow oscillation during which responses became less consistent or even absent. While the phase of the slow oscillation did not alter brain responses in primary sensory cortex, it did modulate responses at higher cortical levels. In addition EEG analyses show a distinct N550 response to tones during the presence of light sleep spindles and suggest that in deep NREM sleep the brain is more responsive during the positive going slope of the slow oscillation. The presence of short temporal windows during which the brain is open to external stimuli is consistent with the fact that even during deep sleep meaningful events can be detected. Altogether, our results emphasize the notion that spontaneous fluctuations of brain activity profoundly modify brain responses to external information across all behavioral states, including deep NREM sleep.

Frequency analysis of the visual steady-state response measured with the fast optical signal in younger and older adults.

PubMed

Tse, Chun-Yu; Gordon, Brian A; Fabiani, Monica; Gratton, Gabriele

2010-09-01

Relatively high frequency activity (>4Hz) carries important information about the state of the brain or its response to high frequency events. The electroencephalogram (EEG) is commonly used to study these changes because it possesses high temporal resolution and a good signal-to-noise ratio. However, it provides limited spatial information. Non-invasive fast optical signals (FOS) have been proposed as a neuroimaging tool combining spatial and temporal resolution. Yet, this technique has not been applied to study high frequency brain oscillations because of its relatively low signal-to-noise ratio. Here we investigate the sensitivity of FOS to relatively high-frequency brain oscillations. We measured the steady-state optical response elicited in medial and lateral occipital cortex by checkerboard reversals occurring at 4, 6, and 8Hz in younger and older adults. Stimulus-dependent oscillations were observed at the predicted stimulation frequency. In addition, in the younger adults the FOS steady-state response was smaller in lateral than medial areas, whereas in the older adults it was reversed in these two cortical regions. This may reflect diminished top-down inhibitory control in the older adults. The results indicate that FOS can be used to study the modulation of relatively high-frequency brain oscillations in adjacent cortical regions. Copyright (c) 2010 Elsevier B.V. All rights reserved.

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

PubMed Central

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

2014-01-01

Developmental cortical malformations comprise a large spectrum of histopathological brain abnormalities and syndromes. Their genetic, developmental and clinical complexity suggests they should be better understood in terms of the complementary action of independently timed perturbations (i.e., the multiple-hit hypothesis). However, understanding the underlying biological processes remains puzzling. Here we induced developmental cortical malformations in offspring, after intraventricular injection of methylazoxymethanol (MAM) in utero in mice. We combined extensive histological and electrophysiological studies to characterize the model. We found that MAM injections at E14 and E15 induced a range of cortical and hippocampal malformations resembling histological alterations of specific genetic mutations and transplacental mitotoxic agent injections. However, in contrast to most of these models, intraventricularly MAM-injected mice remained asymptomatic and showed no clear epilepsy-related phenotype as tested in long-term chronic recordings and with pharmacological manipulations. Instead, they exhibited a non-specific reduction of hippocampal-related brain oscillations (mostly in CA1); including theta, gamma and HFOs; and enhanced thalamocortical spindle activity during non-REM sleep. These data suggest that developmental cortical malformations do not necessarily correlate with epileptiform activity. We propose that the intraventricular in utero MAM approach exhibiting a range of rhythmopathies is a suitable model for multiple-hit studies of associated neurological disorders. PMID:24782720

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

PubMed

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

2014-01-01

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

Dynamics of alpha control: Preparatory suppression of posterior alpha oscillations by frontal modulators revealed with combined EEG and event-related optical signal (EROS)

PubMed Central

Mathewson, Kyle E.; Beck, Diane M.; Ro, Tony; Maclin, Edward L.; Low, Kathy A.; Fabiani, Monica; Gratton, Gabriele

2015-01-01

We investigated the dynamics of brain processes facilitating conscious experience of external stimuli. Previously we proposed that alpha (8-12 Hz) oscillations, which fluctuate with both sustained and directed attention, represent a pulsed inhibition of ongoing sensory brain activity. Here we tested the prediction that inhibitory alpha oscillations in visual cortex are modulated by top-down signals from frontoparietal attention networks. We measured modulations in phase-coherent alpha oscillations from superficial frontal, parietal, and occipital cortices using the event-related optical signal (EROS), a measure of neuronal activity affording high spatiotemporal resolution, along with concurrently-recorded electroencephalogram (EEG), while subjects performed a visual target-detection task. The pre-target alpha oscillations measured with EEG and EROS from posterior areas were larger for subsequently undetected targets, supporting alpha's inhibitory role. Using EROS, we localized brain correlates of these awareness-related alpha oscillations measured at the scalp to the cuneus and precuneus. Crucially, EROS alpha suppression correlated with posterior EEG alpha power across subjects. Sorting the EROS data based on EEG alpha power quartiles to investigate alpha modulators revealed that suppression of posterior alpha was preceded by increased activity in regions of the dorsal attention network, and decreased activity in regions of the cingulo-opercular network. Cross-correlations revealed the temporal dynamics of activity within these preparatory networks prior to posterior alpha modulation. The novel combination of EEG and EROS afforded localization of the sources and correlates of alpha oscillations and their temporal relationships, supporting our proposal that top-down control from attention networks modulates both posterior alpha and awareness of visual stimuli. PMID:24702458

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.

Wavelet entropy characterization of elevated intracranial pressure.

PubMed

Xu, Peng; Scalzo, Fabien; Bergsneider, Marvin; Vespa, Paul; Chad, Miller; Hu, Xiao

2008-01-01

Intracranial Hypertension (ICH) often occurs for those patients with traumatic brain injury (TBI), stroke, tumor, etc. Pathology of ICH is still controversial. In this work, we used wavelet entropy and relative wavelet entropy to study the difference existed between normal and hypertension states of ICP for the first time. The wavelet entropy revealed the similar findings as the approximation entropy that entropy during ICH state is smaller than that in normal state. Moreover, with wavelet entropy, we can see that ICH state has the more focused energy in the low wavelet frequency band (0-3.1 Hz) than the normal state. The relative wavelet entropy shows that the energy distribution in the wavelet bands between these two states is actually different. Based on these results, we suggest that ICH may be formed by the re-allocation of oscillation energy within brain.

Pulsed Out of Awareness: EEG Alpha Oscillations Represent a Pulsed-Inhibition of Ongoing Cortical Processing

PubMed Central

Mathewson, Kyle E.; Lleras, Alejandro; Beck, Diane M.; Fabiani, Monica; Ro, Tony; Gratton, Gabriele

2011-01-01

Alpha oscillations are ubiquitous in the brain, but their role in cortical processing remains a matter of debate. Recently, evidence has begun to accumulate in support of a role for alpha oscillations in attention selection and control. Here we first review evidence that 8–12 Hz oscillations in the brain have a general inhibitory role in cognitive processing, with an emphasis on their role in visual processing. Then, we summarize the evidence in support of our recent proposal that alpha represents a pulsed-inhibition of ongoing neural activity. The phase of the ongoing electroencephalography can influence evoked activity and subsequent processing, and we propose that alpha exerts its inhibitory role through alternating microstates of inhibition and excitation. Finally, we discuss evidence that this pulsed-inhibition can be entrained to rhythmic stimuli in the environment, such that preferential processing occurs for stimuli at predictable moments. The entrainment of preferential phase may provide a mechanism for temporal attention in the brain. This pulsed inhibitory account of alpha has important implications for many common cognitive phenomena, such as the attentional blink, and seems to indicate that our visual experience may at least some times be coming through in waves. PMID:21779257

Ketamine: differential neurophysiological dynamics in functional networks in the rat brain

PubMed Central

Ahnaou, A; Huysmans, H; Biermans, R; Manyakov, N V; Drinkenburg, W H I M

2017-01-01

Recently, the N-methyl-d-aspartate-receptor (NMDAR) antagonist ketamine has emerged as a fast-onset mechanism to achieve antidepressant activity, whereas its psychomimetic, dissociative and amnestic effects have been well documented to pharmacologically model schizophrenia features in rodents. Sleep–wake architecture, neuronal oscillations and network connectivity are key mechanisms supporting brain plasticity and cognition, which are disrupted in mood disorders such as depression and schizophrenia. In rats, we investigated the dynamic effects of acute and chronic subcutaneous administration of ketamine (2.5, 5 and 10 mg kg−1) on sleep–wake cycle, multichannels network interactions assessed by coherence and phase–amplitude cross-frequency coupling, locomotor activity (LMA), cognitive information processing as reflected by the mismatch negativity-like (MMN) component of event-related brain potentials (ERPs). Acute ketamine elicited a short, lasting inhibition of rapid eye movement (REM) sleep, increased coherence in higher gamma frequency oscillations independent of LMA, altered theta-gamma phase–amplitude coupling, increased MMN peak-amplitude response and evoked higher gamma oscillations. In contrast, chronic ketamine reduced large-scale communication among cortical regions by decreasing oscillations and coherent activity in the gamma frequency range, shifted networks activity towards slow alpha rhythm, decreased MMN peak response and enhanced aberrant higher gamma neuronal network oscillations. Altogether, our data show that acute and chronic ketamine elicited differential changes in network connectivity, ERPs and event-related oscillations (EROs), supporting possible underlying alterations in NMDAR–GABAergic signaling. The findings underscore the relevance of intermittent dosing of ketamine to accurately maintain the functional integrity of neuronal networks for long-term plastic changes and therapeutic effect. PMID:28926001

Brain responses to 40-Hz binaural beat and effects on emotion and memory.

PubMed

Jirakittayakorn, Nantawachara; Wongsawat, Yodchanan

2017-10-01

Gamma oscillation plays a role in binding process or sensory integration, a process by which several brain areas beside primary cortex are activated for higher perception of the received stimulus. Beta oscillation is also involved in interpreting received stimulus and occurs following gamma oscillation, and this process is known as gamma-to-beta transition, a process for neglecting unnecessary stimuli in surrounding environment. Gamma oscillation also associates with cognitive functions, memory and emotion. Therefore, modulation of the brain activity can lead to manipulation of cognitive functions. The stimulus used in this study was 40-Hz binaural beat because binaural beat induces frequency following response. This study aimed to investigate the neural oscillation responding to the 40-Hz binaural beat and to evaluate working memory function and emotional states after listening to that stimulus. Two experiments were developed based on the study aims. In the first experiment, electroencephalograms were recorded while participants listened to the stimulus for 30min. The results suggested that frontal, temporal, and central regions were activated within 15min. In the second experiment, word list recall task was conducted before and after listening to the stimulus for 20min. The results showed that, after listening, the recalled words were increase in the working memory portion of the list. Brunel Mood Scale, a questionnaire to evaluate emotional states, revealed changes in emotional states after listening to the stimulus. The emotional results suggested that these changes were consistent with the induced neural oscillations. Copyright © 2017 Elsevier B.V. All rights reserved.

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

Heteroclinic switching between chimeras

NASA Astrophysics Data System (ADS)

Bick, Christian

2018-05-01

Functional oscillator networks, such as neuronal networks in the brain, exhibit switching between metastable states involving many oscillators. We give exact results how such global dynamics can arise in paradigmatic phase oscillator networks: Higher-order network interactions give rise to metastable chimeras—localized frequency synchrony patterns—which are joined by heteroclinic connections. Moreover, we illuminate the mechanisms that underly the switching dynamics in these experimentally accessible networks.

Non-invasive Brain Stimulation: A Paradigm Shift in Understanding Brain Oscillations.

PubMed

Vosskuhl, Johannes; Strüber, Daniel; Herrmann, Christoph S

2018-01-01

Cognitive neuroscience set out to understand the neural mechanisms underlying cognition. One central question is how oscillatory brain activity relates to cognitive processes. Up to now, most of the evidence supporting this relationship was correlative in nature. This situation changed dramatically with the recent development of non-invasive brain stimulation (NIBS) techniques, which open up new vistas for neuroscience by allowing researchers for the first time to validate their correlational theories by manipulating brain functioning directly. In this review, we focus on transcranial alternating current stimulation (tACS), an electrical brain stimulation method that applies sinusoidal currents to the intact scalp of human individuals to directly interfere with ongoing brain oscillations. We outline how tACS can impact human brain oscillations by employing different levels of observation from non-invasive tACS application in healthy volunteers and intracranial recordings in patients to animal studies demonstrating the effectiveness of alternating electric fields on neurons in vitro and in vivo . These findings likely translate to humans as comparable effects can be observed in human and animal studies. Neural entrainment and plasticity are suggested to mediate the behavioral effects of tACS. Furthermore, we focus on mechanistic theories about the relationship between certain cognitive functions and specific parameters of brain oscillaitons such as its amplitude, frequency, phase and phase coherence. For each of these parameters we present the current state of testing its functional relevance by means of tACS. Recent developments in the field of tACS are outlined which include the stimulation with physiologically inspired non-sinusoidal waveforms, stimulation protocols which allow for the observation of online-effects, and closed loop applications of tACS.

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

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.

Theta and Alpha Oscillations in Attentional Interaction during Distracted Driving

PubMed Central

Wang, Yu-Kai; Jung, Tzyy-Ping; Lin, Chin-Teng

2018-01-01

Performing multiple tasks simultaneously usually affects the behavioral performance as compared with executing the single task. Moreover, processing multiple tasks simultaneously often involve more cognitive demands. Two visual tasks, lane-keeping task and mental calculation, were utilized to assess the brain dynamics through 32-channel electroencephalogram (EEG) recorded from 14 participants. A 400-ms stimulus onset asynchrony (SOA) factor was used to induce distinct levels of attentional requirements. In the dual-task conditions, the deteriorated behavior reflected the divided attention and the overlapping brain resources used. The frontal, parietal and occipital components were decomposed by independent component analysis (ICA) algorithm. The event- and response-related theta and alpha oscillations in selected brain regions were investigated first. The increased theta oscillation in frontal component and decreased alpha oscillations in parietal and occipital components reflect the cognitive demands and attentional requirements as executing the designed tasks. Furthermore, time-varying interactive over-additive (O-Add), additive (Add) and under-additive (U-Add) activations were explored and summarized through the comparison between the summation of the elicited spectral perturbations in two single-task conditions and the spectral perturbations in the dual task. Add and U-Add activations were observed while executing the dual tasks. U-Add theta and alpha activations dominated the posterior region in dual-task situations. Our results show that both deteriorated behaviors and interactive brain activations should be comprehensively considered for evaluating workload or attentional interaction precisely. PMID:29479310

Altered thalamocortical rhythmicity and connectivity in mice lacking CaV3.1 T-type Ca2+ channels in unconsciousness

PubMed Central

Choi, Soonwook; Yu, Eunah; Lee, Seongwon; Llinás, Rodolfo R.

2015-01-01

In unconscious status (e.g., deep sleep and anesthetic unconsciousness) where cognitive functions are not generated there is still a significant level of brain activity present. Indeed, the electrophysiology of the unconscious brain is characterized by well-defined thalamocortical rhythmicity. Here we address the ionic basis for such thalamocortical rhythms during unconsciousness. In particular, we address the role of CaV3.1 T-type Ca2+ channels, which are richly expressed in thalamic neurons. Toward this aim, we examined the electrophysiological and behavioral phenotypes of mice lacking CaV3.1 channels (CaV3.1 knockout) during unconsciousness induced by ketamine or ethanol administration. Our findings indicate that CaV3.1 KO mice displayed attenuated low-frequency oscillations in thalamocortical loops, especially in the 1- to 4-Hz delta band, compared with control mice (CaV3.1 WT). Intriguingly, we also found that CaV3.1 KO mice exhibited augmented high-frequency oscillations during unconsciousness. In a behavioral measure of unconsciousness dynamics, CaV3.1 KO mice took longer to fall into the unconscious state than controls. In addition, such unconscious events had a shorter duration than those of control mice. The thalamocortical interaction level between mediodorsal thalamus and frontal cortex in CaV3.1 KO mice was significantly lower, especially for delta band oscillations, compared with that of CaV3.1 WT mice, during unconsciousness. These results suggest that the CaV3.1 channel is required for the generation of a given set of thalamocortical rhythms during unconsciousness. Further, that thalamocortical resonant neuronal activity supported by this channel is important for the control of vigilance states. PMID:26056284

Aging does not affect generalized postural motor learning in response to variable amplitude oscillations of the support surface.

PubMed

Van Ooteghem, Karen; Frank, James S; Allard, Fran; Horak, Fay B

2010-08-01

Postural motor learning for dynamic balance tasks has been demonstrated in healthy older adults (Van Ooteghem et al. in Exp Brain Res 199(2):185-193, 2009). The purpose of this study was to investigate the type of knowledge (general or specific) obtained with balance training in this age group and to examine whether embedding perturbation regularities within a balance task masks specific learning. Two groups of older adults maintained balance on a translating platform that oscillated with variable amplitude and constant frequency. One group was trained using an embedded-sequence (ES) protocol which contained the same 15-s sequence of variable amplitude oscillations in the middle of each trial. A second group was trained using a looped-sequence (LS) protocol which contained a 15-s sequence repeated three times to form each trial. All trials were 45 s. Participants were not informed of any repetition. To examine learning, participants performed a retention test following a 24-h delay. LS participants also completed a transfer task. Specificity of learning was examined by comparing performance for repeated versus random sequences (ES) and training versus transfer sequences (LS). Performance was measured by deriving spatial and temporal measures of whole body center of mass (COM) and trunk orientation. Both groups improved performance with practice as characterized by reduced COM displacement, improved COM-platform phase relationships, and decreased angular trunk motion. Furthermore, improvements reflected general rather than specific postural motor learning regardless of training protocol (ES or LS). This finding is similar to young adults (Van Ooteghem et al. in Exp Brain Res 187(4):603-611, 2008) and indicates that age does not influence the type of learning which occurs for balance control.

Altered thalamocortical rhythmicity and connectivity in mice lacking CaV3.1 T-type Ca2+ channels in unconsciousness.

PubMed

Choi, Soonwook; Yu, Eunah; Lee, Seongwon; Llinás, Rodolfo R

2015-06-23

In unconscious status (e.g., deep sleep and anesthetic unconsciousness) where cognitive functions are not generated there is still a significant level of brain activity present. Indeed, the electrophysiology of the unconscious brain is characterized by well-defined thalamocortical rhythmicity. Here we address the ionic basis for such thalamocortical rhythms during unconsciousness. In particular, we address the role of CaV3.1 T-type Ca(2+) channels, which are richly expressed in thalamic neurons. Toward this aim, we examined the electrophysiological and behavioral phenotypes of mice lacking CaV3.1 channels (CaV3.1 knockout) during unconsciousness induced by ketamine or ethanol administration. Our findings indicate that CaV3.1 KO mice displayed attenuated low-frequency oscillations in thalamocortical loops, especially in the 1- to 4-Hz delta band, compared with control mice (CaV3.1 WT). Intriguingly, we also found that CaV3.1 KO mice exhibited augmented high-frequency oscillations during unconsciousness. In a behavioral measure of unconsciousness dynamics, CaV3.1 KO mice took longer to fall into the unconscious state than controls. In addition, such unconscious events had a shorter duration than those of control mice. The thalamocortical interaction level between mediodorsal thalamus and frontal cortex in CaV3.1 KO mice was significantly lower, especially for delta band oscillations, compared with that of CaV3.1 WT mice, during unconsciousness. These results suggest that the CaV3.1 channel is required for the generation of a given set of thalamocortical rhythms during unconsciousness. Further, that thalamocortical resonant neuronal activity supported by this channel is important for the control of vigilance states.

Rapid cell-free forward engineering of novel genetic ring oscillators

PubMed Central

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

2015-01-01

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

Temporal structure of neuronal population oscillations with empirical model decomposition

NASA Astrophysics Data System (ADS)

Li, Xiaoli

2006-08-01

Frequency analysis of neuronal oscillation is very important for understanding the neural information processing and mechanism of disorder in the brain. This Letter addresses a new method to analyze the neuronal population oscillations with empirical mode decomposition (EMD). Following EMD of neuronal oscillation, a series of intrinsic mode functions (IMFs) are obtained, then Hilbert transform of IMFs can be used to extract the instantaneous time frequency structure of neuronal oscillation. The method is applied to analyze the neuronal oscillation in the hippocampus of epileptic rats in vivo, the results show the neuronal oscillations have different descriptions during the pre-ictal, seizure onset and ictal periods of the epileptic EEG at the different frequency band. This new method is very helpful to provide a view for the temporal structure of neural oscillation.

Characterizing the roles of alpha and theta oscillations in multisensory attention.

PubMed

Keller, Arielle S; Payne, Lisa; Sekuler, Robert

2017-05-01

Cortical alpha oscillations (8-13Hz) appear to play a role in suppressing distractions when just one sensory modality is being attended, but do they also contribute when attention is distributed over multiple sensory modalities? For an answer, we examined cortical oscillations in human subjects who were dividing attention between auditory and visual sequences. In Experiment 1, subjects performed an oddball task with auditory, visual, or simultaneous audiovisual sequences in separate blocks, while the electroencephalogram was recorded using high-density scalp electrodes. Alpha oscillations were present continuously over posterior regions while subjects were attending to auditory sequences. This supports the idea that the brain suppresses processing of visual input in order to advantage auditory processing. During a divided-attention audiovisual condition, an oddball (a rare, unusual stimulus) occurred in either the auditory or the visual domain, requiring that attention be divided between the two modalities. Fronto-central theta band (4-7Hz) activity was strongest in this audiovisual condition, when subjects monitored auditory and visual sequences simultaneously. Theta oscillations have been associated with both attention and with short-term memory. Experiment 2 sought to distinguish these possible roles of fronto-central theta activity during multisensory divided attention. Using a modified version of the oddball task from Experiment 1, Experiment 2 showed that differences in theta power among conditions were independent of short-term memory load. Ruling out theta's association with short-term memory, we conclude that fronto-central theta activity is likely a marker of multisensory divided attention. Copyright © 2017 Elsevier Ltd. All rights reserved.

Characterizing the roles of alpha and theta oscillations in multisensory attention

PubMed Central

Keller, Arielle S.; Payne, Lisa; Sekuler, Robert

2017-01-01

Cortical alpha oscillations (8–13 Hz) appear to play a role in suppressing distractions when just one sensory modality is being attended, but do they also contribute when attention is distributed over multiple sensory modalities? For an answer, we examined cortical oscillations in human subjects who were dividing attention between auditory and visual sequences. In Experiment 1, subjects performed an oddball task with auditory, visual, or simultaneous audiovisual sequences in separate blocks, while the electroencephalogram was recorded using high-density scalp electrodes. Alpha oscillations were present continuously over posterior regions while subjects were attending to auditory sequences. This supports the idea that the brain suppresses processing of visual input in order to advantage auditory processing. During a divided-attention audiovisual condition, an oddball (a rare, unusual stimulus) occurred in either the auditory or the visual domain, requiring that attention be divided between the two modalities. Fronto-central theta band (4–7 Hz) activity was strongest in this audiovisual condition, when subjects monitored auditory and visual sequences simultaneously. Theta oscillations have been associated with both attention and with short-term memory. Experiment 2 sought to distinguish these possible roles of fronto-central theta activity during multisensory divided attention. Using a modified version of the oddball task from Experiment 1, Experiment 2 showed that differences in theta power among conditions were independent of short-term memory load. Ruling out theta’s association with short-term memory, we conclude that fronto-central theta activity is likely a marker of multisensory divided attention. PMID:28259771

Altered cortical beta‐band oscillations reflect motor system degeneration in amyotrophic lateral sclerosis

PubMed Central

Proudfoot, Malcolm; Rohenkohl, Gustavo; Quinn, Andrew; Colclough, Giles L.; Wuu, Joanne; Talbot, Kevin; Woolrich, Mark W.; Benatar, Michael

2016-01-01

Abstract Continuous rhythmic neuronal oscillations underpin local and regional cortical communication. The impact of the motor system neurodegenerative syndrome amyotrophic lateral sclerosis (ALS) on the neuronal oscillations subserving movement might therefore serve as a sensitive marker of disease activity. Movement preparation and execution are consistently associated with modulations to neuronal oscillation beta (15–30 Hz) power. Cortical beta‐band oscillations were measured using magnetoencephalography (MEG) during preparation for, execution, and completion of a visually cued, lateralized motor task that included movement inhibition trials. Eleven “classical” ALS patients, 9 with the primary lateral sclerosis (PLS) phenotype, and 12 asymptomatic carriers of ALS‐associated gene mutations were compared with age‐similar healthy control groups. Augmented beta desynchronization was observed in both contra‐ and ipsilateral motor cortices of ALS patients during motor preparation. Movement execution coincided with excess beta desynchronization in asymptomatic mutation carriers. Movement completion was followed by a slowed rebound of beta power in all symptomatic patients, further reflected in delayed hemispheric lateralization for beta rebound in the PLS group. This may correspond to the particular involvement of interhemispheric fibers of the corpus callosum previously demonstrated in diffusion tensor imaging studies. We conclude that the ALS spectrum is characterized by intensified cortical beta desynchronization followed by delayed rebound, concordant with a broader concept of cortical hyperexcitability, possibly through loss of inhibitory interneuronal influences. MEG may potentially detect cortical dysfunction prior to the development of overt symptoms, and thus be able to contribute to the assessment of future neuroprotective strategies. Hum Brain Mapp 38:237–254, 2017. © 2016 Wiley Periodicals, Inc. PMID:27623516

Lithium lengthens circadian period of cultured brain slices in area specific manner.

PubMed

Yoshikawa, Tomoko; Honma, Sato

2016-11-01

Lithium has been used for the treatment of bipolar disorder (BD). However, the mechanisms how lithium exerts its mood stabilizing effects remain to be studied. The disorder in circadian pacemaking has been suggested as an underlying mechanism of the characteristic mood instability of the BD. Lithium is also known to lengthen the circadian periods. We recently proposed that chronic methamphetamine treatment induced circadian oscillation as a complex oscillator including multiple dopaminergic brain areas, and the complex oscillator regulates behavior rhythm independent from the central circadian oscillator in the suprachiasmatic nucleus (SCN). Sleep-wake pattern of rapid cycling BD exhibits similar rhythm disorganization to methamphetamine treated animals. Therefore, we hypothesized that the dysregulated circadian rhythm in BD patients is caused by desynchronization of sleep-wake rhythms from the central clock in the SCN, and that mood stabilizing effect of lithium is achieved through their resynchronization. In the present experiment, we examined how lithium affects the circadian rhythms of brain areas involved in the complex oscillator as well as the SCN. Here we report that lithium lengthens the circadian periods in the SCN, olfactory bulb, median eminence and substantia nigra with dose and area specific manner. The effective lithium dose was much higher than the plasma levels that are required for lengthening the circadian behavior rhythms as well for therapeutic use. Low dose of lithium did not lengthen the period but enhanced the amplitude of circadian rhythms, which may exert therapeutic effects on BD. Copyright © 2016 Elsevier B.V. All rights reserved.

Nonequilibrium landscape theory of neural networks.

PubMed

Yan, Han; Zhao, Lei; Hu, Liang; Wang, Xidi; Wang, Erkang; Wang, Jin

2013-11-05

The brain map project aims to map out the neuron connections of the human brain. Even with all of the wirings mapped out, the global and physical understandings of the function and behavior are still challenging. Hopfield quantified the learning and memory process of symmetrically connected neural networks globally through equilibrium energy. The energy basins of attractions represent memories, and the memory retrieval dynamics is determined by the energy gradient. However, the realistic neural networks are asymmetrically connected, and oscillations cannot emerge from symmetric neural networks. Here, we developed a nonequilibrium landscape-flux theory for realistic asymmetrically connected neural networks. We uncovered the underlying potential landscape and the associated Lyapunov function for quantifying the global stability and function. We found the dynamics and oscillations in human brains responsible for cognitive processes and physiological rhythm regulations are determined not only by the landscape gradient but also by the flux. We found that the flux is closely related to the degrees of the asymmetric connections in neural networks and is the origin of the neural oscillations. The neural oscillation landscape shows a closed-ring attractor topology. The landscape gradient attracts the network down to the ring. The flux is responsible for coherent oscillations on the ring. We suggest the flux may provide the driving force for associations among memories. We applied our theory to rapid-eye movement sleep cycle. We identified the key regulation factors for function through global sensitivity analysis of landscape topography against wirings, which are in good agreements with experiments.

Nonequilibrium landscape theory of neural networks

PubMed Central

Yan, Han; Zhao, Lei; Hu, Liang; Wang, Xidi; Wang, Erkang; Wang, Jin

2013-01-01

The brain map project aims to map out the neuron connections of the human brain. Even with all of the wirings mapped out, the global and physical understandings of the function and behavior are still challenging. Hopfield quantified the learning and memory process of symmetrically connected neural networks globally through equilibrium energy. The energy basins of attractions represent memories, and the memory retrieval dynamics is determined by the energy gradient. However, the realistic neural networks are asymmetrically connected, and oscillations cannot emerge from symmetric neural networks. Here, we developed a nonequilibrium landscape–flux theory for realistic asymmetrically connected neural networks. We uncovered the underlying potential landscape and the associated Lyapunov function for quantifying the global stability and function. We found the dynamics and oscillations in human brains responsible for cognitive processes and physiological rhythm regulations are determined not only by the landscape gradient but also by the flux. We found that the flux is closely related to the degrees of the asymmetric connections in neural networks and is the origin of the neural oscillations. The neural oscillation landscape shows a closed-ring attractor topology. The landscape gradient attracts the network down to the ring. The flux is responsible for coherent oscillations on the ring. We suggest the flux may provide the driving force for associations among memories. We applied our theory to rapid-eye movement sleep cycle. We identified the key regulation factors for function through global sensitivity analysis of landscape topography against wirings, which are in good agreements with experiments. PMID:24145451

Circadian rhythmicity and light sensitivity of the zebrafish brain.

PubMed

Moore, Helen A; Whitmore, David

2014-01-01

Traditionally, circadian clocks have been thought of as a neurobiological phenomenon. This view changed somewhat over recent years with the discovery of peripheral tissue circadian oscillators. In mammals, however, the suprachiasmatic nucleus (SCN) in the hypothalamus still retains the critical role of a central synchronizer of biological timing. Zebrafish, in contrast, have always reflected a more highly decentralized level of clock organization, as individual cells and tissues contain directly light responsive circadian pacemakers. As a consequence, clock function in the zebrafish brain has remained largely unexplored, and the precise organization of rhythmic and light-sensitive neurons within the brain is unknown. To address this issue, we used the period3 (per3)-luciferase transgenic zebrafish to confirm that multiple brain regions contain endogenous circadian oscillators that are directly light responsive. In addition, in situ hybridization revealed localised neural expression of several rhythmic and light responsive clock genes, including per3, cryptochrome1a (cry1a) and per2. Adult brain nuclei showing significant clock gene expression include the teleost equivalent of the SCN, as well as numerous hypothalamic nuclei, the periventricular grey zone (PGZ) of the optic tectum, and granular cells of the rhombencephalon. To further investigate the light sensitive properties of neurons, expression of c-fos, a marker for neuronal activity, was examined. c-fos mRNA was upregulated in response to changing light conditions in different nuclei within the zebrafish brain. Furthermore, under constant dark (DD) conditions, c-fos shows a significant circadian oscillation. Taken together, these results show that there are numerous areas of the zebrafish central nervous system, which contain deep brain photoreceptors and directly light-entrainable circadian pacemakers. However, there are also multiple brain nuclei, which possess neither, demonstrating a degree of pacemaker complexity that was not previously appreciated.

Circadian Rhythmicity and Light Sensitivity of the Zebrafish Brain

PubMed Central

Moore, Helen A.; Whitmore, David

2014-01-01

Traditionally, circadian clocks have been thought of as a neurobiological phenomenon. This view changed somewhat over recent years with the discovery of peripheral tissue circadian oscillators. In mammals, however, the suprachiasmatic nucleus (SCN) in the hypothalamus still retains the critical role of a central synchronizer of biological timing. Zebrafish, in contrast, have always reflected a more highly decentralized level of clock organization, as individual cells and tissues contain directly light responsive circadian pacemakers. As a consequence, clock function in the zebrafish brain has remained largely unexplored, and the precise organization of rhythmic and light-sensitive neurons within the brain is unknown. To address this issue, we used the period3 (per3)-luciferase transgenic zebrafish to confirm that multiple brain regions contain endogenous circadian oscillators that are directly light responsive. In addition, in situ hybridization revealed localised neural expression of several rhythmic and light responsive clock genes, including per3, cryptochrome1a (cry1a) and per2. Adult brain nuclei showing significant clock gene expression include the teleost equivalent of the SCN, as well as numerous hypothalamic nuclei, the periventricular grey zone (PGZ) of the optic tectum, and granular cells of the rhombencephalon. To further investigate the light sensitive properties of neurons, expression of c-fos, a marker for neuronal activity, was examined. c-fos mRNA was upregulated in response to changing light conditions in different nuclei within the zebrafish brain. Furthermore, under constant dark (DD) conditions, c-fos shows a significant circadian oscillation. Taken together, these results show that there are numerous areas of the zebrafish central nervous system, which contain deep brain photoreceptors and directly light-entrainable circadian pacemakers. However, there are also multiple brain nuclei, which possess neither, demonstrating a degree of pacemaker complexity that was not previously appreciated. PMID:24465943

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

PubMed

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

2018-06-07

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

A Neurophysiological Perspective on a Preventive Treatment against Schizophrenia Using Transcranial Electric Stimulation of the Corticothalamic Pathway

PubMed Central

Pinault, Didier

2017-01-01

Schizophrenia patients are waiting for a treatment free of detrimental effects. Psychotic disorders are devastating mental illnesses associated with dysfunctional brain networks. Ongoing brain network gamma frequency (30–80 Hz) oscillations, naturally implicated in integrative function, are excessively amplified during hallucinations, in at-risk mental states for psychosis and first-episode psychosis. So, gamma oscillations represent a bioelectrical marker for cerebral network disorders with prognostic and therapeutic potential. They accompany sensorimotor and cognitive deficits already present in prodromal schizophrenia. Abnormally amplified gamma oscillations are reproduced in the corticothalamic systems of healthy humans and rodents after a single systemic administration, at a psychotomimetic dose, of the glutamate N-methyl-d-aspartate receptor antagonist ketamine. These translational ketamine models of prodromal schizophrenia are thus promising to work out a preventive noninvasive treatment against first-episode psychosis and chronic schizophrenia. In the present essay, transcranial electric stimulation (TES) is considered an appropriate preventive therapeutic modality because it can influence cognitive performance and neural oscillations. Here, I highlight clinical and experimental findings showing that, together, the corticothalamic pathway, the thalamus, and the glutamatergic synaptic transmission form an etiopathophysiological backbone for schizophrenia and represent a potential therapeutic target for preventive TES of dysfunctional brain networks in at-risk mental state patients against psychotic disorders. PMID:28350371

A Neurophysiological Perspective on a Preventive Treatment against Schizophrenia Using Transcranial Electric Stimulation of the Corticothalamic Pathway.

PubMed

Pinault, Didier

2017-03-28

Schizophrenia patients are waiting for a treatment free of detrimental effects. Psychotic disorders are devastating mental illnesses associated with dysfunctional brain networks. Ongoing brain network gamma frequency (30-80 Hz) oscillations, naturally implicated in integrative function, are excessively amplified during hallucinations, in at-risk mental states for psychosis and first-episode psychosis. So, gamma oscillations represent a bioelectrical marker for cerebral network disorders with prognostic and therapeutic potential. They accompany sensorimotor and cognitive deficits already present in prodromal schizophrenia. Abnormally amplified gamma oscillations are reproduced in the corticothalamic systems of healthy humans and rodents after a single systemic administration, at a psychotomimetic dose, of the glutamate N - methyl -d-aspartate receptor antagonist ketamine. These translational ketamine models of prodromal schizophrenia are thus promising to work out a preventive noninvasive treatment against first-episode psychosis and chronic schizophrenia. In the present essay, transcranial electric stimulation (TES) is considered an appropriate preventive therapeutic modality because it can influence cognitive performance and neural oscillations. Here, I highlight clinical and experimental findings showing that, together, the corticothalamic pathway, the thalamus, and the glutamatergic synaptic transmission form an etiopathophysiological backbone for schizophrenia and represent a potential therapeutic target for preventive TES of dysfunctional brain networks in at-risk mental state patients against psychotic disorders.

Cortex-wide BOLD fMRI activity reflects locally-recorded slow oscillation-associated calcium waves.

PubMed

Schwalm, Miriam; Schmid, Florian; Wachsmuth, Lydia; Backhaus, Hendrik; Kronfeld, Andrea; Aedo Jury, Felipe; Prouvot, Pierre-Hugues; Fois, Consuelo; Albers, Franziska; van Alst, Timo; Faber, Cornelius; Stroh, Albrecht

2017-09-15

Spontaneous slow oscillation-associated slow wave activity represents an internally generated state which is characterized by alternations of network quiescence and stereotypical episodes of neuronal activity - slow wave events. However, it remains unclear which macroscopic signal is related to these active periods of the slow wave rhythm. We used optic fiber-based calcium recordings of local neural populations in cortex and thalamus to detect neurophysiologically defined slow calcium waves in isoflurane anesthetized rats. The individual slow wave events were used for an event-related analysis of simultaneously acquired whole-brain BOLD fMRI. We identified BOLD responses directly related to onsets of slow calcium waves, revealing a cortex-wide BOLD correlate: the entire cortex was engaged in this specific type of slow wave activity. These findings demonstrate a direct relation of defined neurophysiological events to a specific BOLD activity pattern and were confirmed for ongoing slow wave activity by independent component and seed-based analyses.

Cortex-wide BOLD fMRI activity reflects locally-recorded slow oscillation-associated calcium waves

PubMed Central

Backhaus, Hendrik; Kronfeld, Andrea; Aedo Jury, Felipe; Prouvot, Pierre-Hugues; Fois, Consuelo; Albers, Franziska; van Alst, Timo

2017-01-01

Spontaneous slow oscillation-associated slow wave activity represents an internally generated state which is characterized by alternations of network quiescence and stereotypical episodes of neuronal activity - slow wave events. However, it remains unclear which macroscopic signal is related to these active periods of the slow wave rhythm. We used optic fiber-based calcium recordings of local neural populations in cortex and thalamus to detect neurophysiologically defined slow calcium waves in isoflurane anesthetized rats. The individual slow wave events were used for an event-related analysis of simultaneously acquired whole-brain BOLD fMRI. We identified BOLD responses directly related to onsets of slow calcium waves, revealing a cortex-wide BOLD correlate: the entire cortex was engaged in this specific type of slow wave activity. These findings demonstrate a direct relation of defined neurophysiological events to a specific BOLD activity pattern and were confirmed for ongoing slow wave activity by independent component and seed-based analyses. PMID:28914607

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.

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

NASA Astrophysics Data System (ADS)

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

2015-02-01

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

Analysis of structural patterns in the brain with the complex network approach

NASA Astrophysics Data System (ADS)

Maksimenko, Vladimir A.; Makarov, Vladimir V.; Kharchenko, Alexander A.; Pavlov, Alexey N.; Khramova, Marina V.; Koronovskii, Alexey A.; Hramov, Alexander E.

2015-03-01

In this paper we study mechanisms of the phase synchronization in a model network of Van der Pol oscillators and in the neural network of the brain by consideration of macroscopic parameters of these networks. As the macroscopic characteristics of the model network we consider a summary signal produced by oscillators. Similar to the model simulations, we study EEG signals reflecting the macroscopic dynamics of neural network. We show that the appearance of the phase synchronization leads to an increased peak in the wavelet spectrum related to the dynamics of synchronized oscillators. The observed correlation between the phase relations of individual elements and the macroscopic characteristics of the whole network provides a way to detect phase synchronization in the neural networks in the cases of normal and pathological activity.

[The noncoherent components of evoked brain activity].

PubMed

Kovalev, V P; Novototskiĭ-Vlasov, V Iu

1998-01-01

Poststimulus spectral EEG changes and their correlation with evoked potential (EP) were analyzed. The non-stationary components of the brain evoked activity were revealed in 32 volunteers during simple motor reaction and choice reaction to visual stimuli. This nonstationary activity was manifested in poststimulus changes in the mean wave half-period duration (MWHPD) and mean wave half-period power of the delta- and beta-frequency oscillations computed in the EEG realizations after the EP subtraction. The latencies of high-frequency EP components fell into the intervals of the MWHPD decrease and increase in the power of beta-oscillations, and the latencies of low-frequency EP components coincided with the intervals of the MWHPD increase and decrease in the power of delta and beta-oscillations, which pointed to correlation of these changes with the EP.

Brain Oscillations and Diurnal Variations in Hypnotic Responsiveness—A Commentary on “Diurnal Variations in Hypnotic Responsiveness: Is There an Optimal Time to be Hypnotized?”

PubMed Central

Jensen, Mark P.

2016-01-01

A recent study published in the International Journal of Clinical and Experimental Hypnosis reported an interesting diurnal pattern of hypnotic responsivity; specifically, the authors found higher hypnotic responsiveness in a large sample of undergraduates in the morning and early evening. However, they did not have an explanation for this pattern of findings. This pattern is consistent, however, with the theta hypothesis of hypnotic responsivity. Further examination of the associations between brain oscillations and response to hypnosis is needed to determine if specific oscillations such as theta (1) actually facilitate response to some hypnotic suggestions, (2) merely reflect hypnotic responding, or (3) reflect another factor that itself plays a causal role in response to hypnosis. PMID:26599996

[The mechanism and function of hippocampal neural oscillation].

PubMed

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

2017-10-25

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

Oscillatory neural representations in the sensory thalamus predict neuropathic pain relief by deep brain stimulation.

PubMed

Huang, Yongzhi; Green, Alexander L; Hyam, Jonathan; Fitzgerald, James; Aziz, Tipu Z; Wang, Shouyan

2018-01-01

Understanding the function of sensory thalamic neural activity is essential for developing and improving interventions for neuropathic pain. However, there is a lack of investigation of the relationship between sensory thalamic oscillations and pain relief in patients with neuropathic pain. This study aims to identify the oscillatory neural characteristics correlated with pain relief induced by deep brain stimulation (DBS), and develop a quantitative model to predict pain relief by integrating characteristic measures of the neural oscillations. Measures of sensory thalamic local field potentials (LFPs) in thirteen patients with neuropathic pain were screened in three dimensional feature space according to the rhythm, balancing, and coupling neural behaviours, and correlated with pain relief. An integrated approach based on principal component analysis (PCA) and multiple regression analysis is proposed to integrate the multiple measures and provide a predictive model. This study reveals distinct thalamic rhythms of theta, alpha, high beta and high gamma oscillations correlating with pain relief. The balancing and coupling measures between these neural oscillations were also significantly correlated with pain relief. The study enriches the series research on the function of thalamic neural oscillations in neuropathic pain and relief, and provides a quantitative approach for predicting pain relief by DBS using thalamic neural oscillations. Copyright © 2017 Elsevier Inc. All rights reserved.

In sync: gamma oscillations and emotional memory

PubMed Central

Headley, Drew B.; Paré, Denis

2013-01-01

Emotional experiences leave vivid memories that can last a lifetime. The emotional facilitation of memory has been attributed to the engagement of diffusely projecting neuromodulatory systems that enhance the consolidation of synaptic plasticity in regions activated by the experience. This process requires the propagation of signals between brain regions, and for those signals to induce long-lasting synaptic plasticity. Both of these demands are met by gamma oscillations, which reflect synchronous population activity on a fast timescale (35–120 Hz). Regions known to participate in the formation of emotional memories, such as the basolateral amygdala, also promote gamma-band activation throughout cortical and subcortical circuits. Recent studies have demonstrated that gamma oscillations are enhanced during emotional situations, coherent between regions engaged by salient stimuli, and predict subsequent memory for cues associated with aversive stimuli. Furthermore, neutral stimuli that come to predict emotional events develop enhanced gamma oscillations, reflecting altered processing in the brain, which may underpin how past emotional experiences color future learning and memory. PMID:24319416

In sync: gamma oscillations and emotional memory.

PubMed

Headley, Drew B; Paré, Denis

2013-11-21

Emotional experiences leave vivid memories that can last a lifetime. The emotional facilitation of memory has been attributed to the engagement of diffusely projecting neuromodulatory systems that enhance the consolidation of synaptic plasticity in regions activated by the experience. This process requires the propagation of signals between brain regions, and for those signals to induce long-lasting synaptic plasticity. Both of these demands are met by gamma oscillations, which reflect synchronous population activity on a fast timescale (35-120 Hz). Regions known to participate in the formation of emotional memories, such as the basolateral amygdala, also promote gamma-band activation throughout cortical and subcortical circuits. Recent studies have demonstrated that gamma oscillations are enhanced during emotional situations, coherent between regions engaged by salient stimuli, and predict subsequent memory for cues associated with aversive stimuli. Furthermore, neutral stimuli that come to predict emotional events develop enhanced gamma oscillations, reflecting altered processing in the brain, which may underpin how past emotional experiences color future learning and memory.

Increased Amplitude of Thalamocortical Low-Frequency Oscillations in Patients with Migraine

PubMed Central

Wilcox, Sophie L.; Veggeberg, Rosanna; Noseda, Rodrigo; Burstein, Rami; Borsook, David; Becerra, Lino

2016-01-01

For many years, neurobiological theories have emphasized the importance of neuronal oscillations in the emergence of brain function. At the same time, clinical studies have shown that disturbances or irregularities in brain rhythms may relate to various common neurological conditions, including migraine. Increasing evidence suggests that the CNS plays a fundamental role in the predisposition to develop different forms of headache. Here, we present human imaging data that strongly support the presence of abnormal low-frequency oscillations (LFOs) in thalamocortical networks of patients in the interictal phase of migraine. Our results show that the main source of arrhythmic activity was localized to the higher-order thalamic relays of the medial dorsal nucleus. In addition, spontaneous LFOs in the thalamus were selectively associated with the headache attack frequency, meaning that the varying amplitude of dysrhythmia could predispose patients to recurrent attacks. Rhythmic cortical feedback to the thalamus is a major factor in the amplification of thalamocortical oscillations, making it a strong candidate for influencing neuronal excitability. We further speculate that the intrinsic dynamics of thalamocortical network oscillations are crucial for early sensory processing and therefore could underlie important pathophysiological processes involved in multisensory integration. SIGNIFICANCE STATEMENT In many cases, migraine attacks are thought to begin centrally. A major obstacle to studying intrinsic brain activity has been the identification of the precise anatomical structures and functional networks that are involved in migraine. Here, we present imaging data that strongly support the presence of abnormal low-frequency oscillations in thalamocortical networks of patients in the interictal phase of migraine. This arrhythmic activity was localized to the higher-order thalamic relays of the medial dorsal nucleus and was selectively associated with headache attack frequency. Rhythmic cortical feedback to the thalamus is a major factor in the amplification of thalamocortical oscillations, making it a strong candidate for influencing neuronal excitability and higher-level processes involved in multisensory integration. PMID:27466345

[Mg2+]o/[Ca2+]o determines Ca2+ response at fertilization: tuning of adult phenotype?

PubMed

Ozil, Jean-Pierre; Sainte-Beuve, Thierry; Banrezes, Bernadette

2017-11-01

Alteration of the postnatal phenotype has sparked great concern about the developmental impact of culture media used at fertilization. However, the mechanisms and compounds involved are yet to be determined. Here, we used the Ca 2+ responses from mouse eggs fertilized by ICSI as a dynamic and quantitative marker to understand the role of compounds in egg functioning and establish possible correlations with adult phenotypes. We computed 134 Ca 2+ responses from the first to the last oscillation in media with specific formulations. Analyses demonstrate that eggs generated two times as many Ca 2+ oscillations in KSOM as in M16 media (18.8 ± 7.0 vs 9.2 ± 2.5). Moreover, the time increment of the delay between two consecutive oscillations, named TIbO, is the most sensitive coefficient characterizing the mechanism that paces Ca 2+ oscillations once the egg has been fertilized. Neither doubling external free Ca 2+ nor dispermic fertilization increased significantly the total number of Ca 2+ oscillations. In contrast, removing Mg 2+ from the M16 boosted Ca 2+ oscillations to 54.0 ± 35.2. Hence, [Mg 2+ ] o /[Ca 2+ ] o appears to determine the number, duration and frequency of the Ca 2+ oscillations. These changes were correlated with long-term effects. The rate of female's growth was impacted with the 'KSOM' females having only half the fat deposit of 'M16' females. Moreover, adult animals issued from M16 had significantly smaller brain weight vs 'KSOM' and 'control' animals. TIbO is a new Ca 2+ coefficient that gauges the very early functional impact of culture media. It offers the possibility of establishing correlations with postnatal consequences according to IVF medium formulation.Free French abstract: A French translation of this abstract is freely available at http://www.reproduction-online.org/content/154/5/675/suppl/DC2. © 2017 Society for Reproduction and Fertility.

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

NASA Astrophysics Data System (ADS)

Mikkelsen, Kaare; Imparato, Alberto; Torcini, Alessandro

2013-05-01

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

Remote radio control of insect flight.

PubMed

Sato, Hirotaka; Berry, Christopher W; Peeri, Yoav; Baghoomian, Emen; Casey, Brendan E; Lavella, Gabriel; Vandenbrooks, John M; Harrison, Jon F; Maharbiz, Michel M

2009-01-01

We demonstrated the remote control of insects in free flight via an implantable radio-equipped miniature neural stimulating system. The pronotum mounted system consisted of neural stimulators, muscular stimulators, a radio transceiver-equipped microcontroller and a microbattery. Flight initiation, cessation and elevation control were accomplished through neural stimulus of the brain which elicited, suppressed or modulated wing oscillation. Turns were triggered through the direct muscular stimulus of either of the basalar muscles. We characterized the response times, success rates, and free-flight trajectories elicited by our neural control systems in remotely controlled beetles. We believe this type of technology will open the door to in-flight perturbation and recording of insect flight responses.

Auditory closed-loop stimulation of the sleep slow oscillation enhances memory.

PubMed

Ngo, Hong-Viet V; Martinetz, Thomas; Born, Jan; Mölle, Matthias

2013-05-08

Brain rhythms regulate information processing in different states to enable learning and memory formation. The <1 Hz sleep slow oscillation hallmarks slow-wave sleep and is critical to memory consolidation. Here we show in sleeping humans that auditory stimulation in phase with the ongoing rhythmic occurrence of slow oscillation up states profoundly enhances the slow oscillation rhythm, phase-coupled spindle activity, and, consequently, the consolidation of declarative memory. Stimulation out of phase with the ongoing slow oscillation rhythm remained ineffective. Closed-loop in-phase stimulation provides a straight-forward tool to enhance sleep rhythms and their functional efficacy. Copyright © 2013 Elsevier Inc. All rights reserved.

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.

Decoding magnetoencephalographic rhythmic activity using spectrospatial information.

PubMed

Kauppi, Jukka-Pekka; Parkkonen, Lauri; Hari, Riitta; Hyvärinen, Aapo

2013-12-01

We propose a new data-driven decoding method called Spectral Linear Discriminant Analysis (Spectral LDA) for the analysis of magnetoencephalography (MEG). The method allows investigation of changes in rhythmic neural activity as a result of different stimuli and tasks. The introduced classification model only assumes that each "brain state" can be characterized as a combination of neural sources, each of which shows rhythmic activity at one or several frequency bands. Furthermore, the model allows the oscillation frequencies to be different for each such state. We present decoding results from 9 subjects in a four-category classification problem defined by an experiment involving randomly alternating epochs of auditory, visual and tactile stimuli interspersed with rest periods. The performance of Spectral LDA was very competitive compared with four alternative classifiers based on different assumptions concerning the organization of rhythmic brain activity. In addition, the spectral and spatial patterns extracted automatically on the basis of trained classifiers showed that Spectral LDA offers a novel and interesting way of analyzing spectrospatial oscillatory neural activity across the brain. All the presented classification methods and visualization tools are freely available as a Matlab toolbox. © 2013.

Prediction of general mental ability based on neural oscillation measures of sleep.

PubMed

Bódizs, Róbert; Kis, Tamás; Lázár, Alpár Sándor; Havrán, Linda; Rigó, Péter; Clemens, Zsófia; Halász, Péter

2005-09-01

The usual assessment of general mental ability (or intelligence) is based on performance attained in reasoning and problem-solving tasks. Differences in general mental ability have been associated with event-related neural activity patterns of the wakeful working brain or physical, chemical and electrical brain features measured during wakeful resting conditions. Recent evidences suggest that specific sleep electroencephalogram oscillations are related to wakeful cognitive performances. Our aim is to reveal the relationship between non-rapid eye movement sleep-specific oscillations (the slow oscillation, delta activity, slow and fast sleep spindle density, the grouping of slow and fast sleep spindles) and general mental ability assessed by the Raven Progressive Matrices Test (RPMT). The grouping of fast sleep spindles by the cortical slow oscillation in the left frontopolar derivation (Fp1) as well as the density of fast sleep spindles over the right frontal area (Fp2, F4), correlated positively with general mental ability. Data from those selected electrodes that showed the high correlations with general mental ability explained almost 70% of interindividual variance in RPMT scores. Results suggest that individual differences in general mental ability are reflected in fast sleep spindle-related oscillatory activity measured over the frontal cortex.

The phase of prestimulus alpha oscillations affects tactile perception.

PubMed

Ai, Lei; Ro, Tony

2014-03-01

Previous studies have shown that neural oscillations in the 8- to 12-Hz range influence sensory perception. In the current study, we examined whether both the power and phase of these mu/alpha oscillations predict successful conscious tactile perception. Near-threshold tactile stimuli were applied to the left hand while electroencephalographic (EEG) activity was recorded over the contralateral right somatosensory cortex. We found a significant inverted U-shaped relationship between prestimulus mu/alpha power and detection rate, suggesting that there is an intermediate level of alpha power that is optimal for tactile perception. We also found a significant difference in phase angle concentration at stimulus onset that predicted whether the upcoming tactile stimulus was perceived or missed. As has been shown in the visual system, these findings suggest that these mu/alpha oscillations measured over somatosensory areas exert a strong inhibitory control on tactile perception and that pulsed inhibition by these oscillations shapes the state of brain activity necessary for conscious perception. They further suggest that these common phasic processing mechanisms across different sensory modalities and brain regions may reflect a common underlying encoding principle in perceptual processing that leads to momentary windows of perceptual awareness.

Oxytocin enhances inter-brain synchrony during social coordination in male adults

PubMed Central

Mu, Yan; Guo, Chunyan

2016-01-01

Recent brain imaging research has revealed oxytocin (OT) effects on an individual's brain activity during social interaction but tells little about whether and how OT modulates the coherence of inter-brain activity related to two individuals' coordination behavior. We developed a new real-time coordination game that required two individuals of a dyad to synchronize with a partner (coordination task) or with a computer (control task) by counting in mind rhythmically. Electroencephalography (EEG) was recorded simultaneously from a dyad to examine OT effects on inter-brain synchrony of neural activity during interpersonal coordination. Experiment 1 found that dyads showed smaller interpersonal time lags of counting and greater inter-brain synchrony of alpha-band neural oscillations during the coordination (vs control) task and these effects were reliably observed in female but not male dyads. Moreover, the increased alpha-band inter-brain synchrony predicted better interpersonal behavioral synchrony across all participants. Experiment 2, using a double blind, placebo-controlled between-subjects design, revealed that intranasal OT vs placebo administration in male dyads improved interpersonal behavioral synchrony in both the coordination and control tasks but specifically enhanced alpha-band inter-brain neural oscillations during the coordination task. Our findings provide first evidence that OT enhances inter-brain synchrony in male adults to facilitate social coordination. PMID:27510498

Influence of White and Gray Matter Connections on Endogenous Human Cortical Oscillations

PubMed Central

Hawasli, Ammar H.; Kim, DoHyun; Ledbetter, Noah M.; Dahiya, Sonika; Barbour, Dennis L.; Leuthardt, Eric C.

2016-01-01

Brain oscillations reflect changes in electrical potentials summated across neuronal populations. Low- and high-frequency rhythms have different modulation patterns. Slower rhythms are spatially broad, while faster rhythms are more local. From this observation, we hypothesized that low- and high-frequency oscillations reflect white- and gray-matter communications, respectively, and synchronization between low-frequency phase with high-frequency amplitude represents a mechanism enabling distributed brain-networks to coordinate local processing. Testing this common understanding, we selectively disrupted white or gray matter connections to human cortex while recording surface field potentials. Counter to our original hypotheses, we found that cortex consists of independent oscillatory-units (IOUs) that maintain their own complex endogenous rhythm structure. IOUs are differentially modulated by white and gray matter connections. White-matter connections maintain topographical anatomic heterogeneity (i.e., separable processing in cortical space) and gray-matter connections segregate cortical synchronization patterns (i.e., separable temporal processing through phase-power coupling). Modulation of distinct oscillatory modules enables the functional diversity necessary for complex processing in the human brain. PMID:27445767

Human Brain Activity Patterns beyond the Isoelectric Line of Extreme Deep Coma

PubMed Central

Kroeger, Daniel; Florea, Bogdan; Amzica, Florin

2013-01-01

The electroencephalogram (EEG) reflects brain electrical activity. A flat (isoelectric) EEG, which is usually recorded during very deep coma, is considered to be a turning point between a living brain and a deceased brain. Therefore the isoelectric EEG constitutes, together with evidence of irreversible structural brain damage, one of the criteria for the assessment of brain death. In this study we use EEG recordings for humans on the one hand, and on the other hand double simultaneous intracellular recordings in the cortex and hippocampus, combined with EEG, in cats. They serve to demonstrate that a novel brain phenomenon is observable in both humans and animals during coma that is deeper than the one reflected by the isoelectric EEG, and that this state is characterized by brain activity generated within the hippocampal formation. This new state was induced either by medication applied to postanoxic coma (in human) or by application of high doses of anesthesia (isoflurane in animals) leading to an EEG activity of quasi-rhythmic sharp waves which henceforth we propose to call ν-complexes (Nu-complexes). Using simultaneous intracellular recordings in vivo in the cortex and hippocampus (especially in the CA3 region) we demonstrate that ν-complexes arise in the hippocampus and are subsequently transmitted to the cortex. The genesis of a hippocampal ν-complex depends upon another hippocampal activity, known as ripple activity, which is not overtly detectable at the cortical level. Based on our observations, we propose a scenario of how self-oscillations in hippocampal neurons can lead to a whole brain phenomenon during coma. PMID:24058669

Evaluation of spontaneous low-frequency oscillations in cerebral hemodynamics with time-series red-green-blue images

NASA Astrophysics Data System (ADS)

Nishidate, Izumi; Mustari, Afrina; Nakamura, Naoki; Kawauchi, Satoko; Sato, Shunichi; Sato, Manabu; Kokubo, Yasuaki

2017-02-01

The brain relies on a continuous and adequate supply of blood flow, bringing the nutrients that it needs and removing the waste products of metabolism. It is thus one of the most tightly regulated systems in the body, whereby a whole range of mechanisms act to maintain this supply, despite changes in blood pressure etc. Failure of these mechanisms is found in a number of devastating cerebral diseases, including stroke, vascular dementia and brain injury and trauma. Spontaneous contraction and relaxation of arterioles (and in some instances venules) termed vasomotion has been observed in an extensive variety of tissues and species. Vasomotion has a beneficial effect on tissue oxygenation and enhance blood flow. Although vasomotion is strictly a local phenomenon, the regulation of contractile activity of vascular smooth muscle cells is dependent on the complex interplay between vasodilator and vasoconstrictor stimuli from circulating hormones, neurotransmitters, endothelial derived factors, and blood pressure. Therefore, evaluation of the spontaneous oscillations in cerebral vasculatures might be a useful tool for assessing risk and investigating different treatment strategies in neurological disorders, such as traumatic brain injury, seizure, ischemia, and stroke. In the present study, we newly propose a method to visualize the spontaneous low-frequency oscillation of cerebral blood volume based on the sequential RGB images of exposed brain.

Cloud physics laboratory project science and applications working group

NASA Technical Reports Server (NTRS)

Hung, R. J.

1977-01-01

The conditions of the expansion chamber under zero gravity environment were simulated. The following three branches of fluid mechanics simulation under low gravity environment were accomplished: (1) oscillation of the water droplet which characterizes the nuclear oscillation in nuclear physics, bubble oscillation of two phase flow in chemical engineering, and water drop oscillation in meteorology; (2) rotation of the droplet which characterizes nuclear fission in nuclear physics, formation of binary stars and rotating stars in astrophysics, and breakup of the water droplet in meteorology; and (3) collision and coalescence of the water droplets which characterizes nuclear fusion in nuclear physics and processes of rain formation in meteorology.

Stereotyped high-frequency oscillations discriminate seizure onset zones and critical functional cortex in focal epilepsy.

PubMed

Liu, Su; Gurses, Candan; Sha, Zhiyi; Quach, Michael M; Sencer, Altay; Bebek, Nerses; Curry, Daniel J; Prabhu, Sujit; Tummala, Sudhakar; Henry, Thomas R; Ince, Nuri F

2018-01-30

High-frequency oscillations in local field potentials recorded with intracranial EEG are putative biomarkers of seizure onset zones in epileptic brain. However, localized 80-500 Hz oscillations can also be recorded from normal and non-epileptic cerebral structures. When defined only by rate or frequency, physiological high-frequency oscillations are indistinguishable from pathological ones, which limit their application in epilepsy presurgical planning. We hypothesized that pathological high-frequency oscillations occur in a repetitive fashion with a similar waveform morphology that specifically indicates seizure onset zones. We investigated the waveform patterns of automatically detected high-frequency oscillations in 13 epilepsy patients and five control subjects, with an average of 73 subdural and intracerebral electrodes recorded per patient. The repetitive oscillatory waveforms were identified by using a pipeline of unsupervised machine learning techniques and were then correlated with independently clinician-defined seizure onset zones. Consistently in all patients, the stereotypical high-frequency oscillations with the highest degree of waveform similarity were localized within the seizure onset zones only, whereas the channels generating high-frequency oscillations embedded in random waveforms were found in the functional regions independent from the epileptogenic locations. The repetitive waveform pattern was more evident in fast ripples compared to ripples, suggesting a potential association between waveform repetition and the underlying pathological network. Our findings provided a new tool for the interpretation of pathological high-frequency oscillations that can be efficiently applied to distinguish seizure onset zones from functionally important sites, which is a critical step towards the translation of these signature events into valid clinical biomarkers.awx374media15721572971001. © The Author(s) (2018). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

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

Glutamic Acid as Enhancer of Protein Synthesis Kinetics in Hepatocytes from Old Rats.

PubMed

Brodsky, V Y; Malchenko, L A; Butorina, N N; Lazarev Konchenko, D S; Zvezdina, N D; Dubovaya, T K

2017-08-01

Dense cultures of hepatocytes from old rats (~2 years old, body weight 530-610 g) are different from similar cultures of hepatocytes from young rats by the low amplitude of protein synthesis rhythm. Addition of glutamic acid (0.2, 0.4, or 0.6 mg/ml) into the culture medium with hepatocytes of old rats resulted in increase in the oscillation amplitudes of the protein synthesis rhythm to the level of young rats. A similar action of glutamic acid on the protein synthesis kinetics was observed in vivo after feeding old rats with glutamic acid. Inhibition of metabotropic receptors of glutamic acid with α-methyl-4-carboxyphenylglycine (0.01 mg/ml) abolished the effect of glutamic acid. The amplitude of oscillation of the protein synthesis rhythm in a cell population characterizes synchronization of individual oscillations caused by direct cell-cell communications. Hence, glutamic acid, acting as a receptor-dependent transmitter, enhanced direct cell-cell communications of hepatocytes that were decreased with aging. As differentiated from other known membrane signaling factors (gangliosides, norepinephrine, serotonin, dopamine), glutamic acid can penetrate into the brain and thus influence the communications and protein synthesis kinetics that are disturbed with aging not only in hepatocytes, but also in neurons.

Input-dependent modulation of MEG gamma oscillations reflects gain control in the visual cortex.

PubMed

Orekhova, Elena V; Sysoeva, Olga V; Schneiderman, Justin F; Lundström, Sebastian; Galuta, Ilia A; Goiaeva, Dzerasa E; Prokofyev, Andrey O; Riaz, Bushra; Keeler, Courtney; Hadjikhani, Nouchine; Gillberg, Christopher; Stroganova, Tatiana A

2018-05-31

Gamma-band oscillations arise from the interplay between neural excitation (E) and inhibition (I) and may provide a non-invasive window into the state of cortical circuitry. A bell-shaped modulation of gamma response power by increasing the intensity of sensory input was observed in animals and is thought to reflect neural gain control. Here we sought to find a similar input-output relationship in humans with MEG via modulating the intensity of a visual stimulation by changing the velocity/temporal-frequency of visual motion. In the first experiment, adult participants observed static and moving gratings. The frequency of the MEG gamma response monotonically increased with motion velocity whereas power followed a bell-shape. In the second experiment, on a large group of children and adults, we found that despite drastic developmental changes in frequency and power of gamma oscillations, the relative suppression at high motion velocities was scaled to the same range of values across the life-span. In light of animal and modeling studies, the modulation of gamma power and frequency at high stimulation intensities characterizes the capacity of inhibitory neurons to counterbalance increasing excitation in visual networks. Gamma suppression may thus provide a non-invasive measure of inhibitory-based gain control in the healthy and diseased brain.

Self-regulation of brain rhythms in the precuneus: a novel BCI paradigm for patients with ALS

NASA Astrophysics Data System (ADS)

Fomina, Tatiana; Lohmann, Gabriele; Erb, Michael; Ethofer, Thomas; Schölkopf, Bernhard; Grosse-Wentrup, Moritz

2016-12-01

Objective. Electroencephalographic (EEG) brain-computer interfaces (BCIs) hold promise in restoring communication for patients with completely locked-in stage amyotrophic lateral sclerosis (ALS). However, these patients cannot use existing EEG-based BCIs, arguably because such systems rely on brain processes that are impaired in the late stages of ALS. In this work, we introduce a novel BCI designed for patients in late stages of ALS based on high-level cognitive processes that are less likely to be affected by ALS. Approach. We trained two ALS patients via EEG-based neurofeedback to use self-regulation of theta or gamma oscillations in the precuneus for basic communication. Because there is a tight connection between the precuneus and consciousness, precuneus oscillations are arguably generated by high-level cognitive processes, which are less likely to be affected by ALS than processes linked to the peripheral nervous system. Main results. Both patients learned to self-regulate their precuneus oscillations and achieved stable online decoding accuracy over the course of disease progression. One patient achieved a mean online decoding accuracy in a binary decision task of 70.55% across 26 training sessions, and the other patient achieved 59.44% across 16 training sessions. We provide empirical evidence that these oscillations were cortical in nature and originated from the intersection of the precuneus, cuneus, and posterior cingulate. Significance. Our results establish that ALS patients can employ self-regulation of precuneus oscillations for communication. Such a BCI is likely to be available to ALS patients as long as their consciousness supports communication.

Transmission of arterial oxygen partial pressure oscillations to the cerebral microcirculation in a porcine model of acute lung injury caused by cyclic recruitment and derecruitment.

PubMed

Klein, K U; Boehme, S; Hartmann, E K; Szczyrba, M; Heylen, L; Liu, T; David, M; Werner, C; Markstaller, K; Engelhard, K

2013-02-01

Cyclic recruitment and derecruitment (R/D) play a key role in the pathomechanism of acute lung injury (ALI) leading to respiration-dependent oscillations of arterial partial pressure of oxygen (Pa(O(2))). These Pa(O(2)) oscillations could also be forwarded to the cerebral microcirculation. In 12 pigs, partial pressure of oxygen was measured in the thoracic aorta (Pa(O(2))) and subcortical cerebral tissue (Pbr(O(2))). Cerebral cortical haemoglobin oxygen saturation (Sbr(O(2))), cerebral blood flow (CBF), and peripheral haemoglobin saturation (Sp(O(2))) were assessed by spectroscopy and laser Doppler flowmetry. Measurements at different fractions of inspired oxygen (F(I(O(2)))) were performed at baseline and during cyclic R/D. frequency domain analysis, the Mann-Whitney test, linear models to test the influence of Pa(O(2)) and systolic arterial pressure (SAP) oscillations on cerebral measurements. Parameters [mean (SD)] remained stable during baseline. Pa(O(2)) oscillations [10.6 (8) kPa, phase(reference)], systemic arterial pressure (SAP) oscillations [20 (9) mm Hg, phase(Pa(O(2))-SAP) -33 (72)°], and Sp(O(2))oscillations [1.9 (1.7)%, phase(Pa(O(2))-Sp(O(2))) 264 (72)°] were detected during lung R/D at 1.0. Pa(O(2)) oscillations decreased [2.7 (3.5) kPa, P=0.0008] and Sp(O(2)) oscillations increased [6.8 (3.9)%, P=0.0014] at F(I(O(2))) 0.3. In the brain, synchronized Pbr(O(2)) oscillations [0.6 (0.4) kPa, phase(Pa(O(2))-Pbr(O(2))) 90 (39)°], Sbr(O(2)) oscillations [4.1 (1.5)%, phase(Pa(O(2))-Sbr(O(2))) 182 (54)°], and CBF oscillations [198 (176) AU, phase(Pa(O(2))-CBF) 201 (63)°] occurred that were dependent on Pa(O(2)) and SAP oscillations. Pa(O(2)) oscillations caused by cyclic R/D are transmitted to the cerebral microcirculation in a porcine model of ALI. These cyclic oxygen alterations could play a role in the crosstalk of acute lung and brain injury.

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.

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.

Sensitivity to external signals and synchronization properties of a non-isochronous auto-oscillator with delayed feedback

PubMed Central

Tiberkevich, Vasil S.; Khymyn, Roman S.; Tang, Hong X.; Slavin, Andrei N.

2014-01-01

For auto-oscillators of different nature (e.g. active cells in a human heart under the action of a pacemaker, neurons in brain, spin-torque nano-oscillators, micro and nano-mechanical oscillators, or generating Josephson junctions) a critically important property is their ability to synchronize with each other. The synchronization properties of an auto oscillator are directly related to its sensitivity to external signals. Here we demonstrate that a non-isochronous (having generation frequency dependent on the amplitude) auto-oscillator with delayed feedback can have an extremely high sensitivity to external signals and unusually large width of the phase-locking band near the boundary of the stable auto-oscillation regime. This property could be used for the development of synchronized arrays of non-isochronous auto-oscillators in physics and engineering, and, for instance, might bring a better fundamental understanding of ways to control a heart arrythmia in medicine. PMID:24464086

Deep Brain Stimulation Frequency—A Divining Rod for New and Novel Concepts of Nervous System Function and Therapy

PubMed Central

Montgomery, Erwin B.; He, Huang

2016-01-01

The efficacy of Deep Brain Stimulation (DBS) for an expanding array of neurological and psychiatric disorders demonstrates directly that DBS affects the basic electroneurophysiological mechanisms of the brain. The increasing array of active electrode configurations, stimulation currents, pulse widths, frequencies, and pulse patterns provides valuable tools to probe electroneurophysiological mechanisms. The extension of basic electroneurophysiological and anatomical concepts using sophisticated computational modeling and simulation has provided relatively straightforward explanations of all the DBS parameters except frequency. This article summarizes current thought about frequency and relevant observations. Current methodological and conceptual errors are critically examined in the hope that future work will not replicate these errors. One possible alternative theory is presented to provide a contrast to many current theories. DBS, conceptually, is a noisy discrete oscillator interacting with the basal ganglia–thalamic–cortical system of multiple re-entrant, discrete oscillators. Implications for positive and negative resonance, stochastic resonance and coherence, noisy synchronization, and holographic memory (related to movement generation) are presented. The time course of DBS neuronal responses demonstrates evolution of the DBS response consistent with the dynamics of re-entrant mechanisms. Finally, computational modeling demonstrates identical dynamics as seen by neuronal activities recorded from human and nonhuman primates, illustrating the differences of discrete from continuous harmonic oscillators and the power of conceptualizing the nervous system as composed on interacting discrete nonlinear oscillators. PMID:27548234

Fast Dynamical Coupling Enhances Frequency Adaptation of Oscillators for Robotic Locomotion Control

PubMed Central

Nachstedt, Timo; Tetzlaff, Christian; Manoonpong, Poramate

2017-01-01

Rhythmic neural signals serve as basis of many brain processes, in particular of locomotion control and generation of rhythmic movements. It has been found that specific neural circuits, named central pattern generators (CPGs), are able to autonomously produce such rhythmic activities. In order to tune, shape and coordinate the produced rhythmic activity, CPGs require sensory feedback, i.e., external signals. Nonlinear oscillators are a standard model of CPGs and are used in various robotic applications. A special class of nonlinear oscillators are adaptive frequency oscillators (AFOs). AFOs are able to adapt their frequency toward the frequency of an external periodic signal and to keep this learned frequency once the external signal vanishes. AFOs have been successfully used, for instance, for resonant tuning of robotic locomotion control. However, the choice of parameters for a standard AFO is characterized by a trade-off between the speed of the adaptation and its precision and, additionally, is strongly dependent on the range of frequencies the AFO is confronted with. As a result, AFOs are typically tuned such that they require a comparably long time for their adaptation. To overcome the problem, here, we improve the standard AFO by introducing a novel adaptation mechanism based on dynamical coupling strengths. The dynamical adaptation mechanism enhances both the speed and precision of the frequency adaptation. In contrast to standard AFOs, in this system, the interplay of dynamics on short and long time scales enables fast as well as precise adaptation of the oscillator for a wide range of frequencies. Amongst others, a very natural implementation of this mechanism is in terms of neural networks. The proposed system enables robotic applications which require fast retuning of locomotion control in order to react to environmental changes or conditions. PMID:28377710

Brain coordination dynamics: True and false faces of phase synchrony and metastability

PubMed Central

Tognoli, Emmanuelle; Kelso, J.A. Scott

2009-01-01

Understanding the coordination of multiple parts in a complex system such as the brain is a fundamental challenge. We present a theoretical model of cortical coordination dynamics that shows how brain areas may cooperate (integration) and at the same time retain their functional specificity (segregation). This model expresses a range of desirable properties that the brain is known to exhibit, including self-organization, multi-functionality, metastability and switching. Empirically, the model motivates a thorough investigation of collective phase relationships among brain oscillations in neurophysiological data. The most serious obstacle to interpreting coupled oscillations as genuine evidence of inter-areal coordination in the brain stems from volume conduction of electrical fields. Spurious coupling due to volume conduction gives rise to zero-lag (inphase) and antiphase synchronization whose magnitude and persistence obscure the subtle expression of real synchrony. Through forward modeling and the help of a novel colorimetric method, we show how true synchronization can be deciphered from continuous EEG patterns. Developing empirical efforts along the lines of continuous EEG analysis constitutes a major response to the challenge of understanding how different brain areas work together. Key predictions of cortical coordination dynamics can now be tested thereby revealing the essential modus operandi of the intact living brain. PMID:18938209

Alpha Power Modulates Perception Independently of Endogenous Factors.

PubMed

Brüers, Sasskia; VanRullen, Rufin

2018-01-01

Oscillations are ubiquitous in the brain. Alpha oscillations in particular have been proposed to play an important role in sensory perception. Past studies have shown that the power of ongoing EEG oscillations in the alpha band is negatively correlated with visual outcome. Moreover, it also co-varies with other endogenous factors such as attention, vigilance, or alertness. In turn, these endogenous factors influence visual perception. Therefore, it remains unclear how much of the relation between alpha and perception is indirectly mediated by such endogenous factors, and how much reflects a direct causal influence of alpha rhythms on sensory neural processing. We propose to disentangle the direct from the indirect causal routes by introducing modulations of alpha power, independently of any fluctuations in endogenous factors. To this end, we use white-noise sequences to constrain the brain activity of 20 participants. The cross-correlation between the white-noise sequences and the concurrently recorded EEG reveals the impulse response function (IRF), a model of the systematic relationship between stimulation and brain response. These IRFs are then used to reconstruct rather than record the brain activity linked with new random sequences (by convolution). Interestingly, this reconstructed EEG only contains information about oscillations directly linked to the white-noise stimulation; fluctuations in attention and other endogenous factors may still modulate brain alpha rhythms during the task, but our reconstructed EEG is immune to these factors. We found that the detection of near-perceptual threshold targets embedded within these new white-noise sequences depended on the power of the ~10 Hz reconstructed EEG over parieto-occipital channels. Around the time of presentation, higher power led to poorer performance. Thus, fluctuations in alpha power, induced here by random luminance sequences, can directly influence perception: the relation between alpha power and perception is not a mere consequence of fluctuations in endogenous factors.

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.

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

Oxytocin enhances inter-brain synchrony during social coordination in male adults.

PubMed

Mu, Yan; Guo, Chunyan; Han, Shihui

2016-12-01

Recent brain imaging research has revealed oxytocin (OT) effects on an individual's brain activity during social interaction but tells little about whether and how OT modulates the coherence of inter-brain activity related to two individuals' coordination behavior. We developed a new real-time coordination game that required two individuals of a dyad to synchronize with a partner (coordination task) or with a computer (control task) by counting in mind rhythmically. Electroencephalography (EEG) was recorded simultaneously from a dyad to examine OT effects on inter-brain synchrony of neural activity during interpersonal coordination. Experiment 1 found that dyads showed smaller interpersonal time lags of counting and greater inter-brain synchrony of alpha-band neural oscillations during the coordination (vs control) task and these effects were reliably observed in female but not male dyads. Moreover, the increased alpha-band inter-brain synchrony predicted better interpersonal behavioral synchrony across all participants. Experiment 2, using a double blind, placebo-controlled between-subjects design, revealed that intranasal OT vs placebo administration in male dyads improved interpersonal behavioral synchrony in both the coordination and control tasks but specifically enhanced alpha-band inter-brain neural oscillations during the coordination task. Our findings provide first evidence that OT enhances inter-brain synchrony in male adults to facilitate social coordination. © The Author (2016). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Vocal and visual stimulation, congruence and lateralization affect brain oscillations in interspecies emotional positive and negative interactions.

PubMed

Balconi, Michela; Vanutelli, Maria Elide

2016-01-01

The present research explored the effect of cross-modal integration of emotional cues (auditory and visual (AV)) compared with only visual (V) emotional cues in observing interspecies interactions. The brain activity was monitored when subjects processed AV and V situations, which represented an emotional (positive or negative), interspecies (human-animal) interaction. Congruence (emotionally congruous or incongruous visual and auditory patterns) was also modulated. electroencephalography brain oscillations (from delta to beta) were analyzed and the cortical source localization (by standardized Low Resolution Brain Electromagnetic Tomography) was applied to the data. Frequency band (mainly low-frequency delta and theta) showed a significant brain activity increasing in response to negative compared to positive interactions within the right hemisphere. Moreover, differences were found based on stimulation type, with an increased effect for AV compared with V. Finally, delta band supported a lateralized right dorsolateral prefrontal cortex (DLPFC) activity in response to negative and incongruous interspecies interactions, mainly for AV. The contribution of cross-modality, congruence (incongruous patterns), and lateralization (right DLPFC) in response to interspecies emotional interactions was discussed at light of a "negative lateralized effect."

Decoding English Alphabet Letters Using EEG Phase Information

PubMed Central

Wang, YiYan; Wang, Pingxiao; Yu, Yuguo

2018-01-01

Increasing evidence indicates that the phase pattern and power of the low frequency oscillations of brain electroencephalograms (EEG) contain significant information during the human cognition of sensory signals such as auditory and visual stimuli. Here, we investigate whether and how the letters of the alphabet can be directly decoded from EEG phase and power data. In addition, we investigate how different band oscillations contribute to the classification and determine the critical time periods. An English letter recognition task was assigned, and statistical analyses were conducted to decode the EEG signal corresponding to each letter visualized on a computer screen. We applied support vector machine (SVM) with gradient descent method to learn the potential features for classification. It was observed that the EEG phase signals have a higher decoding accuracy than the oscillation power information. Low-frequency theta and alpha oscillations have phase information with higher accuracy than do other bands. The decoding performance was best when the analysis period began from 180 to 380 ms after stimulus presentation, especially in the lateral occipital and posterior temporal scalp regions (PO7 and PO8). These results may provide a new approach for brain-computer interface techniques (BCI) and may deepen our understanding of EEG oscillations in cognition. PMID:29467615

“Too Many betas do not Spoil the Broth”: The Role of Beta Brain Oscillations in Language Processing

PubMed Central

Weiss, Sabine; Mueller, Horst M.

2012-01-01

Over the past 20 years, brain oscillations have proven to be a gateway to the understanding of cognitive processes. It has been shown that different neurocognitive aspects of language processing are associated with brain oscillations at various frequencies. Frequencies in the beta range (13–30 Hz) turned out to be particularly important with respect to cognitive and linguistic manipulations during language processing. Beta activity has been involved in higher-order linguistic functions such as the discrimination of word categories and the retrieval of action semantics as well as semantic memory, and syntactic binding processes, which support meaning construction during sentence processing. From a neurophysiological point of view, the important role of the beta frequencies for such a complex cognitive task as language processing seems reasonable. Experimental evidence suggests that frequencies in the beta range are ideal for maintaining and preserving the activity of neuronal assemblies over time. In particular, recent computational and experimental evidence suggest that beta frequencies are important for linking past and present input and the detection of novelty of stimuli, which are essential processes for language perception as well as production. In addition, the beta frequency’s role in the formation of cell assemblies underlying short-term memory seems indispensable for language analysis. Probably the most important point is the well-known relation of beta oscillations with motor processes. It can be speculated that beta activities reflect the close relationship between language comprehension and motor functions, which is one of the core claims of current theories on embodied cognition. In this article, the importance of beta oscillations for language processing is reviewed based both on findings in psychophysiological and neurophysiological literature. PMID:22737138

Multidimensional analysis of the abnormal neural oscillations associated with lexical processing in schizophrenia.

PubMed

Xu, Tingting; Stephane, Massoud; Parhi, Keshab K

2013-04-01

The neural mechanisms of language abnormalities, the core symptoms in schizophrenia, remain unclear. In this study, a new experimental paradigm, combining magnetoencephalography (MEG) techniques and machine intelligence methodologies, was designed to gain knowledge about the frequency, brain location, and time of occurrence of the neural oscillations that are associated with lexical processing in schizophrenia. The 248-channel MEG recordings were obtained from 12 patients with schizophrenia and 10 healthy controls, during a lexical processing task, where the patients discriminated correct from incorrect lexical stimuli that were visually presented. Event-related desynchronization/synchronization (ERD/ERS) was computed along the frequency, time, and space dimensions combined, that resulted in a large spectral-spatial-temporal ERD/ERS feature set. Machine intelligence techniques were then applied to select a small subset of oscillation patterns that are abnormal in patients with schizophrenia, according to their discriminating power in patient and control classification. Patients with schizophrenia showed abnormal ERD/ERS patterns during both lexical encoding and post-encoding periods. The top-ranked features were located at the occipital and left frontal-temporal areas, and covered a wide frequency range, including δ (1-4 Hz), α (8-12 Hz), β (12-32 Hz), and γ (32-48 Hz) bands. These top features could discriminate the patient group from the control group with 90.91% high accuracy, which demonstrates significant brain oscillation abnormalities in patients with schizophrenia at the specific frequency, time, and brain location indicated by these top features. As neural oscillation abnormality may be due to the mechanisms of the disease, the spectral, spatial, and temporal content of the discriminating features can offer useful information for helping understand the physiological basis of the language disorder in schizophrenia, as well as the pathology of the disease itself.

Spectral spatiotemporal imaging of cortical oscillations and interactions in the human brain

PubMed Central

Lin, Fa-Hsuan; Witzel, Thomas; Hämäläinen, Matti S.; Dale, Anders M.; Belliveau, John W.; Stufflebeam, Steven M.

2010-01-01

This paper presents a computationally efficient source estimation algorithm that localizes cortical oscillations and their phase relationships. The proposed method employs wavelet-transformed magnetoencephalography (MEG) data and uses anatomical MRI to constrain the current locations to the cortical mantle. In addition, the locations of the sources can be further confined with the help of functional MRI (fMRI) data. As a result, we obtain spatiotemporal maps of spectral power and phase relationships. As an example, we show how the phase locking value (PLV), that is, the trial-by-trial phase relationship between the stimulus and response, can be imaged on the cortex. We apply the method to spontaneous, evoked, and driven cortical oscillations measured with MEG. We test the method of combining MEG, structural MRI, and fMRI using simulated cortical oscillations along Heschl’s gyrus (HG). We also analyze sustained auditory gamma-band neuromagnetic fields from MEG and fMRI measurements. Our results show that combining the MEG recording with fMRI improves source localization for the non-noise-normalized wavelet power. In contrast, noise-normalized spectral power or PLV localization may not benefit from the fMRI constraint. We show that if the thresholds are not properly chosen, noise-normalized spectral power or PLV estimates may contain false (phantom) sources, independent of the inclusion of the fMRI prior information. The proposed algorithm can be used for evoked MEG/EEG and block-designed or event-related fMRI paradigms, or for spontaneous MEG data sets. Spectral spatiotemporal imaging of cortical oscillations and interactions in the human brain can provide further understanding of large-scale neural activity and communication between different brain regions. PMID:15488408

Curing the Epilepsies: The Promise of Research

MedlinePlus

... Using microelectrodes, researchers are able to better characterize high-frequency oscillations (HFOs). Abnormal HFOs have been linked to ... Using microelectrodes, researchers are able to better characterize high-frequency oscillations. Top Develop New Animal Models for Studying ...

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

PubMed Central

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

2016-01-01

Abstract The processes of normal aging and aging-related pathologies subject the brain to an active re-organization of its brain networks. Among these, the default-mode network (DMN) is consistently implicated with a demonstrated reduction in functional connectivity within the network. However, no clear stipulation on the underlying mechanisms of the de-synchronization has yet been provided. In this study, we examined the spectral distribution of the intrinsic low-frequency oscillations (LFOs) of the DMN sub-networks in populations of young normals, older subjects, and acute and subacute ischemic stroke patients. The DMN sub-networks were derived using a mid-order group independent component analysis with 117 eyes-closed resting-state functional magnetic resonance imaging (rs-fMRI) sessions from volunteers in those population groups, isolating three robust components of the DMN among other resting-state networks. The posterior component of the DMN presented noticeable differences. Measures of amplitude of low-frequency fluctuation (ALFF) and fractional ALFF (fALFF) of the network component demonstrated a decrease in resting-state cortical oscillation power in the elderly (normal and patient), specifically in the slow-5 (0.01–0.027 Hz) range of oscillations. Furthermore, the contribution of the slow-5 oscillations during the resting state was diminished for a greater influence of the slow-4 (0.027–0.073 Hz) oscillations in the subacute stroke group, not only suggesting a vulnerability of the slow-5 oscillations to disruption but also indicating a change in the distribution of the oscillations within the resting-state frequencies. The reduction of network slow-5 fALFF in the posterior DMN component was found to present a potential association with behavioral measures, suggesting a brain–behavior relationship to those oscillations, with this change in behavior potentially resulting from an altered network integrity induced by a weakening of the slow-5 oscillations during the resting state. The repeated identification of those frequencies in the disruption of DMN stresses a critical role of the slow-5 oscillations in network disruption, and it accentuates the importance of managing those oscillations in the health of the DMN. PMID:27130180

Study of Complex Plasmas with Magnetic Dipoles

DTIC Science & Technology

2017-10-10

variety of collective behavior manifested in a plasma, especially oscillations or waves characterized by high frequency accompanied by the motion of...behavior manifested in a plasma, especially oscillations or waves characterized by high frequency accompanied by the motion of electrons and/or ions...particles characterized by extremely low frequency modes and the collection of plasma particles characterized by high frequency modes. The interaction of

Neurofeedback Tunes Scale-Free Dynamics in Spontaneous Brain Activity.

PubMed

Ros, T; Frewen, P; Théberge, J; Michela, A; Kluetsch, R; Mueller, A; Candrian, G; Jetly, R; Vuilleumier, P; Lanius, R A

2017-10-01

Brain oscillations exhibit long-range temporal correlations (LRTCs), which reflect the regularity of their fluctuations: low values representing more random (decorrelated) while high values more persistent (correlated) dynamics. LRTCs constitute supporting evidence that the brain operates near criticality, a state where neuronal activities are balanced between order and randomness. Here, healthy adults used closed-loop brain training (neurofeedback, NFB) to reduce the amplitude of alpha oscillations, producing a significant increase in spontaneous LRTCs post-training. This effect was reproduced in patients with post-traumatic stress disorder, where abnormally random dynamics were reversed by NFB, correlating with significant improvements in hyperarousal. Notably, regions manifesting abnormally low LRTCs (i.e., excessive randomness) normalized toward healthy population levels, consistent with theoretical predictions about self-organized criticality. Hence, when exposed to appropriate training, spontaneous cortical activity reveals a residual capacity for "self-tuning" its own temporal complexity, despite manifesting the abnormal dynamics seen in individuals with psychiatric disorder. Lastly, we observed an inverse-U relationship between strength of LRTC and oscillation amplitude, suggesting a breakdown of long-range dependence at high/low synchronization extremes, in line with recent computational models. Together, our findings offer a broader mechanistic framework for motivating research and clinical applications of NFB, encompassing disorders with perturbed LRTCs. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Recalling and forgetting dreams: theta and alpha oscillations during sleep predict subsequent dream recall.

PubMed

Marzano, Cristina; Ferrara, Michele; Mauro, Federica; Moroni, Fabio; Gorgoni, Maurizio; Tempesta, Daniela; Cipolli, Carlo; De Gennaro, Luigi

2011-05-04

Under the assumption that dream recall is a peculiar form of declarative memory, we have hypothesized that (1) the encoding of dream contents during sleep should share some electrophysiological mechanisms with the encoding of episodic memories of the awake brain and (2) recalling a dream(s) after awakening from non-rapid eye movement (NREM) and rapid eye movement (REM) sleep should be associated with different brain oscillations. Here, we report that cortical brain oscillations of human sleep are predictive of successful dream recall. In particular, after morning awakening from REM sleep, a higher frontal 5-7 Hz (theta) activity was associated with successful dream recall. This finding mirrors the increase in frontal theta activity during successful encoding of episodic memories in wakefulness. Moreover, in keeping with the different EEG background, a different predictive relationship was found after awakening from stage 2 NREM sleep. Specifically, a lower 8-12 Hz (alpha) oscillatory activity of the right temporal area was associated with a successful dream recall. These findings provide the first evidence of univocal cortical electroencephalographic correlates of dream recall, suggesting that the neurophysiological mechanisms underlying the encoding and recall of episodic memories may remain the same across different states of consciousness.

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

PubMed

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

2009-01-01

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

DCCA cross-correlation coefficients reveals the change of both synchronization and oscillation in EEG of Alzheimer disease patients

NASA Astrophysics Data System (ADS)

Chen, Yingyuan; Cai, Lihui; Wang, Ruofan; Song, Zhenxi; Deng, Bin; Wang, Jiang; Yu, Haitao

2018-01-01

Alzheimer's disease (AD) is a degenerative disorder of neural system that affects mainly the older population. Recently, many researches show that the EEG of AD patients can be characterized by EEG slowing, enhanced complexity of the EEG signals, and EEG synchrony. In order to examine the neural synchrony at multi scales, and to find a biomarker that help detecting AD in diagnosis, detrended cross-correlation analysis (DCCA) of EEG signals is applied in this paper. Several parameters, namely DCCA coefficients in the whole brain, DCCA coefficients at a specific scale, maximum DCCA coefficient over the span of all time scales and the corresponding scale of such coefficients, were extracted to examine the synchronization, respectively. The results show that DCCA coefficients have a trend of increase as scale increases, and decreases as electrode distance increases. Comparing DCCA coefficients in AD patients with healthy controls, a decrease of synchronization in the whole brain, and a bigger scale corresponding to maximum correlation is discovered in AD patients. The change of max-correlation scale may relate to the slowing of oscillatory activities. Linear combination of max DCCA coefficient and max-correlation scale reaches a classification accuracy of 90%. From the above results, it is reasonable to conclude that DCCA coefficient reveals the change of both oscillation and synchrony in AD, and thus is a powerful tool to differentiate AD patients from healthy elderly individuals.

Stochastic process of pragmatic information for 2D spiral wave turbulence in globally and locally coupled Alief-Panfilov oscillators

NASA Astrophysics Data System (ADS)

Kuwahara, Jun; Miyata, Hajime; Konno, Hidetoshi

2017-09-01

Recently, complex dynamics of globally coupled oscillators have been attracting many researcher's attentions. In spite of their numerous studies, their features of nonlinear oscillator systems with global and local couplings in two-dimension (2D) are not understood fully. The paper focuses on 2D states of coherent, clustered and chaotic oscillation especially under the effect of negative global coupling (NGC) in 2D Alief-Panfilov model. It is found that the tuning NGC can cause various new coupling-parameter dependency on the features of oscillations. Then quantitative characterization of various states of oscillations (so called spiral wave turbulence) is examined by using the pragmatic information (PI) which have been utilized in analyzing multimode laser, solar activity and neuronal systems. It is demonstrated that the dynamics of the PI for various oscillations can be characterized successfully by the Hyper-Gamma stochastic process.

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

PubMed Central

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

2017-01-01

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

Resting state cortical oscillations of patients with Parkinson disease and with and without subthalamic deep brain stimulation: a magnetoencephalography study.

PubMed

Cao, Chunyan; Li, Dianyou; Jiang, Tianxiao; Ince, Nuri Firat; Zhan, Shikun; Zhang, Jing; Sha, Zhiyi; Sun, Bomin

2015-04-01

In this study, we investigate the modification to cortical oscillations of patients with Parkinson disease (PD) by subthalamic deep brain stimulation (STN-DBS). Spontaneous cortical oscillations of patients with PD were recorded with magnetoencephalography during on and off subthalamic nucleus deep brain stimulation states. Several features such as average frequency, average power, and relative subband power in regions of interest were extracted in the frequency domain, and these features were correlated with Unified Parkinson Disease Rating Scale III evaluation. The same features were also investigated in patients with PD without surgery and healthy controls. Patients with Parkinson disease without surgery compared with healthy controls had a significantly lower average frequency and an increased average power in 1 to 48 Hz range in whole cortex. Higher relative power in theta and simultaneous decrease in beta and gamma over temporal and occipital were also observed in patients with PD. The Unified Parkinson Disease Rating Scale III rigidity score correlated with the average frequency and with the relative power of beta and gamma in frontal areas. During subthalamic nucleus deep brain stimulation, the average frequency increased significantly when stimulation was on compared with off state. In addition, the relative power dropped in delta, whereas it rose in beta over the whole cortex. Through the course of stimulation, the Unified Parkinson Disease Rating Scale III rigidity and tremor scores correlated with the relative power of alpha over left parietal. Subthalamic nucleus deep brain stimulation improves the symptoms of PD by suppressing the synchronization of alpha rhythm in somatomotor region.

Functional Peptidomics: Stimulus- and Time-of-Day-Specific Peptide Release in the Mammalian Circadian Clock.

PubMed

Atkins, Norman; Ren, Shifang; Hatcher, Nathan; Burgoon, Penny W; Mitchell, Jennifer W; Sweedler, Jonathan V; Gillette, Martha U

2018-06-20

Daily oscillations of brain and body states are under complex temporal modulation by environmental light and the hypothalamic suprachiasmatic nucleus (SCN), the master circadian clock. To better understand mediators of differential temporal modulation, we characterize neuropeptide releasate profiles by nonselective capture of secreted neuropeptides in an optic nerve horizontal SCN brain slice model. Releasates are collected following electrophysiological stimulation of the optic nerve/retinohypothalamic tract under conditions that alter the phase of the SCN activity state. Secreted neuropeptides are identified by intact mass via matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS). We found time-of-day-specific suites of peptides released downstream of optic nerve stimulation. Peptide release was modified differentially with respect to time-of-day by stimulus parameters and by inhibitors of glutamatergic or PACAPergic neurotransmission. The results suggest that SCN physiology is modulated by differential peptide release of both known and unexpected peptides that communicate time-of-day-specific photic signals via previously unreported neuropeptide signatures.

A dynamical systems approach for estimating phase interactions between rhythms of different frequencies from experimental data.

PubMed

Onojima, Takayuki; Goto, Takahiro; Mizuhara, Hiroaki; Aoyagi, Toshio

2018-01-01

Synchronization of neural oscillations as a mechanism of brain function is attracting increasing attention. Neural oscillation is a rhythmic neural activity that can be easily observed by noninvasive electroencephalography (EEG). Neural oscillations show the same frequency and cross-frequency synchronization for various cognitive and perceptual functions. However, it is unclear how this neural synchronization is achieved by a dynamical system. If neural oscillations are weakly coupled oscillators, the dynamics of neural synchronization can be described theoretically using a phase oscillator model. We propose an estimation method to identify the phase oscillator model from real data of cross-frequency synchronized activities. The proposed method can estimate the coupling function governing the properties of synchronization. Furthermore, we examine the reliability of the proposed method using time-series data obtained from numerical simulation and an electronic circuit experiment, and show that our method can estimate the coupling function correctly. Finally, we estimate the coupling function between EEG oscillation and the speech sound envelope, and discuss the validity of these results.

Dynamics of three coupled van der Pol oscillators with application to circadian rhythms

NASA Astrophysics Data System (ADS)

Rompala, Kevin; Rand, Richard; Howland, Howard

2007-08-01

In this work we study a system of three van der Pol oscillators. Two of the oscillators are identical, and are not directly coupled to each other, but rather are coupled via the third oscillator. We investigate the existence of the in-phase mode in which the two identical oscillators have the same behavior. To this end we use the two variable expansion perturbation method (also known as multiple scales) to obtain a slow flow, which we then analyze using the computer algebra system MACSYMA and the numerical bifurcation software AUTO. Our motivation for studying this system comes from the presence of circadian rhythms in the chemistry of the eyes. We model the circadian oscillator in each eye as a van der Pol oscillator. Although there is no direct connection between the two eyes, they are both connected to the brain, especially to the pineal gland, which is here represented by a third van der Pol oscillator.

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

PubMed

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

2013-05-15

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

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

Characterization of 720 and 940 MHz Oscillators with Chip Antenna for Wireless Sensors from Room Temperature to 200 and 250 deg C

NASA Technical Reports Server (NTRS)

Scardelletti, Maximilian C.; Ponchak, George E.

2011-01-01

Oscillators that operate at 720 and 940 MHz and characterized over a temperature range of 25 C to 200 C and 250 C, respectively, are presented. The oscillators are designed on alumina substrates with typical integrated circuit fabrication techniques. Cree SiC MESFETs, thin film metal-insulator-metal capacitors and spiral inductors, and Johanson miniature chip antennas make-up the circuits. The output power and phase noise are presented as a function of temperature and frequency. Index Terms MESFETS, chip antennas, oscillators SiC alumina.

Brain functional connectivity and the pathophysiology of schizophrenia.

PubMed

Angelopoulos, E

2014-01-01

In the last decade there is extensive evidence to suggest that cognitive functions depending on coordination of distributed neuronal responses are associated with synchronized oscillatory activity in various frequency ranges suggesting a functional mechanism of neural oscillations in cortical networks. In addition to their role in normal brain functioning, there is increasing evidence that altered oscillatory activity may be associated with certain neuropsychiatric disorders, such as schizophrenia. Consequently, disturbances in neural synchronization may represent the functional relationship of disordered connectivity of cortical networks underlying the characteristic fragmentation of mind and behavior in schizophrenia. In recent studies the synchronization of oscillatory activity in the experience of characteristic symptoms such as auditory verbal hallucinations and thought blocks have been studied in patients with schizophrenia. Studies involving analysis of EEG activity obtained from individuals in resting state (in cage Faraday, isolated from external influences and with eyes closed). In patients with schizophrenia and persistent auditory verbal hallucinations (AVHs) observed a temporary increase in the synchronization phase of α and high θ oscillations of the electroencephalogram (EEG) compared with those of healthy controls and patients without AVHs . This functional hyper-connection manifested in time windows corresponding to experience AVHs, as noted by the patients during the recording of EEG and observed in speech related cortical areas. In another study an interaction of theta and gamma oscillations engages in the production and experience of AVHs. The results showed increased phase coupling between theta and gamma EEG rhythms in the left temporal cortex during AVHs experiences. A more recent study, approaches the thought blocking experience in terms of functional brain connectivity. Thought blocks (TBs) are characterized by regular interruptions of the flow of thought. Outward signs are abrupt and repeated interruptions in the flow of conversation or actions while subjective experience is that of a total and uncontrollable emptying of the mind. In the very limited bibliography regarding TB, the phenomenon is thought to be conceptualized as a disturbance of consciousness that can be attributed to stoppages of continuous information processing due to an increase in the volume of information to be processed. In an attempt to investigate potential expression of the phenomenon on the functional properties of electroencephalographic (EEG) activity, an EEG study was contacted in schizophrenic patients with persisting auditory verbal hallucinations (AVHs) who additionally exhibited TBs. Phase synchronization analyses performed on EEG segments during the experience of TBs showed that synchrony values exhibited a long-range common mode of coupling (grouped behavior) among the left temporal area and the remaining central and frontal brain areas. These common synchrony-fluctuation schemes were observed for 0.5 to 2 s and were detected in a 4-s window following the estimated initiation of the phenomenon. The observation was frequency specific and detected in the broad alpha band region (6-12 Hz). The introduction of synchrony entropy (SE) analysis applied on the cumulative synchrony distribution showed that TB states were characterized by an explicit preference of the system to be functioned at low values of synchrony, while the synchrony values are broadly distributed during the recovery state. The results indicate that during TB states, the phase locking of several brain areas were converged uniformly in a narrow band of low synchrony values and in a distinct time window, impeding thus the ability of the system to recruit and to process information during this time window. The results of this study seem to have greater importance on neuronal correlation of consciousness. The brain is a highly distributed system in which numerous operations are executed in parallel and that lacks a single coordinating center. This raises the question of how the computations occurring simultaneously in spatially segregated processing areas are coordinated and bound together to give rise to coherent percepts and actions. One of the coordinating mechanisms appears to be the synchronization of neuronal activity by phase locking of self-generated network oscillations. This led to the hypothesis that the cerebral cortex might exploit the option to synchronize the discharges of neurons with millisecond ` theoretical formulations of the binding-by-synchrony hypothesis were proposed earlier by Milner (1974), but the Singer lab in the 1990s was the first to obtain experimental evidence supporting the potential role of synchrony as a relational code. The results concerning the functional connectivity of the brain during TBs further support the hypothesis of phase synchronization as a key mechanism for neuronal assemblies underlying mental representations in the human brain.

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

NASA Astrophysics Data System (ADS)

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

2001-08-01

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

EEG Cortical Connectivity Analysis of Working Memory Reveals Topological Reorganization in Theta and Alpha Bands

PubMed Central

Dai, Zhongxiang; de Souza, Joshua; Lim, Julian; Ho, Paul M.; Chen, Yu; Li, Junhua; Thakor, Nitish; Bezerianos, Anastasios; Sun, Yu

2017-01-01

Numerous studies have revealed various working memory (WM)-related brain activities that originate from various cortical regions and oscillate at different frequencies. However, multi-frequency band analysis of the brain network in WM in the cortical space remains largely unexplored. In this study, we employed a graph theoretical framework to characterize the topological properties of the brain functional network in the theta and alpha frequency bands during WM tasks. Twenty-eight subjects performed visual n-back tasks at two difficulty levels, i.e., 0-back (control task) and 2-back (WM task). After preprocessing, Electroencephalogram (EEG) signals were projected into the source space and 80 cortical brain regions were selected for further analysis. Subsequently, the theta- and alpha-band networks were constructed by calculating the Pearson correlation coefficients between the power series (obtained by concatenating the power values of all epochs in each session) of all pairs of brain regions. Graph theoretical approaches were then employed to estimate the topological properties of the brain networks at different WM tasks. We found higher functional integration in the theta band and lower functional segregation in the alpha band in the WM task compared with the control task. Moreover, compared to the 0-back task, altered regional centrality was revealed in the 2-back task in various brain regions that mainly resided in the frontal, temporal and occipital lobes, with distinct presentations in the theta and alpha bands. In addition, significant negative correlations were found between the reaction time with the average path length of the theta-band network and the local clustering of the alpha-band network, which demonstrates the potential for using the brain network metrics as biomarkers for predicting the task performance during WM tasks. PMID:28553215

Functional neuroimaging insights into the physiology of human sleep.

PubMed

Dang-Vu, Thien Thanh; Schabus, Manuel; Desseilles, Martin; Sterpenich, Virginie; Bonjean, Maxime; Maquet, Pierre

2010-12-01

Functional brain imaging has been used in humans to noninvasively investigate the neural mechanisms underlying the generation of sleep stages. On the one hand, REM sleep has been associated with the activation of the pons, thalamus, limbic areas, and temporo-occipital cortices, and the deactivation of prefrontal areas, in line with theories of REM sleep generation and dreaming properties. On the other hand, during non-REM (NREM) sleep, decreases in brain activity have been consistently found in the brainstem, thalamus, and in several cortical areas including the medial prefrontal cortex (MPFC), in agreement with a homeostatic need for brain energy recovery. Benefiting from a better temporal resolution, more recent studies have characterized the brain activations related to phasic events within specific sleep stages. In particular, they have demonstrated that NREM sleep oscillations (spindles and slow waves) are indeed associated with increases in brain activity in specific subcortical and cortical areas involved in the generation or modulation of these waves. These data highlight that, even during NREM sleep, brain activity is increased, yet regionally specific and transient. Besides refining the understanding of sleep mechanisms, functional brain imaging has also advanced the description of the functional properties of sleep. For instance, it has been shown that the sleeping brain is still able to process external information and even detect the pertinence of its content. The relationship between sleep and memory has also been refined using neuroimaging, demonstrating post-learning reactivation during sleep, as well as the reorganization of memory representation on the systems level, sometimes with long-lasting effects on subsequent memory performance. Further imaging studies should focus on clarifying the role of specific sleep patterns for the processing of external stimuli, as well as the consolidation of freshly encoded information during sleep.

EEG Cortical Connectivity Analysis of Working Memory Reveals Topological Reorganization in Theta and Alpha Bands.

PubMed

Dai, Zhongxiang; de Souza, Joshua; Lim, Julian; Ho, Paul M; Chen, Yu; Li, Junhua; Thakor, Nitish; Bezerianos, Anastasios; Sun, Yu

2017-01-01

Numerous studies have revealed various working memory (WM)-related brain activities that originate from various cortical regions and oscillate at different frequencies. However, multi-frequency band analysis of the brain network in WM in the cortical space remains largely unexplored. In this study, we employed a graph theoretical framework to characterize the topological properties of the brain functional network in the theta and alpha frequency bands during WM tasks. Twenty-eight subjects performed visual n -back tasks at two difficulty levels, i.e., 0-back (control task) and 2-back (WM task). After preprocessing, Electroencephalogram (EEG) signals were projected into the source space and 80 cortical brain regions were selected for further analysis. Subsequently, the theta- and alpha-band networks were constructed by calculating the Pearson correlation coefficients between the power series (obtained by concatenating the power values of all epochs in each session) of all pairs of brain regions. Graph theoretical approaches were then employed to estimate the topological properties of the brain networks at different WM tasks. We found higher functional integration in the theta band and lower functional segregation in the alpha band in the WM task compared with the control task. Moreover, compared to the 0-back task, altered regional centrality was revealed in the 2-back task in various brain regions that mainly resided in the frontal, temporal and occipital lobes, with distinct presentations in the theta and alpha bands. In addition, significant negative correlations were found between the reaction time with the average path length of the theta-band network and the local clustering of the alpha-band network, which demonstrates the potential for using the brain network metrics as biomarkers for predicting the task performance during WM tasks.

Brain networks modulated by subthalamic nucleus deep brain stimulation.

PubMed

Accolla, Ettore A; Herrojo Ruiz, Maria; Horn, Andreas; Schneider, Gerd-Helge; Schmitz-Hübsch, Tanja; Draganski, Bogdan; Kühn, Andrea A

2016-09-01

Deep brain stimulation of the subthalamic nucleus is an established treatment for the motor symptoms of Parkinson's disease. Given the frequent occurrence of stimulation-induced affective and cognitive adverse effects, a better understanding about the role of the subthalamic nucleus in non-motor functions is needed. The main goal of this study is to characterize anatomical circuits modulated by subthalamic deep brain stimulation, and infer about the inner organization of the nucleus in terms of motor and non-motor areas. Given its small size and anatomical intersubject variability, functional organization of the subthalamic nucleus is difficult to investigate in vivo with current methods. Here, we used local field potential recordings obtained from 10 patients with Parkinson's disease to identify a subthalamic area with an analogous electrophysiological signature, namely a predominant beta oscillatory activity. The spatial accuracy was improved by identifying a single contact per macroelectrode for its vicinity to the electrophysiological source of the beta oscillation. We then conducted whole brain probabilistic tractography seeding from the previously identified contacts, and further described connectivity modifications along the macroelectrode's main axis. The designated subthalamic 'beta' area projected predominantly to motor and premotor cortical regions additional to connections to limbic and associative areas. More ventral subthalamic areas showed predominant connectivity to medial temporal regions including amygdala and hippocampus. We interpret our findings as evidence for the convergence of different functional circuits within subthalamic nucleus' portions deemed to be appropriate as deep brain stimulation target to treat motor symptoms in Parkinson's disease. Potential clinical implications of our study are illustrated by an index case where deep brain stimulation of estimated predominant non-motor subthalamic nucleus induced hypomanic behaviour. © 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.

Synchronization Properties of Slow Cortical Oscillations

NASA Astrophysics Data System (ADS)

Takekawa, T.; Aoyagi, T.; Fukai, T.

During slow-wave sleep, the brain shows slow oscillatory activity with remarkable long-range synchrony. Intracellular recordings show that the slow oscillation consists of two phases: an textit{up} state and a textit{down} state. Deriving the phase-response function of simplified neuronal systems, we examine the synchronization properties on slow oscillations between the textit{up} state and the textit{down} state. As a result, the strange interaction functions are found in some parameter ranges. These functions indicate that the states with the smaller phase lag than a critical value are all stable.

Slow waves, sharp waves, ripples, and REM in sleeping dragons.

PubMed

Shein-Idelson, Mark; Ondracek, Janie M; Liaw, Hua-Peng; Reiter, Sam; Laurent, Gilles

2016-04-29

Sleep has been described in animals ranging from worms to humans. Yet the electrophysiological characteristics of brain sleep, such as slow-wave (SW) and rapid eye movement (REM) activities, are thought to be restricted to mammals and birds. Recording from the brain of a lizard, the Australian dragon Pogona vitticeps, we identified SW and REM sleep patterns, thus pushing back the probable evolution of these dynamics at least to the emergence of amniotes. The SW and REM sleep patterns that we observed in lizards oscillated continuously for 6 to 10 hours with a period of ~80 seconds. The networks controlling SW-REM antagonism in amniotes may thus originate from a common, ancient oscillator circuit. Lizard SW dynamics closely resemble those observed in rodent hippocampal CA1, yet they originate from a brain area, the dorsal ventricular ridge, that has no obvious hodological similarity with the mammalian hippocampus. Copyright © 2016, American Association for the Advancement of Science.

The fast detection of rare auditory feature conjunctions in the human brain as revealed by cortical gamma-band electroencephalogram.

PubMed

Ruusuvirta, T; Huotilainen, M

2005-01-01

Natural environments typically contain temporal scatters of sounds emitted from multiple sources. The sounds may often physically stand out from one another in their conjoined rather than simple features. This poses a particular challenge for the brain to detect which of these sounds are rare and, therefore, potentially important for survival. We recorded gamma-band (32-40 Hz) electroencephalographic (EEG) oscillations from the scalp of adult humans who passively listened to a repeated tone carrying frequent and rare conjunctions of its frequency and intensity. EEG oscillations that this tone induced, rather than evoked, differed in amplitude between the two conjunction types within the 56-ms analysis window from tone onset. Our finding suggests that, perhaps with the support of its non-phase-locked synchrony in the gamma band, the human brain is able to detect rare sounds as feature conjunctions very rapidly.

Mapping and mining interictal pathological gamma (30–100 Hz) oscillations with clinical intracranial EEG in patients with epilepsy

PubMed Central

Smart, Otis; Maus, Douglas; Marsh, Eric; Dlugos, Dennis; Litt, Brian; Meador, Kimford

2012-01-01

Localizing an epileptic network is essential for guiding neurosurgery and antiepileptic medical devices as well as elucidating mechanisms that may explain seizure-generation and epilepsy. There is increasing evidence that pathological oscillations may be specific to diseased networks in patients with epilepsy and that these oscillations may be a key biomarker for generating and indentifying epileptic networks. We present a semi-automated method that detects, maps, and mines pathological gamma (30–100 Hz) oscillations (PGOs) in human epileptic brain to possibly localize epileptic networks. We apply the method to standard clinical iEEG (<100 Hz) with interictal PGOs and seizures from six patients with medically refractory epilepsy. We demonstrate that electrodes with consistent PGO discharges do not always coincide with clinically determined seizure onset zone (SOZ) electrodes but at times PGO-dense electrodes include secondary seizure-areas (SS) or even areas without seizures (NS). In 4/5 patients with epilepsy surgery, we observe poor (Engel Class 4) post-surgical outcomes and identify more PGO-activity in SS or NS than in SOZ. Additional studies are needed to further clarify the role of PGOs in epileptic brain. PMID:23105174

Consciousness in waking and dreaming: the roles of neuronal oscillation and neuromodulation in determining similarities and differences.

PubMed

Kahn, D; Pace-Schott, E F; Hobson, J A

1997-05-01

State-dependent aspects of consciousness are explored with particular attention to waking and dreaming. First, those phenomenological differences between waking and dreaming that have been established through subjective reports are reviewed. These differences are robustly expressed in most aspects of consciousness including perception, attention, memory, emotion, orientation, and thought. Next, the roles of high frequency neuronal oscillation and neuromodulation are explored in waking and rapid eye movement sleep, the stage of sleep with which the most intense dreaming is associated. The high frequency neuronal oscillations serve similar functions in the wake and rapid eye movement states sleep but neuromodulation is very different in the two states. The collective high frequency oscillatory activity gives coherence to spatially separate neurons but, because of the different neuromodulation, the binding of sensory input in the wake state is very different from the binding of internally perceived input during rapid eye movement sleep. An explanatory model is presented which states that neuromodulation, as well as input source and brain activation level differentiate states of the brain, while the self-organized collective neuronal oscillations unify consciousness via long range correlations.

Neuronal oscillations on an ultra-slow timescale: daily rhythms in electrical activity and gene expression in the mammalian master circadian clockwork.

PubMed

Belle, Mino D C; Diekman, Casey O

2018-02-03

Neuronal oscillations of the brain, such as those observed in the cortices and hippocampi of behaving animals and humans, span across wide frequency bands, from slow delta waves (0.1 Hz) to ultra-fast ripples (600 Hz). Here, we focus on ultra-slow neuronal oscillators in the hypothalamic suprachiasmatic nuclei (SCN), the master daily clock that operates on interlocking transcription-translation feedback loops to produce circadian rhythms in clock gene expression with a period of near 24 h (< 0.001 Hz). This intracellular molecular clock interacts with the cell's membrane through poorly understood mechanisms to drive the daily pattern in the electrical excitability of SCN neurons, exhibiting an up-state during the day and a down-state at night. In turn, the membrane activity feeds back to regulate the oscillatory activity of clock gene programs. In this review, we emphasise the circadian processes that drive daily electrical oscillations in SCN neurons, and highlight how mathematical modelling contributes to our increasing understanding of circadian rhythm generation, synchronisation and communication within this hypothalamic region and across other brain circuits. © 2018 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

Investigation into the efficacy of generating synthetic pathological oscillations for domain adaptation

NASA Astrophysics Data System (ADS)

Lewis, Rory; Ellenberger, James; Williams, Colton; White, Andrew M.

2013-11-01

In the ongoing investigation of integrating Knowledge Discovery in Databases (KDD) into neuroscience, we present a paper that facilitates overcoming the two challenges preventing this integration. Pathological oscillations found in the human brain are difficult to evaluate because 1) there is often no time to learn and train off of the same distribution in the fatally sick, and 2) sinusoidal signals found in the human brain are complex and transient in nature requiring large data sets to work with which are costly and often very expensive or impossible to acquire. Overcoming these challenges in today's neuro-intensive-care unit (ICU) requires insurmountable resources. For these reasons, optimizing KDD for pathological oscillations so machine learning systems can predict neuropathological states would be of immense value. Domain adaptation, which allows a way of predicting on a separate set of data than the training data, can theoretically overcome the first challenge. However, the challenge of acquiring large data sets that show whether domain adaptation is a good candidate to test in a live neuro ICU remains a challenge. To solve this conundrum, we present a methodology for generating synthesized neuropathological oscillations for domain adaptation.

Differential modulation of global and local neural oscillations in REM sleep by homeostatic sleep regulation

PubMed Central

Kim, Bowon; Kocsis, Bernat; Hwang, Eunjin; Kim, Youngsoo; Strecker, Robert E.; McCarley, Robert W.; Choi, Jee Hyun

2017-01-01

Homeostatic rebound in rapid eye movement (REM) sleep normally occurs after acute sleep deprivation, but REM sleep rebound settles on a persistently elevated level despite continued accumulation of REM sleep debt during chronic sleep restriction (CSR). Using high-density EEG in mice, we studied how this pattern of global regulation is implemented in cortical regions with different functions and network architectures. We found that across all areas, slow oscillations repeated the behavioral pattern of persistent enhancement during CSR, whereas high-frequency oscillations showed progressive increases. This pattern followed a common rule despite marked topographic differences. The findings suggest that REM sleep slow oscillations may translate top-down homeostatic control to widely separated brain regions whereas fast oscillations synchronizing local neuronal ensembles escape this global command. These patterns of EEG oscillation changes are interpreted to reconcile two prevailing theories of the function of sleep, synaptic homeostasis and sleep dependent memory consolidation. PMID:28193862

Differential modulation of global and local neural oscillations in REM sleep by homeostatic sleep regulation.

PubMed

Kim, Bowon; Kocsis, Bernat; Hwang, Eunjin; Kim, Youngsoo; Strecker, Robert E; McCarley, Robert W; Choi, Jee Hyun

2017-02-28

Homeostatic rebound in rapid eye movement (REM) sleep normally occurs after acute sleep deprivation, but REM sleep rebound settles on a persistently elevated level despite continued accumulation of REM sleep debt during chronic sleep restriction (CSR). Using high-density EEG in mice, we studied how this pattern of global regulation is implemented in cortical regions with different functions and network architectures. We found that across all areas, slow oscillations repeated the behavioral pattern of persistent enhancement during CSR, whereas high-frequency oscillations showed progressive increases. This pattern followed a common rule despite marked topographic differences. The findings suggest that REM sleep slow oscillations may translate top-down homeostatic control to widely separated brain regions whereas fast oscillations synchronizing local neuronal ensembles escape this global command. These patterns of EEG oscillation changes are interpreted to reconcile two prevailing theories of the function of sleep, synaptic homeostasis and sleep dependent memory consolidation.

Organization of Anti-Phase Synchronization Pattern in Neural Networks: What are the Key Factors?

PubMed Central

Li, Dong; Zhou, Changsong

2011-01-01

Anti-phase oscillation has been widely observed in cortical neural network. Elucidating the mechanism underlying the organization of anti-phase pattern is of significance for better understanding more complicated pattern formations in brain networks. In dynamical systems theory, the organization of anti-phase oscillation pattern has usually been considered to relate to time delay in coupling. This is consistent to conduction delays in real neural networks in the brain due to finite propagation velocity of action potentials. However, other structural factors in cortical neural network, such as modular organization (connection density) and the coupling types (excitatory or inhibitory), could also play an important role. In this work, we investigate the anti-phase oscillation pattern organized on a two-module network of either neuronal cell model or neural mass model, and analyze the impact of the conduction delay times, the connection densities, and coupling types. Our results show that delay times and coupling types can play key roles in this organization. The connection densities may have an influence on the stability if an anti-phase pattern exists due to the other factors. Furthermore, we show that anti-phase synchronization of slow oscillations can be achieved with small delay times if there is interaction between slow and fast oscillations. These results are significant for further understanding more realistic spatiotemporal dynamics of cortico-cortical communications. PMID:22232576

Suppressed cellular oscillations in after-hours mutant mice are associated with enhanced circadian phase-resetting

PubMed Central

Guilding, Clare; Scott, Fiona; Bechtold, David A; Brown, Timothy M; Wegner, Sven; Piggins, Hugh D

2013-01-01

Within the core molecular clock, protein phosphorylation and degradation play a vital role in determining circadian period. The ‘after-hours’ (Afh) mutation in mouse slows the degradation of the core clock protein Cryptochrome, lengthening the period of the molecular clock in the suprachiasmatic nuclei (SCN) and behavioural wheel-running rhythms. However, we do not yet know how the Afh mutation affects other aspects of physiology or the activity of circadian oscillators in other brain regions. Here we report that daily rhythms of metabolism and ingestive behaviours are altered in these animals, as are PERIOD2::LUCIFERASE (PER2::LUC) rhythms in mediobasal hypothalamic nuclei, which influence these behaviours. Overall there is a trend towards period lengthening and a decrease in amplitude of PER2::LUC rhythms throughout the brain. Imaging of single cells from the arcuate and dorsomedial hypothalamic nuclei revealed this reduction in tissue oscillator amplitude to be due to a decrease in the amplitude, rather than a desynchrony, of single cells. Consistent with existing models of oscillator function, this cellular phenotype was associated with a greater susceptibility to phase-shifting stimuli in vivo and in vitro, with light evoking high-amplitude Type 0 resetting in Afh mutant mice. Together, these findings reveal unexpected consequences of the Afh mutation on the amplitude and synchrony of individual cellular oscillators in the SCN. PMID:23207594

Correlation between cortical beta power and gait speed is suppressed in a parkinsonian model, but restored by therapeutic deep brain stimulation.

PubMed

Polar, Christian A; Gupta, Rahul; Lehmkuhle, Mark J; Dorval, Alan D

2018-05-30

The motor cortex and subthalamic nucleus (STN) of patients with Parkinson's disease (PD) exhibit abnormally high levels of electrophysiological oscillations in the ~12-35 Hz beta-frequency range. Recent studies have shown that beta is partly carried forward to regulate future motor states in the healthy condition, suggesting that steady state beta power is lower when a sequence of movements occurs in a short period of time, such as during fast gait. However, whether this relationship between beta power and motor states persists upon parkinsonian onset or in response to effective therapy is unclear. Using a 6-hydroxy dopamine (6-OHDA) rat model of PD and a custom-built behavioral and neurophysiological recording system, we aimed to elucidate a better understanding of the mechanisms underlying cortical beta power and PD symptoms. In addition to elevated levels of beta oscillations, we show that parkinsonian onset was accompanied by a decoupling of movement intensity - quantified as gait speed - from cortical beta power. Although subthalamic deep brain stimulation (DBS) reduced general levels of beta oscillations in the cortex of all PD animals, the brain's capacity to regulate steady state levels of beta power as a function of movement intensity was only restored in animals with therapeutic DBS. We propose that, in addition to lowering general levels of cortical beta power, restoring the brain's ability to maintain this inverse relationship is critical for effective symptom suppression. Copyright © 2017. Published by Elsevier Inc.

Stimulus-dependent modulation of spontaneous low-frequency oscillations in the rat visual cortex.

PubMed

Huang, Liangming; Liu, Yadong; Gui, Jianjun; Li, Ming; Hu, Dewen

2014-08-06

Research on spontaneous low-frequency oscillations is important to reveal underlying regulatory mechanisms in the brain. The mechanism for the stimulus modulation of low-frequency oscillations is not known. Here, we used the intrinsic optical imaging technique to examine stimulus-modulated low-frequency oscillation signals in the rat visual cortex. The stimulation was presented monocularly as a flashing light with different frequencies and intensities. The phases of low-frequency oscillations in different regions tended to be synchronized and the rhythms typically accelerated within a 30-s period after stimulation. These phenomena were confined to visual stimuli with specific flashing frequencies (12.5-17.5 Hz) and intensities (5-10 mA). The acceleration and synchronization induced by the flashing frequency were more marked than those induced by the intensity. These results show that spontaneous low-frequency oscillations can be modulated by parameter-dependent flashing lights and indicate the potential utility of the visual stimulus paradigm in exploring the origin and function of low-frequency oscillations.

Effects of Different Anesthetics on Oscillations in the Rat Olfactory Bulb

PubMed Central

Li, Anan; Zhang, Lei; Liu, Min; Gong, Ling; Liu, Qing; Xu, Fuqiang

2012-01-01

Different types of oscillations in the olfactory bulb (OB), including θ (1 to 4 and 5 to 12 Hz), β (13 to 30 Hz), and γ oscillations (31 to 64 and 65 to 90 Hz), are important in olfactory information processing and olfactory-related functions and have been investigated extensively in recent decades. The awake and anesthetized states, 2 different brain conditions, are used widely in electrophysiologic studies of OB. Chloral hydrate, pentobarbital, and urethane are commonly used anesthetics in these studies. However, the influence of these anesthetics on the oscillations has not been reported. In the present study, we recorded the local field potential (LFP) in the OB of rats that were freely moving or anesthetized with these agents. Chloral hydrate and pentobarbital had similar effects: they slightly affected the power of θ oscillations; significantly increased the power of β oscillations; significantly decreased the power of γ oscillations, and showed similar recovery of γ oscillations. Urethane had very different effects: it significantly increased oscillations at 1 to 4 Hz but decreased those at 5 to 12 Hz, decreased β and γ oscillations, and showed no overt recovery in γ oscillations. These results provide experimental evidence of different effects of various anesthetics on OB oscillations and suggest that the choice of anesthetic should consider the experimental application. PMID:23043811

Characterization of edge oscillation in a traveling-wave field-effect transistor.

PubMed

Narahara, Koichi

2013-07-01

In this study, we characterize the oscillating pulse edges developed in a traveling-wave field-effect transistor (TWFET). Recently, it has been found that a stable shock front can develop on a TWFET, which can travel in one direction only. Once the reflected pulse edge at the far end is transmitted to the input, the shock front develops and begins to travel on the device again. This process establishes a permanent edge oscillation. This paper discusses the device setup necessary to excite such oscillations and how pulse edges oscillate on a TWFET. By applying the phase reduction scheme to the transmission equations of a TWFET, we obtain phase sensitivity, which appropriately explains the measured spatial dependence of the locking range in frequency. Moreover, multiple oscillating edges can develop simultaneously, which are mutually synchronized. The dynamics of these multiple edges are also described.

Brain oscillatory signatures of motor tasks

PubMed Central

Birbaumer, Niels

2015-01-01

Noninvasive brain-computer-interfaces (BCI) coupled with prosthetic devices were recently introduced in the rehabilitation of chronic stroke and other disorders of the motor system. These BCI systems and motor rehabilitation in general involve several motor tasks for training. This study investigates the neurophysiological bases of an EEG-oscillation-driven BCI combined with a neuroprosthetic device to define the specific oscillatory signature of the BCI task. Controlling movements of a hand robotic orthosis with motor imagery of the same movement generates sensorimotor rhythm oscillation changes and involves three elements of tasks also used in stroke motor rehabilitation: passive and active movement, motor imagery, and motor intention. We recorded EEG while nine healthy participants performed five different motor tasks consisting of closing and opening of the hand as follows: 1) motor imagery without any external feedback and without overt hand movement, 2) motor imagery that moves the orthosis proportional to the produced brain oscillation change with online proprioceptive and visual feedback of the hand moving through a neuroprosthetic device (BCI condition), 3) passive and 4) active movement of the hand with feedback (seeing and feeling the hand moving), and 5) rest. During the BCI condition, participants received contingent online feedback of the decrease of power of the sensorimotor rhythm, which induced orthosis movement and therefore proprioceptive and visual information from the moving hand. We analyzed brain activity during the five conditions using time-frequency domain bootstrap-based statistical comparisons and Morlet transforms. Activity during rest was used as a reference. Significant contralateral and ipsilateral event-related desynchronization of sensorimotor rhythm was present during all motor tasks, largest in contralateral-postcentral, medio-central, and ipsilateral-precentral areas identifying the ipsilateral precentral cortex as an integral part of motor regulation. Changes in task-specific frequency power compared with rest were similar between motor tasks, and only significant differences in the time course and some narrow specific frequency bands were observed between motor tasks. We identified EEG features representing active and passive proprioception (with and without muscle contraction) and active intention and passive involvement (with and without voluntary effort) differentiating brain oscillations during motor tasks that could substantially support the design of novel motor BCI-based rehabilitation therapies. The BCI task induced significantly different brain activity compared with the other motor tasks, indicating neural processes unique to the use of body actuators control in a BCI context. PMID:25810484

Decoding synchronized oscillations within the brain: phase-delayed inhibition provides a robust mechanism for creating a sharp synchrony filter.

PubMed

Patel, Mainak; Joshi, Badal

2013-10-07

The widespread presence of synchronized neuronal oscillations within the brain suggests that a mechanism must exist that is capable of decoding such activity. Two realistic designs for such a decoder include: (1) a read-out neuron with a high spike threshold, or (2) a phase-delayed inhibition network motif. Despite requiring a more elaborate network architecture, phase-delayed inhibition has been observed in multiple systems, suggesting that it may provide inherent advantages over simply imposing a high spike threshold. In this work, we use a computational and mathematical approach to investigate the efficacy of the phase-delayed inhibition motif in detecting synchronized oscillations. We show that phase-delayed inhibition is capable of creating a synchrony detector with sharp synchrony filtering properties that depend critically on the time course of inputs. Additionally, we show that phase-delayed inhibition creates a synchrony filter that is far more robust than that created by a high spike threshold. Copyright © 2013 Elsevier Ltd. All rights reserved.

Directed Communication between Nucleus Accumbens and Neocortex in Humans Is Differentially Supported by Synchronization in the Theta and Alpha Band.

PubMed

Horschig, Jörn M; Smolders, Ruud; Bonnefond, Mathilde; Schoffelen, Jan-Mathijs; van den Munckhof, Pepijn; Schuurman, P Richard; Cools, Roshan; Denys, Damiaan; Jensen, Ole

2015-01-01

Here, we report evidence for oscillatory bi-directional interactions between the nucleus accumbens and the neocortex in humans. Six patients performed a demanding covert visual attention task while we simultaneously recorded brain activity from deep-brain electrodes implanted in the nucleus accumbens and the surface electroencephalogram (EEG). Both theta and alpha oscillations were strongly coherent with the frontal and parietal EEG during the task. Theta-band coherence increased during processing of the visual stimuli. Granger causality analysis revealed that the nucleus accumbens was communicating with the neocortex primarily in the theta-band, while the cortex was communicating the nucleus accumbens in the alpha-band. These data are consistent with a model, in which theta- and alpha-band oscillations serve dissociable roles: Prior to stimulus processing, the cortex might suppress ongoing processing in the nucleus accumbens by modulating alpha-band activity. Subsequently, upon stimulus presentation, theta oscillations might facilitate the active exchange of stimulus information from the nucleus accumbens to the cortex.

Bridging the gap between motor imagery and motor execution with a brain-robot interface.

PubMed

Bauer, Robert; Fels, Meike; Vukelić, Mathias; Ziemann, Ulf; Gharabaghi, Alireza

2015-03-01

According to electrophysiological studies motor imagery and motor execution are associated with perturbations of brain oscillations over spatially similar cortical areas. By contrast, neuroimaging and lesion studies suggest that at least partially distinct cortical networks are involved in motor imagery and execution. We sought to further disentangle this relationship by studying the role of brain-robot interfaces in the context of motor imagery and motor execution networks. Twenty right-handed subjects performed several behavioral tasks as indicators for imagery and execution of movements of the left hand, i.e. kinesthetic imagery, visual imagery, visuomotor integration and tonic contraction. In addition, subjects performed motor imagery supported by haptic/proprioceptive feedback from a brain-robot-interface. Principal component analysis was applied to assess the relationship of these indicators. The respective cortical resting state networks in the α-range were investigated by electroencephalography using the phase slope index. We detected two distinct abilities and cortical networks underlying motor control: a motor imagery network connecting the left parietal and motor areas with the right prefrontal cortex and a motor execution network characterized by transmission from the left to right motor areas. We found that a brain-robot-interface might offer a way to bridge the gap between these networks, opening thereby a backdoor to the motor execution system. This knowledge might promote patient screening and may lead to novel treatment strategies, e.g. for the rehabilitation of hemiparesis after stroke. Copyright © 2014 Elsevier Inc. All rights reserved.

Subthalamic nucleus long-range synchronization—an independent hallmark of human Parkinson's disease

PubMed Central

Moshel, Shay; Shamir, Reuben R.; Raz, Aeyal; de Noriega, Fernando R.; Eitan, Renana; Bergman, Hagai; Israel, Zvi

2013-01-01

Beta-band synchronous oscillations in the dorsolateral region of the subthalamic nucleus (STN) of human patients with Parkinson's disease (PD) have been frequently reported. However, the correlation between STN oscillations and synchronization has not been thoroughly explored. The simultaneous recordings of 2390 multi-unit pairs recorded by two parallel microelectrodes (separated by fixed distance of 2 mm, n = 72 trajectories with two electrode tracks >4 mm STN span) in 57 PD patients undergoing STN deep brain stimulation surgery were analyzed. Automatic procedures were utilized to divide the STN into dorsolateral oscillatory and ventromedial non-oscillatory regions, and to quantify the intensity of STN oscillations and synchronicity. Finally, the synchronicity of simultaneously vs. non-simultaneously recorded pairs were compared using a shuffling procedure. Synchronization was observed predominately in the beta range and only between multi-unit pairs in the dorsolateral oscillatory region (n = 615). In paired recordings between sites in the dorsolateral and ventromedial (n = 548) and ventromedial-ventromedial region pairs (n = 1227), no synchronization was observed. Oscillation and synchronicity intensity decline along the STN dorsolateral-ventromedial axis suggesting a fuzzy border between the STN regions. Synchronization strength was significantly correlated to the oscillation power, but synchronization was no longer observed following shuffling. We conclude that STN long-range beta oscillatory synchronization is due to increased neuronal coupling in the Parkinsonian brain and does not merely reflect the outcome of oscillations at similar frequency. The neural synchronization in the dorsolateral (probably the motor domain) STN probably augments the pathological changes in firing rate and patterns of subthalamic neurons in PD patients. PMID:24312018

A method for closed-loop presentation of sensory stimuli conditional on the internal brain-state of awake animals

PubMed Central

Rutishauser, Ueli; Kotowicz, Andreas; Laurent, Gilles

2013-01-01

Brain activity often consists of interactions between internal—or on-going—and external—or sensory—activity streams, resulting in complex, distributed patterns of neural activity. Investigation of such interactions could benefit from closed-loop experimental protocols in which one stream can be controlled depending on the state of the other. We describe here methods to present rapid and precisely timed visual stimuli to awake animals, conditional on features of the animal’s on-going brain state; those features are the presence, power and phase of oscillations in local field potentials (LFP). The system can process up to 64 channels in real time. We quantified its performance using simulations, synthetic data and animal experiments (chronic recordings in the dorsal cortex of awake turtles). The delay from detection of an oscillation to the onset of a visual stimulus on an LCD screen was 47.5 ms and visual-stimulus onset could be locked to the phase of ongoing oscillations at any frequency ≤40 Hz. Our software’s architecture is flexible, allowing on-the-fly modifications by experimenters and the addition of new closed-loop control and analysis components through plugins. The source code of our system “StimOMatic” is available freely as open-source. PMID:23473800

Long-term normal-appearing brain tissue monitoring after irradiation using proton magnetic resonance spectroscopy in vivo: Statistical analysis of a large group of patients

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

Matulewicz, Lukasz; Sokol, Maria; Michnik, Anna

2006-11-01

Purpose: The aim of this study was to detect the non-neoplastic white-matter changes vs. time after irradiation using {sup 1}H nuclear magnetic resonance (NMR) spectroscopy in vivo. Methods and Materials: A total of 394 {sup 1}H MR spectra were acquired from 100 patients (age 19-74 years; mean and median age, 43 years) before and during 2 years after radiation therapy (the mean absorbed doses calculated for the averaged spectroscopy voxels are similar and close to 20 Gy). Results: Ocilations were observed in choline-containing compounds (Cho)/creatine and phosphocreatine (Cr), Cho/N-acetylaspartate (NAA), and center of gravity (CG) of the lipid band inmore » the range of 0.7-1.5 ppm changes over time reveal oscillations. The parameters have the same 8-month cycle period; however the CG changes precede the other by 2 months. Conclusions: The results indicate the oscillative nature of the brain response to irradiation, which may be caused by the blood-brain barrier disruption and repair processes. These oscillations may influence the NMR results, depending on the cycle phase in which the NMR measurements are performed in. The earliest manifestation of radiation injury detected by magnetic resonance spectroscopy is the CG shift.« less

Ageing affects event-related potentials and brain oscillations: a behavioral and electrophysiological study using a haptic recognition memory task.

PubMed

Sebastián, Manuel; Reales, José M; Ballesteros, Soledad

2011-12-01

In this electrophysiological study, we investigated the effects of ageing on recognition memory for three-dimensional (3D) familiar objects presented to touch in a continuous paradigm. To examine changes in event-related potentials (ERPs) and brain oscillations, we recorded the EEGs of healthy groups of young (n=14; mean age=32.3 years) and older adults (n=14; mean age=65.1). Both age groups exhibited similar accuracy and exploration times when making old-new judgments. Young and older participants showed a marginally significant ERP old/new effect widely distributed over the scalp between 550-750 ms. In addition, the elders showed lower amplitude than younger participants within 1200-1500 ms. There were age-related differences in brain oscillations as measured by event-related spectral perturbation (ERSP). Older adults showed greater alpha and beta power reductions than young participants, suggesting the recruitment of additional neural resources. In contrast, the two age groups showed a reliable old/new effect in the theta band that temporarily overlapped the ERP old/new effect. The present results suggest that despite similar behavioral performance, the young and older adults recruited different neural resources to perform a haptic recognition task. Copyright © 2011 Elsevier Ltd. All rights reserved.

New Perspectives on Spontaneous Brain Activity: Dynamic Networks and Energy Matter.

PubMed

Tozzi, Arturo; Zare, Marzieh; Benasich, April A

2016-01-01

Spontaneous brain activity has received increasing attention as demonstrated by the exponential rise in the number of published article on this topic over the last 30 years. Such "intrinsic" brain activity, generated in the absence of an explicit task, is frequently associated with resting-state or default-mode networks (DMN)s. The focus on characterizing spontaneous brain activity promises to shed new light on questions concerning the structural and functional architecture of the brain and how they are related to "mind". However, many critical questions have yet to be addressed. In this review, we focus on a scarcely explored area, specifically the energetic requirements and constraints of spontaneous activity, taking into account both thermodynamical and informational perspectives. We argue that the "classical" definitions of spontaneous activity do not take into account an important feature, that is, the critical thermodynamic energetic differences between spontaneous and evoked brain activity. Spontaneous brain activity is associated with slower oscillations compared with evoked, task-related activity, hence it exhibits lower levels of enthalpy and "free-energy" (i.e., the energy that can be converted to do work), thus supporting noteworthy thermodynamic energetic differences between spontaneous and evoked brain activity. Increased spike frequency during evoked activity has a significant metabolic cost, consequently, brain functions traditionally associated with spontaneous activity, such as mind wandering, require less energy that other nervous activities. We also review recent empirical observations in neuroscience, in order to capture how spontaneous brain dynamics and mental function can be embedded in a non-linear dynamical framework, which considers nervous activity in terms of phase spaces, particle trajectories, random walks, attractors and/or paths at the edge of the chaos. This takes us from the thermodynamic free-energy, to the realm of "variational free-energy", a theoretical construct pertaining to probability and information theory which allows explanation of unexplored features of spontaneous brain activity.

Noise-driven neuromorphic tuned amplifier.

PubMed

Fanelli, Duccio; Ginelli, Francesco; Livi, Roberto; Zagli, Niccoló; Zankoc, Clement

2017-12-01

We study a simple stochastic model of neuronal excitatory and inhibitory interactions. The model is defined on a directed lattice and internodes couplings are modulated by a nonlinear function that mimics the process of synaptic activation. We prove that such a system behaves as a fully tunable amplifier: the endogenous component of noise, stemming from finite size effects, seeds a coherent (exponential) amplification across the chain generating giant oscillations with tunable frequencies, a process that the brain could exploit to enhance, and eventually encode, different signals. On a wider perspective, the characterized amplification process could provide a reliable pacemaking mechanism for biological systems. The device extracts energy from the finite size bath and operates as an out of equilibrium thermal machine, under stationary conditions.

Quantitative Characterization of Spurious Gibbs Waves in 45 CMIP5 Models

NASA Astrophysics Data System (ADS)

Geil, K. L.; Zeng, X.

2014-12-01

Gibbs oscillations appear in global climate models when representing fields, such as orography, that contain discontinuities or sharp gradients. It has been known for decades that the oscillations are associated with the transformation of the truncated spectral representation of a field to physical space and that the oscillations can also be present in global models that do not use spectral methods. The spurious oscillations are potentially detrimental to model simulations (e.g., over ocean) and this work provides a quantitative characterization of the Gibbs oscillations that appear across the Coupled Model Intercomparison Project Phase 5 (CMIP5) models. An ocean transect running through the South Pacific High toward the Andes is used to characterize the oscillations in ten different variables. These oscillations are found to be stationary and hence are not caused by (physical) waves in the atmosphere. We quantify the oscillation amplitude using the root mean square difference (RMSD) between the transect of a variable and its running mean (rather than the constant mean across the transect). We also compute the RMSD to interannual variability (IAV) ratio, which provides a relative measure of the oscillation amplitude. Of the variables examined, the largest RMSD values exist in the surface pressure field of spectral models, while the smallest RMSD values within the surface pressure field come from models that use finite difference (FD) techniques. Many spectral models have a surface pressure RMSD that is 2 to 15 times greater than IAV over the transect and an RMSD:IAV ratio greater than one for many other variables including surface temperature, incoming shortwave radiation at the surface, incoming longwave radiation at the surface, and total cloud fraction. In general, the FD models out-perform the spectral models, but not all the spectral models have large amplitude oscillations and there are a few FD models where the oscillations do appear. Finally, we present a brief comparison of the numerical methods of a select few models to better understand their Gibbs oscillations.

A dynamical systems approach for estimating phase interactions between rhythms of different frequencies from experimental data

PubMed Central

Goto, Takahiro; Aoyagi, Toshio

2018-01-01

Synchronization of neural oscillations as a mechanism of brain function is attracting increasing attention. Neural oscillation is a rhythmic neural activity that can be easily observed by noninvasive electroencephalography (EEG). Neural oscillations show the same frequency and cross-frequency synchronization for various cognitive and perceptual functions. However, it is unclear how this neural synchronization is achieved by a dynamical system. If neural oscillations are weakly coupled oscillators, the dynamics of neural synchronization can be described theoretically using a phase oscillator model. We propose an estimation method to identify the phase oscillator model from real data of cross-frequency synchronized activities. The proposed method can estimate the coupling function governing the properties of synchronization. Furthermore, we examine the reliability of the proposed method using time-series data obtained from numerical simulation and an electronic circuit experiment, and show that our method can estimate the coupling function correctly. Finally, we estimate the coupling function between EEG oscillation and the speech sound envelope, and discuss the validity of these results. PMID:29337999

Alpha Oscillations Are Causally Linked to Inhibitory Abilities in Ageing.

PubMed

Borghini, Giulia; Candini, Michela; Filannino, Cristina; Hussain, Masud; Walsh, Vincent; Romei, Vincenzo; Zokaei, Nahid; Cappelletti, Marinella

2018-05-02

Aging adults typically show reduced ability to ignore task-irrelevant information, an essential skill for optimal performance in many cognitive operations, including those requiring working memory (WM) resources. In a first experiment, young and elderly human participants of both genders performed an established WM paradigm probing inhibitory abilities by means of valid, invalid, and neutral retro-cues. Elderly participants showed an overall cost, especially in performing invalid trials, whereas younger participants' general performance was comparatively higher, as expected.Inhibitory abilities have been linked to alpha brain oscillations but it is yet unknown whether in aging these oscillations (also typically impoverished) and inhibitory abilities are causally linked. To probe this possible causal link in aging, we compared in a second experiment parietal alpha-transcranial alternating current stimulation (tACS) with either no stimulation (Sham) or with two control stimulation frequencies (theta- and gamma-tACS) in the elderly group while performing the same WM paradigm. Alpha- (but not theta- or gamma-) tACS selectively and significantly improved performance (now comparable to younger adults' performance in the first experiment), particularly for invalid cues where initially elderly showed the highest costs. Alpha oscillations are therefore causally linked to inhibitory abilities and frequency-tuned alpha-tACS interventions can selectively change these abilities in the elderly. SIGNIFICANCE STATEMENT Ignoring task-irrelevant information, an ability associated to rhythmic brain activity in the alpha frequency band, is fundamental for optimal performance. Indeed, impoverished inhibitory abilities contribute to age-related decline in cognitive functions like working memory (WM), the capacity to briefly hold information in mind. Whether in aging adults alpha oscillations and inhibitory abilities are causally linked is yet unknown. We experimentally manipulated frequency-tuned brain activity using transcranial alternating current stimulation (tACS), combined with a retro-cue paradigm assessing WM and inhibition. We found that alpha-tACS induced a significant improvement in target responses and misbinding errors, two indexes of inhibition. We concluded that in aging alpha oscillations are causally linked to inhibitory abilities, and that despite being impoverished, these abilities are still malleable. Copyright © 2018 the authors 0270-6474/18/384419-12$15.00/0.

The alteration of spontaneous low frequency oscillations caused by acute electromagnetic fields exposure.

PubMed

Lv, Bin; Chen, Zhiye; Wu, Tongning; Shao, Qing; Yan, Duo; Ma, Lin; Lu, Ke; Xie, Yi

2014-02-01

The motivation of this study is to evaluate the possible alteration of regional resting state brain activity induced by the acute radiofrequency electromagnetic field (RF-EMF) exposure (30min) of Long Term Evolution (LTE) signal. We designed a controllable near-field LTE RF-EMF exposure environment. Eighteen subjects participated in a double-blind, crossover, randomized and counterbalanced experiment including two sessions (real and sham exposure). The radiation source was close to the right ear. Then the resting state fMRI signals of human brain were collected before and after the exposure in both sessions. We measured the amplitude of low frequency fluctuation (ALFF) and fractional ALFF (fALFF) to characterize the spontaneous brain activity. We found the decreased ALFF value around in left superior temporal gyrus, left middle temporal gyrus, right superior temporal gyrus, right medial frontal gyrus and right paracentral lobule after the real exposure. And the decreased fALFF value was also detected in right medial frontal gyrus and right paracentral lobule. The study provided the evidences that 30min LTE RF-EMF exposure modulated the spontaneous low frequency fluctuations in some brain regions. With resting state fMRI, we found the alteration of spontaneous low frequency fluctuations induced by the acute LTE RF-EMF exposure. Copyright © 2013 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Scale invariant rearrangement of resting state networks in the human brain under sustained stimulation.

PubMed

Tommasin, Silvia; Mascali, Daniele; Moraschi, Marta; Gili, Tommaso; Assan, Ibrahim Eid; Fratini, Michela; DiNuzzo, Mauro; Wise, Richard G; Mangia, Silvia; Macaluso, Emiliano; Giove, Federico

2018-06-14

Brain activity at rest is characterized by widely distributed and spatially specific patterns of synchronized low-frequency blood-oxygenation level-dependent (BOLD) fluctuations, which correspond to physiologically relevant brain networks. This network behaviour is known to persist also during task execution, yet the details underlying task-associated modulations of within- and between-network connectivity are largely unknown. In this study we exploited a multi-parametric and multi-scale approach to investigate how low-frequency fluctuations adapt to a sustained n-back working memory task. We found that the transition from the resting state to the task state involves a behaviourally relevant and scale-invariant modulation of synchronization patterns within both task-positive and default mode networks. Specifically, decreases of connectivity within networks are accompanied by increases of connectivity between networks. In spite of large and widespread changes of connectivity strength, the overall topology of brain networks is remarkably preserved. We show that these findings are strongly influenced by connectivity at rest, suggesting that the absolute change of connectivity (i.e., disregarding the baseline) may be not the most suitable metric to study dynamic modulations of functional connectivity. Our results indicate that a task can evoke scale-invariant, distributed changes of BOLD fluctuations, further confirming that low frequency BOLD oscillations show a specialized response and are tightly bound to task-evoked activation. Copyright © 2018. Published by Elsevier Inc.

Adaptive elimination of synchronization in coupled oscillator

NASA Astrophysics Data System (ADS)

Zhou, Shijie; Ji, Peng; Zhou, Qing; Feng, Jianfeng; Kurths, Jürgen; Lin, Wei

2017-08-01

We present here an adaptive control scheme with a feedback delay to achieve elimination of synchronization in a large population of coupled and synchronized oscillators. We validate the feasibility of this scheme not only in the coupled Kuramoto’s oscillators with a unimodal or bimodal distribution of natural frequency, but also in two representative models of neuronal networks, namely, the FitzHugh-Nagumo spiking oscillators and the Hindmarsh-Rose bursting oscillators. More significantly, we analytically illustrate the feasibility of the proposed scheme with a feedback delay and reveal how the exact topological form of the bimodal natural frequency distribution influences the scheme performance. We anticipate that our developed scheme will deepen the understanding and refinement of those controllers, e.g. techniques of deep brain stimulation, which have been implemented in remedying some synchronization-induced mental disorders including Parkinson disease and epilepsy.

The role of alpha oscillations for illusory perception

PubMed Central

Lange, Joachim; Keil, Julian; Schnitzler, Alfons; van Dijk, Hanneke; Weisz, Nathan

2014-01-01

Alpha oscillations are a prominent electrophysiological signal measured across a wide range of species and cortical and subcortical sites. Alpha oscillations have been viewed for a long time as an “idling” rhythm, purely reflecting inactive sites. Despite earlier evidence from neurophysiology, awareness that alpha oscillations can substantially influence perception and behavior has grown only recently in cognitive neuroscience. Evidence for an active role of alpha for perception comes mainly from several visual, near-threshold experiments. In the current review, we extend this view by summarizing studies showing how alpha-defined brain states relate to illusory perception, i.e. cases of perceptual reports that are not “objectively” verifiable by distinct stimuli or stimulus features. These studies demonstrate that ongoing or prestimulus alpha oscillations substantially influence the perception of auditory, visual or multisensory illusions. PMID:24931795

Diminished modulation of preparatory sensorimotor mu rhythm predicts attention-deficit/hyperactivity disorder severity.

PubMed

Ter Huurne, N; Lozano-Soldevilla, D; Onnink, M; Kan, C; Buitelaar, J; Jensen, O

2017-08-01

Attention-deficit/hyperactivity disorder (ADHD) is characterized by problems in regulating attention and in suppressing disruptive motor activity, i.e. hyperactivity and impulsivity. We recently found evidence that aberrant distribution of posterior α band oscillations (8-12 Hz) is associated with attentional problems in ADHD. The sensorimotor cortex also produces strong 8-12 Hz band oscillations, namely the μ rhythm, and is thought to have a similar inhibitory function. Here, we now investigate whether problems in distributing α band oscillations in ADHD generalize to the μ rhythm in the sensorimotor domain. In a group of adult ADHD (n = 17) and healthy control subjects (n = 18; aged 21-40 years) oscillatory brain activity was recorded using magnetoencephalography during a visuo-spatial attention task. Subjects had to anticipate a target with unpredictable timing and respond by pressing a button. Preparing a motor response, the ADHD group failed to increase hemispheric μ lateralization with relatively higher μ power in sensorimotor regions not engaged in the task, as the controls did (F 1,33 = 8.70, p = 0.006). Moreover, the ADHD group pre-response μ lateralization not only correlated positively with accuracy (r s = 0.64, p = 0.0052) and negatively with intra-individual reaction time variability (r s = -0.52, p = 0.033), but it also correlated negatively with the score on an ADHD rating scale (r s = -0.53, p = 0.028). We suggest that ADHD is associated with an inability to sufficiently inhibit task-irrelevant sensorimotor areas by means of modulating μ oscillatory activity. This could explain disruptive motor activity in ADHD. These results provide further evidence that impaired modulation of α band oscillations is involved in the pathogenesis of ADHD.

Scale-Free Neural and Physiological Dynamics in Naturalistic Stimuli Processing

PubMed Central

Lin, Amy

2016-01-01

Abstract Neural activity recorded at multiple spatiotemporal scales is dominated by arrhythmic fluctuations without a characteristic temporal periodicity. Such activity often exhibits a 1/f-type power spectrum, in which power falls off with increasing frequency following a power-law function: P(f)∝1/fβ, which is indicative of scale-free dynamics. Two extensively studied forms of scale-free neural dynamics in the human brain are slow cortical potentials (SCPs)—the low-frequency (<5 Hz) component of brain field potentials—and the amplitude fluctuations of α oscillations, both of which have been shown to carry important functional roles. In addition, scale-free dynamics characterize normal human physiology such as heartbeat dynamics. However, the exact relationships among these scale-free neural and physiological dynamics remain unclear. We recorded simultaneous magnetoencephalography and electrocardiography in healthy subjects in the resting state and while performing a discrimination task on scale-free dynamical auditory stimuli that followed different scale-free statistics. We observed that long-range temporal correlation (captured by the power-law exponent β) in SCPs positively correlated with that of heartbeat dynamics across time within an individual and negatively correlated with that of α-amplitude fluctuations across individuals. In addition, across individuals, long-range temporal correlation of both SCP and α-oscillation amplitude predicted subjects’ discrimination performance in the auditory task, albeit through antagonistic relationships. These findings reveal interrelations among different scale-free neural and physiological dynamics and initial evidence for the involvement of scale-free neural dynamics in the processing of natural stimuli, which often exhibit scale-free dynamics. PMID:27822495

Neuromorphic computing with nanoscale spintronic oscillators

PubMed Central

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

2017-01-01

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

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

PubMed

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

2018-04-01

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

The Brain Physics: Multi Laser Beam Interaction with the Brain Topions (the Brain Neurocenters)

NASA Astrophysics Data System (ADS)

Stefan, V. Alexander

2015-03-01

A novel method for the treatment of the neurological diseases is proposed. The multiple-energy laser photons (the blue scanning photons and ultraviolet focusing photons) interact with the specific DNA molecules within the topion (such as Parkinson's and Alzheimer's brain topion) via the matching of laser frequency with the oscillation eigen-frequency of a particular molecule within the DNA. In this way, the corrupt molecules (the structure of molecules) can be manipulated so as to treat (eliminate) the neurological disease. Supported by Nikola Tesla Labs, Stefan University.

Joint probabilities and quantum cognition

NASA Astrophysics Data System (ADS)

de Barros, J. Acacio

2012-12-01

In this paper we discuss the existence of joint probability distributions for quantumlike response computations in the brain. We do so by focusing on a contextual neural-oscillator model shown to reproduce the main features of behavioral stimulus-response theory. We then exhibit a simple example of contextual random variables not having a joint probability distribution, and describe how such variables can be obtained from neural oscillators, but not from a quantum observable algebra.

Enhancement of multitasking performance and neural oscillations by transcranial alternating current stimulation

PubMed Central

Zanto, Theodore P.; van Schouwenburg, Martine R.; Gazzaley, Adam

2017-01-01

Multitasking is associated with the generation of stimulus-locked theta (4–7 Hz) oscillations arising from prefrontal cortex (PFC). Transcranial alternating current stimulation (tACS) is a non-invasive brain stimulation technique that influences endogenous brain oscillations. Here, we investigate whether applying alternating current stimulation within the theta frequency band would affect multitasking performance, and explore tACS effects on neurophysiological measures. Brief runs of bilateral PFC theta-tACS were applied while participants were engaged in a multitasking paradigm accompanied by electroencephalography (EEG) data collection. Unlike an active control group, a tACS stimulation group showed enhancement of multitasking performance after a 90-minute session (F1,35 = 6.63, p = 0.01, ηp2 = 0.16; effect size = 0.96), coupled with significant modulation of posterior beta (13–30 Hz) activities (F1,32 = 7.66, p = 0.009, ηp2 = 0.19; effect size = 0.96). Across participant regression analyses indicated that those participants with greater increases in frontal theta, alpha and beta oscillations exhibited greater multitasking performance improvements. These results indicate frontal theta-tACS generates benefits on multitasking performance accompanied by widespread neuronal oscillatory changes, and suggests that future tACS studies with extended treatments are worth exploring as promising tools for cognitive enhancement. PMID:28562642

Enhancement of multitasking performance and neural oscillations by transcranial alternating current stimulation.

PubMed

Hsu, Wan-Yu; Zanto, Theodore P; van Schouwenburg, Martine R; Gazzaley, Adam

2017-01-01

Multitasking is associated with the generation of stimulus-locked theta (4-7 Hz) oscillations arising from prefrontal cortex (PFC). Transcranial alternating current stimulation (tACS) is a non-invasive brain stimulation technique that influences endogenous brain oscillations. Here, we investigate whether applying alternating current stimulation within the theta frequency band would affect multitasking performance, and explore tACS effects on neurophysiological measures. Brief runs of bilateral PFC theta-tACS were applied while participants were engaged in a multitasking paradigm accompanied by electroencephalography (EEG) data collection. Unlike an active control group, a tACS stimulation group showed enhancement of multitasking performance after a 90-minute session (F1,35 = 6.63, p = 0.01, ηp2 = 0.16; effect size = 0.96), coupled with significant modulation of posterior beta (13-30 Hz) activities (F1,32 = 7.66, p = 0.009, ηp2 = 0.19; effect size = 0.96). Across participant regression analyses indicated that those participants with greater increases in frontal theta, alpha and beta oscillations exhibited greater multitasking performance improvements. These results indicate frontal theta-tACS generates benefits on multitasking performance accompanied by widespread neuronal oscillatory changes, and suggests that future tACS studies with extended treatments are worth exploring as promising tools for cognitive enhancement.

Single trial discrimination of individual finger movements on one hand: A combined MEG and EEG study☆

PubMed Central

Quandt, F.; Reichert, C.; Hinrichs, H.; Heinze, H.J.; Knight, R.T.; Rieger, J.W.

2012-01-01

It is crucial to understand what brain signals can be decoded from single trials with different recording techniques for the development of Brain-Machine Interfaces. A specific challenge for non-invasive recording methods are activations confined to small spatial areas on the cortex such as the finger representation of one hand. Here we study the information content of single trial brain activity in non-invasive MEG and EEG recordings elicited by finger movements of one hand. We investigate the feasibility of decoding which of four fingers of one hand performed a slight button press. With MEG we demonstrate reliable discrimination of single button presses performed with the thumb, the index, the middle or the little finger (average over all subjects and fingers 57%, best subject 70%, empirical guessing level: 25.1%). EEG decoding performance was less robust (average over all subjects and fingers 43%, best subject 54%, empirical guessing level 25.1%). Spatiotemporal patterns of amplitude variations in the time series provided best information for discriminating finger movements. Non-phase-locked changes of mu and beta oscillations were less predictive. Movement related high gamma oscillations were observed in average induced oscillation amplitudes in the MEG but did not provide sufficient information about the finger's identity in single trials. Importantly, pre-movement neuronal activity provided information about the preparation of the movement of a specific finger. Our study demonstrates the potential of non-invasive MEG to provide informative features for individual finger control in a Brain-Machine Interface neuroprosthesis. PMID:22155040

Neuromorphic computing with nanoscale spintronic oscillators.

PubMed

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

2017-07-26

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

CONTROL OF SLEEP AND WAKEFULNESS

PubMed Central

Brown, Ritchie E.; Basheer, Radhika; McKenna, James T.; Strecker, Robert E.; McCarley, Robert W.

2013-01-01

This review summarizes the brain mechanisms controlling sleep and wakefulness. Wakefulness promoting systems cause low-voltage, fast activity in the electroencephalogram (EEG). Multiple interacting neurotransmitter systems in the brain stem, hypothalamus, and basal forebrain converge onto common effector systems in the thalamus and cortex. Sleep results from the inhibition of wake-promoting systems by homeostatic sleep factors such as adenosine and nitric oxide and GABAergic neurons in the preoptic area of the hypothalamus, resulting in large-amplitude, slow EEG oscillations. Local, activity-dependent factors modulate the amplitude and frequency of cortical slow oscillations. Non-rapid-eye-movement (NREM) sleep results in conservation of brain energy and facilitates memory consolidation through the modulation of synaptic weights. Rapid-eye-movement (REM) sleep results from the interaction of brain stem cholinergic, aminergic, and GABAergic neurons which control the activity of glutamatergic reticular formation neurons leading to REM sleep phenomena such as muscle atonia, REMs, dreaming, and cortical activation. Strong activation of limbic regions during REM sleep suggests a role in regulation of emotion. Genetic studies suggest that brain mechanisms controlling waking and NREM sleep are strongly conserved throughout evolution, underscoring their enormous importance for brain function. Sleep disruption interferes with the normal restorative functions of NREM and REM sleep, resulting in disruptions of breathing and cardiovascular function, changes in emotional reactivity, and cognitive impairments in attention, memory, and decision making. PMID:22811426

Stomatal oscillations in olive trees: analysis and methodological implications.

PubMed

López-Bernal, Alvaro; García-Tejera, Omar; Testi, Luca; Orgaz, Francisco; Villalobos, Francisco J

2018-04-01

Stomatal oscillations have long been disregarded in the literature despite the fact that the phenomenon has been described for a variety of plant species. This study aims to characterize the occurrence of oscillations in olive trees (Olea europaea L.) under different growing conditions and its methodological implications. Three experiments with young potted olives and one with large field-grown trees were performed. Sap flow measurements were always used to monitor the occurrence of oscillations, with additional determinations of trunk diameter variations and leaf-level stomatal conductance, photosynthesis and water potential also conducted in some cases. Strong oscillations with periods of 30-60 min were generally observed for young trees, while large field trees rarely showed significant oscillations. Severe water stress led to the disappearance of oscillations, but moderate water deficits occasionally promoted them. Simultaneous oscillations were also found for leaf stomatal conductance, leaf photosynthesis and trunk diameter, with the former presenting the highest amplitudes. The strong oscillations found in young potted olive trees preclude the use of infrequent measurements of stomatal conductance and related variables to characterize differences between trees of different cultivars or subjected to different experimental treatments. Under these circumstances, our results suggest that reliable estimates could be obtained using measurement intervals below 15 min.

Pupil fluctuations track fast switching of cortical states during quiet wakefulness

PubMed Central

Reimer, Jacob; Froudarakis, Emmanouil; Cadwell, Cathryn R.; Yatsenko, Dimitri; Denfield, George H.; Tolias, Andreas S.

2014-01-01

Neural responses are modulated by brain state, which varies with arousal, attention, and behavior. In mice, running and whisking desynchronize the cortex and enhance sensory responses, but the quiescent periods between bouts of exploratory behaviors have not been well-studied. We found that these periods of “quiet wakefulness” were characterized by state fluctuations on a timescale of 1–2 seconds. Small fluctuations in pupil diameter tracked these state transitions in multiple cortical areas. During dilation, the intracellular membrane potential was desynchronized, sensory responses were enhanced, and population activity was less correlated. In contrast, constriction was characterized by increased low-frequency oscillations and higher ensemble correlations. Specific subtypes of cortical interneurons were differentially activated during dilation and constriction, consistent with their participation in the observed state changes. Pupillometry has been used to index attention and mental effort in humans, but the intracellular dynamics and differences in population activity underlying this phenomenon were previously unknown. PMID:25374359

Melatonin

PubMed Central

Pévet, Paul

2002-01-01

Melatonin (MEL) is a hormone synthesized and secreted by the pineal gland deep within the brain in response to photoperiodic cues relayed from the retina via an endogenous circadian oscillator within the suprachiasmatic nucleus in the hypothalamus. The circadian rhythm of melatonin production and release, characterized by nocturnal activity and daytime quiescence, is an important temporal signal to the body structures that can read it. Melatonin acts through high-affinity receptors located centrally and in numerous peripheral organs. Different receptor subtypes have been cloned and characterized: MT1 and MT2 (transmembrane G-protein-coupled receptors), and MT3. However, their physiological role remains unelucidated, although livestock management applications already include the control of seasonal breeding and milk production. As for potential therapeutic applications, exogenous melatonin or a melatonin agonist and selective 5-hydroxytrypiamine receptor (5-HT2c) antagonist, eg, S 20098, can be used to manipulate circadian processes such as the sleep-vake cycle, which are frequently disrupted in many conditions, most notably seasonal affective disorder. PMID:22034091

How Sleep Activates Epileptic Networks?

PubMed Central

Halász, Peter

2013-01-01

Background. The relationship between sleep and epilepsy has been long ago studied, and several excellent reviews are available. However, recent development in sleep research, the network concept in epilepsy, and the recognition of high frequency oscillations in epilepsy and more new results may put this matter in a new light. Aim. The review address the multifold interrelationships between sleep and epilepsy networks and with networks of cognitive functions. Material and Methods. The work is a conceptual update of the available clinical data and relevant studies. Results and Conclusions. Studies exploring dynamic microstructure of sleep have found important gating mechanisms for epileptic activation. As a general rule interictal epileptic manifestations seem to be linked to the slow oscillations of sleep and especially to the reactive delta bouts characterized by A1 subtype in the CAP system. Important link between epilepsy and sleep is the interference of epileptiform discharges with the plastic functions in NREM sleep. This is the main reason of cognitive impairment in different forms of early epileptic encephalopathies affecting the brain in a special developmental window. The impairment of cognitive functions via sleep is present especially in epileptic networks involving the thalamocortical system and the hippocampocortical memory encoding system. PMID:24159386

Encoding of Olfactory Information with Oscillating Neural Assemblies

NASA Astrophysics Data System (ADS)

Laurent, Gilles; Davidowitz, Hananel

1994-09-01

In the brain, fast oscillations of local field potentials, which are thought to arise from the coherent and rhythmic activity of large numbers of neurons, were observed first in the olfactory system and have since been described in many neocortical areas. The importance of these oscillations in information coding, however, is controversial. Here, local field potential and intracellular recordings were obtained from the antennal lobe and mushroom body of the locust Schistocerca americana. Different odors evoked coherent oscillations in different, but usually overlapping, ensembles of neurons. The phase of firing of individual neurons relative to the population was not dependent on the odor. The components of a coherently oscillating ensemble of neurons changed over the duration of a single exposure to an odor. It is thus proposed that odors are encoded by specific but dynamic assemblies of coherently oscillating neurons. Such distributed and temporal representation of complex sensory signals may facilitate combinatorial coding and associative learning in these, and possibly other, sensory networks.

Oscillatory network with self-organized dynamical connections for synchronization-based image segmentation.

PubMed

Kuzmina, Margarita; Manykin, Eduard; Surina, Irina

2004-01-01

An oscillatory network of columnar architecture located in 3D spatial lattice was recently designed by the authors as oscillatory model of the brain visual cortex. Single network oscillator is a relaxational neural oscillator with internal dynamics tunable by visual image characteristics - local brightness and elementary bar orientation. It is able to demonstrate either activity state (stable undamped oscillations) or "silence" (quickly damped oscillations). Self-organized nonlocal dynamical connections of oscillators depend on oscillator activity levels and orientations of cortical receptive fields. Network performance consists in transfer into a state of clusterized synchronization. At current stage grey-level image segmentation tasks are carried out by 2D oscillatory network, obtained as a limit version of the source model. Due to supplemented network coupling strength control the 2D reduced network provides synchronization-based image segmentation. New results on segmentation of brightness and texture images presented in the paper demonstrate accurate network performance and informative visualization of segmentation results, inherent in the model.

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

Empirical observation of the impact of traffic oscillations on freeway safety : final report, OTREC-RR-10-13, September 2010.

DOT National Transportation Integrated Search

2010-09-01

Traffic oscillations are typical features of congested traffic flow that are characterized by recurring decelerations : followed by accelerations (stop-and-go driving). The negative environmental impacts of these oscillations are widely : accepted, b...

Attention Modulates TMS-Locked Alpha Oscillations in the Visual Cortex.

PubMed

Herring, Jim D; Thut, Gregor; Jensen, Ole; Bergmann, Til O

2015-10-28

Cortical oscillations, such as 8-12 Hz alpha-band activity, are thought to subserve gating of information processing in the human brain. While most of the supporting evidence is correlational, causal evidence comes from attempts to externally drive ("entrain") these oscillations by transcranial magnetic stimulation (TMS). Indeed, the frequency profile of TMS-evoked potentials (TEPs) closely resembles that of oscillations spontaneously emerging in the same brain region. However, it is unclear whether TMS-locked and spontaneous oscillations are produced by the same neuronal mechanisms. If so, they should react in a similar manner to top-down modulation by endogenous attention. To test this prediction, we assessed the alpha-like EEG response to TMS of the visual cortex during periods of high and low visual attention while participants attended to either the visual or auditory modality in a cross-modal attention task. We observed a TMS-locked local oscillatory alpha response lasting several cycles after TMS (but not after sham stimulation). Importantly, TMS-locked alpha power was suppressed during deployment of visual relative to auditory attention, mirroring spontaneous alpha amplitudes. In addition, the early N40 TEP component, located at the stimulation site, was amplified by visual attention. The extent of attentional modulation for both TMS-locked alpha power and N40 amplitude did depend, with opposite sign, on the individual ability to modulate spontaneous alpha power at the stimulation site. We therefore argue that TMS-locked and spontaneous oscillations are of common neurophysiological origin, whereas the N40 TEP component may serve as an index of current cortical excitability at the time of stimulation. Copyright © 2015 Herring et al.

Decadal variability of drought conditions over the southern part of Europe based on Principal Oscillation Pattern Analysis

NASA Astrophysics Data System (ADS)

Ionita-Scholz, Monica; Tallaksen, Lena M.; Scholz, Patrick

2017-04-01

This study introduces a novel method of estimating the decay time, mean period and forcing statistics of drought conditions over large spatial domains, demonstrated here for southern part of Europe (10°E - 40°E, 35°N - 50°N). It uses a two-dimensional stochastically forced damped linear oscillator model with the model parameters estimated from a Principal Oscillation Pattern (POP) analysis and associated observed power spectra. POP is a diagnostic technique that aims to derive the space-time characteristics of a data set objectively. This analysis is performed on an extended observational time series of 114 years (1902 - 2015) of the Standardized Precipitation Evapotranspiration Index for an accumulation period of 12 months (SPEI12), based on the Climate Research Unit (CRU TS v. 3.24) data set. The POP analysis reveals four exceptionally stable modes of variability, which together explain more than 62% of the total explained variance. The most stable POP mode, which explains 16.3% of the total explained variance, is characterized by a period of oscillation of 14 years and a decay time of 31 years. The real part of POP1 is characterized by a monopole-like structure with the highest loadings over Portugal, western part of Spain and Turkey. The second stable mode, which explains 15.9% of the total explained variance, is characterized by a period of oscillation of 20 years and a decay time of 26.4 years. The spatial structure of the real part of POP2 has a dipole-like structure with the highest positive loadings over France, southern Germany and Romania and negative loadings over southern part of Spain. The third POP mode, in terms of stability, explains 14.0% of the total variance and is characterized by a period of oscillation of 33 years and a decay time of 43.5 years. The real part of POP3 is characterized by negative loadings over the eastern part of Europe and positive loadings over Turkey. The fourth stable POP mode, explaining 15.5% of the total variance, is characterized by an oscillation of 65 years and a damping time of 54 years. The spatial structure of POP4 is characterized by positive loadings over France and negative loadings over the southern part of the Iberian Peninsula and the eastern part of Europe. The stable POP modes identified could be related to preferred modes of climate variability that are characterized by similar oscillation periods (e.g. the Atlantic Multidecadal Oscillation, which is defined as a coherent pattern of variability in basin-wide North Atlantic sea surface temperatures with a period of 60-80 years). The decadal components identified by the POP analysis can be used operationally by decision makers as early predictors of drought conditions over the southern part of Europe.

The maturation of cortical sleep rhythms and networks over early development.

PubMed

Chu, C J; Leahy, J; Pathmanathan, J; Kramer, M A; Cash, S S

2014-07-01

Although neuronal activity drives all aspects of cortical development, how human brain rhythms spontaneously mature remains an active area of research. We sought to systematically evaluate the emergence of human brain rhythms and functional cortical networks over early development. We examined cortical rhythms and coupling patterns from birth through adolescence in a large cohort of healthy children (n=384) using scalp electroencephalogram (EEG) in the sleep state. We found that the emergence of brain rhythms follows a stereotyped sequence over early development. In general, higher frequencies increase in prominence with striking regional specificity throughout development. The coordination of these rhythmic activities across brain regions follows a general pattern of maturation in which broadly distributed networks of low-frequency oscillations increase in density while networks of high frequency oscillations become sparser and more highly clustered. Our results indicate that a predictable program directs the development of key rhythmic components and physiological brain networks over early development. This work expands our knowledge of normal cortical development. The stereotyped neurophysiological processes observed at the level of rhythms and networks may provide a scaffolding to support critical periods of cognitive growth. Furthermore, these conserved patterns could provide a sensitive biomarker for cortical health across development. Copyright © 2013 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

The maturation of cortical sleep rhythms and networks over early development

PubMed Central

Chu, CJ; Leahy, J; Pathmanathan, J; Kramer, MA; Cash, SS

2014-01-01

Objective Although neuronal activity drives all aspects of cortical development, how human brain rhythms spontaneously mature remains an active area of research. We sought to systematically evaluate the emergence of human brain rhythms and functional cortical networks over early development. Methods We examined cortical rhythms and coupling patterns from birth through adolescence in a large cohort of healthy children (n=384) using scalp electroencephalogram (EEG) in the sleep state. Results We found that the emergence of brain rhythms follows a stereotyped sequence over early development. In general, higher frequencies increase in prominence with striking regional specificity throughout development. The coordination of these rhythmic activities across brain regions follows a general pattern of maturation in which broadly distributed networks of low-frequency oscillations increase in density while networks of high frequency oscillations become sparser and more highly clustered. Conclusion Our results indicate that a predictable program directs the development of key rhythmic components and physiological brain networks over early development. Significance This work expands our knowledge of normal cortical development. The stereotyped neurophysiological processes observed at the level of rhythms and networks may provide a scaffolding to support critical periods of cognitive growth. Furthermore, these conserved patterns could provide a sensitive biomarker for cortical health across development. PMID:24418219

Noninvasive optical evaluation of low frequency oscillations in prefrontal cortex hemodynamics during verbal working memory

NASA Astrophysics Data System (ADS)

Li, Ting; Zhao, Yue; Li, Kai; Sun, Yunlong

2014-03-01

The low frequency oscillation (LFO) around 0.1 Hz has been observed recently in cerebral hemodynamic signals during rest/sleep, enhanced breathing, and head- up-tilting, showing that cerebral autoregulation can be accessed by LFOs. However, many brain function researches require direct measurement of LFOs during specified brain function activities. This pilot study explored using near-infrared spectroscopy/imaging (NIRS) to noninvasively and simultaneously detect LFOs of prefrontal cerebral hemodynamics (i.e., oxygenated/deoxygenated/total hemoglobin concentration: △[oxy-Hb]/ △[deoxy-Hb]/ △[tot-Hb]) during N-back visual verbal working memory task. The LFOs were extracted from the measured variables using power spectral analysis. We found the brain activation sites struck clear LFOs while other sites did not. The LFO of △[deoxy-Hb] acted as a negative pike and ranged in (0.05, 0.1) Hz, while LFOs of △[oxy-Hb] and △[tot-Hb] acted as a positive pike and ranged in (0.1, 0.15) Hz. The amplitude difference and frequency lag between △[deoxy-Hb] and △[oxy-Hb]/ △[tot-Hb] produced a more focused and sensitive activation map compare to hemodynamic amplitude-quantified activation maps. This study observed LFOs in brain activities and showed strong potential of LFOs in accessing brain functions.

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

PubMed Central

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

2015-01-01

In this paper, the topographical relationship between functional connectivity (intended as inter-regional synchronization), spectral and non-linear dynamical properties across cortical areas of the healthy human brain is considered. Based upon functional MRI acquisitions of spontaneous activity during wakeful idleness, node degree maps are determined by thresholding the temporal correlation coefficient among all voxel pairs. In addition, for individual voxel time-series, the relative amplitude of low-frequency fluctuations and the correlation dimension (D2), determined with respect to Fourier amplitude and value distribution matched surrogate data, are measured. Across cortical areas, high node degree is associated with a shift towards lower frequency activity and, compared to surrogate data, clearer saturation to a lower correlation dimension, suggesting presence of non-linear structure. An attempt to recapitulate this relationship in a network of single-transistor oscillators is made, based on a diffusive ring (n = 90) with added long-distance links defining four extended hub regions. Similarly to the brain data, it is found that oscillators in the hub regions generate signals with larger low-frequency cycle amplitude fluctuations and clearer saturation to a lower correlation dimension compared to surrogates. The effect emerges more markedly close to criticality. The homology observed between the two systems despite profound differences in scale, coupling mechanism and dynamics appears noteworthy. These experimental results motivate further investigation into the heterogeneity of cortical non-linear dynamics in relation to connectivity and underline the ability for small networks of single-transistor oscillators to recreate collective phenomena arising in much more complex biological systems, potentially representing a future platform for modelling disease-related changes. PMID:25833429

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

PubMed Central

Mori, Hiroki; Okuyama, Yuji; Asada, Minoru

2017-01-01

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

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

PubMed

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

2017-01-01

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

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

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

Minati, Ludovico, E-mail: lminati@ieee.org, E-mail: ludovico.minati@unitn.it, E-mail: lminati@istituto-besta.it; Center for Mind/Brain Sciences, University of Trento, Trento; Chiesa, Pietro

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

Enhancement of oscillatory activity in the endopiriform nucleus of rats raised under abnormal oral conditions.

PubMed

Yoshimura, Hiroshi; Hasumoto-Honjo, Miho; Sugai, Tokio; Segami, Natsuki; Kato, Nobuo

2014-02-21

Endopiriform nucleus (EPN) is located deep to the piriform cortex, and has neural connections with not only neighboring sensory areas but also subcortical areas where emotional and nociceptive information is processed. Well-balanced oral condition might play an important role in stability of brain activities. When the oral condition is impaired, several areas in the brain might be affected. In the present study, we investigated whether abnormal conditions of oral region influence neural activities in the EPN. Orthodontic appliance that generates continuous force and chronic pain-related stress was fixed to maxillary incisors of rats, and raised. Field potential recordings were made from the EPN of brain slices. We previously reported that the EPN has an ability to generate membrane potential oscillation. In the present study, we have applied the same methods to assess activities of neuron clusters in the EPN. In the case of normal rats, stable field potential oscillations were induced in the EPN by application of low-frequency electrical stimulation under the medium with caffeine. In the case of rats with the orthodontic appliance, stable field potential oscillations were also induced, but both duration of oscillatory activities and wavelet number were increased. The enhanced oscillations were depressed by blockade of NMDA receptors. Thus, impairment of oral health under application of continuous orthodontic force and chronic pain-related stress enhanced neural activities in the EPN, in which up-regulation of NMDA receptors may be concerned. These findings suggest that the EPN might be involved in information processing with regard to abnormal conditions of oral region. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Old Brains Come Uncoupled in Sleep: Slow Wave-Spindle Synchrony, Brain Atrophy, and Forgetting.

PubMed

Helfrich, Randolph F; Mander, Bryce A; Jagust, William J; Knight, Robert T; Walker, Matthew P

2018-01-03

The coupled interaction between slow-wave oscillations and sleep spindles during non-rapid-eye-movement (NREM) sleep has been proposed to support memory consolidation. However, little evidence in humans supports this theory. Moreover, whether such dynamic coupling is impaired as a consequence of brain aging in later life, contributing to cognitive and memory decline, is unknown. Combining electroencephalography (EEG), structural MRI, and sleep-dependent memory assessment, we addressed these questions in cognitively normal young and older adults. Directional cross-frequency coupling analyses demonstrated that the slow wave governs a precise temporal coordination of sleep spindles, the quality of which predicts overnight memory retention. Moreover, selective atrophy within the medial frontal cortex in older adults predicted a temporal dispersion of this slow wave-spindle coupling, impairing overnight memory consolidation and leading to forgetting. Prefrontal-dependent deficits in the spatiotemporal coordination of NREM sleep oscillations therefore represent one pathway explaining age-related memory decline. Copyright © 2017 Elsevier Inc. All rights reserved.

Oscillatory frontal theta responses are increased upon bisensory stimulation.

PubMed

Sakowitz, O W; Schürmann, M; Başar, E

2000-05-01

To investigate the functional correlation of oscillatory EEG components with the interaction of sensory modalities following simultaneous audio-visual stimulation. In an experimental study (15 subjects) we compared auditory evoked potentials (AEPs) and visual evoked potentials (VEPs) to bimodal evoked potentials (BEPs; simultaneous auditory and visual stimulation). BEPs were assumed to be brain responses to complex stimuli as a marker for intermodal associative functioning. Frequency domain analysis of these EPs showed marked theta-range components in response to bimodal stimulation. These theta components could not be explained by linear addition of the unimodal responses in the time domain. Considering topography the increased theta-response showed a remarkable frontality in proximity to multimodal association cortices. Referring to methodology we try to demonstrate that, even if various behavioral correlates of brain oscillations exist, common patterns can be extracted by means of a systems-theoretical approach. Serving as an example of functionally relevant brain oscillations, theta responses could be interpreted as an indicator of associative information processing.

Low-frequency oscillation amplitude elevation of prefrontal cerebral hemodynamics with driving duration during prolonged driving test

NASA Astrophysics Data System (ADS)

Deng, Zishan; Gao, Yuan; Li, Ting

2018-02-01

It has been observed that there is a low-frequency oscillation (LFO) around 0.1 Hz in cerebral hemodynamics related to brain activity. Since functional near-infrared spectroscopy (fNIRS) is a novel technique to monitor hemodynamic responses noninvasively, we applied it to detect LFOs of cerebral hemodynamic parameters, such as oxyhemoglobin and deoxyhemoglobin, during prolonged driving. We performed an experiment lasting for 7 hours and an experimental test was done every hour and 8 times altogether. 7 subjects were recruited and the data of 3 of them were analyzed. By means of Fourier transformation, the amplitude of the three parameters during each test at 0.1 Hz in frequency domain was extracted. The results showed an increasing trend in the 0.1 Hz amplitudes of the three hemodynamic parameters during 7 hours' simulated driving test. Our findings indicated the potential of LFOs of prefrontal cerebral hemodynamics in brain research and brain function evaluation.

Mass synchronization: Occurrence and its control with possible applications to brain dynamics

NASA Astrophysics Data System (ADS)

Chandrasekar, V. K.; Sheeba, Jane H.; Lakshmanan, M.

2010-12-01

Occurrence of strong or mass synchronization of a large number of neuronal populations in the brain characterizes its pathological states. In order to establish an understanding of the mechanism underlying such pathological synchronization, we present a model of coupled populations of phase oscillators representing the interacting neuronal populations. Through numerical analysis, we discuss the occurrence of mass synchronization in the model, where a source population which gets strongly synchronized drives the target populations onto mass synchronization. We hypothesize and identify a possible cause for the occurrence of such a synchronization, which is so far unknown: Pathological synchronization is caused not just because of the increase in the strength of coupling between the populations but also because of the strength of the strong synchronization of the drive population. We propose a demand controlled method to control this pathological synchronization by providing a delayed feedback where the strength and frequency of the synchronization determine the strength and the time delay of the feedback. We provide an analytical explanation for the occurrence of pathological synchronization and its control in the thermodynamic limit.

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.

Phase computations and phase models for discrete molecular oscillators.

PubMed

Suvak, Onder; Demir, Alper

2012-06-11

Biochemical oscillators perform crucial functions in cells, e.g., they set up circadian clocks. The dynamical behavior of oscillators is best described and analyzed in terms of the scalar quantity, phase. A rigorous and useful definition for phase is based on the so-called isochrons of oscillators. Phase computation techniques for continuous oscillators that are based on isochrons have been used for characterizing the behavior of various types of oscillators under the influence of perturbations such as noise. In this article, we extend the applicability of these phase computation methods to biochemical oscillators as discrete molecular systems, upon the information obtained from a continuous-state approximation of such oscillators. In particular, we describe techniques for computing the instantaneous phase of discrete, molecular oscillators for stochastic simulation algorithm generated sample paths. We comment on the accuracies and derive certain measures for assessing the feasibilities of the proposed phase computation methods. Phase computation experiments on the sample paths of well-known biological oscillators validate our analyses. The impact of noise that arises from the discrete and random nature of the mechanisms that make up molecular oscillators can be characterized based on the phase computation techniques proposed in this article. The concept of isochrons is the natural choice upon which the phase notion of oscillators can be founded. The isochron-theoretic phase computation methods that we propose can be applied to discrete molecular oscillators of any dimension, provided that the oscillatory behavior observed in discrete-state does not vanish in a continuous-state approximation. Analysis of the full versatility of phase noise phenomena in molecular oscillators will be possible if a proper phase model theory is developed, without resorting to such approximations.

Phase computations and phase models for discrete molecular oscillators

PubMed Central

2012-01-01

Background Biochemical oscillators perform crucial functions in cells, e.g., they set up circadian clocks. The dynamical behavior of oscillators is best described and analyzed in terms of the scalar quantity, phase. A rigorous and useful definition for phase is based on the so-called isochrons of oscillators. Phase computation techniques for continuous oscillators that are based on isochrons have been used for characterizing the behavior of various types of oscillators under the influence of perturbations such as noise. Results In this article, we extend the applicability of these phase computation methods to biochemical oscillators as discrete molecular systems, upon the information obtained from a continuous-state approximation of such oscillators. In particular, we describe techniques for computing the instantaneous phase of discrete, molecular oscillators for stochastic simulation algorithm generated sample paths. We comment on the accuracies and derive certain measures for assessing the feasibilities of the proposed phase computation methods. Phase computation experiments on the sample paths of well-known biological oscillators validate our analyses. Conclusions The impact of noise that arises from the discrete and random nature of the mechanisms that make up molecular oscillators can be characterized based on the phase computation techniques proposed in this article. The concept of isochrons is the natural choice upon which the phase notion of oscillators can be founded. The isochron-theoretic phase computation methods that we propose can be applied to discrete molecular oscillators of any dimension, provided that the oscillatory behavior observed in discrete-state does not vanish in a continuous-state approximation. Analysis of the full versatility of phase noise phenomena in molecular oscillators will be possible if a proper phase model theory is developed, without resorting to such approximations. PMID:22687330

A brain-computer interface based on self-regulation of gamma-oscillations in the superior parietal cortex

NASA Astrophysics Data System (ADS)

Grosse-Wentrup, Moritz; Schölkopf, Bernhard

2014-10-01

Objective. Brain-computer interface (BCI) systems are often based on motor- and/or sensory processes that are known to be impaired in late stages of amyotrophic lateral sclerosis (ALS). We propose a novel BCI designed for patients in late stages of ALS that only requires high-level cognitive processes to transmit information from the user to the BCI. Approach. We trained subjects via EEG-based neurofeedback to self-regulate the amplitude of gamma-oscillations in the superior parietal cortex (SPC). We argue that parietal gamma-oscillations are likely to be associated with high-level attentional processes, thereby providing a communication channel that does not rely on the integrity of sensory- and/or motor-pathways impaired in late stages of ALS. Main results. Healthy subjects quickly learned to self-regulate gamma-power in the SPC by alternating between states of focused attention and relaxed wakefulness, resulting in an average decoding accuracy of 70.2%. One locked-in ALS patient (ALS-FRS-R score of zero) achieved an average decoding accuracy significantly above chance-level though insufficient for communication (55.8%). Significance. Self-regulation of gamma-power in the SPC is a feasible paradigm for brain-computer interfacing and may be preserved in late stages of ALS. This provides a novel approach to testing whether completely locked-in ALS patients retain the capacity for goal-directed thinking.

Stability of entrainment of a continuum of coupled oscillators

DOE PAGES

Snyder, Jordan; Zlotnik, Anatoly; Hagberg, Aric

2017-10-05

Complex natural and engineered systems are ubiquitous, and their behavior is challenging to characterize and control. Here, we examine the design of the entrainment process for an uncountably infinite collection of coupled phase oscillators that are all subject to the same periodic driving signal. In the absence of coupling, an appropriately designed input can result in each oscillator attaining the frequency of the driving signal, with a phase offset determined by its natural frequency. We also consider a special case of interacting oscillators in which the coupling tends to destabilize the phase configuration to which the driving signal would sendmore » the collection in the absence of coupling. In this setting, we derive stability results that characterize the trade-off between the effects of driving and coupling, and compare these results to the well-known Kuramoto model of a collection of free-running coupled oscillators.« less

Stability of entrainment of a continuum of coupled oscillators

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

Snyder, Jordan; Zlotnik, Anatoly; Hagberg, Aric

Complex natural and engineered systems are ubiquitous, and their behavior is challenging to characterize and control. Here, we examine the design of the entrainment process for an uncountably infinite collection of coupled phase oscillators that are all subject to the same periodic driving signal. In the absence of coupling, an appropriately designed input can result in each oscillator attaining the frequency of the driving signal, with a phase offset determined by its natural frequency. We also consider a special case of interacting oscillators in which the coupling tends to destabilize the phase configuration to which the driving signal would sendmore » the collection in the absence of coupling. In this setting, we derive stability results that characterize the trade-off between the effects of driving and coupling, and compare these results to the well-known Kuramoto model of a collection of free-running coupled oscillators.« less

Simulation of cortico-basal ganglia oscillations and their suppression by closed loop deep brain stimulation.

PubMed

Grant, Peadar F; Lowery, Madeleine M

2013-07-01

A new model of deep brain stimulation (DBS) is presented that integrates volume conduction effects with a neural model of pathological beta-band oscillations in the cortico-basal ganglia network. The model is used to test the clinical hypothesis that closed-loop control of the amplitude of DBS may be possible, based on the average rectified value of beta-band oscillations in the local field potential. Simulation of closed-loop high-frequency DBS was shown to yield energy savings, with the magnitude of the energy saved dependent on the strength of coupling between the subthalamic nucleus and the remainder of the cortico-basal ganglia network. When closed-loop DBS was applied to a strongly coupled cortico-basal ganglia network, the stimulation energy delivered over a 480 s period was reduced by up to 42%. Greater energy reductions were observed for weakly coupled networks, as the stimulation amplitude reduced to zero once the initial desynchronization had occurred. The results provide support for the application of closed-loop high-frequency DBS based on electrophysiological biomarkers.

Prestimulus oscillatory activity in the alpha band predicts visual discrimination ability.

PubMed

van Dijk, Hanneke; Schoffelen, Jan-Mathijs; Oostenveld, Robert; Jensen, Ole

2008-02-20

Although the resting and baseline states of the human electroencephalogram and magnetoencephalogram (MEG) are dominated by oscillations in the alpha band (approximately 10 Hz), the functional role of these oscillations remains unclear. In this study we used MEG to investigate how spontaneous oscillations in humans presented before visual stimuli modulate visual perception. Subjects had to report if there was a subtle difference in gray levels between two superimposed presented discs. We then compared the prestimulus brain activity for correctly (hits) versus incorrectly (misses) identified stimuli. We found that visual discrimination ability decreased with an increase in prestimulus alpha power. Given that reaction times did not vary systematically with prestimulus alpha power changes in vigilance are not likely to explain the change in discrimination ability. Source reconstruction using spatial filters allowed us to identify the brain areas accounting for this effect. The dominant sources modulating visual perception were localized around the parieto-occipital sulcus. We suggest that the parieto-occipital alpha power reflects functional inhibition imposed by higher level areas, which serves to modulate the gain of the visual stream.

Functional correlates of brain aging: beta and gamma frequency band responses to age-related cortical changes.

PubMed

Christov, Mario; Dushanova, Juliana

2016-01-01

The brain as a system with gradually declined resources by age maximizes its performance by neural network reorganization for greater efficiency of neuronal oscillations in a given frequency band. Whether event-related high-frequency band responses are related to plasticity in neural recruitment contributed to the stability of sensory/cognitive mechanisms accompanying aging or are underlined pathological changes seen in aging brain remains unknown. Aged effect on brain electrical activity was studied in auditory discrimination task (low-frequency and high-frequency tone) at particular cortical locations in beta (β1: 12.5-20; β2: 20.5-30 Hz) and gamma frequency bands (γ1: 30.5-49; γ2: 52-69 Hz) during sensory (post-stimulus interval 0-250 ms) and cognitive processing (250-600 ms). Beta1 activity less affected by age during sensory processing. Reduced beta1 activity was more widespread during cognitive processing. This difference increased in fronto-parietal direction more expressed after high-frequency tone stimulation. Beta2 and gamma activity were more pronounced with progressive age during sensory processing. Reducing regional-process specificity with progressing age characterized age-related and tone-dependent beta2 changes during sensory, but not during cognitive processing. Beta2 and gamma activity diminished with age on cognitive processes, except the higher frontal tone-dependent gamma activity during cognitive processing. With increasing age, larger gamma2 activity was more expressed over the frontal brain areas to high tone discrimination and hand reaction choice. These gamma2 differences were shifted from posterior to anterior brain regions with advancing age. The aged influence was higher on cognitive processes than on perceptual ones.

Electrical Brain Responses to an Auditory Illusion and the Impact of Musical Expertise

PubMed Central

Ioannou, Christos I.; Pereda, Ernesto; Lindsen, Job P.; Bhattacharya, Joydeep

2015-01-01

The presentation of two sinusoidal tones, one to each ear, with a slight frequency mismatch yields an auditory illusion of a beating frequency equal to the frequency difference between the two tones; this is known as binaural beat (BB). The effect of brief BB stimulation on scalp EEG is not conclusively demonstrated. Further, no studies have examined the impact of musical training associated with BB stimulation, yet musicians' brains are often associated with enhanced auditory processing. In this study, we analysed EEG brain responses from two groups, musicians and non-musicians, when stimulated by short presentation (1 min) of binaural beats with beat frequency varying from 1 Hz to 48 Hz. We focused our analysis on alpha and gamma band EEG signals, and they were analysed in terms of spectral power, and functional connectivity as measured by two phase synchrony based measures, phase locking value and phase lag index. Finally, these measures were used to characterize the degree of centrality, segregation and integration of the functional brain network. We found that beat frequencies belonging to alpha band produced the most significant steady-state responses across groups. Further, processing of low frequency (delta, theta, alpha) binaural beats had significant impact on cortical network patterns in the alpha band oscillations. Altogether these results provide a neurophysiological account of cortical responses to BB stimulation at varying frequencies, and demonstrate a modulation of cortico-cortical connectivity in musicians' brains, and further suggest a kind of neuronal entrainment of a linear and nonlinear relationship to the beating frequencies. PMID:26065708

Electrical Brain Responses to an Auditory Illusion and the Impact of Musical Expertise.

PubMed

Ioannou, Christos I; Pereda, Ernesto; Lindsen, Job P; Bhattacharya, Joydeep

2015-01-01

The presentation of two sinusoidal tones, one to each ear, with a slight frequency mismatch yields an auditory illusion of a beating frequency equal to the frequency difference between the two tones; this is known as binaural beat (BB). The effect of brief BB stimulation on scalp EEG is not conclusively demonstrated. Further, no studies have examined the impact of musical training associated with BB stimulation, yet musicians' brains are often associated with enhanced auditory processing. In this study, we analysed EEG brain responses from two groups, musicians and non-musicians, when stimulated by short presentation (1 min) of binaural beats with beat frequency varying from 1 Hz to 48 Hz. We focused our analysis on alpha and gamma band EEG signals, and they were analysed in terms of spectral power, and functional connectivity as measured by two phase synchrony based measures, phase locking value and phase lag index. Finally, these measures were used to characterize the degree of centrality, segregation and integration of the functional brain network. We found that beat frequencies belonging to alpha band produced the most significant steady-state responses across groups. Further, processing of low frequency (delta, theta, alpha) binaural beats had significant impact on cortical network patterns in the alpha band oscillations. Altogether these results provide a neurophysiological account of cortical responses to BB stimulation at varying frequencies, and demonstrate a modulation of cortico-cortical connectivity in musicians' brains, and further suggest a kind of neuronal entrainment of a linear and nonlinear relationship to the beating frequencies.

Plasma Oscillation Characterization of NASA's HERMeS Hall Thruster via High Speed Imaging

NASA Technical Reports Server (NTRS)

Huang, Wensheng; Kamhawi, Hani; Haag, Thomas W.

2016-01-01

The performance and facility effect characterization tests of NASA's 12.5-kW Hall Effect Rocket with Magnetic Shielding had been completed. As a part of these tests, three plasma oscillation characterization studies were performed to help determine operation settings and quantify margins. The studies included the magnetic field strength variation study, background pressure effect study, and cathode flow fraction study. Separate high-speed videos of the thruster including the cathode and of only the cathode were recorded. Breathing mode at 10-15 kHz and cathode gradient-driven mode at 60-75 kHz were observed. An additional high frequency (40-70 kHz) global oscillation mode with sinusoidal probability distribution function was identified.

Morning nutrition and executive function processes in preadolescents: modulation of frontal event-related theta, beta and gamma EEG oscillations during a go/ no-go task

USDA-ARS?s Scientific Manuscript database

Executive functions (i.e., goal-directed behavior such as inhibition and flexibility of action) have been linked to frontal brain regions and to covariations in oscillatory brain activity, e.g., theta and gamma activity. We studied the effects of morning nutritional status on executive function rel...

Magnetometer based on the opto-electronic microwave oscillator

NASA Astrophysics Data System (ADS)

Matsko, Andrey B.; Strekalov, Dmitry; Maleki, Lute

2005-03-01

We present a scheme for an all-optical self-oscillating magnetometer based on the opto-electronic oscillator stabilized with an atomic vapor cell. We demonstrate a proof of the principle with DC magnetic field measurements characterized by 2 × 10-7 G sensitivity and 1-1000 mG dynamic range.

Congenital Head Nodding and Nystagmus with Cerebrocerebellar Degeneration

ERIC Educational Resources Information Center

Kalyanaraman, K.; And Others

1973-01-01

Reported are three case histories of children with congenital head nodding and nystagmus (rhytmic oscillation of the eyeballs) associated with brain degeneration and motor and mental retardation. (DB)

USE OF NEUROFEEDBACK AND MINDFULNESS TO ENHANCE RESPONSE TO HYPNOSIS TREATMENT IN INDIVIDUALS WITH MULTIPLE SCLEROSIS: Results From a Pilot Randomized Clinical Trial.

PubMed

Jensen, Mark P; Battalio, Samuel L; Chan, Joy F; Edwards, Karlyn A; Day, Melissa A; Sherlin, Leslie H; Ehde, Dawn M

2018-01-01

This pilot study evaluated the possibility that 2 interventions hypothesized to increase slower brain oscillations (e.g., theta) may enhance the efficacy of hypnosis treatment, given evidence that hypnotic responding is associated with slower brain oscillations. Thirty-two individuals with multiple sclerosis and chronic pain, fatigue, or both, were randomly assigned to 1 of 2 interventions thought to increase slow wave activity (mindfulness meditation or neurofeedback training) or no enhancing intervention, and then given 5 sessions of self-hypnosis training targeting their presenting symptoms. The findings supported the potential for both neurofeedback and mindfulness to enhance response to hypnosis treatment. Research using larger sample sizes to determine the generalizability of these findings is warranted.

Neuronal and oscillatory activity during reward processing in the human ventral striatum.

PubMed

Lega, Bradley C; Kahana, Michael J; Jaggi, Jurg; Baltuch, Gordon H; Zaghloul, Kareem

2011-11-16

Accumulated evidence from animal studies implicates the ventral striatum in the processing of reward information. Recently, deep brain stimulation (DBS) surgery has enabled researchers to analyze neurophysiological recordings from humans engaged in reward tasks. We present data recorded from the human ventral striatum during deep brain stimulation surgery as a participant played a video game coupled to the receipt of visual reward images. To our knowledge, we identify the first instances of reward-sensitive single unit activity in the human ventral striatum. Local field potential data suggest that alpha oscillations are sensitive to positive feedback, whereas beta oscillations exhibit significantly higher power during unrewarded trials. We report evidence of alpha-gamma cross-frequency coupling that differentiates between positive and negative feedback. © 2011 Wolters Kluwer Health | Lippincott Williams & Wilkins.

Sensory-driven and spontaneous gamma oscillations engage distinct cortical circuitry

PubMed Central

2015-01-01

Gamma oscillations are a robust component of sensory responses but are also part of the background spontaneous activity of the brain. To determine whether the properties of gamma oscillations in cortex are specific to their mechanism of generation, we compared in mouse visual cortex in vivo the laminar geometry and single-neuron rhythmicity of oscillations produced during sensory representation with those occurring spontaneously in the absence of stimulation. In mouse visual cortex under anesthesia (isoflurane and xylazine), visual stimulation triggered oscillations mainly between 20 and 50 Hz, which, because of their similar functional significance to gamma oscillations in higher mammals, we define here as gamma range. Sensory representation in visual cortex specifically increased gamma oscillation amplitude in the supragranular (L2/3) and granular (L4) layers and strongly entrained putative excitatory and inhibitory neurons in infragranular layers, while spontaneous gamma oscillations were distributed evenly through the cortical depth and primarily entrained putative inhibitory neurons in the infragranular (L5/6) cortical layers. The difference in laminar distribution of gamma oscillations during the two different conditions may result from differences in the source of excitatory input to the cortex. In addition, modulation of superficial gamma oscillation amplitude did not result in a corresponding change in deep-layer oscillations, suggesting that superficial and deep layers of cortex may utilize independent but related networks for gamma generation. These results demonstrate that stimulus-driven gamma oscillations engage cortical circuitry in a manner distinct from spontaneous oscillations and suggest multiple networks for the generation of gamma oscillations in cortex. PMID:26719085

Automated asteroseismic peak detections

NASA Astrophysics Data System (ADS)

García Saravia Ortiz de Montellano, Andrés; Hekker, S.; Themeßl, N.

2018-05-01

Space observatories such as Kepler have provided data that can potentially revolutionize our understanding of stars. Through detailed asteroseismic analyses we are capable of determining fundamental stellar parameters and reveal the stellar internal structure with unprecedented accuracy. However, such detailed analyses, known as peak bagging, have so far been obtained for only a small percentage of the observed stars while most of the scientific potential of the available data remains unexplored. One of the major challenges in peak bagging is identifying how many solar-like oscillation modes are visible in a power density spectrum. Identification of oscillation modes is usually done by visual inspection that is time-consuming and has a degree of subjectivity. Here, we present a peak-detection algorithm especially suited for the detection of solar-like oscillations. It reliably characterizes the solar-like oscillations in a power density spectrum and estimates their parameters without human intervention. Furthermore, we provide a metric to characterize the false positive and false negative rates to provide further information about the reliability of a detected oscillation mode or the significance of a lack of detected oscillation modes. The algorithm presented here opens the possibility for detailed and automated peak bagging of the thousands of solar-like oscillators observed by Kepler.

Mathematical Modeling of an Oscillating Droplet

NASA Technical Reports Server (NTRS)

Berry, S.; Hyers, R. W.; Racz, L. M.; Abedian, B.; Rose, M. Franklin (Technical Monitor)

2000-01-01

Oscillating droplets are of interest in a number of disciplines. A practical application is the oscillating drop method, which is a technique for measuring surface tension and viscosity of liquid metals. It is especially suited to undercooled and highly reactive metals, because it is performed by electromagnetic levitation. The natural oscillation frequency of the droplets is related to the surface tension of the material, and the decay of oscillations is related to its viscosity. The fluid flow inside the droplet must be laminar in order for this technique to yield good results. Because no experimental method has yet been developed to visualize flow in electromagnetically-levitated oscillating metal droplets, mathematical modeling is required to determine whether or not turbulence occurs. Three mathematical models of the flow: (1) assuming laminar conditions, (2) using the k-epsilon turbulence model, and (3) using the RNG turbulence model, respectively, are compared and contrasted to determine the physical characteristics of the flow. It is concluded that the RNG model is the best suited for describing this problem. The goal of the presented work was to characterize internal flow in an oscillating droplet of liquid metal, and to verify the accuracy of the characterization by comparing calculated surface tension and viscosity.

Robustness effect of gap junctions between Golgi cells on cerebellar cortex oscillations

PubMed Central

2011-01-01

Background Previous one-dimensional network modeling of the cerebellar granular layer has been successfully linked with a range of cerebellar cortex oscillations observed in vivo. However, the recent discovery of gap junctions between Golgi cells (GoCs), which may cause oscillations by themselves, has raised the question of how gap-junction coupling affects GoC and granular-layer oscillations. To investigate this question, we developed a novel two-dimensional computational model of the GoC-granule cell (GC) circuit with and without gap junctions between GoCs. Results Isolated GoCs coupled by gap junctions had a strong tendency to generate spontaneous oscillations without affecting their mean firing frequencies in response to distributed mossy fiber input. Conversely, when GoCs were synaptically connected in the granular layer, gap junctions increased the power of the oscillations, but the oscillations were primarily driven by the synaptic feedback loop between GoCs and GCs, and the gap junctions did not change oscillation frequency or the mean firing rate of either GoCs or GCs. Conclusion Our modeling results suggest that gap junctions between GoCs increase the robustness of cerebellar cortex oscillations that are primarily driven by the feedback loop between GoCs and GCs. The robustness effect of gap junctions on synaptically driven oscillations observed in our model may be a general mechanism, also present in other regions of the brain. PMID:22330240

Genetic Psychophysiology: advances, problems, and future directions

PubMed Central

Anokhin, Andrey P.

2014-01-01

This paper presents an overview of historical advances and the current state of genetic psychophysiology, a rapidly developing interdisciplinary research linking genetics, brain, and human behavior, discusses methodological problems, and outlines future directions of research. The main goals of genetic psychophysiology are to elucidate the neural pathways and mechanisms mediating genetic influences on cognition and emotion, identify intermediate brain-based phenotypes for psychopathology, and provide a functional characterization of genes being discovered by large association studies of behavioral phenotypes. Since the initiation of this neurogenetic approach to human individual differences in the 1970s, numerous twin and family studies have provided strong evidence for heritability of diverse aspects of brain function including resting-state brain oscillations, functional connectivity, and event-related neural activity in a variety of cognitive and emotion processing tasks, as well as peripheral psychophysiological responses. These data indicate large differences in the presence and strength of genetic influences across measures and domains, permitting the selection of heritable characteristics for gene finding studies. More recently, candidate gene association studies began to implicate specific genetic variants in different aspects of neurocognition. However, great caution is needed in pursuing this line of research due to its demonstrated proneness to generate false-positive findings. Recent developments in methods for physiological signal analysis, hemodynamic imaging, and genomic technologies offer new exciting opportunities for the investigation of the interplay between genetic and environmental factors in the development of individual differences in behavior, both normal and abnormal. PMID:24739435

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.

Neural dynamics in motor preparation: From phase-mediated global computation to amplitude-mediated local computation.

PubMed

Kajihara, Takafumi; Anwar, Muhammad Nabeel; Kawasaki, Masahiro; Mizuno, Yuji; Nakazawa, Kimitaka; Kitajo, Keiichi

2015-09-01

Oscillatory activity plays a critical role in the brain. Here, we illustrate the dynamics of neural oscillations in the motor system of the brain. We used a non-directional cue to instruct participants to prepare a motor response with either the left or the right hand and recorded electroencephalography during the preparation of the response. Consistent with previous findings, the amplitude of alpha-band (8-14Hz) oscillations significantly decreased over the motor region contralateral to the hand prepared for the response. Prior to this decrease, there were a number of inter-regional phase synchronies at lower frequencies (2-4Hz; delta band). Cross-frequency coupling was quantified to further explore the direct link between alpha amplitudes and delta synchrony. The cross-frequency coupling of showed response-specific modulation, whereby the motor region contralateral to the preparation hand exhibited an increase in coupling relative to the baseline. The amplitude of alpha oscillations had an unpreferred and a preferred delta phase, in which the amplitude was modulated negatively and positively, respectively. Given the amplitude of alpha-band oscillations decreased over the analyzed period, the alpha amplitude might be down-regulated by the phase-amplitude coupling, although we do not have direct evidence for that. Taken together, these results show global-to-local computation in the motor system, which started from inter-regional delta phase synchrony and ended at an effector-specific decrease in the amplitude of alpha-band oscillations, with phase-amplitude coupling connecting both computations. Copyright © 2015. Published by Elsevier Inc.

Cortical thickness as a contributor to abnormal oscillations in schizophrenia?

PubMed

Edgar, J Christopher; Chen, Yu-Han; Lanza, Matthew; Howell, Breannan; Chow, Vivian Y; Heiken, Kory; Liu, Song; Wootton, Cassandra; Hunter, Michael A; Huang, Mingxiong; Miller, Gregory A; Cañive, José M

2014-01-01

Although brain rhythms depend on brain structure (e.g., gray and white matter), to our knowledge associations between brain oscillations and structure have not been investigated in healthy controls (HC) or in individuals with schizophrenia (SZ). Observing function-structure relationships, for example establishing an association between brain oscillations (defined in terms of amplitude or phase) and cortical gray matter, might inform models on the origins of psychosis. Given evidence of functional and structural abnormalities in primary/secondary auditory regions in SZ, the present study examined how superior temporal gyrus (STG) structure relates to auditory STG low-frequency and 40 Hz steady-state activity. Given changes in brain activity as a function of age, age-related associations in STG oscillatory activity were also examined. Thirty-nine individuals with SZ and 29 HC were recruited. 40 Hz amplitude-modulated tones of 1 s duration were presented. MEG and T1-weighted sMRI data were obtained. Using the sources localizing 40 Hz evoked steady-state activity (300 to 950 ms), left and right STG total power and inter-trial coherence were computed. Time-frequency group differences and associations with STG structure and age were also examined. Decreased total power and inter-trial coherence in SZ were observed in the left STG for initial post-stimulus low-frequency activity (~ 50 to 200 ms, ~ 4 to 16 Hz) as well as 40 Hz steady-state activity (~ 400 to 1000 ms). Left STG 40 Hz total power and inter-trial coherence were positively associated with left STG cortical thickness in HC, not in SZ. Left STG post-stimulus low-frequency and 40 Hz total power were positively associated with age, again only in controls. Left STG low-frequency and steady-state gamma abnormalities distinguish SZ and HC. Disease-associated damage to STG gray matter in schizophrenia may disrupt the age-related left STG gamma-band function-structure relationships observed in controls.

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.

Kinematic and neurophysiological consequences of an assisted-force-feedback brain-machine interface training: a case study.

PubMed

Silvoni, Stefano; Cavinato, Marianna; Volpato, Chiara; Cisotto, Giulia; Genna, Clara; Agostini, Michela; Turolla, Andrea; Ramos-Murguialday, Ander; Piccione, Francesco

2013-01-01

In a proof-of-principle prototypical demonstration we describe a new type of brain-machine interface (BMI) paradigm for upper limb motor-training. The proposed technique allows a fast contingent and proportionally modulated stimulation of afferent proprioceptive and motor output neural pathways using operant learning. Continuous and immediate assisted-feedback of force proportional to rolandic rhythm oscillations during actual movements was employed and illustrated with a single case experiment. One hemiplegic patient was trained for 2 weeks coupling somatosensory brain oscillations with force-field control during a robot-mediated center-out motor-task whose execution approaches movements of everyday life. The robot facilitated actual movements adding a modulated force directed to the target, thus providing a non-delayed proprioceptive feedback. Neuro-electric, kinematic, and motor-behavioral measures were recorded in pre- and post-assessments without force assistance. Patient's healthy arm was used as control since neither a placebo control was possible nor other control conditions. We observed a generalized and significant kinematic improvement in the affected arm and a spatial accuracy improvement in both arms, together with an increase and focalization of the somatosensory rhythm changes used to provide assisted-force-feedback. The interpretation of the neurophysiological and kinematic evidences reported here is strictly related to the repetition of the motor-task and the presence of the assisted-force-feedback. Results are described as systematic observations only, without firm conclusions about the effectiveness of the methodology. In this prototypical view, the design of appropriate control conditions is discussed. This study presents a novel operant-learning-based BMI-application for motor-training coupling brain oscillations and force feedback during an actual movement.

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

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

PubMed Central

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

2014-01-01

Despite the ubiquity of sleep across phylogeny, its function remains elusive. In this review, we consider one compelling candidate: brain plasticity associated with memory processing. Focusing largely on hippocampus-dependent memory in rodents and humans, we describe molecular, cellular, network, whole-brain and behavioral evidence establishing a role for sleep both in preparation for initial memory encoding, and in the subsequent offline consolidation ofmemory. Sleep and sleep deprivation bidirectionally alter molecular signaling pathways that regulate synaptic strength and control plasticity-related gene transcription and protein translation. At the cellular level, sleep deprivation impairs cellular excitability necessary for inducing synaptic potentiation and accelerates the decay of long-lasting forms of synaptic plasticity. In contrast, NREM and REM sleep enhance previously induced synaptic potentiation, although synaptic de-potentiation during sleep has also been observed. Beyond single cell dynamics, large-scale cell ensembles express coordinated replay of prior learning-related firing patterns during subsequent sleep. This occurs in the hippocampus, in the cortex, and between the hippocampus and cortex, commonly in association with specific NREM sleep oscillations. At the whole-brain level, somewhat analogous learning-associated hippocampal (re)activation during NREM sleep has been reported in humans. Moreover, the same cortical NREM oscillations associated with replay in rodents also promote human hippocampal memory consolidation, and this process can be manipulated using exogenous reactivation cues during sleep. Mirroring molecular findings in rodents, specific NREM sleep oscillations before encoding refresh human hippocampal learning capacity, while deprivation of sleep conversely impairs subsequent hippocampal activity and associated encoding. Together, these cross-descriptive level findings demonstrate that the unique neurobiology of sleep exert powerful effects on molecular, cellular and network mechanism of plasticity that govern both initial learning and subsequent long-term memory consolidation. PMID:24028961

Genetic influences on functional connectivity associated with feedback processing and prediction error: Phase coupling of theta-band oscillations in twins.

PubMed

Demiral, Şükrü Barış; Golosheykin, Simon; Anokhin, Andrey P

2017-05-01

Detection and evaluation of the mismatch between the intended and actually obtained result of an action (reward prediction error) is an integral component of adaptive self-regulation of behavior. Extensive human and animal research has shown that evaluation of action outcome is supported by a distributed network of brain regions in which the anterior cingulate cortex (ACC) plays a central role, and the integration of distant brain regions into a unified feedback-processing network is enabled by long-range phase synchronization of cortical oscillations in the theta band. Neural correlates of feedback processing are associated with individual differences in normal and abnormal behavior, however, little is known about the role of genetic factors in the cerebral mechanisms of feedback processing. Here we examined genetic influences on functional cortical connectivity related to prediction error in young adult twins (age 18, n=399) using event-related EEG phase coherence analysis in a monetary gambling task. To identify prediction error-specific connectivity pattern, we compared responses to loss and gain feedback. Monetary loss produced a significant increase of theta-band synchronization between the frontal midline region and widespread areas of the scalp, particularly parietal areas, whereas gain resulted in increased synchrony primarily within the posterior regions. Genetic analyses showed significant heritability of frontoparietal theta phase synchronization (24 to 46%), suggesting that individual differences in large-scale network dynamics are under substantial genetic control. We conclude that theta-band synchronization of brain oscillations related to negative feedback reflects genetically transmitted differences in the neural mechanisms of feedback processing. To our knowledge, this is the first evidence for genetic influences on task-related functional brain connectivity assessed using direct real-time measures of neuronal synchronization. Copyright © 2016 Elsevier B.V. All rights reserved.

Functional Neuroimaging Insights into the Physiology of Human Sleep

PubMed Central

Dang-Vu, Thien Thanh; Schabus, Manuel; Desseilles, Martin; Sterpenich, Virginie; Bonjean, Maxime; Maquet, Pierre

2010-01-01

Functional brain imaging has been used in humans to noninvasively investigate the neural mechanisms underlying the generation of sleep stages. On the one hand, REM sleep has been associated with the activation of the pons, thalamus, limbic areas, and temporo-occipital cortices, and the deactivation of prefrontal areas, in line with theories of REM sleep generation and dreaming properties. On the other hand, during non-REM (NREM) sleep, decreases in brain activity have been consistently found in the brainstem, thalamus, and in several cortical areas including the medial prefrontal cortex (MPFC), in agreement with a homeostatic need for brain energy recovery. Benefiting from a better temporal resolution, more recent studies have characterized the brain activations related to phasic events within specific sleep stages. In particular, they have demonstrated that NREM sleep oscillations (spindles and slow waves) are indeed associated with increases in brain activity in specific subcortical and cortical areas involved in the generation or modulation of these waves. These data highlight that, even during NREM sleep, brain activity is increased, yet regionally specific and transient. Besides refining the understanding of sleep mechanisms, functional brain imaging has also advanced the description of the functional properties of sleep. For instance, it has been shown that the sleeping brain is still able to process external information and even detect the pertinence of its content. The relationship between sleep and memory has also been refined using neuroimaging, demonstrating post-learning reactivation during sleep, as well as the reorganization of memory representation on the systems level, sometimes with long-lasting effects on subsequent memory performance. Further imaging studies should focus on clarifying the role of specific sleep patterns for the processing of external stimuli, as well as the consolidation of freshly encoded information during sleep. Citation: Dang-Vu TT; Schabus M; Desseilles M; Sterpenich V; Bonjean M; Maquet P. Functional neuroimaging insights into the physiology of human sleep. SLEEP 2010;33(12):1589-1603. PMID:21120121

Design of memristive interface between electronic neurons

NASA Astrophysics Data System (ADS)

Gerasimova, S. A.; Mikhaylov, A. N.; Belov, A. I.; Korolev, D. S.; Guseinov, D. V.; Lebedeva, A. V.; Gorshkov, O. N.; Kazantsev, V. B.

2018-05-01

Nonlinear dynamics of two electronic oscillators coupled via a memristive device has been investigated. Such model mimics the interaction between synaptically coupled brain neurons with the memristive device imitating neuron axon. The synaptic connection is provided by the adaptive behavior of memristive device that changes its resistance under the action of spike-like activity. Mathematical model of such a memristive interface has been developed to describe and predict the experimentally observed regularities of forced synchronization of neuron-like oscillators.

Coherence between Rat Sensorimotor System and Hippocampus Is Enhanced during Tactile Discrimination

PubMed Central

Zuo, Yangfang; Stella, Federico; Diamond, Mathew E.

2016-01-01

Rhythms with time scales of multiple cycles per second permeate the mammalian brain, yet neuroscientists are not certain of their functional roles. One leading idea is that coherent oscillation between two brain regions facilitates the exchange of information between them. In rats, the hippocampus and the vibrissal sensorimotor system both are characterized by rhythmic oscillation in the theta range, 5–12 Hz. Previous work has been divided as to whether the two rhythms are independent or coherent. To resolve this question, we acquired three measures from rats—whisker motion, hippocampal local field potential (LFP), and barrel cortex unit firing—during a whisker-mediated texture discrimination task and during control conditions (not engaged in a whisker-mediated memory task). Compared to control conditions, the theta band of hippocampal LFP showed a marked increase in power as the rats approached and then palpated the texture. Phase synchronization between whisking and hippocampal LFP increased by almost 50% during approach and texture palpation. In addition, a greater proportion of barrel cortex neurons showed firing that was phase-locked to hippocampal theta while rats were engaged in the discrimination task. Consistent with a behavioral consequence of phase synchronization, the rats identified the texture more rapidly and with lower error likelihood on trials in which there was an increase in theta-whisking coherence at the moment of texture palpation. These results suggest that coherence between the whisking rhythm, barrel cortex firing, and hippocampal LFP is augmented selectively during epochs in which the rat collects sensory information and that such coherence enhances the efficiency of integration of stimulus information into memory and decision-making centers. PMID:26890254

Controlled Ultrasound-Induced Blood-Brain Barrier Disruption Using Passive Acoustic Emissions Monitoring

PubMed Central

Arvanitis, Costas D.; Livingstone, Margaret S.; Vykhodtseva, Natalia; McDannold, Nathan

2012-01-01

The ability of ultrasonically-induced oscillations of circulating microbubbles to permeabilize vascular barriers such as the blood-brain barrier (BBB) holds great promise for noninvasive targeted drug delivery. A major issue has been a lack of control over the procedure to ensure both safe and effective treatment. Here, we evaluated the use of passively-recorded acoustic emissions as a means to achieve this control. An acoustic emissions monitoring system was constructed and integrated into a clinical transcranial MRI-guided focused ultrasound system. Recordings were analyzed using a spectroscopic method that isolates the acoustic emissions caused by the microbubbles during sonication. This analysis characterized and quantified harmonic oscillations that occur when the BBB is disrupted, and broadband emissions that occur when tissue damage occurs. After validating the system's performance in pilot studies that explored a wide range of exposure levels, the measurements were used to control the ultrasound exposure level during transcranial sonications at 104 volumes over 22 weekly sessions in four macaques. We found that increasing the exposure level until a large harmonic emissions signal was observed was an effective means to ensure BBB disruption without broadband emissions. We had a success rate of 96% in inducing BBB disruption as measured by in contrast-enhanced MRI, and we detected broadband emissions in less than 0.2% of the applied bursts. The magnitude of the harmonic emissions signals was significantly (P<0.001) larger for sonications where BBB disruption was detected, and it correlated with BBB permeabilization as indicated by the magnitude of the MRI signal enhancement after MRI contrast administration (R2 = 0.78). Overall, the results indicate that harmonic emissions can be a used to control focused ultrasound-induced BBB disruption. These results are promising for clinical translation of this technology. PMID:23029240

Transition between Functional Regimes in an Integrate-And-Fire Network Model of the Thalamus

PubMed Central

Barardi, Alessandro; Mazzoni, Alberto

2016-01-01

The thalamus is a key brain element in the processing of sensory information. During the sleep and awake states, this brain area is characterized by the presence of two distinct dynamical regimes: in the sleep state activity is dominated by spindle oscillations (7 − 15 Hz) weakly affected by external stimuli, while in the awake state the activity is primarily driven by external stimuli. Here we develop a simple and computationally efficient model of the thalamus that exhibits two dynamical regimes with different information-processing capabilities, and study the transition between them. The network model includes glutamatergic thalamocortical (TC) relay neurons and GABAergic reticular (RE) neurons described by adaptive integrate-and-fire models in which spikes are induced by either depolarization or hyperpolarization rebound. We found a range of connectivity conditions under which the thalamic network composed by these neurons displays the two aforementioned dynamical regimes. Our results show that TC-RE loops generate spindle-like oscillations and that a minimum level of clustering (i.e. local connectivity density) in the RE-RE connections is necessary for the coexistence of the two regimes. We also observe that the transition between the two regimes occurs when the external excitatory input on TC neurons (mimicking sensory stimulation) is large enough to cause a significant fraction of them to switch from hyperpolarization-rebound-driven firing to depolarization-driven firing. Overall, our model gives a novel and clear description of the role that the two types of neurons and their connectivity play in the dynamical regimes observed in the thalamus, and in the transition between them. These results pave the way for the development of efficient models of the transmission of sensory information from periphery to cortex. PMID:27598260

The role of alpha-rhythm states in perceptual learning: insights from experiments and computational models

PubMed Central

Sigala, Rodrigo; Haufe, Sebastian; Roy, Dipanjan; Dinse, Hubert R.; Ritter, Petra

2014-01-01

During the past two decades growing evidence indicates that brain oscillations in the alpha band (~10 Hz) not only reflect an “idle” state of cortical activity, but also take a more active role in the generation of complex cognitive functions. A recent study shows that more than 60% of the observed inter-subject variability in perceptual learning can be ascribed to ongoing alpha activity. This evidence indicates a significant role of alpha oscillations for perceptual learning and hence motivates to explore the potential underlying mechanisms. Hence, it is the purpose of this review to highlight existent evidence that ascribes intrinsic alpha oscillations a role in shaping our ability to learn. In the review, we disentangle the alpha rhythm into different neural signatures that control information processing within individual functional building blocks of perceptual learning. We further highlight computational studies that shed light on potential mechanisms regarding how alpha oscillations may modulate information transfer and connectivity changes relevant for learning. To enable testing of those model based hypotheses, we emphasize the need for multidisciplinary approaches combining assessment of behavior and multi-scale neuronal activity, active modulation of ongoing brain states and computational modeling to reveal the mathematical principles of the complex neuronal interactions. In particular we highlight the relevance of multi-scale modeling frameworks such as the one currently being developed by “The Virtual Brain” project. PMID:24772077

Activation of TRPV4 channels does not mediate inversion of neurovascular coupling after SAH.

PubMed

Koide, Masayo; Wellman, George C

2015-01-01

Neurovascular coupling (NVC) allows increased blood flow to metabolically active neurons and involves the Ca²⁺ -dependent release of vasodilator influences by astrocyte endfeet that encase parenchymal arterioles. We previously reported inversion of NVC from dilation to constriction in brain slices from subarachnoid hemorrhage (SAH) model rats. Corresponding to NVC inversion, there was a marked increase in the amplitude of spontaneous Ca²⁺ oscillations in astrocyte endfeet. Calcium-permeable transient receptor potential vanilloid (TRPV)-4 channels have been reported in astrocyte endfeet, and activators of these channels enhance Ca²⁺ oscillations in healthy animals. Here, we examined the role of TRPV4 channels in the development of high-amplitude spontaneous Ca²⁺ oscillations in astrocyte endfeet and the inversion of neurovascular coupling after SAH. Treatment of brain slices with the TRPV4 channel antagonist, HC-067047 (10 μM), did not alter the amplitude of spontaneous Ca²⁺ oscillations after SAH. In addition, HC-067047 did not inhibit or change SAH-induced inversion of neurovascular coupling. In summary, TRPV4 channels do not appear to be involved in the inversion of neurovascular coupling after SAH. Further studies examining the impact of SAH on additional Ca²⁺ signaling pathways in astrocytes are likely to reveal valuable insights into new therapeutic strategies to advance SAH treatments.

Multi-frequency localization of aberrant brain activity in autism spectrum disorder.

PubMed

Xiang, Jing; Korostenskaja, Milena; Molloy, Cynthia; deGrauw, Xinyao; Leiken, Kimberly; Gilman, Carley; Meinzen-Derr, Jareen; Fujiwara, Hisako; Rose, Douglas F; Mitchell, Terry; Murray, Donna S

2016-01-01

The abnormality of intrinsic brain activity in autism spectrum disorders (ASDs) is still inconclusive. Contradictory results have been found pointing towards hyper-activity or hypo-activity in various brain regions. The present research aims to investigate the spatial and spectral signatures of aberrant brain activity in an unprecedented frequency range of 1-2884 Hz at source levels in ASD using newly developed methods. Seven ASD subjects and age- and gender-matched controls were studied using a high-sampling rate magnetoencephalography (MEG) system. Brain activity in delta (1-4 Hz), theta (4-8 Hz), alpha (8-12 Hz), beta (12-30 Hz), low gamma (30-55 Hz), high gamma (65-90 Hz), ripples (90-200 Hz), high-frequency oscillations (HFOs, 200-1000 Hz), and very high-frequency oscillations (VHFOs, 1000-2884 Hz) was volumetrically localized and measured using wavelet and beamforming. In comparison to controls, ASD subjects had significantly higher odds of alpha activity (8-12 Hz) in the sensorimotor cortex (mu rhythm), and generally high-frequency activity (90-2884 Hz) in the frontal cortex. The source power of HFOs (200-1000 Hz) in the frontal cortex in ASD was significantly elevated as compared with controls. The results suggest that ASD has significantly altered intrinsic brain activity in both low- and high-frequency ranges. Increased intrinsic high-frequency activity in the frontal cortex may play a key role in ASD. Copyright © 2015 The Japanese Society of Child Neurology. Published by Elsevier B.V. All rights reserved.

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.

Control channels in the brain and their influence on brain executive functions

NASA Astrophysics Data System (ADS)

Meng, Qinglei; Choa, Fow-Sen; Hong, Elliot; Wang, Zhiguang; Islam, Mohammad

2014-05-01

In a computer network there are distinct data channels and control channels where massive amount of visual information are transported through data channels but the information streams are routed and controlled by intelligent algorithm through "control channels". Recent studies on cognition and consciousness have shown that the brain control channels are closely related to the brainwave beta (14-40 Hz) and alpha (7-13 Hz) oscillations. The high-beta wave is used by brain to synchronize local neural activities and the alpha oscillation is for desynchronization. When two sensory inputs are simultaneously presented to a person, the high-beta is used to select one of the inputs and the alpha is used to deselect the other so that only one input will get the attention. In this work we demonstrated that we can scan a person's brain using binaural beats technique and identify the individual's preferred control channels. The identified control channels can then be used to influence the subject's brain executive functions. In the experiment, an EEG measurement system was used to record and identify a subject's control channels. After these channels were identified, the subject was asked to do Stroop tests. Binaural beats was again used to produce these control-channel frequencies on the subject's brain when we recorded the completion time of each test. We found that the high-beta signal indeed speeded up the subject's executive function performance and reduced the time to complete incongruent tests, while the alpha signal didn't seem to be able to slow down the executive function performance.

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.

The role of high-frequency oscillations in epilepsy surgery planning

PubMed Central

Gloss, David; Nolan, Sarah J; Staba, Richard

2014-01-01

Background Epilepsy is a serious brain disorder characterized by recurrent unprovoked seizures. Approximately two-thirds of seizures can be controlled with antiepileptic medications (Kwan 2000). For some of the others, surgery can completely eliminate or significantly reduce the occurrence of disabling seizures. Localization of epileptogenic areas for resective surgery is far from perfect, and new tools are being investigated to more accurately localize the epileptogenic zone (the zone of the brain where the seizures begin) and improve the likelihood of freedom from postsurgical seizures. Recordings of pathological high-frequency oscillations (HFOs) may be one such tool. Objectives To assess the ability of HFOs to improve the outcomes of epilepsy surgery by helping to identify more accurately the epileptogenic areas of the brain. Search methods We searched the Cochrane Epilepsy Group Specialized Register (15 April 2013), the Cochrane Central Register of Controlled Trials (CENTRAL) in The Cochrane Library (2013, Issue 3), MEDLINE (Ovid) (1946 to 15 April 2013), CINAHL (EBSCOhost) (15 April 2013), Web of Knowledge (Thomson Reuters) (15 April 2013), www.clinicaltrials.gov (15 April 2013), and the World Health Organization International Clinical Trials Registry Platform (15 April 2013). Selection criteria We included studies that provided information on the outcomes of epilepsy surgery at at least six months and which used high-frequency oscillations in making decisions about epilepsy surgery. Data collection and analysis The primary outcome of the review was the Engel Class Outcome System. Secondary outcomes were responder rate, International League Against Epilepsy (ILAE) epilepsy surgery outcome, frequency of adverse events from any source and quality of life outcomes. We intended to analyse outcomes via an aggregated data fixed-effect model meta-analysis. Main results Two studies met the inclusion criteria. Both studies were small non-randomised trials, with no control group and no blinding. The quality of evidence for all outcomes was very low. The combination of these two studies resulted in 11 participants who prospectively used ictal HFOs for epilepsy surgery decision making. Results of the postsurgical seizure freedom Engel class I to IV outcome were determined over a period of 12 to 38 months (average 23.4 months) and indicated that six participants had an Engel class I outcome (seizure freedom), two had class II (rare disabling seizures), three had class III (worthwhile improvement). No adverse effects were reported. Neither study compared surgical results guided by HFOs versus surgical results guided without HFOs. Authors’ conclusions No reliable conclusions can be drawn regarding the efficacy of using HFOs in epilepsy surgery decision making at present. PMID:24431136

The role of high-frequency oscillations in epilepsy surgery planning.

PubMed

Gloss, David; Nolan, Sarah J; Staba, Richard

2014-01-15

Epilepsy is a serious brain disorder characterized by recurrent unprovoked seizures. Approximately two-thirds of seizures can be controlled with antiepileptic medications (Kwan 2000). For some of the others, surgery can completely eliminate or significantly reduce the occurrence of disabling seizures. Localization of epileptogenic areas for resective surgery is far from perfect, and new tools are being investigated to more accurately localize the epileptogenic zone (the zone of the brain where the seizures begin) and improve the likelihood of freedom from postsurgical seizures. Recordings of pathological high-frequency oscillations (HFOs) may be one such tool. To assess the ability of HFOs to improve the outcomes of epilepsy surgery by helping to identify more accurately the epileptogenic areas of the brain. We searched the Cochrane Epilepsy Group Specialized Register (15 April 2013), the Cochrane Central Register of Controlled Trials (CENTRAL) in The Cochrane Library (2013, Issue 3), MEDLINE (Ovid) (1946 to 15 April 2013), CINAHL (EBSCOhost) (15 April 2013), Web of Knowledge (Thomson Reuters) (15 April 2013), www.clinicaltrials.gov (15 April 2013), and the World Health Organization International Clinical Trials Registry Platform (15 April 2013). We included studies that provided information on the outcomes of epilepsy surgery at at least six months and which used high-frequency oscillations in making decisions about epilepsy surgery. The primary outcome of the review was the Engel Class Outcome System. Secondary outcomes were responder rate, International League Against Epilepsy (ILAE) epilepsy surgery outcome, frequency of adverse events from any source and quality of life outcomes. We intended to analyse outcomes via an aggregated data fixed-effect model meta-analysis. Two studies met the inclusion criteria. Both studies were small non-randomised trials, with no control group and no blinding. The quality of evidence for all outcomes was very low. The combination of these two studies resulted in 11 participants who prospectively used ictal HFOs for epilepsy surgery decision making. Results of the postsurgical seizure freedom Engel class I to IV outcome were determined over a period of 12 to 38 months (average 23.4 months) and indicated that six participants had an Engel class I outcome (seizure freedom), two had class II (rare disabling seizures), three had class III (worthwhile improvement). No adverse effects were reported. Neither study compared surgical results guided by HFOs versus surgical results guided without HFOs. No reliable conclusions can be drawn regarding the efficacy of using HFOs in epilepsy surgery decision making at present.

Event-related oscillations (EROs) and event-related potentials (ERPs) comparison in facial expression recognition.

PubMed

Balconi, Michela; Pozzoli, Uberto

2007-09-01

The study aims to explore the significance of event-related potentials (ERPs) and event-related brain oscillations (EROs) (delta, theta, alpha, beta, gamma power) in response to emotional (fear, happiness, sadness) when compared with neutral faces during 180-250 post-stimulus time interval. The ERP results demonstrated that the emotional face elicited a negative peak at approximately 230 ms (N2). Moreover, EEG measures showed that motivational significance of face (emotional vs. neutral) could modulate the amplitude of EROs, but only for some frequency bands (i.e. theta and gamma bands). In a second phase, we considered the resemblance of the two EEG measures by a regression analysis. It revealed that theta and gamma oscillations mainly effect as oscillation activity at the N2 latency. Finally, a posterior increased power of theta was found for emotional faces.

High-frequency neural oscillations and visual processing deficits in schizophrenia

PubMed Central

Tan, Heng-Ru May; Lana, Luiz; Uhlhaas, Peter J.

2013-01-01

Visual information is fundamental to how we understand our environment, make predictions, and interact with others. Recent research has underscored the importance of visuo-perceptual dysfunctions for cognitive deficits and pathophysiological processes in schizophrenia. In the current paper, we review evidence for the relevance of high frequency (beta/gamma) oscillations towards visuo-perceptual dysfunctions in schizophrenia. In the first part of the paper, we examine the relationship between beta/gamma band oscillations and visual processing during normal brain functioning. We then summarize EEG/MEG-studies which demonstrate reduced amplitude and synchrony of high-frequency activity during visual stimulation in schizophrenia. In the final part of the paper, we identify neurobiological correlates as well as offer perspectives for future research to stimulate further inquiry into the role of high-frequency oscillations in visual processing impairments in the disorder. PMID:24130535

Selective population rate coding: a possible computational role of gamma oscillations in selective attention.

PubMed

Masuda, Naoki

2009-12-01

Selective attention is often accompanied by gamma oscillations in local field potentials and spike field coherence in brain areas related to visual, motor, and cognitive information processing. Gamma oscillations are implicated to play an important role in, for example, visual tasks including object search, shape perception, and speed detection. However, the mechanism by which gamma oscillations enhance cognitive and behavioral performance of attentive subjects is still elusive. Using feedforward fan-in networks composed of spiking neurons, we examine a possible role for gamma oscillations in selective attention and population rate coding of external stimuli. We implement the concept proposed by Fries ( 2005 ) that under dynamic stimuli, neural populations effectively communicate with each other only when there is a good phase relationship among associated gamma oscillations. We show that the downstream neural population selects a specific dynamic stimulus received by an upstream population and represents it by population rate coding. The encoded stimulus is the one for which gamma rhythm in the corresponding upstream population is resonant with the downstream gamma rhythm. The proposed role for gamma oscillations in stimulus selection is to enable top-down control, a neural version of time division multiple access used in communication engineering.

Dendritic Learning as a Paradigm Shift in Brain Learning.

PubMed

Sardi, Shira; Vardi, Roni; Goldental, Amir; Tugendhaft, Yael; Uzan, Herut; Kanter, Ido

2018-06-20

Experimental and theoretical results reveal a new underlying mechanism for fast brain learning process, dendritic learning, as opposed to the misdirected research in neuroscience over decades, which is based solely on slow synaptic plasticity. The presented paradigm indicates that learning occurs in closer proximity to the neuron, the computational unit, dendritic strengths are self-oscillating, and weak synapses, which comprise the majority of our brain and previously were assumed to be insignificant, play a key role in plasticity. The new learning sites of the brain call for a reevaluation of current treatments for disordered brain functionality and for a better understanding of proper chemical drugs and biological mechanisms to maintain, control and enhance learning.

Slow spontaneous hemodynamic oscillations during sleep measured with near-infrared spectroscopy

NASA Astrophysics Data System (ADS)

Virtanen, Jaakko; Näsi, Tiina; Noponen, Tommi; Toppila, Jussi; Salmi, Tapani; Ilmoniemi, Risto J.

2011-07-01

Spontaneous cerebral hemodynamic oscillations below 100 mHz reflect the level of cerebral activity, modulate hemodynamic responses to tasks and stimuli, and may aid in detecting various pathologies of the brain. Near-infrared spectroscopy (NIRS) is ideally suited for both measuring spontaneous hemodynamic oscillations and monitoring sleep, but little research has been performed to combine these two applications. We analyzed 30 all-night NIRS-electroencephalography (EEG) sleep recordings to investigate spontaneous hemodynamic activity relative to sleep stages determined by polysomnography. Signal power of hemodynamic oscillations in the low-frequency (LF, 40-150 mHz) and very-low-frequency (VLF, 3-40 mHz) bands decreased in slow-wave sleep (SWS) compared to light sleep (LS) and rapid-eye-movement (REM) sleep. No statistically significant (p < 0.05) differences in oscillation power between LS and REM were observed. However, the period of VLF oscillations around 8 mHz increased in REM sleep in line with earlier studies with other modalities. These results increase our knowledge of the physiology of sleep, complement EEG data, and demonstrate the applicability of NIRS to studying spontaneous hemodynamic fluctuations during sleep.

Analysis of the Drosophila Clock promoter reveals heterogeneity in expression between subgroups of central oscillator cells and identifies a novel enhancer region.

PubMed

Gummadova, Jennet Orazmuradovna; Coutts, Graham Andrew; Glossop, Nicholas Robert John

2009-10-01

The CLOCK-CYCLE (CLK-CYC) heterodimer lies at the heart of the circadian oscillator mechanism in Drosophila, yet little is known about the identity of transcription factors that regulate the expression of Clk and/or cyc. Here, the authors have used a transgenic approach to isolate regions of the Clk locus that are necessary for expression in central oscillator neurons in the adult fly brain. This analysis shows that central clock cells can be subdivided into 2 distinct groups based on Clk gene regulation. Expression in the lateral neuron (LN), dorsal neuron 1 anterior (DN1a) and 2 (DN2) clusters requires cis-elements located in a 122 base-pair (bp) region (-206 to -84) of the Clk promoter. Expression in the remaining dorsal neurons, 1 posterior (DN1p) and 3 (DN3) and the lateral posterior neurons (LPN), requires regulatory elements located in the -856 to -206 region. In addition, expression in photoreceptors of the compound eye is enhanced by cis-elements located in a 3rd region of the Clk locus (-1982 to -856). This region also enhances expression in nonoscillator cells in the brain including the Kenyon cells, but expression in these neurons is suppressed by regulatory sites located further upstream of -1982. The authors' analysis reveals clear heterogeneity in Clk gene expression in the adult brain and provides a necessary focus to isolate novel transcription factors that bind at the Clk locus to regulate expression in different oscillator neuron subgroups. These results also suggest that the DN1a/DN2 neurons may have more molecular commonality with the LNs than they do with the DN1p/DN3/LPN neurons. Finally, this analysis has generated new transgenic lines that will enable genes to be misexpressed in subgroups of central oscillator cells that have previously been resistant to discrete genetic manipulation. Hence, these lines provide important new tools to facilitate a more complete dissection of the neural network that regulates output rhythms in physiology and behavior.

Enhanced inter-subject brain computer interface with associative sensorimotor oscillations.

PubMed

Saha, Simanto; Ahmed, Khawza I; Mostafa, Raqibul; Khandoker, Ahsan H; Hadjileontiadis, Leontios

2017-02-01

Electroencephalography (EEG) captures electrophysiological signatures of cortical events from the scalp with high-dimensional electrode montages. Usually, excessive sources produce outliers and potentially affect the actual event related sources. Besides, EEG manifests inherent inter-subject variability of the brain dynamics, at the resting state and/or under the performance of task(s), caused probably due to the instantaneous fluctuation of psychophysiological states. A wavelet coherence (WC) analysis for optimally selecting associative inter-subject channels is proposed here and is being used to boost performances of motor imagery (MI)-based inter-subject brain computer interface (BCI). The underlying hypothesis is that optimally associative inter-subject channels can reduce the effects of outliers and, thus, eliminate dissimilar cortical patterns. The proposed approach has been tested on the dataset IVa from BCI competition III, including EEG data acquired from five healthy subjects who were given visual cues to perform 280 trials of MI for the right hand and right foot. Experimental results have shown increased classification accuracy (81.79%) using the WC-based selected 16 channels compared to the one (56.79%) achieved using all the available 118 channels. The associative channels lie mostly around the sensorimotor regions of the brain, reinforced by the previous literature, describing spatial brain dynamics during sensorimotor oscillations. Apparently, the proposed approach paves the way for optimised EEG channel selection that could boost further the efficiency and real-time performance of BCI systems.

Patients with Chronic Visceral Pain Show Sex-Related Alterations in Intrinsic Oscillations of the Resting Brain

PubMed Central

Hong, Jui-Yang; Kilpatrick, Lisa A.; Labus, Jennifer; Gupta, Arpana; Jiang, Zhiguo; Ashe-McNalley, Cody; Stains, Jean; Heendeniya, Nuwanthi; Ebrat, Bahar; Smith, Suzanne; Tillisch, Kirsten; Naliboff, Bruce

2013-01-01

Abnormal responses of the brain to delivered and expected aversive gut stimuli have been implicated in the pathophysiology of irritable bowel syndrome (IBS), a visceral pain syndrome occurring more commonly in women. Task-free resting-state functional magnetic resonance imaging (fMRI) can provide information about the dynamics of brain activity that may be involved in altered processing and/or modulation of visceral afferent signals. Fractional amplitude of low-frequency fluctuation is a measure of the power spectrum intensity of spontaneous brain oscillations. This approach was used here to identify differences in the resting-state activity of the human brain in IBS subjects compared with healthy controls (HCs) and to identify the role of sex-related differences. We found that both the female HCs and female IBS subjects had a frequency power distribution skewed toward high frequency to a greater extent in the amygdala and hippocampus compared with male subjects. In addition, female IBS subjects had a frequency power distribution skewed toward high frequency in the insula and toward low frequency in the sensorimotor cortex to a greater extent than male IBS subjects. Correlations were observed between resting-state blood oxygen level-dependent signal dynamics and some clinical symptom measures (e.g., abdominal discomfort). These findings provide the first insight into sex-related differences in IBS subjects compared with HCs using resting-state fMRI. PMID:23864686

Oscillatory networks of high-level mental alignment: A perspective-taking MEG study.

PubMed

Seymour, R A; Wang, H; Rippon, G; Kessler, K

2018-08-15

Mentally imagining another's perspective is a high-level social process, reliant on manipulating internal representations of the self in an embodied manner. Recently Wang et al. (2016) showed that theta-band (3-7 Hz) brain oscillations within the right temporo-parietal junction (rTPJ) and brain regions coding for motor/body schema contribute to the process of perspective-taking. Using a similar paradigm, we set out to unravel the extended functional brain network in detail. Increasing the angle between self and other perspective was accompanied by longer reaction times and increases in theta power within rTPJ, right lateral prefrontal cortex (PFC) and right anterior cingulate cortex (ACC). Using Granger-causality, we showed that lateral PFC and ACC exert top-down influence over rTPJ, indicative of executive control processes required for managing conflicts between self and other perspectives. Finally, we quantified patterns of whole-brain phase coupling in relation to the rTPJ. Results suggest that rTPJ increases its theta-band phase synchrony with brain regions involved in mentalizing and regions coding for motor/body schema; whilst decreasing synchrony to visual regions. Implications for neurocognitive models are discussed, and it is proposed that rTPJ acts as a 'hub' to route bottom-up visual information to internal representations of the self during perspective-taking, co-ordinated by theta-band oscillations. Copyright © 2018 Elsevier Inc. All rights reserved.

Attention Modulates TMS-Locked Alpha Oscillations in the Visual Cortex

PubMed Central

Herring, Jim D.; Thut, Gregor; Jensen, Ole

2015-01-01

Cortical oscillations, such as 8–12 Hz alpha-band activity, are thought to subserve gating of information processing in the human brain. While most of the supporting evidence is correlational, causal evidence comes from attempts to externally drive (“entrain”) these oscillations by transcranial magnetic stimulation (TMS). Indeed, the frequency profile of TMS-evoked potentials (TEPs) closely resembles that of oscillations spontaneously emerging in the same brain region. However, it is unclear whether TMS-locked and spontaneous oscillations are produced by the same neuronal mechanisms. If so, they should react in a similar manner to top-down modulation by endogenous attention. To test this prediction, we assessed the alpha-like EEG response to TMS of the visual cortex during periods of high and low visual attention while participants attended to either the visual or auditory modality in a cross-modal attention task. We observed a TMS-locked local oscillatory alpha response lasting several cycles after TMS (but not after sham stimulation). Importantly, TMS-locked alpha power was suppressed during deployment of visual relative to auditory attention, mirroring spontaneous alpha amplitudes. In addition, the early N40 TEP component, located at the stimulation site, was amplified by visual attention. The extent of attentional modulation for both TMS-locked alpha power and N40 amplitude did depend, with opposite sign, on the individual ability to modulate spontaneous alpha power at the stimulation site. We therefore argue that TMS-locked and spontaneous oscillations are of common neurophysiological origin, whereas the N40 TEP component may serve as an index of current cortical excitability at the time of stimulation. SIGNIFICANCE STATEMENT Rhythmic transcranial magnetic stimulation (TMS) is a promising tool to experimentally “entrain” cortical activity. If TMS-locked oscillatory responses actually recruit the same neuronal mechanisms as spontaneous cortical oscillations, they qualify as a valid tool to study the causal role of neuronal oscillations in cognition but also to enable new treatments targeting aberrant oscillatory activity in, for example, neurological conditions. Here, we provide first-time evidence that TMS-locked and spontaneous oscillations are indeed tightly related and are likely to rely on the same neuronal generators. In addition, we demonstrate that an early local component of the TMS-evoked potential (the N40) may serve as a new objective and noninvasive probe of visual cortex excitability, which so far was only accessible via subjective phosphene reports. PMID:26511236

Induction of slow oscillations by rhythmic acoustic stimulation.

PubMed

Ngo, Hong-Viet V; Claussen, Jens C; Born, Jan; Mölle, Matthias

2013-02-01

Slow oscillations are electrical potential oscillations with a spectral peak frequency of ∼0.8 Hz, and hallmark the electroencephalogram during slow-wave sleep. Recent studies have indicated a causal contribution of slow oscillations to the consolidation of memories during slow-wave sleep, raising the question to what extent such oscillations can be induced by external stimulation. Here, we examined whether slow oscillations can be effectively induced by rhythmic acoustic stimulation. Human subjects were examined in three conditions: (i) with tones presented at a rate of 0.8 Hz ('0.8-Hz stimulation'); (ii) with tones presented at a random sequence ('random stimulation'); and (iii) with no tones presented in a control condition ('sham'). Stimulation started during wakefulness before sleep and continued for the first ∼90 min of sleep. Compared with the other two conditions, 0.8-Hz stimulation significantly delayed sleep onset. However, once sleep was established, 0.8-Hz stimulation significantly increased and entrained endogenous slow oscillation activity. Sleep after the 90-min period of stimulation did not differ between the conditions. Our data show that rhythmic acoustic stimulation can be used to effectively enhance slow oscillation activity. However, the effect depends on the brain state, requiring the presence of stable non-rapid eye movement sleep. © 2012 European Sleep Research Society.

Chimera and phase-cluster states in populations of coupled chemical oscillators

NASA Astrophysics Data System (ADS)

Tinsley, Mark R.; Nkomo, Simbarashe; Showalter, Kenneth

2012-09-01

Populations of coupled oscillators may exhibit two coexisting subpopulations, one with synchronized oscillations and the other with unsynchronized oscillations, even though all of the oscillators are coupled to each other in an equivalent manner. This phenomenon, discovered about ten years ago in theoretical studies, was then further characterized and named the chimera state after the Greek mythological creature made up of different animals. The highly counterintuitive coexistence of coherent and incoherent oscillations in populations of identical oscillators, each with an equivalent coupling structure, inspired great interest and a flurry of theoretical activity. Here we report on experimental studies of chimera states and their relation to other synchronization states in populations of coupled chemical oscillators. Our experiments with coupled Belousov-Zhabotinsky oscillators and corresponding simulations reveal chimera behaviour that differs significantly from the behaviour found in theoretical studies of phase-oscillator models.

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

PubMed

Qian, Yu; Cui, Xiaohua; Zheng, Zhigang

2017-07-18

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

Region-Specific Slowing of Alpha Oscillations is Associated with Visual-Perceptual Abilities in Children Born Very Preterm

PubMed Central

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

2013-01-01

Children born very preterm (≤32 weeks gestational age) without major intellectual or neurological impairments often express selective deficits in visual-perceptual abilities. The alterations in neurophysiological development underlying these problems, however, remain poorly understood. Recent research has indicated that spontaneous alpha oscillations are slowed in children born very preterm, and that atypical alpha-mediated functional network connectivity may underlie selective developmental difficulties in visual-perceptual ability in this group. The present study provides the first source-resolved analysis of slowing of spontaneous alpha oscillations in very preterm children, indicating alterations in a distributed set of brain regions concentrated in areas of posterior parietal and inferior temporal regions associated with visual perception, as well as prefrontal cortical regions and thalamus. We also uniquely demonstrate that slowing of alpha oscillations is associated with selective difficulties in visual-perceptual ability in very preterm children. These results indicate that region-specific slowing of alpha oscillations contribute to selective developmental difficulties prevalent in this population. PMID:24298250

Analysis of the role of the low threshold currents IT and Ih in intrinsic delta oscillations of thalamocortical neurons.

PubMed

Amarillo, Yimy; Mato, Germán; Nadal, Marcela S

2015-01-01

Thalamocortical neurons are involved in the generation and maintenance of brain rhythms associated with global functional states. The repetitive burst firing of TC neurons at delta frequencies (1-4 Hz) has been linked to the oscillations recorded during deep sleep and during episodes of absence seizures. To get insight into the biophysical properties that are the basis for intrinsic delta oscillations in these neurons, we performed a bifurcation analysis of a minimal conductance-based thalamocortical neuron model including only the IT channel and the sodium and potassium leak channels. This analysis unveils the dynamics of repetitive burst firing of TC neurons, and describes how the interplay between the amplifying variable mT and the recovering variable hT of the calcium channel IT is sufficient to generate low threshold oscillations in the delta band. We also explored the role of the hyperpolarization activated cationic current Ih in this reduced model and determine that, albeit not required, Ih amplifies and stabilizes the oscillation.

Neural Cross-Frequency Coupling: Connecting Architectures, Mechanisms, and Functions.

PubMed

Hyafil, Alexandre; Giraud, Anne-Lise; Fontolan, Lorenzo; Gutkin, Boris

2015-11-01

Neural oscillations are ubiquitously observed in the mammalian brain, but it has proven difficult to tie oscillatory patterns to specific cognitive operations. Notably, the coupling between neural oscillations at different timescales has recently received much attention, both from experimentalists and theoreticians. We review the mechanisms underlying various forms of this cross-frequency coupling. We show that different types of neural oscillators and cross-frequency interactions yield distinct signatures in neural dynamics. Finally, we associate these mechanisms with several putative functions of cross-frequency coupling, including neural representations of multiple environmental items, communication over distant areas, internal clocking of neural processes, and modulation of neural processing based on temporal predictions. Copyright © 2015 Elsevier Ltd. All rights reserved.

Time delay induced different synchronization patterns in repulsively coupled chaotic oscillators

NASA Astrophysics Data System (ADS)

Yao, Chenggui; Yi, Ming; Shuai, Jianwei

2013-09-01

Time delayed coupling plays a crucial role in determining the system's dynamics. We here report that the time delay induces transition from the asynchronous state to the complete synchronization (CS) state in the repulsively coupled chaotic oscillators. In particular, by changing the coupling strength or time delay, various types of synchronous patterns, including CS, antiphase CS, antiphase synchronization (ANS), and phase synchronization, can be generated. In the transition regions between different synchronous patterns, bistable synchronous oscillators can be observed. Furthermore, we show that the time-delay-induced phase flip bifurcation is of key importance for the emergence of CS. All these findings may light on our understanding of neuronal synchronization and information processing in the brain.

In vivo mouse inferior olive neurons exhibit heterogeneous subthreshold oscillations and spiking patterns

PubMed Central

Khosrovani, S.; Van Der Giessen, R. S.; De Zeeuw, C. I.; De Jeu, M. T. G.

2007-01-01

In vitro whole-cell recordings of the inferior olive have demonstrated that its neurons are electrotonically coupled and have a tendency to oscillate. However, it remains to be shown to what extent subthreshold oscillations do indeed occur in the inferior olive in vivo and whether its spatiotemporal firing pattern may be dynamically generated by including or excluding different types of oscillatory neurons. Here, we did whole-cell recordings of olivary neurons in vivo to investigate the relation between their subthreshold activities and their spiking behavior in an intact brain. The vast majority of neurons (85%) showed subthreshold oscillatory activities. The frequencies of these subthreshold oscillations were used to distinguish four main olivary subtypes by statistical means. Type I showed both sinusoidal subthreshold oscillations (SSTOs) and low-threshold Ca2+ oscillations (LTOs) (16%); type II showed only sinusoidal subthreshold oscillations (13%); type III showed only low-threshold Ca2+ oscillations (56%); and type IV did not reveal any subthreshold oscillations (15%). These subthreshold oscillation frequencies were strongly correlated with the frequencies of preferred spiking. The frequency characteristics of the subthreshold oscillations and spiking behavior of virtually all olivary neurons were stable throughout the recordings. However, the occurrence of spontaneous or evoked action potentials modified the subthreshold oscillation by resetting the phase of its peak toward 90°. Together, these findings indicate that the inferior olive in intact mammals offers a rich repertoire of different neurons with relatively stable frequency settings, which can be used to generate and reset temporal firing patterns in a dynamically coupled ensemble. PMID:17895389

Multiscale modeling of brain dynamics: from single neurons and networks to mathematical tools.

PubMed

Siettos, Constantinos; Starke, Jens

2016-09-01

The extreme complexity of the brain naturally requires mathematical modeling approaches on a large variety of scales; the spectrum ranges from single neuron dynamics over the behavior of groups of neurons to neuronal network activity. Thus, the connection between the microscopic scale (single neuron activity) to macroscopic behavior (emergent behavior of the collective dynamics) and vice versa is a key to understand the brain in its complexity. In this work, we attempt a review of a wide range of approaches, ranging from the modeling of single neuron dynamics to machine learning. The models include biophysical as well as data-driven phenomenological models. The discussed models include Hodgkin-Huxley, FitzHugh-Nagumo, coupled oscillators (Kuramoto oscillators, Rössler oscillators, and the Hindmarsh-Rose neuron), Integrate and Fire, networks of neurons, and neural field equations. In addition to the mathematical models, important mathematical methods in multiscale modeling and reconstruction of the causal connectivity are sketched. The methods include linear and nonlinear tools from statistics, data analysis, and time series analysis up to differential equations, dynamical systems, and bifurcation theory, including Granger causal connectivity analysis, phase synchronization connectivity analysis, principal component analysis (PCA), independent component analysis (ICA), and manifold learning algorithms such as ISOMAP, and diffusion maps and equation-free techniques. WIREs Syst Biol Med 2016, 8:438-458. doi: 10.1002/wsbm.1348 For further resources related to this article, please visit the WIREs website. © 2016 Wiley Periodicals, Inc.

Characterizing complex networks through statistics of Möbius transformations

NASA Astrophysics Data System (ADS)

Jaćimović, Vladimir; Crnkić, Aladin

2017-04-01

It is well-known now that dynamics of large populations of globally (all-to-all) coupled oscillators can be reduced to low-dimensional submanifolds (WS transformation and OA ansatz). Marvel et al. (2009) described an intriguing algebraic structure standing behind this reduction: oscillators evolve by the action of the group of Möbius transformations. Of course, dynamics in complex networks of coupled oscillators is highly complex and not reducible. Still, closer look unveils that even in complex networks some (possibly overlapping) groups of oscillators evolve by Möbius transformations. In this paper, we study properties of the network by identifying Möbius transformations in the dynamics of oscillators. This enables us to introduce some new (statistical) concepts that characterize the network. In particular, the notion of coherence of the network (or subnetwork) is proposed. This conceptual approach is meaningful for the broad class of networks, including those with time-delayed, noisy or mixed interactions. In this paper, several simple (random) graphs are studied illustrating the meaning of the concepts introduced in the paper.

Evidence of Mixed-mode oscillations and Farey arithmetic in double plasma system in presence of fireball

NASA Astrophysics Data System (ADS)

Mitra, Vramori; Sarma, Bornali; Sarma, Arun

2017-10-01

Plasma fireballs are luminous glowing region formed around a positively biased electrode. The present work reports the observation of mix mode oscillation (MMO) in the dynamics of plasma oscillations that are excited in the presence of fireball in a double plasma device. Source voltage and applied electrode voltage are considered as the controlling parameters for the experiment. Many sequences of distinct multi peaked periodic states reflects the presence of MMO with the variation of control parameter. The sequences of states with two patterns are characterized well by Farey arithmetic, which provides rational approximations of irrational numbers. These states can be characterized by a firing number, the ratio of the number of small amplitude oscillations to the total number of oscillations per period. The dynamical transition in plasma fireball is also demonstrated by spectral analysis, recurrence quantification analysis (RQA) and by statistical measures viz., skewness and kurtosis. The mix mode phenomenon observed in the experiment is consistent with a model that describes the dynamics of ionization instabilities.

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

PubMed Central

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

2015-01-01

Neural dynamics preceding seizures are of interest because they may shed light on mechanisms of seizure generation and could be predictive. In healthy animals, hippocampal network activity is shaped by behavioral brain state and, in epilepsy, seizures selectively emerge during specific brain states. To determine the degree to which changes in network dynamics before seizure are pathological or reflect ongoing fluctuations in brain state, dorsal hippocampal neurons were recorded during spontaneous seizures in a rat model of temporal lobe epilepsy. Seizures emerged from all brain states, but with a greater likelihood after REM sleep, potentially due to an observed increase in baseline excitability during periods of REM compared with other brains states also characterized by sustained theta oscillations. When comparing the firing patterns of the same neurons across brain states associated with and without seizures, activity dynamics before seizures followed patterns typical of the ongoing brain state, or brain state transitions, and did not differ until the onset of the electrographic seizure. Next, we tested whether disparate activity patterns during distinct brain states would influence the effectiveness of optogenetic curtailment of hippocampal seizures in a mouse model of temporal lobe epilepsy. Optogenetic curtailment was significantly more effective for seizures preceded by non-theta states compared with seizures that emerged from theta states. Our results indicate that consideration of behavioral brain state preceding a seizure is important for the appropriate interpretation of network dynamics leading up to a seizure and for designing effective seizure intervention. SIGNIFICANCE STATEMENT Hippocampal single-unit activity is strongly shaped by behavioral brain state, yet this relationship has been largely ignored when studying activity dynamics before spontaneous seizures in medial temporal lobe epilepsy. In light of the increased attention on using single-unit activity for the prediction of seizure onset and closed-loop seizure intervention, we show a need for monitoring brain state to interpret correctly whether changes in neural activity before seizure onset is pathological or normal. Moreover, we also find that the brain state preceding a seizure determines the success of therapeutic interventions to curtail seizure duration. Together, these findings suggest that seizure prediction and intervention will be more successful if tailored for the specific brain states from which seizures emerge. PMID:26609157

Magnetometer Based on the Opto-Electronic Oscillator

NASA Technical Reports Server (NTRS)

Matsko, Andrey B.; Strekalov, Dmitry; Maleki, Lute

2005-01-01

We theoretically propose and discuss properties of two schemes of an all-optical self-oscillating magnetometer based on an opto-electronic oscillator stabilized with an atomic vapor cell. Proof of the principle DC magnetic field measurements characterized with 2 x 10(exp -7) G sensitivity and 1 - 1000 mG dynamic range in one of the schemes are demonstrated.

Simple Optoelectronic Feedback in Microwave Oscillators

NASA Technical Reports Server (NTRS)

Maleki, Lute; Iltchenko, Vladimir

2009-01-01

A proposed method of stabilizing microwave and millimeter-wave oscillators calls for the use of feedback in optoelectronic delay lines characterized by high values of the resonance quality factor (Q). The method would extend the applicability of optoelectronic feedback beyond the previously reported class of optoelectronic oscillators that comprise two-port electronic amplifiers in closed loops with high-Q feedback circuits.

Periodic synchronization in a system of coupled phase oscillators with attractive and repulsive interactions

NASA Astrophysics Data System (ADS)

Yuan, Di; Tian, Jun-Long; Lin, Fang; Ma, Dong-Wei; Zhang, Jing; Cui, Hai-Tao; Xiao, Yi

2018-06-01

In this study we investigate the collective behavior of the generalized Kuramoto model with an external pinning force in which oscillators with positive and negative coupling strengths are conformists and contrarians, respectively. We focus on a situation in which the natural frequencies of the oscillators follow a uniform probability density. By numerically simulating the model, it is shown that the model supports multistable synchronized states such as a traveling wave state, π state and periodic synchronous state: an oscillating π state. The oscillating π state may be characterized by the phase distribution oscillating in a confined region and the phase difference between conformists and contrarians oscillating around π periodically. In addition, we present the parameter space of the oscillating π state and traveling wave state of the model.

[Multi-channel in vivo recording techniques: analysis of phase coupling between spikes and rhythmic oscillations of local field potentials].

PubMed

Wang, Ce-Qun; Chen, Qiang; Zhang, Lu; Xu, Jia-Min; Lin, Long-Nian

2014-12-25

The purpose of this article is to introduce the measurements of phase coupling between spikes and rhythmic oscillations of local field potentials (LFPs). Multi-channel in vivo recording techniques allow us to record ensemble neuronal activity and LFPs simultaneously from the same sites in the brain. Neuronal activity is generally characterized by temporal spike sequences, while LFPs contain oscillatory rhythms in different frequency ranges. Phase coupling analysis can reveal the temporal relationships between neuronal firing and LFP rhythms. As the first step, the instantaneous phase of LFP rhythms can be calculated using Hilbert transform, and then for each time-stamped spike occurred during an oscillatory epoch, we marked instantaneous phase of the LFP at that time stamp. Finally, the phase relationships between the neuronal firing and LFP rhythms were determined by examining the distribution of the firing phase. Phase-locked spikes are revealed by the non-random distribution of spike phase. Theta phase precession is a unique phase relationship between neuronal firing and LFPs, which is one of the basic features of hippocampal place cells. Place cells show rhythmic burst firing following theta oscillation within a place field. And phase precession refers to that rhythmic burst firing shifted in a systematic way during traversal of the field, moving progressively forward on each theta cycle. This relation between phase and position can be described by a linear model, and phase precession is commonly quantified with a circular-linear coefficient. Phase coupling analysis helps us to better understand the temporal information coding between neuronal firing and LFPs.

Detecting event-related changes of multivariate phase coupling in dynamic brain networks.

PubMed

Canolty, Ryan T; Cadieu, Charles F; Koepsell, Kilian; Ganguly, Karunesh; Knight, Robert T; Carmena, Jose M

2012-04-01

Oscillatory phase coupling within large-scale brain networks is a topic of increasing interest within systems, cognitive, and theoretical neuroscience. Evidence shows that brain rhythms play a role in controlling neuronal excitability and response modulation (Haider B, McCormick D. Neuron 62: 171-189, 2009) and regulate the efficacy of communication between cortical regions (Fries P. Trends Cogn Sci 9: 474-480, 2005) and distinct spatiotemporal scales (Canolty RT, Knight RT. Trends Cogn Sci 14: 506-515, 2010). In this view, anatomically connected brain areas form the scaffolding upon which neuronal oscillations rapidly create and dissolve transient functional networks (Lakatos P, Karmos G, Mehta A, Ulbert I, Schroeder C. Science 320: 110-113, 2008). Importantly, testing these hypotheses requires methods designed to accurately reflect dynamic changes in multivariate phase coupling within brain networks. Unfortunately, phase coupling between neurophysiological signals is commonly investigated using suboptimal techniques. Here we describe how a recently developed probabilistic model, phase coupling estimation (PCE; Cadieu C, Koepsell K Neural Comput 44: 3107-3126, 2010), can be used to investigate changes in multivariate phase coupling, and we detail the advantages of this model over the commonly employed phase-locking value (PLV; Lachaux JP, Rodriguez E, Martinerie J, Varela F. Human Brain Map 8: 194-208, 1999). We show that the N-dimensional PCE is a natural generalization of the inherently bivariate PLV. Using simulations, we show that PCE accurately captures both direct and indirect (network mediated) coupling between network elements in situations where PLV produces erroneous results. We present empirical results on recordings from humans and nonhuman primates and show that the PCE-estimated coupling values are different from those using the bivariate PLV. Critically on these empirical recordings, PCE output tends to be sparser than the PLVs, indicating fewer significant interactions and perhaps a more parsimonious description of the data. Finally, the physical interpretation of PCE parameters is straightforward: the PCE parameters correspond to interaction terms in a network of coupled oscillators. Forward modeling of a network of coupled oscillators with parameters estimated by PCE generates synthetic data with statistical characteristics identical to empirical signals. Given these advantages over the PLV, PCE is a useful tool for investigating multivariate phase coupling in distributed brain networks.

Nonlinear assessment of cerebral autoregulation from spontaneous blood pressure and cerebral blood flow fluctuations.

PubMed

Hu, Kun; Peng, C K; Czosnyka, Marek; Zhao, Peng; Novak, Vera

2008-03-01

Cerebral autoregulation (CA) is an most important mechanism responsible for the relatively constant blood flow supply to brain when cerebral perfusion pressure varies. Its assessment in nonacute cases has been relied on the quantification of the relationship between noninvasive beat-to-beat blood pressure (BP) and blood flow velocity (BFV). To overcome the nonstationary nature of physiological signals such as BP and BFV, a computational method called multimodal pressure-flow (MMPF) analysis was recently developed to study the nonlinear BP-BFV relationship during the Valsalva maneuver (VM). The present study aimed to determine (i) whether this method can estimate autoregulation from spontaneous BP and BFV fluctuations during baseline rest conditions; (ii) whether there is any difference between the MMPF measures of autoregulation based on intra-arterial BP (ABP) and based on cerebral perfusion pressure (CPP); and (iii) whether the MMPF method provides reproducible and reliable measure for noninvasive assessment of autoregulation. To achieve these aims, we analyzed data from existing databases including: (i) ABP and BFV of 12 healthy control, 10 hypertensive, and 10 stroke subjects during baseline resting conditions and during the Valsalva maneuver, and (ii) ABP, CPP, and BFV of 30 patients with traumatic brain injury (TBI) who were being paralyzed, sedated, and ventilated. We showed that autoregulation in healthy control subjects can be characterized by specific phase shifts between BP and BFV oscillations during the Valsalva maneuver, and the BP-BFV phase shifts were reduced in hypertensive and stroke subjects (P < 0.01), indicating impaired autoregulation. Similar results were found during baseline condition from spontaneous BP and BFV oscillations. The BP-BFV phase shifts obtained during baseline and during VM were highly correlated (R > 0.8, P < 0.0001), showing no statistical difference (paired-t test P > 0.47). In TBI patients there were strong correlations between phases of ABP and CPP oscillations (R = 0.99, P < 0.0001) and, thus, between ABP-BFV and CPP-BFV phase shifts (P < 0.0001, R = 0.76). By repeating the MMPF 4 times on data of TBI subjects, each time on a selected cycle of spontaneous BP and BFV oscillations, we showed that MMPF had better reproducibility than traditional autoregulation index. These results indicate that the MMPF method, based on instantaneous phase relationships between cerebral blood flow velocity and peripheral blood pressure, has better performance than the traditional standard method, and can reliably assess cerebral autoregulation dynamics from ambulatory blood pressure and cerebral blood flow during supine rest conditions.

Nonlinear Assessment of Cerebral Autoregulation from Spontaneous Blood Pressure and Cerebral Blood Flow Fluctuations

PubMed Central

Peng, C. K.; Czosnyka, Marek; Zhao, Peng

2009-01-01

Cerebral autoregulation (CA) is an most important mechanism responsible for the relatively constant blood flow supply to brain when cerebral perfusion pressure varies. Its assessment in nonacute cases has been relied on the quantification of the relationship between noninvasive beat-to-beat blood pressure (BP) and blood flow velocity (BFV). To overcome the nonstationary nature of physiological signals such as BP and BFV, a computational method called multimodal pressure-flow (MMPF) analysis was recently developed to study the nonlinear BP–BFV relationship during the Valsalva maneuver (VM). The present study aimed to determine (i) whether this method can estimate autoregulation from spontaneous BP and BFV fluctuations during baseline rest conditions; (ii) whether there is any difference between the MMPF measures of autoregulation based on intra-arterial BP (ABP) and based on cerebral perfusion pressure (CPP); and (iii) whether the MMPF method provides reproducible and reliable measure for noninvasive assessment of autoregulation. To achieve these aims, we analyzed data from existing databases including: (i) ABP and BFV of 12 healthy control, 10 hypertensive, and 10 stroke subjects during baseline resting conditions and during the Valsalva maneuver, and (ii) ABP, CPP, and BFV of 30 patients with traumatic brain injury (TBI) who were being paralyzed, sedated, and ventilated. We showed that autoregulation in healthy control subjects can be characterized by specific phase shifts between BP and BFV oscillations during the Valsalva maneuver, and the BP–BFV phase shifts were reduced in hypertensive and stroke subjects (P < 0.01), indicating impaired autoregulation. Similar results were found during baseline condition from spontaneous BP and BFV oscillations. The BP–BFV phase shifts obtained during baseline and during VM were highly correlated (R > 0.8, P < 0.0001), showing no statistical difference (paired-t test P > 0.47). In TBI patients there were strong correlations between phases of ABP and CPP oscillations (R = 0.99, P < 0.0001) and, thus, between ABP–BFV and CPP–BFV phase shifts (P < 0.0001, R = 0.76). By repeating the MMPF 4 times on data of TBI subjects, each time on a selected cycle of spontaneous BP and BFV oscillations, we showed that MMPF had better reproducibility than traditional autoregulation index. These results indicate that the MMPF method, based on instantaneous phase relationships between cerebral blood flow velocity and peripheral blood pressure, has better performance than the traditional standard method, and can reliably assess cerebral autoregulation dynamics from ambulatory blood pressure and cerebral blood flow during supine rest conditions. PMID:18080758

[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.

EEG Classification for Hybrid Brain-Computer Interface Using a Tensor Based Multiclass Multimodal Analysis Scheme

PubMed Central

Ji, Hongfei; Li, Jie; Lu, Rongrong; Gu, Rong; Cao, Lei; Gong, Xiaoliang

2016-01-01

Electroencephalogram- (EEG-) based brain-computer interface (BCI) systems usually utilize one type of changes in the dynamics of brain oscillations for control, such as event-related desynchronization/synchronization (ERD/ERS), steady state visual evoked potential (SSVEP), and P300 evoked potentials. There is a recent trend to detect more than one of these signals in one system to create a hybrid BCI. However, in this case, EEG data were always divided into groups and analyzed by the separate processing procedures. As a result, the interactive effects were ignored when different types of BCI tasks were executed simultaneously. In this work, we propose an improved tensor based multiclass multimodal scheme especially for hybrid BCI, in which EEG signals are denoted as multiway tensors, a nonredundant rank-one tensor decomposition model is proposed to obtain nonredundant tensor components, a weighted fisher criterion is designed to select multimodal discriminative patterns without ignoring the interactive effects, and support vector machine (SVM) is extended to multiclass classification. Experiment results suggest that the proposed scheme can not only identify the different changes in the dynamics of brain oscillations induced by different types of tasks but also capture the interactive effects of simultaneous tasks properly. Therefore, it has great potential use for hybrid BCI. PMID:26880873

EEG Classification for Hybrid Brain-Computer Interface Using a Tensor Based Multiclass Multimodal Analysis Scheme.

PubMed

Ji, Hongfei; Li, Jie; Lu, Rongrong; Gu, Rong; Cao, Lei; Gong, Xiaoliang

2016-01-01

Electroencephalogram- (EEG-) based brain-computer interface (BCI) systems usually utilize one type of changes in the dynamics of brain oscillations for control, such as event-related desynchronization/synchronization (ERD/ERS), steady state visual evoked potential (SSVEP), and P300 evoked potentials. There is a recent trend to detect more than one of these signals in one system to create a hybrid BCI. However, in this case, EEG data were always divided into groups and analyzed by the separate processing procedures. As a result, the interactive effects were ignored when different types of BCI tasks were executed simultaneously. In this work, we propose an improved tensor based multiclass multimodal scheme especially for hybrid BCI, in which EEG signals are denoted as multiway tensors, a nonredundant rank-one tensor decomposition model is proposed to obtain nonredundant tensor components, a weighted fisher criterion is designed to select multimodal discriminative patterns without ignoring the interactive effects, and support vector machine (SVM) is extended to multiclass classification. Experiment results suggest that the proposed scheme can not only identify the different changes in the dynamics of brain oscillations induced by different types of tasks but also capture the interactive effects of simultaneous tasks properly. Therefore, it has great potential use for hybrid BCI.

Lateralized theta wave connectivity and language performance in 2- to 5-year-old children.

PubMed

Kikuchi, Mitsuru; Shitamichi, Kiyomi; Yoshimura, Yuko; Ueno, Sanae; Remijn, Gerard B; Hirosawa, Tetsu; Munesue, Toshio; Tsubokawa, Tsunehisa; Haruta, Yasuhiro; Oi, Manabu; Higashida, Haruhiro; Minabe, Yoshio

2011-10-19

Recent neuroimaging studies support the view that a left-lateralized brain network is crucial for language development in children. However, no previous studies have demonstrated a clear link between lateralized brain functional network and language performance in preschool children. Magnetoencephalography (MEG) is a noninvasive brain imaging technique and is a practical neuroimaging method for use in young children. MEG produces a reference-free signal, and is therefore an ideal tool to compute coherence between two distant cortical rhythms. In the present study, using a custom child-sized MEG system, we investigated brain networks while 78 right-handed preschool human children (32-64 months; 96% were 3-4 years old) listened to stories with moving images. The results indicated that left dominance of parietotemporal coherence in theta band activity (6-8 Hz) was specifically correlated with higher performance of language-related tasks, whereas this laterality was not correlated with nonverbal cognitive performance, chronological age, or head circumference. Power analyses did not reveal any specific frequencies that contributed to higher language performance. Our results suggest that it is not the left dominance in theta oscillation per se, but the left-dominant phase-locked connectivity via theta oscillation that contributes to the development of language ability in young children.

Erythropoietin modulation of astrocyte water permeability as a component of neuroprotection

PubMed Central

Gunnarson, Eli; Song, Yutong; Kowalewski, Jacob M.; Brismar, Hjalmar; Brines, Michael; Cerami, Anthony; Andersson, Ulf; Zelenina, Marina; Aperia, Anita

2009-01-01

Disturbed brain water homeostasis with swelling of astroglial cells is a common complication in stroke, trauma, and meningitis and is considered to be a major cause of permanent brain damage. Astroglial cells possess the water channel aquaporin 4 (AQP4). Recent studies from our laboratory have shown that glutamate, acting on group I metabotropic glutamate receptors (mGluRs), increases the permeability of astrocyte AQP4, which, in situations of hypoxia-ischemia, will increase astrocyte water uptake. Here we report that erythropoietin (EPO), which in recent years has emerged as a potent neuro-protective agent, antagonizes the effect of a group I mGluR agonist on astrocyte water permeability. Activation of group I mGluRs triggers fast and highly regular intracellular calcium oscillations and we show that EPO interferes with this signaling event by altering the frequency of the oscillations. These effects of EPO are immediate, in contrast to the neuroprotective effects of EPO that are known to depend upon gene activation. Our findings indicate that EPO may directly reduce the risk of astrocyte swelling in stroke and other brain insults. In support of this conclusion we found that EPO reduced the neurological symptoms in a mouse model of primary brain edema known to depend upon AQP4 water transport. PMID:19164545

Competition in the Brain. The Contribution of EEG and fNIRS Modulation and Personality Effects in Social Ranking.

PubMed

Balconi, Michela; Vanutelli, Maria E

2016-01-01

In the present study, the social ranking perception in competition was explored. Brain response (alpha band oscillations, EEG; hemodynamic activity, O2Hb), as well as self-perception of social ranking, cognitive performance, and personality trait (Behavioral Activation System, BAS) were considered during a competitive joint-action. Subjects were required to develop a strategy to obtain a better outcome than a competitor (C) (in term of error rate, and response time, RT). A pre-feedback (without a specific feedback on the performance) and a post-feedback condition (which reinforced the improved performance) were provided. It was found that higher-BAS participants responded in greater measure to perceived higher cognitive performance (post-feedback condition), with increased left prefrontal activity, higher ranking perception, and a better real performance (reduced RTs). These results were explained in term of increased sense of self-efficacy and social position, probably based on higher-BAS sensitivity to reinforcing conditions. In addition, the hemispheric effect in favor of the left side characterized the competitive behavior, showing an imbalance for high-BAS in comparison to low-BAS in the case of a rewarding (post-feedback) context. Therefore, the present results confirmed the significance of BAS in modulating brain responsiveness, self-perceived social position, and real performance during an interpersonal competitive action which is considered highly relevant for social status.

Chronic Ketamine Reduces the Peak Frequency of Gamma Oscillations in Mouse Prefrontal Cortex Ex vivo.

PubMed

McNally, James M; McCarley, Robert W; Brown, Ritchie E

2013-01-01

Abnormalities in EEG gamma band oscillations (GBO, 30-80 Hz) serve as a prominent biomarker of schizophrenia (Sz), associated with positive, negative, and cognitive symptoms. Chronic, subanesthetic administration of antagonists of N-methyl-D-aspartate receptors (NMDAR), such as ketamine, elicits behavioral effects, and alterations in cortical interneurons similar to those observed in Sz. However, the chronic effects of ketamine on neocortical GBO are unknown. Thus, here we examine the effects of chronic (five daily i.p. injections) application of ketamine (5 and 30 mg/kg) and the more specific NMDAR antagonist, MK-801 (0.02, 0.5, and 2 mg/kg), on neocortical GBO ex vivo. Oscillations were generated by focal application of the glutamate receptor agonist, kainate (KA), in coronal brain slices containing the prelimbic cortex. This region constitutes the rodent analog of the human dorsolateral prefrontal cortex, a brain region strongly implicated in Sz-pathophysiology. Here we report the novel finding that chronic ketamine elicits a reduction in the peak oscillatory frequency of KA-elicited oscillations (from 47 to 40 Hz at 30 mg/kg). Moreover, the power of GBO in the 40-50 Hz band was reduced. These findings are reminiscent of both the reduced resonance frequency and power of cortical oscillations observed in Sz clinical studies. Surprisingly, MK-801 had no significant effect, suggesting care is needed when equating Sz-like behavioral effects elicited by different NMDAR antagonists to alterations in GBO activity. We conclude that chronic ketamine in the mouse mimics GBO abnormalities observed in Sz patients. Use of this ex vivo slice model may be useful in testing therapeutic compounds which rescue these GBO abnormalities.

Localization of beta and high-frequency oscillations within the subthalamic nucleus region.

PubMed

van Wijk, B C M; Pogosyan, A; Hariz, M I; Akram, H; Foltynie, T; Limousin, P; Horn, A; Ewert, S; Brown, P; Litvak, V

2017-01-01

Parkinsonian bradykinesia and rigidity are typically associated with excessive beta band oscillations in the subthalamic nucleus. Recently another spectral peak has been identified that might be implicated in the pathophysiology of the disease: high-frequency oscillations (HFO) within the 150-400 Hz range. Beta-HFO phase-amplitude coupling (PAC) has been found to correlate with severity of motor impairment. However, the neuronal origin of HFO and its usefulness as a potential target for deep brain stimulation remain to be established. For example, it is unclear whether HFO arise from the same neural populations as beta oscillations. We intraoperatively recorded local field potentials from the subthalamic nucleus while advancing DBS electrodes in 2 mm steps from 4 mm above the surgical target point until 2 mm below, resulting in 4 recording sites. Data from 26 nuclei from 14 patients were analysed. For each trajectory, we identified the recording site with the largest spectral peak in the beta range (13-30 Hz), and the largest peak in the HFO range separately. In addition, we identified the recording site with the largest beta-HFO PAC. Recording sites with largest beta power and largest HFO power coincided in 50% of cases. In the other 50%, HFO was more likely to be detected at a more superior recording site in the target area. PAC followed more closely the site with largest HFO (45%) than beta power (27%). HFO are likely to arise from spatially close, but slightly more superior neural populations than beta oscillations. Further work is necessary to determine whether the different activities can help fine-tune deep brain stimulation targeting.

Neural Oscillations Carry Speech Rhythm through to Comprehension

PubMed Central

Peelle, Jonathan E.; Davis, Matthew H.

2012-01-01

A key feature of speech is the quasi-regular rhythmic information contained in its slow amplitude modulations. In this article we review the information conveyed by speech rhythm, and the role of ongoing brain oscillations in listeners’ processing of this content. Our starting point is the fact that speech is inherently temporal, and that rhythmic information conveyed by the amplitude envelope contains important markers for place and manner of articulation, segmental information, and speech rate. Behavioral studies demonstrate that amplitude envelope information is relied upon by listeners and plays a key role in speech intelligibility. Extending behavioral findings, data from neuroimaging – particularly electroencephalography (EEG) and magnetoencephalography (MEG) – point to phase locking by ongoing cortical oscillations to low-frequency information (~4–8 Hz) in the speech envelope. This phase modulation effectively encodes a prediction of when important events (such as stressed syllables) are likely to occur, and acts to increase sensitivity to these relevant acoustic cues. We suggest a framework through which such neural entrainment to speech rhythm can explain effects of speech rate on word and segment perception (i.e., that the perception of phonemes and words in connected speech is influenced by preceding speech rate). Neuroanatomically, acoustic amplitude modulations are processed largely bilaterally in auditory cortex, with intelligible speech resulting in differential recruitment of left-hemisphere regions. Notable among these is lateral anterior temporal cortex, which we propose functions in a domain-general fashion to support ongoing memory and integration of meaningful input. Together, the reviewed evidence suggests that low-frequency oscillations in the acoustic speech signal form the foundation of a rhythmic hierarchy supporting spoken language, mirrored by phase-locked oscillations in the human brain. PMID:22973251

High-density EEG characterization of brain responses to auditory rhythmic stimuli during wakefulness and NREM sleep.

PubMed

Lustenberger, Caroline; Patel, Yogi A; Alagapan, Sankaraleengam; Page, Jessica M; Price, Betsy; Boyle, Michael R; Fröhlich, Flavio

2018-04-01

Auditory rhythmic sensory stimulation modulates brain oscillations by increasing phase-locking to the temporal structure of the stimuli and by increasing the power of specific frequency bands, resulting in Auditory Steady State Responses (ASSR). The ASSR is altered in different diseases of the central nervous system such as schizophrenia. However, in order to use the ASSR as biological markers for disease states, it needs to be understood how different vigilance states and underlying brain activity affect the ASSR. Here, we compared the effects of auditory rhythmic stimuli on EEG brain activity during wake and NREM sleep, investigated the influence of the presence of dominant sleep rhythms on the ASSR, and delineated the topographical distribution of these modulations. Participants (14 healthy males, 20-33 years) completed on the same day a 60 min nap session and two 30 min wakefulness sessions (before and after the nap). During these sessions, amplitude modulated (AM) white noise auditory stimuli at different frequencies were applied. High-density EEG was continuously recorded and time-frequency analyses were performed to assess ASSR during wakefulness and NREM periods. Our analysis revealed that depending on the electrode location, stimulation frequency applied and window/frequencies analysed the ASSR was significantly modulated by sleep pressure (before and after sleep), vigilance state (wake vs. NREM sleep), and the presence of slow wave activity and sleep spindles. Furthermore, AM stimuli increased spindle activity during NREM sleep but not during wakefulness. Thus, (1) electrode location, sleep history, vigilance state and ongoing brain activity needs to be carefully considered when investigating ASSR and (2) auditory rhythmic stimuli during sleep might represent a powerful tool to boost sleep spindles. Copyright © 2017 Elsevier Inc. All rights reserved.

Weld pool oscillation during GTA welding of mild steel

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

Xiao, Y.H.; Ouden, G. den

1993-08-01

In this paper the results are reported of a study dealing with the oscillation behavior of weld pools in the case of GTA bead-on-plate welding of mild steel, Fe 360. During welding, the weld pool was brought into oscillation by applying short current pulses, and the oscillation frequency and amplitude were measured by monitoring the arc voltage. It was found that the oscillation of the partially penetrated weld pool is dominated by one of two different oscillation modes (Mode 1 and Mode 2) depending on the welding conditions, whereas the oscillation of the fully penetrated weld pool is characterized bymore » a third oscillation mode (Mode 3). It is possible to maintain partially penetrated weld pool oscillation in Mode 1 by choosing appropriate welding conditions. Under these conditions, an abrupt decrease in oscillation frequency occurs when the weld pool transfers from partial penetration to full penetration. Thus, weld penetration can be in-process controlled by monitoring the oscillation frequency during welding.« less

Long-range correlation of the membrane potential in neocortical neurons during slow oscillation

PubMed Central

Volgushev, Maxim; Chauvette, Sylvain; Timofeev, Igor

2012-01-01

Large amplitude slow waves are characteristic for the summary brain activity, recorded as electroencephalogram (EEG) or local field potentials (LFP), during deep stages of sleep and some types of anesthesia. Slow rhythm of the synchronized EEG reflects an alternation of active (depolarized, UP) and silent (hyperpolarized, DOWN) states of neocortical neurons. In neurons, involvement in the generalized slow oscillation results in a long-range synchronization of changes of their membrane potential as well as their firing. Here, we aimed at intracellular analysis of details of this synchronization. We asked which components of neuronal activity exhibit long-range correlations during the synchronized EEG? To answer this question, we made simultaneous intracellular recordings from two to four neocortical neurons in cat neocortex. We studied how correlated is the occurrence of active and silent states, and how correlated are fluctuations of the membrane potential in pairs of neurons located close one to the other or separated by up to 13 mm. We show that strong long-range correlation of the membrane potential was observed only (i) during the slow oscillation but not during periods without the oscillation, (ii) during periods which included transitions between the states but not during within-the-state periods, and (iii) for the low-frequency (<5 Hz) components of membrane potential fluctuations but not for the higher-frequency components (>10 Hz). In contrast to the neurons located several millimeters one from the other, membrane potential fluctuations in neighboring neurons remain strongly correlated during periods without slow oscillation. We conclude that membrane potential correlation in distant neurons is brought about by synchronous transitions between the states, while activity within the states is largely uncorrelated. The lack of the generalized fine-scale synchronization of membrane potential changes in neurons during the active states of slow oscillation may allow individual neurons to selectively engage in short living episodes of correlated activity—a process that may be similar to dynamical formation of neuronal ensembles during activated brain states. PMID:21854963

Cortical evoked potentials to an auditory illusion: binaural beats.

PubMed

Pratt, Hillel; Starr, Arnold; Michalewski, Henry J; Dimitrijevic, Andrew; Bleich, Naomi; Mittelman, Nomi

2009-08-01

To define brain activity corresponding to an auditory illusion of 3 and 6Hz binaural beats in 250Hz or 1000Hz base frequencies, and compare it to the sound onset response. Event-Related Potentials (ERPs) were recorded in response to unmodulated tones of 250 or 1000Hz to one ear and 3 or 6Hz higher to the other, creating an illusion of amplitude modulations (beats) of 3Hz and 6Hz, in base frequencies of 250Hz and 1000Hz. Tones were 2000ms in duration and presented with approximately 1s intervals. Latency, amplitude and source current density estimates of ERP components to tone onset and subsequent beats-evoked oscillations were determined and compared across beat frequencies with both base frequencies. All stimuli evoked tone-onset P(50), N(100) and P(200) components followed by oscillations corresponding to the beat frequency, and a subsequent tone-offset complex. Beats-evoked oscillations were higher in amplitude with the low base frequency and to the low beat frequency. Sources of the beats-evoked oscillations across all stimulus conditions located mostly to left lateral and inferior temporal lobe areas in all stimulus conditions. Onset-evoked components were not different across stimulus conditions; P(50) had significantly different sources than the beats-evoked oscillations; and N(100) and P(200) sources located to the same temporal lobe regions as beats-evoked oscillations, but were bilateral and also included frontal and parietal contributions. Neural activity with slightly different volley frequencies from left and right ear converges and interacts in the central auditory brainstem pathways to generate beats of neural activity to modulate activities in the left temporal lobe, giving rise to the illusion of binaural beats. Cortical potentials recorded to binaural beats are distinct from onset responses. Brain activity corresponding to an auditory illusion of low frequency beats can be recorded from the scalp.

Cortical Evoked Potentials to an Auditory Illusion: Binaural Beats

PubMed Central

Pratt, Hillel; Starr, Arnold; Michalewski, Henry J.; Dimitrijevic, Andrew; Bleich, Naomi; Mittelman, Nomi

2009-01-01

Objective: To define brain activity corresponding to an auditory illusion of 3 and 6 Hz binaural beats in 250 Hz or 1,000 Hz base frequencies, and compare it to the sound onset response. Methods: Event-Related Potentials (ERPs) were recorded in response to unmodulated tones of 250 or 1000 Hz to one ear and 3 or 6 Hz higher to the other, creating an illusion of amplitude modulations (beats) of 3 Hz and 6 Hz, in base frequencies of 250 Hz and 1000 Hz. Tones were 2,000 ms in duration and presented with approximately 1 s intervals. Latency, amplitude and source current density estimates of ERP components to tone onset and subsequent beats-evoked oscillations were determined and compared across beat frequencies with both base frequencies. Results: All stimuli evoked tone-onset P50, N100 and P200 components followed by oscillations corresponding to the beat frequency, and a subsequent tone-offset complex. Beats-evoked oscillations were higher in amplitude with the low base frequency and to the low beat frequency. Sources of the beats-evoked oscillations across all stimulus conditions located mostly to left lateral and inferior temporal lobe areas in all stimulus conditions. Onset-evoked components were not different across stimulus conditions; P50 had significantly different sources than the beats-evoked oscillations; and N100 and P200 sources located to the same temporal lobe regions as beats-evoked oscillations, but were bilateral and also included frontal and parietal contributions. Conclusions: Neural activity with slightly different volley frequencies from left and right ear converges and interacts in the central auditory brainstem pathways to generate beats of neural activity to modulate activities in the left temporal lobe, giving rise to the illusion of binaural beats. Cortical potentials recorded to binaural beats are distinct from onset responses. Significance: Brain activity corresponding to an auditory illusion of low frequency beats can be recorded from the scalp. PMID:19616993

The Primary Visual Cortex Is Differentially Modulated by Stimulus-Driven and Top-Down Attention

PubMed Central

Bekisz, Marek; Bogdan, Wojciech; Ghazaryan, Anaida; Waleszczyk, Wioletta J.; Kublik, Ewa; Wróbel, Andrzej

2016-01-01

Selective attention can be focused either volitionally, by top-down signals derived from task demands, or automatically, by bottom-up signals from salient stimuli. Because the brain mechanisms that underlie these two attention processes are poorly understood, we recorded local field potentials (LFPs) from primary visual cortical areas of cats as they performed stimulus-driven and anticipatory discrimination tasks. Consistent with our previous observations, in both tasks, we found enhanced beta activity, which we have postulated may serve as an attention carrier. We characterized the functional organization of task-related beta activity by (i) cortical responses (EPs) evoked by electrical stimulation of the optic chiasm and (ii) intracortical LFP correlations. During the anticipatory task, peripheral stimulation that was preceded by high-amplitude beta oscillations evoked large-amplitude EPs compared with EPs that followed low-amplitude beta. In contrast, during the stimulus-driven task, cortical EPs preceded by high-amplitude beta oscillations were, on average, smaller than those preceded by low-amplitude beta. Analysis of the correlations between the different recording sites revealed that beta activation maps were heterogeneous during the bottom-up task and homogeneous for the top-down task. We conclude that bottom-up attention activates cortical visual areas in a mosaic-like pattern, whereas top-down attentional modulation results in spatially homogeneous excitation. PMID:26730705

From amusic to musical?--Improving pitch memory in congenital amusia with transcranial alternating current stimulation.

PubMed

Schaal, Nora K; Pfeifer, Jasmin; Krause, Vanessa; Pollok, Bettina

2015-11-01

Brain imaging studies highlighted structural differences in congenital amusia, a life-long perceptual disorder that is associated with pitch perception and pitch memory deficits. A functional anomaly characterized by decreased low gamma oscillations (30-40 Hz range) in the right dorsolateral prefrontal cortex (DLPFC) during pitch memory has been revealed recently. Thus, the present study investigates whether applying transcranial alternating current stimulation (tACS) at 35 Hz to the right DLPFC would improve pitch memory. Nine amusics took part in two tACS sessions (either 35 Hz or 90 Hz) and completed a pitch and visual memory task before and during stimulation. 35 Hz stimulation facilitated pitch memory significantly. No modulation effects were found with 90 Hz stimulation or on the visual task. While amusics showed a selective impairment of pitch memory before stimulation, the performance during 35 Hz stimulation was not significantly different to healthy controls anymore. Taken together, the study shows that modulating the right DLPFC with 35 Hz tACS in congenital amusia selectively improves pitch memory performance supporting the hypothesis that decreased gamma oscillations within the DLPFC are causally involved in disturbed pitch memory and highlight the potential use of tACS to interact with cognitive processes. Copyright © 2015 Elsevier B.V. All rights reserved.

Effect of Background Pressure on the Plasma Oscillation Characteristics of the HiVHAc Hall Thruster

DTIC Science & Technology

2014-06-01

Hall thruster , a number of plasma diagnostics were implemented to study the effect of varying facility background pressure on thruster operation. These diagnostics characterized the thruster performance, the plume, and the plasma oscillations in the thruster. Thruster performance and plume characteristics as functions of background pressure were previously published. This paper will focus on changes in the plasma oscillation characteristics with changing background pressure. The diagnostics used to study plasma oscillations include a high-speed camera and a set of

Formation of visual memories controlled by gamma power phase-locked to alpha oscillations.

PubMed

Park, Hyojin; Lee, Dong Soo; Kang, Eunjoo; Kang, Hyejin; Hahm, Jarang; Kim, June Sic; Chung, Chun Kee; Jiang, Haiteng; Gross, Joachim; Jensen, Ole

2016-06-16

Neuronal oscillations provide a window for understanding the brain dynamics that organize the flow of information from sensory to memory areas. While it has been suggested that gamma power reflects feedforward processing and alpha oscillations feedback control, it remains unknown how these oscillations dynamically interact. Magnetoencephalography (MEG) data was acquired from healthy subjects who were cued to either remember or not remember presented pictures. Our analysis revealed that in anticipation of a picture to be remembered, alpha power decreased while the cross-frequency coupling between gamma power and alpha phase increased. A measure of directionality between alpha phase and gamma power predicted individual ability to encode memory: stronger control of alpha phase over gamma power was associated with better memory. These findings demonstrate that encoding of visual information is reflected by a state determined by the interaction between alpha and gamma activity.

Analysis of dynamic brain oscillations: methodological advances.

PubMed

Le Van Quyen, Michel; Bragin, Anatol

2007-07-01

In recent years, new recording technologies have advanced such that, at high temporal and spatial resolutions, oscillations of neuronal networks can be identified from simultaneous, multisite recordings. However, because of the deluge of multichannel data generated by these experiments, achieving the full potential of parallel neuronal recordings also depends on the development of new mathematical methods that can extract meaningful information relating to time, frequency and space. Here, we aim to bridge this gap by focusing on up-to-date recording techniques for measurement of network oscillations and new analysis tools for their quantitative assessment. In particular, we emphasize how these methods can be applied, what property might be inferred from neuronal signals and potentially productive future directions. This review is part of the INMED and TINS special issue, Physiogenic and pathogenic oscillations: the beauty and the beast, derived from presentations at the annual INMED and TINS symposium (http://inmednet.com).

Calibrated mitotic oscillator drives motile ciliogenesis.

PubMed

Al Jord, Adel; Shihavuddin, Asm; Servignat d'Aout, Raphaël; Faucourt, Marion; Genovesio, Auguste; Karaiskou, Anthi; Sobczak-Thépot, Joëlle; Spassky, Nathalie; Meunier, Alice

2017-11-10

Cell division and differentiation depend on massive and rapid organelle remodeling. The mitotic oscillator, centered on the cyclin-dependent kinase 1-anaphase-promoting complex/cyclosome (CDK1-APC/C) axis, spatiotemporally coordinates this reorganization in dividing cells. Here we discovered that nondividing cells could also implement this mitotic clocklike regulatory circuit to orchestrate subcellular reorganization associated with differentiation. We probed centriole amplification in differentiating mouse-brain multiciliated cells. These postmitotic progenitors fine-tuned mitotic oscillator activity to drive the orderly progression of centriole production, maturation, and motile ciliation while avoiding the mitosis commitment threshold. Insufficient CDK1 activity hindered differentiation, whereas excessive activity accelerated differentiation yet drove postmitotic progenitors into mitosis. Thus, postmitotic cells can redeploy and calibrate the mitotic oscillator to uncouple cytoplasmic from nuclear dynamics for organelle remodeling associated with differentiation. Copyright © 2017 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

Formation of visual memories controlled by gamma power phase-locked to alpha oscillations

PubMed Central

Park, Hyojin; Lee, Dong Soo; Kang, Eunjoo; Kang, Hyejin; Hahm, Jarang; Kim, June Sic; Chung, Chun Kee; Jiang, Haiteng; Gross, Joachim; Jensen, Ole

2016-01-01

Neuronal oscillations provide a window for understanding the brain dynamics that organize the flow of information from sensory to memory areas. While it has been suggested that gamma power reflects feedforward processing and alpha oscillations feedback control, it remains unknown how these oscillations dynamically interact. Magnetoencephalography (MEG) data was acquired from healthy subjects who were cued to either remember or not remember presented pictures. Our analysis revealed that in anticipation of a picture to be remembered, alpha power decreased while the cross-frequency coupling between gamma power and alpha phase increased. A measure of directionality between alpha phase and gamma power predicted individual ability to encode memory: stronger control of alpha phase over gamma power was associated with better memory. These findings demonstrate that encoding of visual information is reflected by a state determined by the interaction between alpha and gamma activity. PMID:27306959

Synchronization and spatiotemporal patterns in coupled phase oscillators on a weighted planar network

NASA Astrophysics Data System (ADS)

Kagawa, Yuki; Takamatsu, Atsuko

2009-04-01

To reveal the relation between network structures found in two-dimensional biological systems, such as protoplasmic tube networks in the plasmodium of true slime mold, and spatiotemporal oscillation patterns emerged on the networks, we constructed coupled phase oscillators on weighted planar networks and investigated their dynamics. Results showed that the distribution of edge weights in the networks strongly affects (i) the propensity for global synchronization and (ii) emerging ratios of oscillation patterns, such as traveling and concentric waves, even if the total weight is fixed. In-phase locking, traveling wave, and concentric wave patterns were, respectively, observed most frequently in uniformly weighted, center weighted treelike, and periphery weighted ring-shaped networks. Controlling the global spatiotemporal patterns with the weight distribution given by the local weighting (coupling) rules might be useful in biological network systems including the plasmodial networks and neural networks in the brain.

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.

What neurophysiological recordings tell us about cognitive and behavioral functions of the human subthalamic nucleus.

PubMed

Marceglia, Sara; Fumagalli, Manuela; Priori, Alberto

2011-01-01

The behavioral implications of deep brain stimulation (DBS) observed in Parkinson's disease patients provided evidence for a possible nonexclusively motor role of the subthalamic nucleus (STN) in basal ganglia circuitry. Basal ganglia pathophysiology can be studied directly by the analysis of neural rhythms measured in local field potentials recorded through DBS electrodes. Recent studies demonstrated that specific oscillations in the STN are involved in cognitive and behavioral information processing: action representation is mediated through β oscillations (13-35 Hz); cognitive information related to decision-making processes is mediated through the low-frequency oscillation (5-12 Hz); and limbic and emotional information is mediated through the α oscillation (8-12 Hz). These results revealed an important involvement of STN in decisional processes, cognitive functions, emotion control and conflict that could explain the post-DBS occurrence of behavioral disturbances.

Formation of visual memories controlled by gamma power phase-locked to alpha oscillations

NASA Astrophysics Data System (ADS)

Park, Hyojin; Lee, Dong Soo; Kang, Eunjoo; Kang, Hyejin; Hahm, Jarang; Kim, June Sic; Chung, Chun Kee; Jiang, Haiteng; Gross, Joachim; Jensen, Ole

2016-06-01

Neuronal oscillations provide a window for understanding the brain dynamics that organize the flow of information from sensory to memory areas. While it has been suggested that gamma power reflects feedforward processing and alpha oscillations feedback control, it remains unknown how these oscillations dynamically interact. Magnetoencephalography (MEG) data was acquired from healthy subjects who were cued to either remember or not remember presented pictures. Our analysis revealed that in anticipation of a picture to be remembered, alpha power decreased while the cross-frequency coupling between gamma power and alpha phase increased. A measure of directionality between alpha phase and gamma power predicted individual ability to encode memory: stronger control of alpha phase over gamma power was associated with better memory. These findings demonstrate that encoding of visual information is reflected by a state determined by the interaction between alpha and gamma activity.

Novel High Temperature Capacitive Pressure Sensor Utilizing SiC Integrated Circuit Twin Ring Oscillators

NASA Technical Reports Server (NTRS)

Scardelletti, M.; Neudeck, P.; Spry, D.; Meredith, R.; Jordan, J.; Prokop, N.; Krasowski, M.; Beheim, G.; Hunter, G.

2017-01-01

This paper describes initial development and testing of a novel high temperature capacitive pressure sensor system. The pressure sensor system consists of two 4H-SiC 11-stage ring oscillators and a SiCN capacitive pressure sensor. One oscillator has the capacitive pressure sensor fixed at one node in its feedback loop and varies as a function of pressure and temperature while the other provides a pressure-independent reference frequency which can be used to temperature compensate the output of the first oscillator. A two-day repeatability test was performed up to 500C on the oscillators and the oscillator fundamental frequency changed by only 1. The SiCN capacitive pressure sensor was characterized at room temperature from 0 to 300 psi. The sensor had an initial capacitance of 3.76 pF at 0 psi and 1.75 pF at 300 psi corresponding to a 54 change in capacitance. The integrated pressure sensor system was characterized from 0 to 300 psi in steps of 50 psi over a temperature range of 25 to 500C. The pressure sensor system sensitivity was 0.113 kHzpsi at 25C and 0.026 kHzpsi at 500C.

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.

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

Short desynchronization episodes prevail in synchronous dynamics of human brain rhythms.

PubMed

Ahn, Sungwoo; Rubchinsky, Leonid L

2013-03-01

Neural synchronization is believed to be critical for many brain functions. It frequently exhibits temporal variability, but it is not known if this variability has a specific temporal patterning. This study explores these synchronization/desynchronization patterns. We employ recently developed techniques to analyze the fine temporal structure of phase-locking to study the temporal patterning of synchrony of the human brain rhythms. We study neural oscillations recorded by electroencephalograms in α and β frequency bands in healthy human subjects at rest and during the execution of a task. While the phase-locking strength depends on many factors, dynamics of synchrony has a very specific temporal pattern: synchronous states are interrupted by frequent, but short desynchronization episodes. The probability for a desynchronization episode to occur decreased with its duration. The transition matrix between synchronized and desynchronized states has eigenvalues close to 0 and 1 where eigenvalue 1 has multiplicity 1, and therefore if the stationary distribution between these states is perturbed, the system converges back to the stationary distribution very fast. The qualitative similarity of this patterning across different subjects, brain states and electrode locations suggests that this may be a general type of dynamics for the brain. Earlier studies indicate that not all oscillatory networks have this kind of patterning of synchronization/desynchronization dynamics. Thus, the observed prevalence of short (but potentially frequent) desynchronization events (length of one cycle of oscillations) may have important functional implications for the brain. Numerous short desynchronizations (as opposed to infrequent, but long desynchronizations) may allow for a quick and efficient formation and break-up of functionally significant neuronal assemblies.

Serotonergic Psychedelics Temporarily Modify Information Transfer in Humans

PubMed Central

Alonso, Joan Francesc; Romero, Sergio; Mañanas, Miquel Àngel

2015-01-01

Background: Psychedelics induce intense modifications in the sensorium, the sense of “self,” and the experience of reality. Despite advances in our understanding of the molecular and cellular level mechanisms of these drugs, knowledge of their actions on global brain dynamics is still incomplete. Recent imaging studies have found changes in functional coupling between frontal and parietal brain structures, suggesting a modification in information flow between brain regions during acute effects. Methods: Here we assessed the psychedelic-induced changes in directionality of information flow during the acute effects of a psychedelic in humans. We measured modifications in connectivity of brain oscillations using transfer entropy, a nonlinear measure of directed functional connectivity based on information theory. Ten healthy male volunteers with prior experience with psychedelics participated in 2 experimental sessions. They received a placebo or a dose of ayahuasca, a psychedelic preparation containing the serotonergic 5-HT2A agonist N,N-dimethyltryptamine. Results: The analysis showed significant changes in the coupling of brain oscillations between anterior and posterior recording sites. Transfer entropy analysis showed that frontal sources decreased their influence over central, parietal, and occipital sites. Conversely, sources in posterior locations increased their influence over signals measured at anterior locations. Exploratory correlations found that anterior-to-posterior transfer entropy decreases were correlated with the intensity of subjective effects, while the imbalance between anterior-to-posterior and posterior-to-anterior transfer entropy correlated with the degree of incapacitation experienced. Conclusions: These results suggest that psychedelics induce a temporary disruption of neural hierarchies by reducing top-down control and increasing bottom-up information transfer in the human brain. PMID:25820842

Short desynchronization episodes prevail in synchronous dynamics of human brain rhythms

NASA Astrophysics Data System (ADS)

Ahn, Sungwoo; Rubchinsky, Leonid L.

2013-03-01

Neural synchronization is believed to be critical for many brain functions. It frequently exhibits temporal variability, but it is not known if this variability has a specific temporal patterning. This study explores these synchronization/desynchronization patterns. We employ recently developed techniques to analyze the fine temporal structure of phase-locking to study the temporal patterning of synchrony of the human brain rhythms. We study neural oscillations recorded by electroencephalograms in α and β frequency bands in healthy human subjects at rest and during the execution of a task. While the phase-locking strength depends on many factors, dynamics of synchrony has a very specific temporal pattern: synchronous states are interrupted by frequent, but short desynchronization episodes. The probability for a desynchronization episode to occur decreased with its duration. The transition matrix between synchronized and desynchronized states has eigenvalues close to 0 and 1 where eigenvalue 1 has multiplicity 1, and therefore if the stationary distribution between these states is perturbed, the system converges back to the stationary distribution very fast. The qualitative similarity of this patterning across different subjects, brain states and electrode locations suggests that this may be a general type of dynamics for the brain. Earlier studies indicate that not all oscillatory networks have this kind of patterning of synchronization/desynchronization dynamics. Thus, the observed prevalence of short (but potentially frequent) desynchronization events (length of one cycle of oscillations) may have important functional implications for the brain. Numerous short desynchronizations (as opposed to infrequent, but long desynchronizations) may allow for a quick and efficient formation and break-up of functionally significant neuronal assemblies.

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

Concurrent tACS-fMRI Reveals Causal Influence of Power Synchronized Neural Activity on Resting State fMRI Connectivity.

PubMed

Bächinger, Marc; Zerbi, Valerio; Moisa, Marius; Polania, Rafael; Liu, Quanying; Mantini, Dante; Ruff, Christian; Wenderoth, Nicole

2017-05-03

Resting state fMRI (rs-fMRI) is commonly used to study the brain's intrinsic neural coupling, which reveals specific spatiotemporal patterns in the form of resting state networks (RSNs). It has been hypothesized that slow rs-fMRI oscillations (<0.1 Hz) are driven by underlying electrophysiological rhythms that typically occur at much faster timescales (>5 Hz); however, causal evidence for this relationship is currently lacking. Here we measured rs-fMRI in humans while applying transcranial alternating current stimulation (tACS) to entrain brain rhythms in left and right sensorimotor cortices. The two driving tACS signals were tailored to the individual's α rhythm (8-12 Hz) and fluctuated in amplitude according to a 1 Hz power envelope. We entrained the left versus right hemisphere in accordance to two different coupling modes where either α oscillations were synchronized between hemispheres (phase-synchronized tACS) or the slower oscillating power envelopes (power-synchronized tACS). Power-synchronized tACS significantly increased rs-fMRI connectivity within the stimulated RSN compared with phase-synchronized or no tACS. This effect outlasted the stimulation period and tended to be more effective in individuals who exhibited a naturally weak interhemispheric coupling. Using this novel approach, our data provide causal evidence that synchronized power fluctuations contribute to the formation of fMRI-based RSNs. Moreover, our findings demonstrate that the brain's intrinsic coupling at rest can be selectively modulated by choosing appropriate tACS signals, which could lead to new interventions for patients with altered rs-fMRI connectivity. SIGNIFICANCE STATEMENT Resting state fMRI (rs-fMRI) has become an important tool to estimate brain connectivity. However, relatively little is known about how slow hemodynamic oscillations measured with fMRI relate to electrophysiological processes. It was suggested that slowly fluctuating power envelopes of electrophysiological signals synchronize across brain areas and that the topography of this activity is spatially correlated to resting state networks derived from rs-fMRI. Here we take a novel approach to address this problem and establish a causal link between the power fluctuations of electrophysiological signals and rs-fMRI via a new neuromodulation paradigm, which exploits these power synchronization mechanisms. These novel mechanistic insights bridge different scientific domains and are of broad interest to researchers in the fields of Medical Imaging, Neuroscience, Physiology, and Psychology. Copyright © 2017 the authors 0270-6474/17/374766-12$15.00/0.

Changes in ganglion cell physiology during retinal degeneration influence excitability by prosthetic electrodes

NASA Astrophysics Data System (ADS)

Cho, Alice; Ratliff, Charles; Sampath, Alapakkam; Weiland, James

2016-04-01

Objective. Here we investigate ganglion cell physiology in healthy and degenerating retina to test its influence on threshold to electrical stimulation. Approach. Age-related Macular Degeneration and Retinitis Pigmentosa cause blindness via outer retinal degeneration. Inner retinal pathways that transmit visual information to the central brain remain intact, so direct electrical stimulation from prosthetic devices offers the possibility for visual restoration. Since inner retinal physiology changes during degeneration, we characterize physiological properties and responses to electrical stimulation in retinal ganglion cells (RGCs) of both wild type mice and the rd10 mouse model of retinal degeneration. Main results. Our aggregate results support previous observations that elevated thresholds characterize diseased retinas. However, a physiology-driven classification scheme reveals distinct sub-populations of ganglion cells with thresholds either normal or strongly elevated compared to wild-type. When these populations are combined, only a weakly elevated threshold with large variance is observed. The cells with normal threshold are more depolarized at rest and exhibit periodic oscillations. Significance. During degeneration, physiological changes in RGCs affect the threshold stimulation currents required to evoke action potentials.

Sleep for cognitive enhancement.

PubMed

Diekelmann, Susanne

2014-01-01

Sleep is essential for effective cognitive functioning. Loosing even a few hours of sleep can have detrimental effects on a wide variety of cognitive processes such as attention, language, reasoning, decision making, learning and memory. While sleep is necessary to ensure normal healthy cognitive functioning, it can also enhance performance beyond the boundaries of the normal condition. This article discusses the enhancing potential of sleep, mainly focusing on the domain of learning and memory. Sleep is known to facilitate the consolidation of memories learned before sleep as well as the acquisition of new memories to be learned after sleep. According to a widely held model this beneficial effect of sleep relies on the neuronal reactivation of memories during sleep that is associated with sleep-specific brain oscillations (slow oscillations, spindles, ripples) as well as a characteristic neurotransmitter milieu. Recent research indicates that memory processing during sleep can be boosted by (i) cueing memory reactivation during sleep; (ii) stimulating sleep-specific brain oscillations; and (iii) targeting specific neurotransmitter systems pharmacologically. Olfactory and auditory cues can be used, for example, to increase reactivation of associated memories during post-learning sleep. Intensifying neocortical slow oscillations (the hallmark of slow wave sleep (SWS)) by electrical or auditory stimulation and modulating specific neurotransmitters such as noradrenaline and glutamate likewise facilitates memory processing during sleep. With this evidence in mind, this article concludes by discussing different methodological caveats and ethical issues that should be considered when thinking about using sleep for cognitive enhancement in everyday applications.

Sleep for cognitive enhancement

PubMed Central

Diekelmann, Susanne

2014-01-01

Sleep is essential for effective cognitive functioning. Loosing even a few hours of sleep can have detrimental effects on a wide variety of cognitive processes such as attention, language, reasoning, decision making, learning and memory. While sleep is necessary to ensure normal healthy cognitive functioning, it can also enhance performance beyond the boundaries of the normal condition. This article discusses the enhancing potential of sleep, mainly focusing on the domain of learning and memory. Sleep is known to facilitate the consolidation of memories learned before sleep as well as the acquisition of new memories to be learned after sleep. According to a widely held model this beneficial effect of sleep relies on the neuronal reactivation of memories during sleep that is associated with sleep-specific brain oscillations (slow oscillations, spindles, ripples) as well as a characteristic neurotransmitter milieu. Recent research indicates that memory processing during sleep can be boosted by (i) cueing memory reactivation during sleep; (ii) stimulating sleep-specific brain oscillations; and (iii) targeting specific neurotransmitter systems pharmacologically. Olfactory and auditory cues can be used, for example, to increase reactivation of associated memories during post-learning sleep. Intensifying neocortical slow oscillations (the hallmark of slow wave sleep (SWS)) by electrical or auditory stimulation and modulating specific neurotransmitters such as noradrenaline and glutamate likewise facilitates memory processing during sleep. With this evidence in mind, this article concludes by discussing different methodological caveats and ethical issues that should be considered when thinking about using sleep for cognitive enhancement in everyday applications. PMID:24765066

High spectral purity Kerr frequency comb radio frequency photonic oscillator

PubMed Central

Liang, W.; Eliyahu, D.; Ilchenko, V. S.; Savchenkov, A. A.; Matsko, A. B.; Seidel, D.; Maleki, L.

2015-01-01

Femtosecond laser-based generation of radio frequency signals has produced astonishing improvements in achievable spectral purity, one of the basic features characterizing the performance of an radio frequency oscillator. Kerr frequency combs hold promise for transforming these lab-scale oscillators to chip-scale level. In this work we demonstrate a miniature 10 GHz radio frequency photonic oscillator characterized with phase noise better than −60 dBc Hz−1 at 10 Hz, −90 dBc Hz−1 at 100 Hz and −170 dBc Hz−1 at 10 MHz. The frequency stability of this device, as represented by Allan deviation measurements, is at the level of 10−10 at 1–100 s integration time—orders of magnitude better than existing radio frequency photonic devices of similar size, weight and power consumption. PMID:26260955

High frequency oscillations in brain hemodynamic response

NASA Astrophysics Data System (ADS)

Akin, Ata; Bolay, Hayrunnisa

2007-07-01

Tight autoregulation of vessel tone guarantees proper delivery of nutrients to the tissues. This regulation is maintained at a more delicate level in the brain since any decrease in the supply of glucose and oxygen to neuronal tissues might lead to unrecoverable injury. Functional near infrared spectroscopy has been proposed as a new tool to monitor the cerebrovascular response during cognitive activity. We have observed that during a Stroop task three distinct oscillatory patterns govern the control of the cerebrovascular reactivity: very low frequency (0.02-0.05 Hz), low frequency (0.08-0.12 Hz) and high frequency (0.12-0.18 Hz). High frequency oscillations have been shown to be related to stress level of the subjects. Our findings indicate that as the stress level is increased so does the energy of the high frequency component indicating a higher stimulation from the autonomic nervous system.

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.

Short bouts of vocalization induce long lasting fast gamma oscillations in a sensorimotor nucleus

PubMed Central

Lewandowski, Brian; Schmidt, Marc

2011-01-01

Performance evaluation is a critical feature of motor learning. In the vocal system, it requires the integration of auditory feedback signals with vocal motor commands. The network activity that supports such integration is unknown, but it has been proposed that vocal performance evaluation occurs offline. Recording from NIf, a sensorimotor structure in the avian song system, we show that short bouts of singing in adult male zebra finches (Taeniopygia guttata) induce persistent increases in firing activity and coherent oscillations in the fast gamma range (90–150 Hz). Single units are strongly phase-locked to these oscillations, which can last up to 30 s, often outlasting vocal activity by an order of magnitude. In other systems, oscillations often are triggered by events or behavioral tasks but rarely outlast the event that triggered them by more than 1 second. The present observations are the longest reported gamma oscillations triggered by an isolated behavioral event. In mammals, gamma oscillations have been associated with memory consolidation and are hypothesized to facilitate communication between brain regions. We suggest that the timing and persistent nature of NIf’s fast gamma oscillations make them well suited to facilitate the integration of auditory and vocal motor traces associated with vocal performance evaluation. PMID:21957255

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

Brain Oscillations Elicited by the Cold Pressor Test: A Putative Index of Untreated Essential Hypertension.

PubMed

Papageorgiou, Christos; Manios, Efstathios; Tsaltas, Eleftheria; Koroboki, Eleni; Alevizaki, Maria; Angelopoulos, Elias; Dimopoulos, Meletios-Athanasios; Papageorgiou, Charalabos; Zakopoulos, Nikolaos

2017-01-01

Essential hypertension is associated with reduced pain sensitivity of unclear aetiology. This study explores this issue using the Cold Pressor Test (CPT), a reliable pain/stress model, comparing CPT-related EEG activity in first episode hypertensives and controls. 22 untreated hypertensives and 18 matched normotensives underwent 24-hour ambulatory blood pressure monitoring (ABPM). EEG recordings were taken before, during, and after CPT exposure. Significant group differences in CPT-induced EEG oscillations were covaried with the most robust cardiovascular differentiators by means of a Canonical Analysis. Positive correlations were noted between ABPM variables and Delta (1-4 Hz) oscillations during the tolerance phase; in high-alpha (10-12 Hz) oscillations during the stress unit and posttest phase; and in low-alpha (8-10 Hz) oscillations during CPT phases overall. Negative correlations were found between ABPM variables and Beta2 oscillations (16.5-20 Hz) during the posttest phase and Gamma (28.5-45 Hz) oscillations during the CPT phases overall. These relationships were localised at several sites across the cerebral hemispheres with predominance in the right hemisphere and left frontal lobe. These findings provide a starting point for increasing our understanding of the complex relationships between cerebral activation and cardiovascular functioning involved in regulating blood pressure changes.

Oscillatory encoding of visual stimulus familiarity.

PubMed

Kissinger, Samuel T; Pak, Alexandr; Tang, Yu; Masmanidis, Sotiris C; Chubykin, Alexander A

2018-06-18

Familiarity of the environment changes the way we perceive and encode incoming information. However, the neural substrates underlying this phenomenon are poorly understood. Here we describe a new form of experience-dependent low frequency oscillations in the primary visual cortex (V1) of awake adult male mice. The oscillations emerged in visually evoked potentials (VEPs) and single-unit activity following repeated visual stimulation. The oscillations were sensitive to the spatial frequency content of a visual stimulus and required the muscarinic acetylcholine receptors (mAChRs) for their induction and expression. Finally, ongoing visually evoked theta (4-6 Hz) oscillations boost the VEP amplitude of incoming visual stimuli if the stimuli are presented at the high excitability phase of the oscillations. Our results demonstrate that an oscillatory code can be used to encode familiarity and serves as a gate for oncoming sensory inputs. Significance Statement. Previous experience can influence the processing of incoming sensory information by the brain and alter perception. However, the mechanistic understanding of how this process takes place is lacking. We have discovered that persistent low frequency oscillations in the primary visual cortex encode information about familiarity and the spatial frequency of the stimulus. These familiarity evoked oscillations influence neuronal responses to the oncoming stimuli in a way that depends on the oscillation phase. Our work demonstrates a new mechanism of visual stimulus feature detection and learning. Copyright © 2018 the authors.

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

PubMed Central

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

2011-01-01

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

Mind over chatter: plastic up-regulation of the fMRI salience network directly after EEG neurofeedback

PubMed Central

Ros, Tomas; Théberge, Jean; Frewen, Paul A.; Kluetsch, Rosemarie; Densmore, Maria; Calhoun, Vince D.; Lanius, Ruth A.

2016-01-01

Neurofeedback (NFB) involves a brain-computer interface that allows users to learn to voluntarily control their cortical oscillations, reflected in the electroencephalogram (EEG). Although NFB is being pioneered as a noninvasive tool for treating brain disorders, there is insufficient evidence on the mechanism of its impact on brain function. Furthermore, the dominant rhythm of the human brain is the alpha oscillation (8–12 Hz), yet its behavioral significance remains multifaceted and largely correlative. In this study with 34 healthy participants, we examined whether during the performance of an attentional task, the functional connectivity of distinct fMRI networks would be plastically altered after a 30-min session of voluntary reduction of alpha rhythm (n=17) versus a sham-feedback condition (n=17). We reveal that compared to sham-feedback, NFB induced an increase of connectivity within the salience network (dorsal anterior cingulate focus), which was detectable 30 minutes after termination of training. This increase in connectivity was negatively correlated with changes in 'on-task' mind-wandering as well as resting state alpha rhythm. Crucially, there was a causal dependence between alpha rhythm modulations during NFB and at subsequent resting state, not exhibited by the sham group. Our findings provide neurobehavioral evidence for a temporally direct, plastic impact of NFB on a key cognitive control network of the brain, suggesting a promising basis for its use to treat cognitive disorders under physiological conditions. PMID:23022326

DNA microarray unravels rapid changes in transcriptome of MK-801 treated rat brain

PubMed Central

Kobayashi, Yuka; Kulikova, Sofya P; Shibato, Junko; Rakwal, Randeep; Satoh, Hiroyuki; Pinault, Didier; Masuo, Yoshinori

2015-01-01

AIM: To investigate the impact of MK-801 on gene expression patterns genome wide in rat brain regions. METHODS: Rats were treated with an intraperitoneal injection of MK-801 [0.08 (low-dose) and 0.16 (high-dose) mg/kg] or NaCl (vehicle control). In a first series of experiment, the frontoparietal electrocorticogram was recorded 15 min before and 60 min after injection. In a second series of experiments, the whole brain of each animal was rapidly removed at 40 min post-injection, and different regions were separated: amygdala, cerebral cortex, hippocampus, hypothalamus, midbrain and ventral striatum on ice followed by DNA microarray (4 × 44 K whole rat genome chip) analysis. RESULTS: Spectral analysis revealed that a single systemic injection of MK-801 significantly and selectively augmented the power of baseline gamma frequency (30-80 Hz) oscillations in the frontoparietal electroencephalogram. DNA microarray analysis showed the largest number (up- and down- regulations) of gene expressions in the cerebral cortex (378), midbrain (376), hippocampus (375), ventral striatum (353), amygdala (301), and hypothalamus (201) under low-dose (0.08 mg/kg) of MK-801. Under high-dose (0.16 mg/kg), ventral striatum (811) showed the largest number of gene expression changes. Gene expression changes were functionally categorized to reveal expression of genes and function varies with each brain region. CONCLUSION: Acute MK-801 treatment increases synchrony of baseline gamma oscillations, and causes very early changes in gene expressions in six individual rat brain regions, a first report. PMID:26629322

Low frequency steady-state brain responses modulate large scale functional networks in a frequency-specific means.

PubMed

Wang, Yi-Feng; Long, Zhiliang; Cui, Qian; Liu, Feng; Jing, Xiu-Juan; Chen, Heng; Guo, Xiao-Nan; Yan, Jin H; Chen, Hua-Fu

2016-01-01

Neural oscillations are essential for brain functions. Research has suggested that the frequency of neural oscillations is lower for more integrative and remote communications. In this vein, some resting-state studies have suggested that large scale networks function in the very low frequency range (<1 Hz). However, it is difficult to determine the frequency characteristics of brain networks because both resting-state studies and conventional frequency tagging approaches cannot simultaneously capture multiple large scale networks in controllable cognitive activities. In this preliminary study, we aimed to examine whether large scale networks can be modulated by task-induced low frequency steady-state brain responses (lfSSBRs) in a frequency-specific pattern. In a revised attention network test, the lfSSBRs were evoked in the triple network system and sensory-motor system, indicating that large scale networks can be modulated in a frequency tagging way. Furthermore, the inter- and intranetwork synchronizations as well as coherence were increased at the fundamental frequency and the first harmonic rather than at other frequency bands, indicating a frequency-specific modulation of information communication. However, there was no difference among attention conditions, indicating that lfSSBRs modulate the general attention state much stronger than distinguishing attention conditions. This study provides insights into the advantage and mechanism of lfSSBRs. More importantly, it paves a new way to investigate frequency-specific large scale brain activities. © 2015 Wiley Periodicals, Inc.

Human EEG gamma oscillations in neuropsychiatric disorders.

PubMed

Herrmann, C S; Demiralp, T

2005-12-01

Due to their small amplitude, the importance of high-frequency EEG oscillations with respect to cognitive functions and disorders is often underestimated as compared to slower oscillations. This article reviews the literature on the alterations of gamma oscillations (about 30-80 Hz) during the course of neuropsychiatric disorders and relates them to a model for the functional role of these oscillations for memory matching. The synchronous firing of neurons in the gamma-band has been proposed to bind multiple features of an object, which are coded in a distributed manner in the brain, and is modulated by cognitive processes such as attention and memory. In certain neuropsychiatric disorders the gamma activity shows significant changes. In schizophrenic patients, negative symptoms correlate with a decrease of gamma responses, whereas a significant increase in gamma amplitudes is observed during positive symptoms such as hallucinations. A reduction is also observed in Alzheimer's Disease (AD), whereas an increase is found in epileptic patients, probably reflecting both cortical excitation and perceptual distortions such as déjà vu phenomena frequently observed in epilepsy. ADHD patients also exhibit increased gamma amplitudes. A hypothesis of a gamma axis of these disorders mainly based on the significance of gamma oscillations for memory matching is formulated.

Metabolic modulation of neuronal gamma-band oscillations.

PubMed

Vodovozov, Wadim; Schneider, Justus; Elzoheiry, Shehabeldin; Hollnagel, Jan-Oliver; Lewen, Andrea; Kann, Oliver

2018-05-28

Gamma oscillations (30-100 Hz) represent a physiological fast brain rhythm that occurs in many cortex areas in awake mammals, including humans. They associate with sensory perception, voluntary movement, and memory formation and require precise synaptic transmission between excitatory glutamatergic neurons and inhibitory GABAergic interneurons such as parvalbumin-positive basket cells. Notably, gamma oscillations are exquisitely sensitive to shortage in glucose and oxygen supply (metabolic stress), with devastating consequences for higher cognitive functions. Herein, we explored the robustness of gamma oscillations against changes in the availability of alternative energy substrates and amino acids, which is partially regulated by glial cells such as astrocytes. We used organotypic slice cultures of the rat hippocampus expressing acetylcholine-induced persistent gamma oscillations under normoxic recording conditions (20% oxygen fraction). Our main findings are (1) partial substitution of glucose with pyruvate and the ketone body β-hydroxybutyrate increases the frequency of gamma oscillations, even at different stages of neuronal tissue development. (2) Supplementation with the astrocytic neurotransmitter precursor glutamine has no effect on the properties of gamma oscillations. (3) Supplementation with glycine increases power, frequency, and inner coherence of gamma oscillations in a dose-dependent manner. (4) During these treatments switches to other frequency bands or pathological network states such as neural burst firing or synchronized epileptic activity are absent. Our study indicates that cholinergic gamma oscillations show general robustness against these changes in nutrient and amino acid composition of the cerebrospinal fluid; however, modulation of their properties may impact on cortical information processing under physiological and pathophysiological conditions.

Selective Coupling between Theta Phase and Neocortical Fast Gamma Oscillations during REM-Sleep in Mice

PubMed Central

Scheffzük, Claudia; Kukushka, Valeriy I.; Vyssotski, Alexei L.; Draguhn, Andreas

2011-01-01

Background The mammalian brain expresses a wide range of state-dependent network oscillations which vary in frequency and spatial extension. Such rhythms can entrain multiple neurons into coherent patterns of activity, consistent with a role in behaviour, cognition and memory formation. Recent evidence suggests that locally generated fast network oscillations can be systematically aligned to long-range slow oscillations. It is likely that such cross-frequency coupling supports specific tasks including behavioural choice and working memory. Principal Findings We analyzed temporal coupling between high-frequency oscillations and EEG theta activity (4–12 Hz) in recordings from mouse parietal neocortex. Theta was exclusively present during active wakefulness and REM-sleep. Fast oscillations occurred in two separate frequency bands: gamma (40–100 Hz) and fast gamma (120–160 Hz). Theta, gamma and fast gamma were more prominent during active wakefulness as compared to REM-sleep. Coupling between theta and the two types of fast oscillations, however, was more pronounced during REM-sleep. This state-dependent cross-frequency coupling was particularly strong for theta-fast gamma interaction which increased 9-fold during REM as compared to active wakefulness. Theta-gamma coupling increased only by 1.5-fold. Significance State-dependent cross-frequency-coupling provides a new functional characteristic of REM-sleep and establishes a unique property of neocortical fast gamma oscillations. Interactions between defined patterns of slow and fast network oscillations may serve selective functions in sleep-dependent information processing. PMID:22163023

On parasupersymmetric oscillators and relativistic vector mesons in constant magnetic fields

NASA Technical Reports Server (NTRS)

Debergh, Nathalie; Beckers, Jules

1995-01-01

Johnson-Lippmann considerations on oscillators and their connection with the minimal coupling schemes are visited in order to introduce a new Sakata-Taketani equation describing vector mesons in interaction with a constant magnetic field. This new proposal, based on a specific parasupersymmetric oscillator-like system, is characterized by real energies as opposed to previously pointed out relativistic equations corresponding to this interacting context.

Improved Band-to-Band Registration Characterization for VIIRS Reflective Solar Bands Based on Lunar Observations

NASA Technical Reports Server (NTRS)

Wang, Zhipeng; Xiong, Xiaoxiong; Li, Yonghong

2015-01-01

Spectral bands of the Visible Infrared Imaging Radiometer Suite (VIIRS) instrumentaboard the Suomi National Polar-orbiting Partnership (S-NPP) satellite are spatially co-registered.The accuracy of the band-to-band registration (BBR) is one of the key spatial parameters that must becharacterized. Unlike its predecessor, the Moderate Resolution Imaging Spectroradiometer (MODIS), VIIRS has no on-board calibrator specifically designed to perform on-orbit BBR characterization.To circumvent this problem, a BBR characterization method for VIIRS reflective solar bands (RSB) based on regularly-acquired lunar images has been developed. While its results can satisfactorily demonstrate that the long-term stability of the BBR is well within +/- 0.1 moderate resolution bandpixels, undesired seasonal oscillations have been observed in the trending. The oscillations are most obvious between the visiblenear-infrared bands and short-middle wave infrared bands. This paper investigates the oscillations and identifies their cause as the band spectral dependence of the centroid position and the seasonal rotation of the lunar images over calibration events. Accordingly, an improved algorithm is proposed to quantify the rotation and compensate for its impact. After the correction, the seasonal oscillation in the resulting BBR is reduced from up to 0.05 moderate resolution band pixels to around 0.01 moderate resolution band pixels. After removing this spurious seasonal oscillation, the BBR, as well as its long-term drift are well determined.

A fully integrated oven controlled microelectromechanical oscillator – Part II. Characterization and measurement

DOE PAGES

Wojciechowski, Kenneth E.; Olsson, Roy H.

2015-06-24

Our paper reports the measurement and characterization of a fully integrated oven controlled microelectromechanical oscillator (OCMO). The OCMO takes advantage of high thermal isolation and monolithic integration of both aluminum nitride (AlN) micromechanical resonators and electronic circuitry to thermally stabilize or ovenize all the components that comprise an oscillator. Operation at microscale sizes allows implementation of high thermal resistance platform supports that enable thermal stabilization at very low-power levels when compared with the state-of-the-art oven controlled crystal oscillators. A prototype OCMO has been demonstrated with a measured temperature stability of -1.2 ppb/°C, over the commercial temperature range while using tensmore » of milliwatts of supply power and with a volume of 2.3 mm 3 (not including the printed circuit board-based thermal control loop). Additionally, due to its small thermal time constant, the thermal compensation loop can maintain stability during fast thermal transients (>10 °C/min). This new technology has resulted in a new paradigm in terms of power, size, and warm up time for high thermal stability oscillators.« less

Oscillation patterns are enhanced and firing threshold is lowered in medullary respiratory neuron discharges by threshold doses of a μ-opioid receptor agonist

PubMed Central

Mifflin, Steve W.

2017-01-01

μ-Opioid receptors are distributed widely in the brain stem respiratory network, and opioids with selectivity for μ-type receptors slow in vivo respiratory rhythm in lowest effective doses. Several studies have reported μ-opioid receptor effects on the three-phase rhythm of respiratory neurons, but there are until now no reports of opioid effects on oscillatory activity within respiratory discharges. In this study, effects of the μ-opioid receptor agonist fentanyl on spike train discharge properties of several different types of rhythm-modulating medullary respiratory neuron discharges were analyzed. Doses of fentanyl that were just sufficient for prolongation of discharges and slowing of the three-phase respiratory rhythm also produced pronounced enhancement of spike train properties. Oscillation and burst patterns detected by autocorrelation measurements were greatly enhanced, and interspike intervals were prolonged. Spike train properties under control conditions and after fentanyl were uniform within each experiment, but varied considerably between experiments, which might be related to variability in acid-base balance in the brain stem extracellular fluid. Discharge threshold was shifted to more negative levels of membrane potential. The effects on threshold are postulated to result from opioid-mediated disinhibition and postsynaptic enhancement of N-methyl-d- aspartate receptor current. Lowering of firing threshold, enhancement of spike train oscillations and bursts and prolongation of discharges by lowest effective doses of fentanyl could represent compensatory adjustments in the brain stem respiratory network to override opioid blunting of CO2/pH chemosensitivity. PMID:28202437

Expectancy for food or expectancy for chocolate reveals timing systems for metabolism and reward.

PubMed

Angeles-Castellanos, M; Salgado-Delgado, R; Rodríguez, K; Buijs, R M; Escobar, C

2008-07-31

The clock gene protein Per 1 (PER1) is expressed in several brain structures and oscillates associated with the suprachiasmatic nucleus (SCN). Restricted feeding schedules (RFS) induce anticipatory activity and impose daily oscillations of c-Fos and clock proteins in brain structures. Daily access to a palatable treat (chocolate) also elicits anticipatory activity and induces c-Fos expression mainly in corticolimbic structures. Here the influence of daily access to food or chocolate was explored by the analysis of the oscillatory patterns of PER1 in hypothalamic and corticolimbic structures. Wistar rats were exposed to RFS or to daily access to chocolate for 3 weeks. Persistence of food or chocolate entrained rhythms was determined 8 days after cessation of the feeding protocols. RFS and chocolate induced a phase shift in PER1 rhythmicity in corticolimbic structures with peak values at zeitgeber time 12 and a higher amplitude in the chocolate group. Both RFS and chocolate groups showed an upregulation of PER1 in the SCN. Food and chocolate entrained rhythms persisted for 8 days in behavior and in PER1 expression in the dorsomedial hypothalamic nucleus, accumbens, prefrontal cortex and central amygdala. The present data demonstrate the existence of different oscillatory systems in the brain that can be activated by entrainment to metabolic stimuli or to reward and suggest the participation of PER1 in both entraining pathways. Persistence and amplification of PER1 oscillations in structures associated with reward suggest that this oscillatory process is fundamental to food addictive behavior.

Oscillation patterns are enhanced and firing threshold is lowered in medullary respiratory neuron discharges by threshold doses of a μ-opioid receptor agonist.

PubMed

Lalley, Peter M; Mifflin, Steve W

2017-05-01

μ-Opioid receptors are distributed widely in the brain stem respiratory network, and opioids with selectivity for μ-type receptors slow in vivo respiratory rhythm in lowest effective doses. Several studies have reported μ-opioid receptor effects on the three-phase rhythm of respiratory neurons, but there are until now no reports of opioid effects on oscillatory activity within respiratory discharges. In this study, effects of the μ-opioid receptor agonist fentanyl on spike train discharge properties of several different types of rhythm-modulating medullary respiratory neuron discharges were analyzed. Doses of fentanyl that were just sufficient for prolongation of discharges and slowing of the three-phase respiratory rhythm also produced pronounced enhancement of spike train properties. Oscillation and burst patterns detected by autocorrelation measurements were greatly enhanced, and interspike intervals were prolonged. Spike train properties under control conditions and after fentanyl were uniform within each experiment, but varied considerably between experiments, which might be related to variability in acid-base balance in the brain stem extracellular fluid. Discharge threshold was shifted to more negative levels of membrane potential. The effects on threshold are postulated to result from opioid-mediated disinhibition and postsynaptic enhancement of N -methyl-d- aspartate receptor current. Lowering of firing threshold, enhancement of spike train oscillations and bursts and prolongation of discharges by lowest effective doses of fentanyl could represent compensatory adjustments in the brain stem respiratory network to override opioid blunting of CO 2 /pH chemosensitivity. Copyright © 2017 the American Physiological Society.

Chemical event chain model of coupled genetic oscillators.

PubMed

Jörg, David J; Morelli, Luis G; Jülicher, Frank

2018-03-01

We introduce a stochastic model of coupled genetic oscillators in which chains of chemical events involved in gene regulation and expression are represented as sequences of Poisson processes. We characterize steady states by their frequency, their quality factor, and their synchrony by the oscillator cross correlation. The steady state is determined by coupling and exhibits stochastic transitions between different modes. The interplay of stochasticity and nonlinearity leads to isolated regions in parameter space in which the coupled system works best as a biological pacemaker. Key features of the stochastic oscillations can be captured by an effective model for phase oscillators that are coupled by signals with distributed delays.

Chemical event chain model of coupled genetic oscillators

NASA Astrophysics Data System (ADS)

Jörg, David J.; Morelli, Luis G.; Jülicher, Frank

2018-03-01

We introduce a stochastic model of coupled genetic oscillators in which chains of chemical events involved in gene regulation and expression are represented as sequences of Poisson processes. We characterize steady states by their frequency, their quality factor, and their synchrony by the oscillator cross correlation. The steady state is determined by coupling and exhibits stochastic transitions between different modes. The interplay of stochasticity and nonlinearity leads to isolated regions in parameter space in which the coupled system works best as a biological pacemaker. Key features of the stochastic oscillations can be captured by an effective model for phase oscillators that are coupled by signals with distributed delays.

Multimode and multistate ladder oscillator and frequency recognition device

NASA Technical Reports Server (NTRS)

Aumann, Herbert M. (Inventor)

1976-01-01

A ladder oscillator composed of capacitive and inductive impedances connected together to form a ladder network which has a chosen number N oscillation modes at N different frequencies. Each oscillation mode is characterized by a unique standing wave voltage pattern along the nodes of the ladder oscillator, with the mode in which the ladder oscillator is oscillating being determinable from the amplitudes or phase of the oscillations at the nodes. A logic circuit may be connected to the nodes of the oscillator to compare the phases of selected nodes and thereby determine which mode the oscillator is oscillating in. A ladder oscillator composed of passive capacitive and inductive impedances can be utilized as a frequency recognition device, since the passive ladder oscillator will display the characteristic standing wave patterns if an input signal impressed upon the ladder oscillator is close to one of the mode frequencies of the oscillator. A CL ladder oscillator having series capacitive impedances and shunt inductive impedances can exhibit sustained and autonomous oscillations if active nonlinear devices are connected in parallel with the shunt inductive impedances. The active CL ladder oscillator can be synchronized to input frequencies impressed upon the oscillator, and will continue to oscillate after the input signal has been removed at a mode frequency which is, in general, nearest to the input signal frequency. Autonomous oscillations may also be obtained as desired from the active CL ladder oscillator at the mode frequencies.

Cortical thickness as a contributor to abnormal oscillations in schizophrenia?☆

PubMed Central

Edgar, J. Christopher; Chen, Yu-Han; Lanza, Matthew; Howell, Breannan; Chow, Vivian Y.; Heiken, Kory; Liu, Song; Wootton, Cassandra; Hunter, Michael A.; Huang, Mingxiong; Miller, Gregory A.; Cañive, José M.

2013-01-01

Introduction Although brain rhythms depend on brain structure (e.g., gray and white matter), to our knowledge associations between brain oscillations and structure have not been investigated in healthy controls (HC) or in individuals with schizophrenia (SZ). Observing function–structure relationships, for example establishing an association between brain oscillations (defined in terms of amplitude or phase) and cortical gray matter, might inform models on the origins of psychosis. Given evidence of functional and structural abnormalities in primary/secondary auditory regions in SZ, the present study examined how superior temporal gyrus (STG) structure relates to auditory STG low-frequency and 40 Hz steady-state activity. Given changes in brain activity as a function of age, age-related associations in STG oscillatory activity were also examined. Methods Thirty-nine individuals with SZ and 29 HC were recruited. 40 Hz amplitude-modulated tones of 1 s duration were presented. MEG and T1-weighted sMRI data were obtained. Using the sources localizing 40 Hz evoked steady-state activity (300 to 950 ms), left and right STG total power and inter-trial coherence were computed. Time–frequency group differences and associations with STG structure and age were also examined. Results Decreased total power and inter-trial coherence in SZ were observed in the left STG for initial post-stimulus low-frequency activity (~ 50 to 200 ms, ~ 4 to 16 Hz) as well as 40 Hz steady-state activity (~ 400 to 1000 ms). Left STG 40 Hz total power and inter-trial coherence were positively associated with left STG cortical thickness in HC, not in SZ. Left STG post-stimulus low-frequency and 40 Hz total power were positively associated with age, again only in controls. Discussion Left STG low-frequency and steady-state gamma abnormalities distinguish SZ and HC. Disease-associated damage to STG gray matter in schizophrenia may disrupt the age-related left STG gamma-band function–structure relationships observed in controls. PMID:24371794

Analysis of the role of the low threshold currents IT and Ih in intrinsic delta oscillations of thalamocortical neurons

PubMed Central

Amarillo, Yimy; Mato, Germán; Nadal, Marcela S.

2015-01-01

Thalamocortical neurons are involved in the generation and maintenance of brain rhythms associated with global functional states. The repetitive burst firing of TC neurons at delta frequencies (1–4 Hz) has been linked to the oscillations recorded during deep sleep and during episodes of absence seizures. To get insight into the biophysical properties that are the basis for intrinsic delta oscillations in these neurons, we performed a bifurcation analysis of a minimal conductance-based thalamocortical neuron model including only the IT channel and the sodium and potassium leak channels. This analysis unveils the dynamics of repetitive burst firing of TC neurons, and describes how the interplay between the amplifying variable mT and the recovering variable hT of the calcium channel IT is sufficient to generate low threshold oscillations in the delta band. We also explored the role of the hyperpolarization activated cationic current Ih in this reduced model and determine that, albeit not required, Ih amplifies and stabilizes the oscillation. PMID:25999847

Alterations of cortical GABA neurons and network oscillations in schizophrenia.

PubMed

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

2010-08-01

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

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

PubMed Central

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

2016-01-01

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

Neuron Bifurcations in an Analog Electronic Burster

NASA Astrophysics Data System (ADS)

Savino, Guillermo V.; Formigli, Carlos M.

2007-05-01

Although bursting electrical activity is typical in some brain neurons and biological excitable systems, its functions and mechanisms of generation are yet unknown. In modeling such complex oscillations, analog electronic models are faster than mathematical ones, whether phenomenologically or theoretically based. We show experimentally that bursting oscillator circuits can be greatly simplified by using the nonlinear characteristics of two bipolar transistors. Since our circuit qualitatively mimics Hodgkin and Huxley model neurons bursting activity, and bifurcations originating neuro-computational properties, it is not only a caricature but a realistic model.

Chaos in Atomic Force Microscopy

NASA Astrophysics Data System (ADS)

Hu, Shuiqing; Raman, Arvind

2006-01-01

Chaotic oscillations of microcantilever tips in dynamic atomic force microscopy (AFM) are reported and characterized. Systematic experiments performed using a variety of microcantilevers under a wide range of operating conditions indicate that softer AFM microcantilevers bifurcate from periodic to chaotic oscillations near the transition from the noncontact to the tapping regimes. Careful Lyapunov exponent and noise titration calculations of the tip oscillation data confirm their chaotic nature. AFM images taken by scanning the chaotically oscillating tips over the sample show small, but significant metrology errors at the nanoscale due to this “deterministic” uncertainty.

Condensed-matter physics: Marching to a different quantum beat

NASA Astrophysics Data System (ADS)

Nayak, Chetan

2017-03-01

Periodic oscillations are common in nature but they generally decay or fall out of phase. Two experiments have found evidence for a Floquet time crystal, which is characterized by persistent in-phase oscillations. See Letters p.217 & p. 221

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

Resting State EEG in Children With Learning Disabilities: An Independent Component Analysis Approach.

PubMed

Jäncke, Lutz; Alahmadi, Nsreen

2016-01-01

In this study, the neurophysiological underpinnings of learning disabilities (LD) in children are examined using resting state EEG. We were particularly interested in the neurophysiological differences between children with learning disabilities not otherwise specified (LD-NOS), learning disabilities with verbal disabilities (LD-Verbal), and healthy control (HC) children. We applied 2 different approaches to examine the differences between the different groups. First, we calculated theta/beta and theta/alpha ratios in order to quantify the relationship between slow and fast EEG oscillations. Second, we used a recently developed method for analyzing spectral EEG, namely the group independent component analysis (gICA) model. Using these measures, we identified substantial differences between LD and HC children and between LD-NOS and LD-Verbal children in terms of their spectral EEG profiles. We obtained the following findings: (a) theta/beta and theta/alpha ratios were substantially larger in LD than in HC children, with no difference between LD-NOS and LD-Verbal children; (b) there was substantial slowing of EEG oscillations, especially for gICs located in frontal scalp positions, with LD-NOS children demonstrating the strongest slowing; (c) the estimated intracortical sources of these gICs were mostly located in brain areas involved in the control of executive functions, attention, planning, and language; and (d) the LD-Verbal children demonstrated substantial differences in EEG oscillations compared with LD-NOS children, and these differences were localized in language-related brain areas. The general pattern of atypical neurophysiological activation found in LD children suggests that they suffer from neurophysiological dysfunction in brain areas involved with the control of attention, executive functions, planning, and language functions. LD-Verbal children also demonstrate atypical activation, especially in language-related brain areas. These atypical neurophysiological activation patterns might provide a helpful guide for rehabilitation strategies to treat the deficiencies in these children with LD. © EEG and Clinical Neuroscience Society (ECNS) 2015.

Nonsinusoidal Beta Oscillations Reflect Cortical Pathophysiology in Parkinson's Disease.

PubMed

Cole, Scott R; van der Meij, Roemer; Peterson, Erik J; de Hemptinne, Coralie; Starr, Philip A; Voytek, Bradley

2017-05-03

Oscillations in neural activity play a critical role in neural computation and communication. There is intriguing new evidence that the nonsinusoidal features of the oscillatory waveforms may inform underlying physiological and pathophysiological characteristics. Time-domain waveform analysis approaches stand in contrast to traditional Fourier-based methods, which alter or destroy subtle waveform features. Recently, it has been shown that the waveform features of oscillatory beta (13-30 Hz) events, a prominent motor cortical oscillation, may reflect near-synchronous excitatory synaptic inputs onto cortical pyramidal neurons. Here we analyze data from invasive human primary motor cortex (M1) recordings from patients with Parkinson's disease (PD) implanted with a deep brain stimulator (DBS) to test the hypothesis that the beta waveform becomes less sharp with DBS, suggesting that M1 input synchrony may be decreased. We find that, in PD, M1 beta oscillations have sharp, asymmetric, nonsinusoidal features, specifically asymmetries in the ratio between the sharpness of the beta peaks compared with the troughs. This waveform feature is nearly perfectly correlated with beta-high gamma phase-amplitude coupling ( r = 0.94), a neural index previously shown to track PD-related motor deficit. Our results suggest that the pathophysiological beta generator is altered by DBS, smoothing out the beta waveform. This has implications not only for the interpretation of the physiological mechanism by which DBS reduces PD-related motor symptoms, but more broadly for our analytic toolkit in general. That is, the often-overlooked time-domain features of oscillatory waveforms may carry critical physiological information about neural processes and dynamics. SIGNIFICANCE STATEMENT To better understand the neural basis of cognition and disease, we need to understand how groups of neurons interact to communicate with one another. For example, there is evidence that parkinsonian bradykinesia and rigidity may arise from an oversynchronization of afferents to the motor cortex, and that these symptoms are treatable using deep brain stimulation. Here we show that the waveform shape of beta (13-30 Hz) oscillations, which may reflect input synchrony onto the cortex, is altered by deep brain stimulation. This suggests that mechanistic inferences regarding physiological and pathophysiological neural communication may be made from the temporal dynamics of oscillatory waveform shape. Copyright © 2017 the authors 0270-6474/17/374830-11$15.00/0.

Consciousness and arousal effects on emotional face processing as revealed by brain oscillations. A gamma band analysis.

PubMed

Balconi, Michela; Lucchiari, Claudio

2008-01-01

It remains an open question whether it is possible to assign a single brain operation or psychological function for facial emotion decoding to a certain type of oscillatory activity. Gamma band activity (GBA) offers an adequate tool for studying cortical activation patterns during emotional face information processing. In the present study brain oscillations were analyzed in response to facial expression of emotions. Specifically, GBA modulation was measured when twenty subjects looked at emotional (angry, fearful, happy, and sad faces) or neutral faces in two different conditions: supraliminal (10 ms) vs subliminal (150 ms) stimulation (100 target-mask pairs for each condition). The results showed that both consciousness and significance of the stimulus in terms of arousal can modulate the power synchronization (ERD decrease) during 150-350 time range: an early oscillatory event showed its peak at about 200 ms post-stimulus. GBA was enhanced by supraliminal more than subliminal elaboration, as well as more by high arousal (anger and fear) than low arousal (happiness and sadness) emotions. Finally a left-posterior dominance for conscious elaboration was found, whereas right hemisphere was discriminant in emotional processing of face in comparison with neutral face.

D1 and D2 antagonists reverse the effects of appetite suppressants on weight loss, food intake, locomotion, and rebalance spiking inhibition in the rat NAc shell

PubMed Central

Kalyanasundar, B.; Perez, Claudia I.; Luna, Alvaro; Solorio, Jessica; Moreno, Mario G.; Elias, David; Simon, Sidney A.

2015-01-01

Obesity is a worldwide health problem that has reached epidemic proportions. To ameliorate this problem, one approach is the use of appetite suppressants. These compounds are frequently amphetamine congeners such as diethylpropion (DEP), phentermine (PHEN), and bupropion (BUP), whose effects are mediated through serotonin, norepinephrine, and dopaminergic pathways. The nucleus accumbens (NAc) shell receives dopaminergic inputs and is involved in feeding and motor activity. However, little is known about how appetite suppressants modulate its activity. Therefore, we characterized behavioral and neuronal NAc shell responses to short-term treatments of DEP, PHEN, and BUP. These compounds caused a transient decrease in weight and food intake while increasing locomotion, stereotypy, and insomnia. They evoked a large inhibitory imbalance in NAc shell spiking activity that correlated with the onset of locomotion and stereotypy. Analysis of the local field potentials (LFPs) showed that all three drugs modulated beta, theta, and delta oscillations. These oscillations do not reflect an aversive-malaise brain state, as ascertained from taste aversion experiments, but tracked both the initial decrease in weight and food intake and the subsequent tolerance to these drugs. Importantly, the appetite suppressant-induced weight loss and locomotion were markedly reduced by intragastric (and intra-NAc shell) infusions of dopamine antagonists SCH-23390 (D1 receptor) or raclopride (D2 receptor). Furthermore, both antagonists attenuated appetite suppressant-induced LFP oscillations and partially restored the imbalance in NAc shell activity. These data reveal that appetite suppressant-induced behavioral and neuronal activity recorded in the NAc shell depend, to various extents, on dopaminergic activation and thus point to an important role for D1/D2-like receptors (in the NAc shell) in the mechanism of action for these anorexic compounds. PMID:25972577

Temporal-spatial characteristics of phase-amplitude coupling in electrocorticogram for human temporal lobe epilepsy.

PubMed

Zhang, Ruihua; Ren, Ye; Liu, Chunyan; Xu, Na; Li, Xiaoli; Cong, Fengyu; Ristaniemi, Tapani; Wang, YuPing

2017-09-01

Neural activity of the epileptic human brain contains low- and high-frequency oscillations in different frequency bands, some of which have been used as reliable biomarkers of the epileptogenic brain areas. However, the relationship between the low- and high-frequency oscillations in different cortical areas during the period from pre-seizure to post-seizure has not been completely clarified. We recorded electrocorticogram data from the temporal lobe and hippocampus of seven patients with temporal lobe epilepsy. The modulation index based on the Kullback-Leibler distance and the phase-amplitude coupling co-modulogram were adopted to quantify the coupling strength between the phase of low-frequency oscillations (0.2-10Hz) and the amplitude of high-frequency oscillations (11-400Hz) in different seizure epochs. The time-varying phase-amplitude modulogram was used to analyze the phase-amplitude coupling pattern during the entire period from pre-seizure to post-seizure in both the left and right temporal lobe and hippocampus. Channels with strong modulation index were compared with the seizure onset channels identified by the neurosurgeons and the resection channels in the clinical surgery. The phase-amplitude coupling strength (modulation index) increased significantly in the mid-seizure epoch and decrease significantly in seizure termination and post-seizure epochs (p<0.001). The strong phase-amplitude-modulating low- and high-frequency oscillations in the mid-seizure epoch were mainly δ, θ, and α oscillations and γ and ripple oscillations, respectively. The phase-amplitude modulation and strength varied among channels and was asymmetrical in the left and right temporal cortex and hippocampus. The "fall-max" phase-amplitude modulation pattern, i.e., high-frequency amplitudes were largest in the low-frequency phase range [-π, 0], which corresponded to the falling edges of low-frequency oscillations, appeared in the middle period of the seizures at epileptic focus channels. Channels with strong modulation index appeared on the corresponding left or right temporal cortex of surgical resection and overlapped with the clinical resection zones in all patients. The "fall-max" pattern between the phase of low-frequency oscillation and amplitude of high-frequency oscillation that appeared in the middle period of the seizures is a reliable biomarker in epileptogenic cortical areas. The modulation index can be used as a good tool for lateralization and localization for the epileptic focus in patients with epilepsy. Phase-amplitude coupling can provide meaningful reference for accurate resection of epileptogenic focus and provide insight into the underlying neural dynamics of the epileptic seizure in patients with temporal lobe epilepsy. Copyright © 2017 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

The Drosophila Clock Neuron Network Features Diverse Coupling Modes and Requires Network-wide Coherence for Robust Circadian Rhythms.

PubMed

Yao, Zepeng; Bennett, Amelia J; Clem, Jenna L; Shafer, Orie T

2016-12-13

In animals, networks of clock neurons containing molecular clocks orchestrate daily rhythms in physiology and behavior. However, how various types of clock neurons communicate and coordinate with one another to produce coherent circadian rhythms is not well understood. Here, we investigate clock neuron coupling in the brain of Drosophila and demonstrate that the fly's various groups of clock neurons display unique and complex coupling relationships to core pacemaker neurons. Furthermore, we find that coordinated free-running rhythms require molecular clock synchrony not only within the well-characterized lateral clock neuron classes but also between lateral clock neurons and dorsal clock neurons. These results uncover unexpected patterns of coupling in the clock neuron network and reveal that robust free-running behavioral rhythms require a coherence of molecular oscillations across most of the fly's clock neuron network. Copyright © 2016 The Author(s). Published by Elsevier Inc. All rights reserved.

Reorganization of the human central nervous system.

PubMed

Schalow, G; Zäch, G A

2000-10-01

The key strategies on which the discovery of the functional organization of the central nervous system (CNS) under physiologic and pathophysiologic conditions have been based included (1) our measurements of phase and frequency coordination between the firings of alpha- and gamma-motoneurons and secondary muscle spindle afferents in the human spinal cord, (2) knowledge on CNS reorganization derived upon the improvement of the functions of the lesioned CNS in our patients in the short-term memory and the long-term memory (reorganization), and (3) the dynamic pattern approach for re-learning rhythmic coordinated behavior. The theory of self-organization and pattern formation in nonequilibrium systems is explicitly related to our measurements of the natural firing patterns of sets of identified single neurons in the human spinal premotor network and re-learned coordinated movements following spinal cord and brain lesions. Therapy induced cell proliferation, and maybe, neurogenesis seem to contribute to the host of structural changes during the process of re-learning of the lesioned CNS. So far, coordinated functions like movements could substantially be improved in every of the more than 100 patients with a CNS lesion by applying coordination dynamic therapy. As suggested by the data of our patients on re-learning, the human CNS seems to have a second integrative strategy for learning, re-learning, storing and recalling, which makes an essential contribution of the functional plasticity following a CNS lesion. A method has been developed by us for the simultaneous recording with wire electrodes of extracellular action potentials from single human afferent and efferent nerve fibres of undamaged sacral nerve roots. A classification scheme of the nerve fibres in the human peripheral nervous system (PNS) could be set up in which the individual classes of nerve fibres are characterized by group conduction velocities and group nerve fibre diameters. Natural impulse patterns of several identified single afferent and efferent nerve fibres (motoneuron axons) were extracted from multi-unit impulse patterns, and human CNS functions could be analyzed under physiologic and pathophysiologic conditions. With our discovery of premotor spinal oscillators it became possible to judge upon CNS neuronal network organization based on the firing patterns of these spinal oscillators and their driving afferents. Since motoneurons fire occasionally for low activation and oscillatory for high activation, the coherent organization of subnetworks to generate macroscopic function is very complex and for the time being, may be best described by the theory of coordination dynamics. Since oscillatory firing has also been observed by us in single motor unit firing patterns measured electromyographically, it seems possible to follow up therapeutic intervention in patients with spinal cord and brain lesions not only based on the activity levels and phases of motor programs during locomotion but also based on the physiologic and pathophysiologic firing patterns and recruitment of spinal oscillators. The improvement of the coordination dynamics of the CNS can be partly measured directly by rhythmicity upon the patient performing rhythmic movements coordinated up to milliseconds. Since rhythmic dynamic, coordinated, stereotyped movements are mainly located in the spinal cord and only little supraspinal drive is necessary to initiate, maintain, and terminate them, rhythmic, dynamic, coordinated movements were used in therapy to enforce reorganization of the lesioned CNS by improving the self-organization and relative coordination of spinal oscillators (and their interactions with occasionally firing motoneurons) which became pathologic in their firing following CNS lesion. Paraparetic, tetraparetic spinal cord and brain-lesioned patients re-learned running and other movements by an oscillator formation and coordination dynamic therapy. Our development in neurorehabilitation is in accordance with those of theoretical and computational neurosciences which deal with the self-organization of neuronal networks. In particular, jumping on a springboard 'in-phase' and in 'anti-phase' to re-learn phase relations of oscillator coupling can be understood in the framework of the Haken-Kelso-Bunz coordination dynamic model. By introducing broken symmetry, intention, learning and spasticity in the landscape of the potential function of the integrated CNS activity, the change in self-organization becomes understandable. Movement patterns re-learned by oscillator formation and coordination dynamic therapy evolve from reorganization and regeneration of the lesioned CNS by cooperative and competitive interplay between intrinsic coordination dynamics, extrinsic therapy related inputs with physiologic re-afferent input, including intention, motivation, supervised learning, interpersonal coordination, and genetic constraints including neurogenesis. (ABSTRACT TRUNCATED)

Serotonergic psychedelics temporarily modify information transfer in humans.

PubMed

Alonso, Joan Francesc; Romero, Sergio; Mañanas, Miquel Àngel; Riba, Jordi

2015-03-28

Psychedelics induce intense modifications in the sensorium, the sense of "self," and the experience of reality. Despite advances in our understanding of the molecular and cellular level mechanisms of these drugs, knowledge of their actions on global brain dynamics is still incomplete. Recent imaging studies have found changes in functional coupling between frontal and parietal brain structures, suggesting a modification in information flow between brain regions during acute effects. Here we assessed the psychedelic-induced changes in directionality of information flow during the acute effects of a psychedelic in humans. We measured modifications in connectivity of brain oscillations using transfer entropy, a nonlinear measure of directed functional connectivity based on information theory. Ten healthy male volunteers with prior experience with psychedelics participated in 2 experimental sessions. They received a placebo or a dose of ayahuasca, a psychedelic preparation containing the serotonergic 5-HT2A agonist N,N-dimethyltryptamine. The analysis showed significant changes in the coupling of brain oscillations between anterior and posterior recording sites. Transfer entropy analysis showed that frontal sources decreased their influence over central, parietal, and occipital sites. Conversely, sources in posterior locations increased their influence over signals measured at anterior locations. Exploratory correlations found that anterior-to-posterior transfer entropy decreases were correlated with the intensity of subjective effects, while the imbalance between anterior-to-posterior and posterior-to-anterior transfer entropy correlated with the degree of incapacitation experienced. These results suggest that psychedelics induce a temporary disruption of neural hierarchies by reducing top-down control and increasing bottom-up information transfer in the human brain. © The Author 2015. Published by Oxford University Press on behalf of CINP.

Cross-frequency coupling in real and virtual brain networks

PubMed Central

Jirsa, Viktor; Müller, Viktor

2013-01-01

Information processing in the brain is thought to rely on the convergence and divergence of oscillatory behaviors of widely distributed brain areas. This information flow is captured in its simplest form via the concepts of synchronization and desynchronization and related metrics. More complex forms of information flow are transient synchronizations and multi-frequency behaviors with metrics related to cross-frequency coupling (CFC). It is supposed that CFC plays a crucial role in the organization of large-scale networks and functional integration across large distances. In this study, we describe different CFC measures and test their applicability in simulated and real electroencephalographic (EEG) data obtained during resting state. For these purposes, we derive generic oscillator equations from full brain network models. We systematically model and simulate the various scenarios of CFC under the influence of noise to obtain biologically realistic oscillator dynamics. We find that (i) specific CFC-measures detect correctly in most cases the nature of CFC under noise conditions, (ii) bispectrum (BIS) and bicoherence (BIC) correctly detect the CFCs in simulated data, (iii) empirical resting state EEG show a prominent delta-alpha CFC as identified by specific CFC measures and the more classic BIS and BIC. This coupling was mostly asymmetric (directed) and generally higher in the eyes closed (EC) than in the eyes open (EO) condition. In conjunction, these two sets of measures provide a powerful toolbox to reveal the nature of couplings from experimental data and as such allow inference on the brain state dependent information processing. Methodological advantages of using CFC measures and theoretical significance of delta and alpha interactions during resting and other brain states are discussed. PMID:23840188

Modulation and detection of single neuron activity using spin transfer nano-oscillators

NASA Astrophysics Data System (ADS)

Algarin, Jose Miguel; Ramaswamy, Bharath; Venuti, Lucy; Swierzbinski, Matthew; Villar, Pablo; Chen, Yu-Jin; Krivorotov, Ilya; Weinberg, Irving N.; Herberholz, Jens; Araneda, Ricardo; Shapiro, Benjamin; Waks, Edo

2017-09-01

The brain is a complex network of interconnected circuits that exchange electrical signals with each other. These electrical signals provide insight on how neural circuits code information, and give rise to sensations, thoughts, emotions and actions. Currents methods to detect and modulate these electrical signals use implanted electrodes or optical fields with light sensitive dyes in the brain. These techniques require complex surgeries or suffer low resolution. In this talk we explore a new method to both image and stimulate single neurons using spintronics. We propose using a Spin Transfer Nano-Oscillators (STNOs) as a nanoscale sensor that converts neuronal action potentials to microwave field oscillations that can be detected wirelessly by magnetic induction. We will describe our recent proof-of-concept demonstration of both detection and wireless modulation of neuronal activity using STNOs. For detection we use electrodes to connect a STNO to a lateral giant crayfish neuron. When we stimulate the neuron, the STNO responds to the neuronal activity with a corresponding microwave signal. For modulation, we stimulate the STNOs wirelessly using an inductively coupled solenoid. The STNO rectifies the induced microwave signal to produce a direct voltage. This direct voltage from the STNO, when applied in the vicinity of a mammalian neuron, changes the frequency of electrical signals produced by the neuron.

β oscillation during slow wave sleep and rapid eye movement sleep in the electroencephalogram of a transgenic mouse model of Huntington's disease.

PubMed

Jeantet, Yannick; Cayzac, Sebastien; Cho, Yoon H

2013-01-01

To search for early abnormalities in electroencephalogram (EEG) during sleep which may precede motor symptoms in a transgenic mouse model of hereditary neurodegenerative Huntington's disease (HD). In the R6/1 transgenic mouse model of HD, rhythmic brain activity in EEG recordings was monitored longitudinally and across vigilance states through the onset and progression of disease. Mice with chronic electrode implants were recorded monthly over wake-sleep cycles (4 hours), beginning at 9-11 weeks (presymptomatic period) through 6-7 months (symptomatic period). Recording data revealed a unique β rhythm (20-35 Hz), present only in R6/1 transgenic mice, which evolves in close parallel with the disease. In addition, there was an unusual relationship between this β oscillation and vigilance states: while nearly absent during the active waking state, the β oscillation appeared with drowsiness and during slow wave sleep (SWS) and, interestingly, strengthened rather than dissipating when the brain returned to an activated state during rapid eye movement (REM) sleep. In addition to providing a new in vivo biomarker and insight into Huntington's disease pathophysiology, this serendipitous observation opens a window onto the rarely explored neurophysiology of the cortico-basal ganglia circuit during SWS and REM sleep.

Brain computer interface to enhance episodic memory in human participants

PubMed Central

Burke, John F.; Merkow, Maxwell B.; Jacobs, Joshua; Kahana, Michael J.

2015-01-01

Recent research has revealed that neural oscillations in the theta (4–8 Hz) and alpha (9–14 Hz) bands are predictive of future success in memory encoding. Because these signals occur before the presentation of an upcoming stimulus, they are considered stimulus-independent in that they correlate with enhanced memory encoding independent of the item being encoded. Thus, such stimulus-independent activity has important implications for the neural mechanisms underlying episodic memory as well as the development of cognitive neural prosthetics. Here, we developed a brain computer interface (BCI) to test the ability of such pre-stimulus activity to modulate subsequent memory encoding. We recorded intracranial electroencephalography (iEEG) in neurosurgical patients as they performed a free recall memory task, and detected iEEG theta and alpha oscillations that correlated with optimal memory encoding. We then used these detected oscillatory changes to trigger the presentation of items in the free recall task. We found that item presentation contingent upon the presence of pre-stimulus theta and alpha oscillations modulated memory performance in more sessions than expected by chance. Our results suggest that an electrophysiological signal may be causally linked to a specific behavioral condition, and contingent stimulus presentation has the potential to modulate human memory encoding. PMID:25653605

Electroencephalogram Signatures of Ketamine-Induced Unconsciousness

PubMed Central

Akeju, Oluwaseun; Song, Andrew H.; Hamilos, Allison E.; Pavone, Kara J.; Flores, Francisco J.; Brown, Emery N.; Purdon, Patrick L.

2016-01-01

Objectives Ketamine is an N-methyl-D-aspartate receptor antagonist commonly administered as a general anesthetic. However, circuit level mechanisms to explain ketamine-induced unconsciousness in humans are yet to be clearly defined. Disruption of frontal-parietal network connectivity has been proposed as a mechanism to explain this brain state. However, this mechanism was recently demonstrated at subanesthetic doses of ketamine in awake-patients. Therefore we investigated whether there is an electroencephalogram (EEG) marker for ketamine-induced unconsciousness. Methods We retrospectively studied the EEG in 12 patients who received ketamine for the induction of general anesthesia. We analyzed the EEG dynamics using power spectral and coherence methods. Results Following the administration of a bolus dose of ketamine to induce unconsciousness, we observed a “gamma burst” EEG pattern that consisted of alternating slow-delta (0.1-4 Hz) and gamma (~27-40 Hz) oscillations. This pattern was also associated with increased theta oscillations (~4-8 Hz) and decreased alpha/beta oscillations (~10-24 Hz). Conclusions Ketamine-induced unconsciousness is associated with a gamma burst EEG pattern. Significance We postulate that the gamma burst pattern is a thalamocortical rhythm based on insights previously obtained from cat neurophysiological experiments. This EEG signature of ketamine-induced unconsciousness may offer new insights into general anesthesia induced brain states. PMID:27178861

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.

Distinct spatio-temporal profiles of beta-oscillations within visual and sensorimotor areas during action recognition as revealed by MEG.

PubMed

Pavlidou, Anastasia; Schnitzler, Alfons; Lange, Joachim

2014-05-01

The neural correlates of action recognition have been widely studied in visual and sensorimotor areas of the human brain. However, the role of neuronal oscillations involved during the process of action recognition remains unclear. Here, we were interested in how the plausibility of an action modulates neuronal oscillations in visual and sensorimotor areas. Subjects viewed point-light displays (PLDs) of biomechanically plausible and implausible versions of the same actions. Using magnetoencephalography (MEG), we examined dynamic changes of oscillatory activity during these action recognition processes. While both actions elicited oscillatory activity in visual and sensorimotor areas in several frequency bands, a significant difference was confined to the beta-band (∼20 Hz). An increase of power for plausible actions was observed in left temporal, parieto-occipital and sensorimotor areas of the brain, in the beta-band in successive order between 1650 and 2650 msec. These distinct spatio-temporal beta-band profiles suggest that the action recognition process is modulated by the degree of biomechanical plausibility of the action, and that spectral power in the beta-band may provide a functional interaction between visual and sensorimotor areas in humans. Copyright © 2014 Elsevier Ltd. All rights reserved.

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.

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.

Heteroclinic dynamics of coupled semiconductor lasers with optoelectronic feedback.

PubMed

Shahin, S; Vallini, F; Monifi, F; Rabinovich, M; Fainman, Y

2016-11-15

Generalized Lotka-Volterra (GLV) equations are important equations used in various areas of science to describe competitive dynamics among a population of N interacting nodes in a network topology. In this Letter, we introduce a photonic network consisting of three optoelectronically cross-coupled semiconductor lasers to realize a GLV model. In such a network, the interaction of intensity and carrier inversion rates, as well as phases of laser oscillator nodes, result in various dynamics. We study the influence of asymmetric coupling strength and frequency detuning between semiconductor lasers and show that inhibitory asymmetric coupling is required to achieve consecutive amplitude oscillations of the laser nodes. These studies were motivated primarily by the dynamical models used to model brain cognitive activities and their correspondence with dynamics obtained among coupled laser oscillators.

The role of high-frequency oscillations in epilepsy surgery planning.

PubMed

Gloss, David; Nevitt, Sarah J; Staba, Richard

2017-10-05

Epilepsy is a serious brain disorder characterized by recurrent unprovoked seizures. Approximately two-thirds of seizures can be controlled with antiepileptic medications (Kwan 2000). For some of the others, surgery can completely eliminate or significantly reduce the occurrence of disabling seizures. Localization of epileptogenic areas for resective surgery is far from perfect, and new tools are being investigated to more accurately localize the epileptogenic zone (the zone of the brain where the seizures begin) and improve the likelihood of freedom from postsurgical seizures. Recordings of pathological high-frequency oscillations (HFOs) may be one such tool. To assess the ability of HFOs to improve the outcomes of epilepsy surgery by helping to identify more accurately the epileptogenic areas of the brain. For the latest update, we searched the Cochrane Epilepsy Group Specialized Register (25 July 2016), the Cochrane Central Register of Controlled Trials (CENTRAL) via the Cochrane Register of Studies Online (CRSO, 25 July 2016), MEDLINE (Ovid, 1946 to 25 July 2016), CINAHL Plus (EBSCOhost, 25 July 2016), Web of Science (Thomson Reuters, 25 July 2016), ClinicalTrials.gov (25 July 2016), and the World Health Organization International Clinical Trials Registry Platform ICTRP (25 July 2016). We included studies that provided information on the outcomes of epilepsy surgery for at least six months and which used high-frequency oscillations in making decisions about epilepsy surgery. The primary outcome of the review was the Engel Class Outcome System (class I = no disabling seizures, II = rare disabling seizures, III = worthwhile improvement, IV = no worthwhile improvement). Secondary outcomes were responder rate, International League Against Epilepsy (ILAE) epilepsy surgery outcome, frequency of adverse events from any source and quality of life outcomes. We intended to analyse outcomes via an aggregated data fixed-effect model meta-analysis. Two studies representing 11 participants met the inclusion criteria. Both studies were small non-randomised trials, with no control group and no blinding. The quality of evidence for all outcomes was very low. The combination of these two studies resulted in 11 participants who prospectively used ictal HFOs for epilepsy surgery decision making. Results of the postsurgical seizure freedom Engel class I to IV outcome were determined over a period of 12 to 38 months (average 23.4 months) and indicated that six participants had an Engel class I outcome (seizure freedom), two had class II (rare disabling seizures), three had class III (worthwhile improvement). No adverse effects were reported. Neither study compared surgical results guided by HFOs versus surgical results guided without HFOs. No reliable conclusions can be drawn regarding the efficacy of using HFOs in epilepsy surgery decision making at present.

Psilocybin-induced spiritual experiences and insightfulness are associated with synchronization of neuronal oscillations.

PubMed

Kometer, Michael; Pokorny, Thomas; Seifritz, Erich; Volleinweider, Franz X

2015-10-01

During the last years, considerable progress has been made toward understanding the neuronal basis of consciousness by using sophisticated behavioral tasks, brain-imaging techniques, and various psychoactive drugs. Nevertheless, the neuronal mechanisms underlying some of the most intriguing states of consciousness, including spiritual experiences, remain unknown. To elucidate state of consciousness-related neuronal mechanisms, human subjects were given psilocybin, a naturally occurring serotonergic agonist and hallucinogen that has been used for centuries to induce spiritual experiences in religious and medical rituals. In this double-blind, placebo-controlled study, 50 healthy human volunteers received a moderate dose of psilocybin, while high-density electroencephalogram (EEG) recordings were taken during eyes-open and eyes-closed resting states. The current source density and the lagged phase synchronization of neuronal oscillations across distributed brain regions were computed and correlated with psilocybin-induced altered states of consciousness. Psilocybin decreased the current source density of neuronal oscillations at 1.5-20 Hz within a neural network comprising the anterior and posterior cingulate cortices and the parahippocampal regions. Most intriguingly, the intensity levels of psilocybin-induced spiritual experience and insightfulness correlated with the lagged phase synchronization of delta oscillations (1.5-4 Hz) between the retrosplenial cortex, the parahippocampus, and the lateral orbitofrontal area. These results provide systematic evidence for the direct association of a specific spatiotemporal neuronal mechanism with spiritual experiences and enhanced insight into life and existence. The identified mechanism may constitute a pathway for modulating mental health, as spiritual experiences can promote sustained well-being and psychological resilience.

EEG oscillations entrain their phase to high-level features of speech sound.

PubMed

Zoefel, Benedikt; VanRullen, Rufin

2016-01-01

Phase entrainment of neural oscillations, the brain's adjustment to rhythmic stimulation, is a central component in recent theories of speech comprehension: the alignment between brain oscillations and speech sound improves speech intelligibility. However, phase entrainment to everyday speech sound could also be explained by oscillations passively following the low-level periodicities (e.g., in sound amplitude and spectral content) of auditory stimulation-and not by an adjustment to the speech rhythm per se. Recently, using novel speech/noise mixture stimuli, we have shown that behavioral performance can entrain to speech sound even when high-level features (including phonetic information) are not accompanied by fluctuations in sound amplitude and spectral content. In the present study, we report that neural phase entrainment might underlie our behavioral findings. We observed phase-locking between electroencephalogram (EEG) and speech sound in response not only to original (unprocessed) speech but also to our constructed "high-level" speech/noise mixture stimuli. Phase entrainment to original speech and speech/noise sound did not differ in the degree of entrainment, but rather in the actual phase difference between EEG signal and sound. Phase entrainment was not abolished when speech/noise stimuli were presented in reverse (which disrupts semantic processing), indicating that acoustic (rather than linguistic) high-level features play a major role in the observed neural entrainment. Our results provide further evidence for phase entrainment as a potential mechanism underlying speech processing and segmentation, and for the involvement of high-level processes in the adjustment to the rhythm of speech. Copyright © 2015 Elsevier Inc. All rights reserved.

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.

Network recruitment to coherent oscillations in a hippocampal computer model

PubMed Central

Krieger, Abba; Litt, Brian

2011-01-01

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

Brain Oscillations Elicited by the Cold Pressor Test: A Putative Index of Untreated Essential Hypertension

PubMed Central

Tsaltas, Eleftheria; Koroboki, Eleni; Alevizaki, Maria; Angelopoulos, Elias; Dimopoulos, Meletios-Athanasios; Papageorgiou, Charalabos; Zakopoulos, Nikolaos

2017-01-01

Objective Essential hypertension is associated with reduced pain sensitivity of unclear aetiology. This study explores this issue using the Cold Pressor Test (CPT), a reliable pain/stress model, comparing CPT-related EEG activity in first episode hypertensives and controls. Method 22 untreated hypertensives and 18 matched normotensives underwent 24-hour ambulatory blood pressure monitoring (ABPM). EEG recordings were taken before, during, and after CPT exposure. Results Significant group differences in CPT-induced EEG oscillations were covaried with the most robust cardiovascular differentiators by means of a Canonical Analysis. Positive correlations were noted between ABPM variables and Delta (1–4 Hz) oscillations during the tolerance phase; in high-alpha (10–12 Hz) oscillations during the stress unit and posttest phase; and in low-alpha (8–10 Hz) oscillations during CPT phases overall. Negative correlations were found between ABPM variables and Beta2 oscillations (16.5–20 Hz) during the posttest phase and Gamma (28.5–45 Hz) oscillations during the CPT phases overall. These relationships were localised at several sites across the cerebral hemispheres with predominance in the right hemisphere and left frontal lobe. Conclusions These findings provide a starting point for increasing our understanding of the complex relationships between cerebral activation and cardiovascular functioning involved in regulating blood pressure changes. PMID:28573048

Structure Shapes Dynamics and Directionality in Diverse Brain Networks: Mathematical Principles and Empirical Confirmation in Three Species

NASA Astrophysics Data System (ADS)

Moon, Joon-Young; Kim, Junhyeok; Ko, Tae-Wook; Kim, Minkyung; Iturria-Medina, Yasser; Choi, Jee-Hyun; Lee, Joseph; Mashour, George A.; Lee, Uncheol

2017-04-01

Identifying how spatially distributed information becomes integrated in the brain is essential to understanding higher cognitive functions. Previous computational and empirical studies suggest a significant influence of brain network structure on brain network function. However, there have been few analytical approaches to explain the role of network structure in shaping regional activities and directionality patterns. In this study, analytical methods are applied to a coupled oscillator model implemented in inhomogeneous networks. We first derive a mathematical principle that explains the emergence of directionality from the underlying brain network structure. We then apply the analytical methods to the anatomical brain networks of human, macaque, and mouse, successfully predicting simulation and empirical electroencephalographic data. The results demonstrate that the global directionality patterns in resting state brain networks can be predicted solely by their unique network structures. This study forms a foundation for a more comprehensive understanding of how neural information is directed and integrated in complex brain networks.

Optically pumped coherent mechanical oscillators: the laser rate equation theory and experimental verification

NASA Astrophysics Data System (ADS)

Khurgin, J. B.; Pruessner, M. W.; Stievater, T. H.; Rabinovich, W. S.

2012-10-01

We develop a theory describing the operation of an opto-mechanical oscillator as a phonon laser using a set of coupled equations that is analogous to the standard set of laser rate equations. We show that laser-like parameters that characterize gain, stored energy, threshold, efficiency, oscillation frequency linewidth, and saturation power can be introduced for an opto-mechanical oscillator driven by photo-thermal or radiation pressure forces. We then apply the theoretical model to the experimental results for photo-thermally driven oscillations in a Si waveguide opto-mechanical resonator and show good agreement between the theory and experiments. We also consider the microscopic mechanism that transforms the energy of incoherent thermal phonons into coherent oscillations of a single phonon mode and show remarkable parallels with the three-wave parametric interactions in optics and also with opto-electronic oscillators used in microwave photonics.

MHD oscillations observed in the solar photosphere with the Michelson Doppler Imager

NASA Astrophysics Data System (ADS)

Norton, A.; Ulrich, R. K.; Bogart, R. S.; Bush, R. I.; Hoeksema, J. T.

Magnetohydrodynamic oscillations are observed in the solar photosphere with the Michelson Doppler Imager (MDI). Images of solar surface velocity and magnetic field strength with 4'' spatial resolution and a 60 second temporal resolution are analyzed. A two dimensional gaussian aperture with a FWHM of 10'' is applied to the data in regions of sunspot, plage and quiet sun and the resulting averaged signal is returned each minute. Significant power is observed in the magnetic field oscillations with periods of five minutes. The effect of misregistration between MDI's left circularly polarized (LCP) and right circularly polarized (RCP) images has been investigated and is found not to be the cause of the observed magnetic oscillations. It is assumed that the large amplitude acoustic waves with 5 minute periods are the driving mechanism behind the magnetic oscillations. The nature of the magnetohydrodynamic oscillations are characterized by their phase relations with simultaneously observed solar surface velocity oscillations.

An optical system for detecting 3D high-speed oscillation of a single ultrasound microbubble

PubMed Central

Liu, Yuan; Yuan, Baohong

2013-01-01

As contrast agents, microbubbles have been playing significant roles in ultrasound imaging. Investigation of microbubble oscillation is crucial for microbubble characterization and detection. Unfortunately, 3-dimensional (3D) observation of microbubble oscillation is challenging and costly because of the bubble size—a few microns in diameter—and the high-speed dynamics under MHz ultrasound pressure waves. In this study, a cost-efficient optical confocal microscopic system combined with a gated and intensified charge-coupled device (ICCD) camera were developed to detect 3D microbubble oscillation. The capability of imaging microbubble high-speed oscillation with much lower costs than with an ultra-fast framing or streak camera system was demonstrated. In addition, microbubble oscillations along both lateral (x and y) and axial (z) directions were demonstrated. Accordingly, this system is an excellent alternative for 3D investigation of microbubble high-speed oscillation, especially when budgets are limited. PMID:24049677

Basic and functional effects of transcranial Electrical Stimulation (tES)-An introduction.

PubMed

Yavari, Fatemeh; Jamil, Asif; Mosayebi Samani, Mohsen; Vidor, Liliane Pinto; Nitsche, Michael A

2018-02-01

Non-invasive brain stimulation (NIBS) has been gaining increased popularity in human neuroscience research during the last years. Among the emerging NIBS tools is transcranial electrical stimulation (tES), whose main modalities are transcranial direct, and alternating current stimulation (tDCS, tACS). In tES, a small current (usually less than 3mA) is delivered through the scalp. Depending on its shape, density, and duration, the applied current induces acute or long-lasting effects on excitability and activity of cerebral regions, and brain networks. tES is increasingly applied in different domains to (a) explore human brain physiology with regard to plasticity, and brain oscillations, (b) explore the impact of brain physiology on cognitive processes, and (c) treat clinical symptoms in neurological and psychiatric diseases. In this review, we give a broad overview of the main mechanisms and applications of these brain stimulation tools. Copyright © 2017 Elsevier Ltd. All rights reserved.

New concept for a toxicity assay based on multiple indexes from the wave shape of damped metabolic oscillation induced in living yeast cells (part I): characterization of the phenomenon.

PubMed

Nakamura, H; Suzuki, M

2007-10-01

The damped glycolytic oscillation phenomenon occurring in starved cells of the yeast Saccharomyces cerevisiae (NBRC 0565) was characterization for application to a toxicity bioassay. S. cerevisiae was grown under semi-anaerobic conditions. The transient oscillations were observed photometrically as the time course of the fluorescent intensity of reduced pyridine nucleotide resulting from instantaneous addition of glucose to a cell suspension. In this study, simple and reproducible conditions inducing damped oscillations were obtained by modifying a literature method. For estimation of the wave shapes of the damped oscillations we used six indexes. To investigate the total reproducibility as the averaged relative standard deviation (RSD(av)) for the six indexes obtained from the wave shapes, the damped oscillations were induced under the optimum conditions and the RSD(av) values were calculated as 14% in a buffer cell suspension (n = 62) and 22% in a water cell suspension (n = 78). Finally, the effects of glucose concentration on the six indexes were examined, and all the indexes changed when the glucose concentration was changed. Excellent correlations were obtained between the index of oscillation-state time and the concentration of glucose in a buffer cell suspension (r = 0.9985, 0.5-250 mmol L(-1), 10 points) and in a water cell suspension (r = 0.9989, 2.5 micromol L(-1)-250 mmol L(-1), 12 points), respectively.

Synchronizing theta oscillations with direct-current stimulation strengthens adaptive control in the human brain.

PubMed

Reinhart, Robert M G; Zhu, Julia; Park, Sohee; Woodman, Geoffrey F

2015-07-28

Executive control and flexible adjustment of behavior following errors are essential to adaptive functioning. Loss of adaptive control may be a biomarker of a wide range of neuropsychiatric disorders, particularly in the schizophrenia spectrum. Here, we provide support for the view that oscillatory activity in the frontal cortex underlies adaptive adjustments in cognitive processing following errors. Compared with healthy subjects, patients with schizophrenia exhibited low frequency oscillations with abnormal temporal structure and an absence of synchrony over medial-frontal and lateral-prefrontal cortex following errors. To demonstrate that these abnormal oscillations were the origin of the impaired adaptive control in patients with schizophrenia, we applied noninvasive dc electrical stimulation over the medial-frontal cortex. This noninvasive stimulation descrambled the phase of the low-frequency neural oscillations that synchronize activity across cortical regions. Following stimulation, the behavioral index of adaptive control was improved such that patients were indistinguishable from healthy control subjects. These results provide unique causal evidence for theories of executive control and cortical dysconnectivity in schizophrenia.

A neural circuit for gamma-band coherence across the retinotopic map in mouse visual cortex

PubMed Central

Hakim, Richard; Shamardani, Kiarash

2018-01-01

Cortical gamma oscillations have been implicated in a variety of cognitive, behavioral, and circuit-level phenomena. However, the circuit mechanisms of gamma-band generation and synchronization across cortical space remain uncertain. Using optogenetic patterned illumination in acute brain slices of mouse visual cortex, we define a circuit composed of layer 2/3 (L2/3) pyramidal cells and somatostatin (SOM) interneurons that phase-locks ensembles across the retinotopic map. The network oscillations generated here emerge from non-periodic stimuli, and are stimulus size-dependent, coherent across cortical space, narrow band (30 Hz), and depend on SOM neuron but not parvalbumin (PV) neuron activity; similar to visually induced gamma oscillations observed in vivo. Gamma oscillations generated in separate cortical locations exhibited high coherence as far apart as 850 μm, and lateral gamma entrainment depended on SOM neuron activity. These data identify a circuit that is sufficient to mediate long-range gamma-band coherence in the primary visual cortex. PMID:29480803

Voluntary control of intracortical oscillations for reconfiguration of network activity

PubMed Central

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

2016-01-01

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

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.

Low-frequency oscillations in default mode subnetworks are associated with episodic memory impairments in Alzheimer's disease.

PubMed

Veldsman, Michele; Egorova, Natalia; Singh, Baljeet; Mungas, Dan; DeCarli, Charles; Brodtmann, Amy

2017-11-01

Disruptions to functional connectivity in subsystems of the default mode network are evident in Alzheimer's disease (AD). Functional connectivity estimates correlations in the time course of low-frequency activity. Much less is known about other potential perturbations to this activity, such as changes in the amplitude of oscillations and how this relates to cognition. We examined the amplitude of low-frequency fluctuations in 44 AD patients and 128 cognitively normal participants and related this to episodic memory, the core deficit in AD. We show higher amplitudes of low-frequency oscillations in AD patients. Rather than being compensatory, this appears to be maladaptive, with greater amplitude in the ventral default mode subnetwork associated with poorer episodic memory. Perturbations to default mode subnetworks in AD are evident in the amplitude of low-frequency oscillations in the resting brain. These disruptions are associated with episodic memory demonstrating their behavioral and clinical relevance in AD. Copyright © 2017 Elsevier Inc. All rights reserved.

Near-infrared deep brain stimulation via upconversion nanoparticle–mediated optogenetics

NASA Astrophysics Data System (ADS)

Chen, Shuo; Weitemier, Adam Z.; Zeng, Xiao; He, Linmeng; Wang, Xiyu; Tao, Yanqiu; Huang, Arthur J. Y.; Hashimotodani, Yuki; Kano, Masanobu; Iwasaki, Hirohide; Parajuli, Laxmi Kumar; Okabe, Shigeo; Teh, Daniel B. Loong; All, Angelo H.; Tsutsui-Kimura, Iku; Tanaka, Kenji F.; Liu, Xiaogang; McHugh, Thomas J.

2018-02-01

Optogenetics has revolutionized the experimental interrogation of neural circuits and holds promise for the treatment of neurological disorders. It is limited, however, because visible light cannot penetrate deep inside brain tissue. Upconversion nanoparticles (UCNPs) absorb tissue-penetrating near-infrared (NIR) light and emit wavelength-specific visible light. Here, we demonstrate that molecularly tailored UCNPs can serve as optogenetic actuators of transcranial NIR light to stimulate deep brain neurons. Transcranial NIR UCNP-mediated optogenetics evoked dopamine release from genetically tagged neurons in the ventral tegmental area, induced brain oscillations through activation of inhibitory neurons in the medial septum, silenced seizure by inhibition of hippocampal excitatory cells, and triggered memory recall. UCNP technology will enable less-invasive optical neuronal activity manipulation with the potential for remote therapy.

A Simple Demonstration of a Gas Evolution Oscillator.

ERIC Educational Resources Information Center

Kaushik, S. M.; And Others

1986-01-01

The best-characterized gas evolution oscillator is the dehydration of formic acid in concentrated sulfuric acid. Reports on an improved demonstration which exhibits at least as dramatic behavior, although for a shorter time. Includes background information, principles illustrated, procedures used, and typical results obtained. (JN)

Depression-like behaviour in mice is associated with disrupted circadian rhythms in nucleus accumbens and periaqueductal grey.

PubMed

Landgraf, Dominic; Long, Jaimie E; Welsh, David K

2016-05-01

An association between circadian rhythms and mood regulation is well established, and disturbed circadian clocks are believed to contribute to the development of mood disorders, including major depressive disorder. The circadian system is coordinated by the suprachiasmatic nucleus (SCN), the master pacemaker in the hypothalamus that receives light input from the retina and synchronizes circadian oscillators in other brain regions and peripheral tissues. Lacking the tight neuronal network that couples single-cell oscillators in the SCN, circadian clocks outside the SCN may be less stable and more susceptible to disturbances, for example by clock gene mutations or uncontrollable stress. However, non-SCN circadian clocks have not been studied extensively in rodent models of mood disorders. In the present study, it was hypothesized that disturbances of local circadian clocks in mood-regulating brain areas are associated with depression-like behaviour in mice. Using the learned helplessness procedure, depression-like behaviour was evoked in mice bearing the PER2::LUC circadian reporter, and then circadian rhythms of PER2 expression were examined in brain slices from these mice using luminometry and bioluminescence imaging. It was found that helplessness is associated with absence of circadian rhythms in the nucleus accumbens and the periaqueductal grey, two of the most critical brain regions within the reward circuit. The current study provides evidence that susceptibility of mice to depression-like behaviour is associated with disturbed local circadian clocks in a subset of mood-regulating brain areas, but the direction of causality remains to be determined. © 2015 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

Neural computational modeling reveals a major role of corticospinal gating of central oscillations in the generation of essential tremor.

PubMed

Qu, Hong-En; Niu, Chuanxin M; Li, Si; Hao, Man-Zhao; Hu, Zi-Xiang; Xie, Qing; Lan, Ning

2017-12-01

Essential tremor, also referred to as familial tremor, is an autosomal dominant genetic disease and the most common movement disorder. It typically involves a postural and motor tremor of the hands, head or other part of the body. Essential tremor is driven by a central oscillation signal in the brain. However, the corticospinal mechanisms involved in the generation of essential tremor are unclear. Therefore, in this study, we used a neural computational model that includes both monosynaptic and multisynaptic corticospinal pathways interacting with a propriospinal neuronal network. A virtual arm model is driven by the central oscillation signal to simulate tremor activity behavior. Cortical descending commands are classified as alpha or gamma through monosynaptic or multisynaptic corticospinal pathways, which converge respectively on alpha or gamma motoneurons in the spinal cord. Several scenarios are evaluated based on the central oscillation signal passing down to the spinal motoneurons via each descending pathway. The simulated behaviors are compared with clinical essential tremor characteristics to identify the corticospinal pathways responsible for transmitting the central oscillation signal. A propriospinal neuron with strong cortical inhibition performs a gating function in the generation of essential tremor. Our results indicate that the propriospinal neuronal network is essential for relaying the central oscillation signal and the production of essential tremor.

Cannabinoid Receptors Mediate Methamphetamine Induction of High Frequency Gamma Oscillations in the Nucleus Accumbens

PubMed Central

Morra, Joshua T.; Glick, Stanley D.; Cheer, Joseph F.

2012-01-01

Patients suffering from amphetamine---induced psychosis display repetitive behaviors, partially alleviated by antipsychotics, which are reminiscent of rodent stereotypies. Due to recent evidence implicating endocannabinoid involvement in brain disorders, including psychosis, we studied the effects of endocannabinoid signaling on neuronal oscillations of rats exhibiting methamphetamine stereotypy. Neuronal network oscillations were recorded with multiple single electrode arrays aimed at the nucleus accumbens of freely moving rats. During the experiments, animals were dosed intravenously with the CB1 receptor antagonist rimonabant (0.3 mg/kg) or vehicle followed by an ascending dose regimen of methamphetamine (0.01, 0.1, 1, and 3 mg/kg; cumulative dosing). The effects of drug administration on stereotypy and local gamma oscillations were evaluated. Methamphetamine treatment significantly increased high frequency gamma oscillations (~ 80 Hz). Entrainment of a subpopulation of nucleus accumbens neurons to high frequency gamma was associated with stereotypy encoding in putative fast-spiking interneurons, but not in putative medium spiny neurons. The observed ability of methamphetamine to induce both stereotypy and high frequency gamma power was potently disrupted following CB1 receptor blockade. The present data suggest that CB1 receptor-dependent mechanisms are recruited by methamphetamine to modify striatal interneuron oscillations that accompany changes in psychomotor state, further supporting the link between endocannabinoids and schizophrenia spectrum disorders. PMID:22609048

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

PubMed

Berke, J D

2009-09-01

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

Entropy Generation in Regenerative Systems

NASA Technical Reports Server (NTRS)

Kittel, Peter

1995-01-01

Heat exchange to the oscillating flows in regenerative coolers generates entropy. These flows are characterized by oscillating mass flows and oscillating temperatures. Heat is transferred between the flow and heat exchangers and regenerators. In the former case, there is a steady temperature difference between the flow and the heat exchangers. In the latter case, there is no mean temperature difference. In this paper a mathematical model of the entropy generated is developed for both cases. Estimates of the entropy generated by this process are given for oscillating flows in heat exchangers and in regenerators. The practical significance of this entropy is also discussed.