Synchronization Of Neural Oscillations Research Articles

Neural Oscillations and Multisensory Processing.

Neural oscillations play a role in sensory processing by coordinating synchronized neuronal activity. Synchronization of gamma oscillations is engaged in local computation of feedforward signals and synchronization of alpha-beta oscillations is engaged in feedback processing over long-range areas. These spatially and spectrally segregated bi-directional signals may be integrated by a mechanism of cross-frequency coupling. Synchronization of neural oscillations has also been proposed as a mechanism for information integration across multiple sensory modalities. A transient stimulus or rhythmic stimulus from one modality may lead to phase alignment of ongoing neural oscillations in multiple sensory cortices, through a mechanism of cross-modal phase reset or cross-modal neural entrainment. Synchronized activities in multiple sensory cortices are more likely to boost stronger activities in downstream areas. Compared to synchronized oscillations, asynchronized oscillations may impede signal processing, and may contribute to sensory selection by setting the oscillations in the target-related cortex and the oscillations in the distractor-related cortex to opposite phases.

Impact of Network Topology on Neural Synchrony in a Model of the Subthalamic Nucleus-Globus Pallidus Circuit.

Synchronous neural oscillations within the beta frequency range are observed across the parkinsonian basal ganglia network, including within the subthalamic nucleus (STN) - globus pallidus (GPe) subcircuit. The emergence of pathological synchrony in Parkinson's disease is often attributed to changes in neural properties or connection strength, and less often to the network topology, i.e. the structural arrangement of connections between neurons. This study investigates the relationship between network structure and neural synchrony in a model of the STN-GPe circuit comprised of conductance-based spiking neurons. Changes in net synaptic input were controlled for through a synaptic scaling rule, which facilitated separation of the effects of network structure from net synaptic input. Five topologies were examined as structures for the STN-GPe circuit: Watts-Strogatz, preferential attachment, spatial, stochastic block, k-regular random. Beta band synchrony generally increased as the number of connections increased, however the exact relationship was topology specific. Varying the wiring pattern while maintaining a constant number of connections caused network synchrony to be enhanced or suppressed, demonstrating the ability of purely structural changes to alter synchrony. This relationship was well-captured by the algebraic connectivity of the network, the second smallest eigenvalue of the network's Laplacian matrix. The structure-synchrony relationship was further investigated in a network model designed to emulate the action selection role of the STN-GPe circuit. It was found that increasing the number of connections and/or the overlap of action selection channels could lead to a rapid transition to synchrony, which was also predicted by the algebraic connectivity.

Neuromodulation in the developing visual cortex after long-term monocular deprivation.

Neural dynamics are altered in the primary visual cortex (V1) during critical period monocular deprivation (MD). Synchronization of neural oscillations is pertinent to physiological functioning of the brain. Previous studies have reported chronic disruption of V1 functional properties such as ocular dominance, spatial acuity, and binocular matching after long-term monocular deprivation (LTMD). However, the possible neuromodulation and neural synchrony has been less explored. Here, we investigated the difference between juvenile and adult experience-dependent plasticity in mice from intracellular calcium signals with fluorescent indicators. We also studied alterations in local field potentials power bands and phase-amplitude coupling (PAC) of specific brain oscillations. Our results showed that LTMD in juveniles causes higher neuromodulatory changes as seen by high-intensity fluorescent signals from the non-deprived eye (NDE). Meanwhile, adult mice showed a greater response from the deprived eye (DE). LTMD in juvenile mice triggered alterations in the power of delta, theta, and gamma oscillations, followed by enhancement of delta-gamma PAC in the NDE. However, LTMD in adult mice caused alterations in the power of delta oscillations and enhancement of delta-gamma PAC in the DE. These markers are intrinsic to cortical neuronal processing during LTMD and apply to a wide range of nested oscillatory markers.

Alterations in a cross-hemispheric circuit associates with novelty discrimination deficits in mouse models of neurodegeneration

A major pathological hallmark of neurodegenerative diseases, including Alzheimer's, is a significant reduction in the white matter connecting the two cerebral hemispheres, as well as in the correlated activity between anatomically corresponding bilateral brain areas. However, the underlying circuit mechanisms and the cognitive relevance of cross-hemispheric (CH) communication remain poorly understood. Here, we show that novelty discrimination behavior activates CH neurons and enhances homotopic synchronized neural oscillations in the visual cortex. CH neurons provide excitatory drive required for synchronous neural oscillations between hemispheres, and unilateral inhibition of the CH circuit is sufficient to impair synchronous oscillations and novelty discrimination behavior. In the 5XFAD and Tau P301S mouse models, CH communication is altered, and novelty discrimination is impaired. These data reveal a hitherto uncharacterized CH circuit in the visual cortex, establishing a causal link between this circuit and novelty discrimination behavior and highlighting its impairment in mouse models of neurodegeneration.

P486. Cross-Hemispheric Gamma Synchrony in Prefrontal PVI and Subpopulations of Projection Neurons are Modulated Differentially in a Task-Dependent Manner

Neural networks in the prefrontal cortex (PFC) are responsible for several cognitive processes known to be disrupted in conditions such as schizophrenia. These networks, which are organized by both local microcircuits and inter-regional projections, require precisely tuned neuronal activity to generate appropriate cognitive responses. One way these networks achieve this precision is through synchronization of neural oscillations which may entrain relevant neurons and/or reduce the activity of irrelevant neurons. Gamma-frequency oscillations in particular have been shown to play an important role in prefrontal-dependent cognition.

Stimulating at the right time to recover network states in a model of the cortico-basal ganglia-thalamic circuit.

Synchronization of neural oscillations is thought to facilitate communication in the brain. Neurodegenerative pathologies such as Parkinson's disease (PD) can result in synaptic reorganization of the motor circuit, leading to altered neuronal dynamics and impaired neural communication. Treatments for PD aim to restore network function via pharmacological means such as dopamine replacement, or by suppressing pathological oscillations with deep brain stimulation. We tested the hypothesis that brain stimulation can operate beyond a simple "reversible lesion" effect to augment network communication. Specifically, we examined the modulation of beta band (14-30 Hz) activity, a known biomarker of motor deficits and potential control signal for stimulation in Parkinson's. To do this we setup a neural mass model of population activity within the cortico-basal ganglia-thalamic (CBGT) circuit with parameters that were constrained to yield spectral features comparable to those in experimental Parkinsonism. We modulated the connectivity of two major pathways known to be disrupted in PD and constructed statistical summaries of the spectra and functional connectivity of the resulting spontaneous activity. These were then used to assess the network-wide outcomes of closed-loop stimulation delivered to motor cortex and phase locked to subthalamic beta activity. Our results demonstrate that the spatial pattern of beta synchrony is dependent upon the strength of inputs to the STN. Precisely timed stimulation has the capacity to recover network states, with stimulation phase inducing activity with distinct spectral and spatial properties. These results provide a theoretical basis for the design of the next-generation brain stimulators that aim to restore neural communication in disease.

Detecting changes in dynamical structures in synchronous neural oscillations using probabilistic inference

Recent neuroscience studies have suggested that cognitive functions and learning capacity are reflected in the time-evolving dynamics of brain networks. However, an efficient method to detect changes in dynamical brain structures using neural data has yet to be established. To address this issue, we developed a new model-based approach to detect change points in dynamical network structures by combining the model-based network estimation with a phase-coupled oscillator model and sequential Bayesian inference. By giving the model parameter as the prior distribution, applying Bayesian inference allows the extent of temporal changes in dynamic brain networks to be quantified by comparing the prior distribution with the posterior distribution using information theoretical criteria. For this, we used the Kullback-Leibler divergence as an index of such changes. To validate our method, we applied it to numerical data and electroencephalography data. As a result, we confirmed that the Kullback-Leibler divergence only increased when changes in dynamical network structures occurred. Our proposed method successfully estimated both directed network couplings and change points of dynamical structures in the numerical and electroencephalography data. These results suggest that our proposed method can reveal the neural basis of dynamic brain networks.

Frequency- and Area-Specific Phase Entrainment of Intrinsic Cortical Oscillations by Repetitive Transcranial Magnetic Stimulation.

Synchronous oscillations are ubiquitous throughout the cortex, but the frequency of oscillations differs from area to area. To elucidate the mechanistic architectures underlying various rhythmic activities, we tested whether spontaneous neural oscillations in different local cortical areas and large-scale networks can be phase-entrained by direct perturbation with distinct frequencies of repetitive transcranial magnetic stimulation (rTMS). While recording the electroencephalogram (EEG), we applied single-pulse TMS (sp-TMS) and rTMS at 5, 11, and 23 Hz over the motor or visual cortex. We assessed local and global modulation of phase dynamics using the phase-locking factor (PLF). sp-TMS to the motor and the visual cortex triggered a transient increase in PLF in distinct frequencies that peaked at 21 and 8 Hz, respectively. rTMS at 23 Hz over the motor cortex and 11 Hz over the visual cortex induced a prominent and progressive increase in PLF that lasted for a few cycles after the termination of rTMS. Moreover, the local increase in PLF propagated to other cortical areas. These results suggest that distinct cortical areas have area-specific oscillatory frequencies, and the manipulation of oscillations in local areas impacts other areas through the large-scale oscillatory network with the corresponding frequency specificity. We speculate that rTMS that is close to area-specific frequencies (natural frequencies) enables direct manipulation of brain dynamics and is thus useful for investigating the causal roles of synchronous neural oscillations. Moreover, this technique could be used to treat clinical symptoms associated with impaired oscillations and synchrony.

A neurophysiological model of speech production deficits in fragile X syndrome.

Fragile X syndrome is the most common inherited intellectual disability and monogenic cause of autism spectrum disorder. Expressive language deficits, especially in speech production, are nearly ubiquitous among individuals with fragile X, but understanding of the neurological bases for these deficits remains limited. Speech production depends on feedforward control and the synchronization of neural oscillations between speech-related areas of frontal cortex and auditory areas of temporal cortex. Interaction in this circuitry allows the corollary discharge of intended speech generated from an efference copy of speech commands to be compared against actual speech sounds, which is critical for making adaptive adjustments to optimize future speech. We aimed to determine whether alterations in coherence between frontal and temporal cortices prior to speech production are present in individuals with fragile X and whether they relate to expressive language dysfunction. Twenty-one participants with full-mutation fragile X syndrome (aged 7–55 years, eight females) and 20 healthy controls (matched on age and sex) completed a talk/listen paradigm during high-density EEG recordings. During the talk task, participants repeated pronounced short vocalizations of ‘Ah’ every 1–2 s for a total of 180 s. During the listen task, participants passively listened to their recordings from the talk task. We compared pre-speech event-related potential activity, N1 suppression to speech sounds, single trial gamma power and fronto-temporal coherence between groups during these tasks and examined their relation to performance during a naturalistic language task. Prior to speech production, fragile X participants showed reduced pre-speech negativity, reduced fronto-temporal connectivity and greater frontal gamma power compared to controls. N1 suppression during self-generated speech did not differ between groups. Reduced pre-speech activity and increased frontal gamma power prior to speech production were related to less intelligible speech as well as broader social communication deficits in fragile X syndrome. Our findings indicate that coordinated pre-speech activity between frontal and temporal cortices is disrupted in individuals with fragile X in a clinically relevant way and represents a mechanism contributing to prominent speech production problems in the disorder.

Effects of Electroacupuncture on Pain Memory-Related Behaviors and Synchronous Neural Oscillations in the Rostral Anterior Cingulate Cortex in Freely Moving Rats.

Our previous studies have confirmed that electroacupuncture (EA) can effectively intervene in pain memory, but the neural mechanism involved remains unclear. In this study, we observed the effects of EA in regulating pain memory-related behaviors and synchronous neural oscillations in the rostral anterior cingulate cortex (rACC). During nociceptive behavioral testing, pain memory induced a nonpain stimulus that spurred a neural oscillatory reaction similar to that caused by pain stimuli in the rACC. After EA, nonpain stimuli did not induce decreased neural oscillatory activity in the rACC until the presentation of pain stimuli. During aversive behavioral testing, EA, through the downregulation of theta power, inhibited the retrieval of aversive memory and relieved pain memory-induced aversive behaviors. These changes of oscillatory activity may be the hallmarks of EA therapy for pain memory.

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

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.

Synchrony changes on different time-scales during in vitro neuronal network development

Synchrony changes on different time-scales during in vitro neuronal network development

P119 Repetitive TMS can modulate local phase and global phase synchronization of human brain activity

The brain is certainly a nonlinear dynamical system which exhibits intriguing features such as oscillations and synchronization of neural activity. A number of studies have indicated that synchronous neuronal oscillations in different frequency bands are responsible for distinct classes of cognitive processes, e.g. perception and cognition. Furthermore, large-scale phase synchronization of oscillatory activity is a plausible mechanism for network communication between distant areas. To gain a further understanding of the causal links between phase synchronous neural oscillations and cognitive functions, we tested if we can directly manipulate the local and global phase dynamics of ongoing oscillations by TMS (Transcranial magnetic stimulation)-EEG (Electroencephalography) concurrent recordings in the human brain. Fourteen healthy volunteers participated in the experiment after giving written informed consent. While participants fixate a central cross with earplugs to attenuate TMS click sound, single-shot TMS, or repetitive TMS (rTMS) (5, 11, 23 Hz, 5-pulse trains) were delivered to the right visual or the left motor cortices at the intensity of 90% active motor threshold. We removed TMS-related EEG artifact by a combination of linear interpolation and ICA. We assessed spatiotemporal profiles regarding instantaneous phase and amplitude dynamics for the EEG data. At the local stimulation site, we observed prominent phase locking at each stimulation frequency in both visual and motor cortices. We found that phase locking was progressively enhanced by successive TMS pulses within a stimulus train. Moreover, the enhanced phase locking was likely to last for a few cycles after stimulation. Intriguingly, phase synchronization between the stimulation area and other brain areas was also enhanced at the stimulation frequency. We have demonstrated that rTMS can control local and global phase synchronization of ongoing oscillations in a frequency-specific way. rTMS, therefore, can be a promising tool for probing causal links between large-scale phase synchronization and brain functions in future We suggest that there is a great potential to aid and augment the disabled human performance associated with impaired synchrony by boosting synchrony in a frequency-specific manner by rTMS.

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

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.

Steady-state BOLD Response to Higher-order Cognition Modulates Low-Frequency Neural Oscillations.

Steady-state responses (SSRs) reflect the synchronous neural oscillations evoked by noninvasive and consistently repeated stimuli at the fundamental or harmonic frequencies. The steady-state evoked potentials (SSEPs; the representative form of the SSRs) have been widely used in the cognitive and clinical neurosciences and brain-computer interface research. However, the steady-state evoked potentials have limitations in examining high-frequency neural oscillations and basic cognition. In addition, synchronous neural oscillations in the low frequency range (<1 Hz) and in higher-order cognition have received a little attention. Therefore, we examined the SSRs in the low frequency range using a new index, the steady-state BOLD responses (SSBRs) evoked by semantic stimuli. Our results revealed that the significant SSBRs were induced at the fundamental frequency of stimuli and the first harmonic in task-related regions, suggesting the enhanced variability of neural oscillations entrained by exogenous stimuli. The SSBRs were independent of neurovascular coupling and characterized by sensorimotor bias, an indication of regional-dependent neuroplasticity. Furthermore, the amplitude of SSBRs may predict behavioral performance and show the psychophysiological relevance. Our findings provide valuable insights into the understanding of the SSRs evoked by higher-order cognition and how the SSRs modulate low-frequency neural oscillations.

Neural Oscillations and Synchrony in Brain Dysfunction and Neuropsychiatric Disorders: It's About Time.

Neural oscillations are rhythmic fluctuations over time in the activity or excitability of single neurons, local neuronal populations or "assemblies," and/or multiple regionally distributed neuronal assemblies. Synchronized oscillations among large numbers of neurons are evident in electrocorticographic, electroencephalographic, magnetoencephalographic, and local field potential recordings and are generally understood to depend on inhibition that paces assemblies of excitatory neurons to produce alternating temporal windows of reduced and increased excitability. Synchronization of neural oscillations is supported by the extensive networks of local and long-range feedforward and feedback bidirectional connections between neurons. Here, we review some of the major methods and measures used to characterize neural oscillations, with a focus on gamma oscillations. Distinctions are drawn between stimulus-independent oscillations recorded during resting states or intervals between task events, stimulus-induced oscillations that are time locked but not phase locked to stimuli, and stimulus-evoked oscillations that are both time and phase locked to stimuli. Synchrony of oscillations between recording sites, and between the amplitudes and phases of oscillations of different frequencies (cross-frequency coupling), is described and illustrated. Molecular mechanisms underlying gamma oscillations are also reviewed. Ultimately, understanding the temporal organization of neuronal network activity, including interactions between neural oscillations, is critical for elucidating brain dysfunction in neuropsychiatric disorders.

Cognitive Rehabilitation and Modulating Neuroplasticity with Brain Stimulation: Promises and Challenges

A substantial proportion of the severe functional disability observed in patients with schizophrenia is attributable to their persistent negative symptoms and cognitive deficits [1, 2]. Identifying these determinants of functional disability becomes even more crucial when patients remit from their florid hallucinations and delusions [3]. Indeed, there are very few evidence-guided interventions (e.g., cognitive remediation) that specifically target the neural systems underlying the persistent cognitive and volitional impairments. Despite showing promising results, the magnitude of benefits from cognitive remediation strategies could at best be described as modest [4]. It is therefore critical to explore and empirically examine alternative strategies to ameliorate cognitive deficits and improve functional outcome. The core deficits in schizophrenia are increasingly being viewed as resulting from aberrant neuroplasticity, operating at multiple mechanistic levels of brain functioning— such as synapses, axons, glia and network plasticity. This maladaptive ‘‘dysplasticity’’ may involve both hypoplastic changes in strategic brain networks supporting cognitive functions and goal-directed behavior or volition, and hyperplastic changes in neural systems governing salience detection, emotion regulation as well as default mode systems [5]. A range of neurophysiological investigations probing plasticity at multiple levels supports these conclusions. For example, synchronous neural oscillations during spindle sleep, which have been considered, as markers of learningrelated synaptic plasticity are reduced in schizophrenia. Moreover, they also predict deficits in attention, motor learning and executive functions [6, 7]. Similarly, pairing median nerve stimulation with transcranial magnetic stimulation (TMS) over the motor cortex produces lesser plasticity-dependent facilitation of motor potentials in schizophrenia when compared with healthy subjects; these plasticity-impairments were also significantly associated with the motor learning deficits observed in these patients [8]. One strategy that has promising therapeutic potential to adaptively modulate neuroplasticity is the use of non-invasive brain stimulation using TMS or transcranial direct current stimulation (tDCS). TMS is a non-convulsive method of modulating focal brain activity via induced electrical currents that result in neuronal depolarization. Repeated pulses (rTMS) administered at low (B1 Hz) and high frequencies (C5 Hz) can either inhibit or enhance the underlying cortical activity respectively [9]. The application of TMS in treating cognitive deficits, supported by advancing neurobiological evidence is only recently gaining momentum [10]. For instance, 4-weeks of 20-Hz rTMS delivered to bilateral dorsolateral prefrontal cortices resulted in significant improvement on working memory performance in schizophrenia patients, when compared to sham TMS [11]. Potentiation of task-evoked frontal gamma oscillatory activity may mediate this response [12]. However, another study using unilateral (left) 10-Hz rTMS to the dorsolateral prefrontal cortex did not find similar benefits [13]. Initial evidence suggests that social cognition deficits may also benefit from high frequency rTMS to the & Urvakhsh Meherwan Mehta urvakhsh@gmail.com

Neocortical pathological high-frequency oscillations are associated with frequency-dependent alterations in functional network topology

Synchronization of neural oscillations is thought to integrate distributed neural populations into functional cell assemblies. Epilepsy is widely regarded as a disorder of neural synchrony. Knowledge is scant, however, regarding whether ictal changes in synchrony involving epileptogenic cortex are expressed similarly across various frequency ranges. Cortical regions involved in epileptic networks also exhibit pathological high-frequency oscillations (pHFOs, >80 Hz), which are increasingly utilized as biomarkers of epileptogenic tissue. It is uncertain how pHFO amplitudes are related to epileptic network connectivity. By calculating phase-locking values among intracranial electrodes implanted in children with intractable epilepsy, we constructed ictal connectivity networks and performed graph theoretical analysis to characterize their network properties at distinct frequency bands. Ictal data from 17 children were analyzed with a hierarchical mixed-effects model adjusting for patient-level covariates. Epileptogenic cortex was defined in two ways: 1) a hypothesis-driven method using the visually defined seizure-onset zone and 2) a data-agnostic method using the high-frequency amplitude of each electrode. Epileptogenic cortex exhibited a logarithmic decrease in interregional functional connectivity at high frequencies (>30 Hz) during seizure initiation and propagation but not at termination. At slower frequencies, conversely, epileptogenic cortex expressed a relative increase in functional connectivity. Our findings suggest that pHFOs reflect epileptogenic network interactions, yielding theoretical support for their utility in the presurgical evaluation of intractable epilepsy. The view that abnormal network synchronization plays a critical role in ictogenesis and seizure dynamics is supported by the observation that functional isolation of epileptogenic cortex at high frequencies is absent at seizure termination.

P 197. Frequency-specific directed connectivity and information flow in large-scale synchrony networks in the human brain-A TMS-EEG manipulative approach

Synchronous neural oscillations are important in mediating information processing in the brain. To our knowledge, no study, however, has succeeded in analyzing directed connectivity and information flow in large-scale synchrony networks in humans. We therefore propose a novel manipulative approach for estimating frequency-specific network connectivity and information flow. We analyzed how single-shot TMS-modulated phase dynamics of ongoing oscillations at one cortical area propagates to the rest of the brain using phase resetting and amplitude measures in combination with an information flow measure, namely, transfer entropy. Using TMS-compatible electroencephalography (EEG) amplifiers, we recorded TMS-modulated ongoing brain activity while participants (N = 26 in total) sit on a chair with their eyes closed or eyes open fixating a gray cross. We targeted single-pulse TMS to the left primary motor cortex (95% motor threshold) or the visual cortex (95% phosphene threshold). First, we computed the instantaneous phase and amplitude of the filtered EEG signals. Next we calculated the phase locking values across trials as a measure for TMS-induced phase resetting at each electrode at different frequencies. We analyzed spatial propagation of TMS-induced phase resetting and amplitude changes. Finally, we estimated directed information flow between EEG phase signals and amplitude signals by transfer entropy ( Schreiber, 2000 ). We found prominent phase resetting of ongoing oscillations elicited by TMS. The phase resetting propagated from the stimulated area to the rest of the brain at various frequency bands. The spatio-temporal patterns of propagation of phase resetting were frequency-specific and state-dependent ( Fig. 1 ). Specifically we found more prominent global propagation of phase resetting in the eyes-open condition than in the eyes-closed condition most prominently at the 10 Hz alpha band in both motor and visual area targeted experiments. Amplitude changes were also frequency-specific and state-dependent. Significant increase of directed information flow from the stimulated area to the rest of the brain estimated by transfer entropy was also observed in the phase dynamics in all experimental conditions. We propose that this manipulative approach by TMS/EEG in combination with the transfer entropy method is good for estimating directed connectivity and information flow in the cortical and/or thalamocortical synchrony networks in the intact human brain. Since propagation of TMS-induced phase resetting is a robust and causal phenomenon, we can adjust and evaluate parameters of causality measures such as transfer entropy and Granger causality, which can indirectly assess directed connectivity and information flow from time series data. The results indicate that alpha synchrony networks are more globally connected in eyes-open condition than in eyes-closed condition, which is not obvious from indirect methods such as phase synchronization analyses of ongoing EEG activity, presumably associated with differences in gating of visual information processing.

Emotion regulation by cognitive reappraisal — The role of frontal theta oscillations

The regulation of emotion by cognitive reappraisal has attracted a lot of attention over the last decade. Studies using functional magnetic resonance imaging (fMRI) revealed a wide-spread network of multiple prefrontal and sub-cortical brain regions involved in the successful decrease of negative emotions. However, less is known about the temporal dynamics and the physiological mechanisms underlying these regulation processes. Synchronization of neural oscillations in specific frequency bands plays a key-role in the long-range interaction of different brain regions and oscillatory coupling in the theta frequency range was recently identified to play an important role in the interaction of prefrontal structures, the amygdala and the hippocampus in animal models. Accordingly, we investigated the role of prefrontal theta oscillations during the cognitive reappraisal of aversive pictures in humans. We hypothesized an increase in frontal theta oscillations during emotion regulation and a relationship between frontal theta power and the subjective success of emotion regulation. EEG from 30 healthy participants was recorded while they were asked to passively watch or reappraise the content of pictures with negative content. As expected, we found a significant increase in frequencies around 4Hz at electrode Fz during the regulation condition ‘decrease’ compared to the ‘maintain’ condition (p=.006) as well as for the regulation condition ‘increase’ compared to the ‘maintain’ condition (p=.017). Additionally, the strength of theta power was positively correlated with the regulation success as reported by the participants (r=0.463, p<.05). The estimation of possible generators of the theta oscillations was done using standardized low resolution electromagnetic tomography (sLORETA). Results suggested the left middle/inferior frontal gyrus as a possible generator. The results of the present study are in line with previous findings of fMRI studies suggesting the same regions as part of the regulation network and provide a first direct link between the imaging based knowledge of emotion regulation and a possible physiological mechanism.