EEG gamma-band phase synchronization between posterior and frontal cortex during mental rotation in humans

Early musical training benefits to non-musical cognitive ability associated with the Gestalt principles

Musical training has been evidenced to facilitate music perception, which refers to the consistencies, boundaries, and segmentations in pieces of music that are associated with the Gestalt principles. The current study aims to test whether musical training is beneficial to non-musical cognitive ability with Gestalt principles. Three groups of Chinese participants (with early, late, and no musical training) were compared in terms of their performances on the Motor-Free Visual Perception Test (MVPT). The results show that the participants with early musical training had significantly better performance in the Gestalt-like Visual Closure subtest than those with late and no musical training, but no significances in other Gestalt-unlike subtests was identified (Visual Memory, Visual Discrimination, Spatial Relationship, Figure Ground in MVPT). This study suggests the benefit of early musical training on non-musical cognitive ability with Gestalt principles.

Resting State Dynamic Reconfiguration of Spatial Attention Cortical Networks and Visuospatial Functioning in Non-Verbal Learning Disability (NVLD): A HD-EEG Investigation

Nonverbal learning disability (NVLD) is a neurodevelopmental disorder characterized by deficits in visuospatial processing but spared verbal competencies. Neurocognitive markers may provide confirmatory evidence for characterizing NVLD as a separate neurodevelopmental disorder. Visuospatial performance and high-density electroencephalography (EEG) were measured in 16 NLVD and in 16 typically developing (TD) children. Cortical source modeling was applied to assess resting-state functional connectivity (rs-FC) in spatial attention networks (dorsal (DAN) and ventral attention networks (VAN)) implicated in visuospatial abilities. A machine-learning approach was applied to investigate whether group membership could be predicted from rs-FC maps and if these connectivity patterns were predictive of visuospatial performance. Graph theoretical measures were applied to nodes inside each network. EEG rs-FC maps in the gamma and beta band differentiated children with and without NVLD, with increased but more diffuse and less efficient functional connections bilaterally in the NVLD group. While rs-FC of the left DAN in the gamma range predicted visuospatial scores for TD children, in the NVLD group rs-FC of the right DAN in the delta range predicted impaired visuospatial performance, confirming that NVLD is a disorder with a predominant dysfunction in right hemisphere connectivity patterns.

Enhanced effective connectivity from the middle frontal gyrus to the parietal lobe is associated with impaired mental rotation after total sleep deprivation: An electroencephalogram study

Sleep deprivation impairs cognitive functions, including attention, memory, and decision-making. Studies on the neuro-electro-physiological mechanisms underlying total sleep deprivation (TSD) that impairs spatial cognition are limited. Based on electroencephalogram (EEG) and Exact Low Resolution Brain Electromagnetic Tomography (eLORETA), this study focused on the effects of TSD on mental rotation and the cognitive neural mechanisms underlying its damage. Twenty-four healthy college students completed mental rotation tasks while resting and after 36 h of TSD; their EEG data were simultaneously recorded. The amplitude of P300 component associated with mental rotation was observed and localized through source reconstruction, while changes in effective connectivity between multiple brain regions associated with mental rotation cognitive processing were calculated using isolated effective coherence (iCoh) of eLORETA. Compared with the baseline before TSD, the amplitude of the P300 component related to mental rotation decreased. The task-state data of P300 were localized to the source of the difference in ERP current density, and it was found that the brain regions related to the difference in the decrease in P300 amplitude included the superior parietal lobule, precuneus, prefrontal lobe, and other related regions. Effective connectivity analysis found that TSD enhanced the effective connectivity from the left middle frontal gyrus to the left superior parietal lobule, left inferior parietal lobule, and left precuneus under the identical condition. Pearson correlation analysis showed a positive correlation between the decrease in accuracy of mental rotation and increase in effective connectivity. Thus, our study suggests that TSD impairs the ability of the mental rotation, showing a decrease in P300 amplitude and an enhanced effective connectivity between the middle frontal gyrus and the parietal lobe in the task state.

Gamma-band synchronisation in a frontotemporal auditory information processing network

Neural oscillations are fundamental mechanisms of the human brain that enable coordinated activity of different brain regions during perceptual and cognitive processes. A frontotemporal network generated by means of gamma oscillations and comprising the auditory cortex (AC) and the anterior cingulate cortex (ACC) has been shown to be involved in the cognitively demanding auditory information processing. This study aims to reveal patterns of functional and effective connectivity within this network in healthy subjects by means of simultaneously recorded electroencephalography (EEG) and functional magnetic resonance imaging (fMRI). We simultaneously recorded EEG and fMRI in 28 healthy subjects during the performance of a cognitively demanding auditory choice reaction task. Connectivity between the ACC and AC was analysed employing EEG and fMRI connectivity measures. We found a significant BOLD signal correlation between the ACC and AC, a significant task-dependant increase of fMRI connectivity (gPPI) and a significant increase in functional coupling in the gamma frequency range between these regions (LPS), which was increased in top-down direction (granger analysis). EEG and fMRI connectivity measures were positively correlated. The results of these study point to a role of a top-down influence of the ACC on the AC executed by means of gamma synchronisation. The replication of fMRI connectivity patterns in simultaneously recorded EEG data and the correlation between connectivity measures from both domains found in our study show, that brain connectivity based on the synchronisation of gamma oscillations is mirrored in fMRI connectivity patterns.

Music Training, Working Memory, and Neural Oscillations: A Review

This review focuses on reports that link music training to working memory and neural oscillations. Music training is increasingly associated with improvement in working memory, which is strongly related to both localized and distributed patterns of neural oscillations. Importantly, there is a small but growing number of reports of relationships between music training, working memory, and neural oscillations in adults. Taken together, these studies make important contributions to our understanding of the neural mechanisms that support effects of music training on behavioral measures of executive functions. In addition, they reveal gaps in our knowledge that hold promise for further investigation. The current review is divided into the main sections that follow: (1) discussion of behavioral measures of working memory, and effects of music training on working memory in adults; (2) relationships between music training and neural oscillations during temporal stages of working memory; (3) relationships between music training and working memory in children; (4) relationships between music training and working memory in older adults; and (5) effects of entrainment of neural oscillations on cognitive processing. We conclude that the study of neural oscillations is proving useful in elucidating the neural mechanisms of relationships between music training and the temporal stages of working memory. Moreover, a lifespan approach to these studies will likely reveal strategies to improve and maintain executive function during development and aging.

Gamma electroencephalographic coherence and theory of mind in healthy subjects

PURPOSE

Structural brain imaging has revealed that damage to different brain regions may impair theory of mind (ToM) while functional imaging has shown that distributed neural circuits are activated by ToM and empathy. However, the coherence of the electroencephalogram (EEG) frequencies in a definite time span may change during these processes, indicating different neurophysiological correlates. This study evaluated the changes of EEG coherence during ToM tasks in comparison with Empathy, Physical causality, and baseline conditions, aiming to determine the neurophysiological correlates of ToM.

METHODS

Sixteen healthy adults underwent a visual activation paradigm using 30 comic strips concerning ToM, Empathy, or Physical causality during EEG recording. The interhemispheric coherence was estimated using a bivariate autoregressive (AR) parametric model. The coherence spectra were analyzed in the alpha, beta, and gamma frequency EEG bands.

RESULTS

Coherence analysis taking all of the responses showed that in the gamma band, in comparison with the Empathy, Physical causality, and baseline conditions, ToM was associated with significantly higher peaks between the frontal and parietal areas in the right hemisphere and, in comparison with the Physical causality and baseline conditions, in the left hemisphere. Analysis taking the correct responses confirmed these results.

CONCLUSIONS

In healthy adults, ToM processes are associated with immediate specific changes of brain connectivity, as expressed by high cortical coherence within the right frontal and parietal areas. These previously unexplored aspects indicate an online involvement of the right hemisphere networks in normal ToM. In patients with epilepsy, the study of EEG coherence during specific tasks may help determine the neural dysfunctions associated with impaired ToM. This article is part of the Special Issue "Epilepsy and social cognition across the lifespan".

Electroencephalographic Motor Imagery Brain Connectivity Analysis for BCI: A Review

Recent research has reached a consensus on the feasibility of motor imagery brain-computer interface (MI-BCI) for different applications, especially in stroke rehabilitation. Most MI-BCI systems rely on temporal, spectral, and spatial features of single channels to distinguish different MI patterns. However, no successful communication has been established for a completely locked-in subject. To provide more useful and informative features, it has been recommended to take into account the relationships among electroencephalographic (EEG) sensor/source signals in the form of brain connectivity as an efficient tool of neuroscience. In this review, we briefly report the challenges and limitations of conventional MI-BCIs. Brain connectivity analysis, particularly functional and effective, has been described as one of the most promising approaches for improving MI-BCI performance. An extensive literature on EEG-based MI brain connectivity analysis of healthy subjects is reviewed. We subsequently discuss the brain connectomes during left and right hand, feet, and tongue MI movements. Moreover, key components involved in brain connectivity analysis that considerably affect the results are explained. Finally, possible technical shortcomings that may have influenced the results in previous research are addressed and suggestions are provided.

Representation of cognitive reappraisal goals in frontal gamma oscillations

Recently, numerous efforts have been made to understand the neural mechanisms underlying cognitive regulation of emotion, such as cognitive reappraisal. Many studies have reported that cognitive control of emotion induces increases in neural activity of the control system, including the prefrontal cortex and the dorsal anterior cingulate cortex, and increases or decreases (depending upon the regulation goal) in neural activity of the appraisal system, including the amygdala and the insula. It has been hypothesized that information about regulation goals needs to be processed through interactions between the control and appraisal systems in order to support cognitive reappraisal. However, how this information is represented in the dynamics of cortical activity remains largely unknown. To address this, we investigated temporal changes in gamma band activity (35-55 Hz) in human electroencephalograms during a cognitive reappraisal task that was comprised of three reappraisal goals: to decease, maintain, or increase emotional responses modulated by affect-laden pictures. We examined how the characteristics of gamma oscillations, such as spectral power and large-scale phase synchronization, represented cognitive reappraisal goals. We found that left frontal gamma power decreased, was sustained, or increased when the participants suppressed, maintained, or amplified their emotions, respectively. This change in left frontal gamma power appeared during an interval of 1926 to 2453 ms after stimulus onset. We also found that the number of phase-synchronized pairs of gamma oscillations over the entire brain increased when participants regulated their emotions compared to when they maintained their emotions. These results suggest that left frontal gamma power may reflect cortical representation of emotional states modulated by cognitive reappraisal goals and gamma phase synchronization across whole brain regions may reflect emotional regulatory efforts to achieve these goals. Our study may provide the basis for an electroencephalogram-based neurofeedback system for the cognitive regulation of emotion.

Cross-modal facilitation of mental rotation: effects of modality and complexity

Performance in a visual mental rotation (MR) task has been reported to predict the ability to recognize retrograde-transformed melodies. The current study investigated the effects of melodic structure on the MR of sequentially presented visual patterns. Each trial consisted of a five-segment sequentially presented visual pattern (standard) followed by a five-tone melody that was either identical in structure to the standard or its retrograde. A visual target pattern was either the rotated version of the standard or unrelated to it. The task was to indicate whether the target pattern was a rotated version of the standard or not. Periodic patterns were not rotated but melodies facilitated the rotation of non-periodic patterns. For these, rotation latency was determined by a quantitative index of complexity (number of runs). This study provides the first experimental confirmation for cross-modal facilitation of MR.

Epileptic neuronal networks: methods of identification and clinical relevance

The main objective of this paper is to examine evidence for the concept that epileptic activity should be envisaged in terms of functional connectivity and dynamics of neuronal networks. Basic concepts regarding structure and dynamics of neuronal networks are briefly described. Particular attention is given to approaches that are derived, or related, to the concept of causality, as formulated by Granger. Linear and non-linear methodologies aiming at characterizing the dynamics of neuronal networks applied to EEG/MEG and combined EEG/fMRI signals in epilepsy are critically reviewed. The relevance of functional dynamical analysis of neuronal networks with respect to clinical queries in focal cortical dysplasias, temporal lobe epilepsies, and "generalized" epilepsies is emphasized. In the light of the concepts of epileptic neuronal networks, and recent experimental findings, the dichotomic classification in focal and generalized epilepsy is re-evaluated. It is proposed that so-called "generalized epilepsies," such as absence seizures, are actually fast spreading epilepsies, the onset of which can be tracked down to particular neuronal networks using appropriate network analysis. Finally new approaches to delineate epileptogenic networks are discussed.

A note on the phase locking value and its properties

We investigate the properties of the Phase Locking Value (PLV) and the Phase Lag Index (PLI) as metrics for quantifying interactions in bivariate local field potential (LFP), electroencephalography (EEG) and magnetoencephalography (MEG) data. In particular we describe the relationship between nonparametric estimates of PLV and PLI and the parameters of two distributions that can both be used to model phase interactions. The first of these is the von Mises distribution, for which the sample PLV is a maximum likelihood estimator. The second is the relative phase distribution associated with bivariate circularly symmetric complex Gaussian data. We derive an explicit expression for the PLV for this distribution and show that it is a function of the cross-correlation between the two signals. We compare the bias and variance of the sample PLV and the PLV computed from the cross-correlation. We also show that both the von Mises and Gaussian models are suitable for representing relative phase in application to LFP data from a visually-cued motor study in macaque. We then compare results using the two different PLV estimators and conclude that, for this data, the sample PLV provides equivalent information to the cross-correlation of the two complex time series.

Covert tracking: a combined ERP and fixational eye movement study

Attention can be directed to particular spatial locations, or to objects that appear at anticipated points in time. While most work has focused on spatial or temporal attention in isolation, we investigated covert tracking of smoothly moving objects, which requires continuous coordination of both. We tested two propositions about the neural and cognitive basis of this operation: first that covert tracking is a right hemisphere function, and second that pre-motor components of the oculomotor system are responsible for driving covert spatial attention during tracking. We simultaneously recorded event related potentials (ERPs) and eye position while participants covertly tracked dots that moved leftward or rightward at 12 or 20°/s. ERPs were sensitive to the direction of target motion. Topographic development in the leftward motion was a mirror image of the rightward motion, suggesting that both hemispheres contribute equally to covert tracking. Small shifts in eye position were also lateralized according to the direction of target motion, implying covert activation of the oculomotor system. The data addresses two outstanding questions about the nature of visuospatial tracking. First, covert tracking is reliant upon a symmetrical frontoparietal attentional system, rather than being right lateralized. Second, this same system controls both pursuit eye movements and covert tracking.

Connectivity measures applied to human brain electrophysiological data

Connectivity measures are (typically bivariate) statistical measures that may be used to estimate interactions between brain regions from electrophysiological data. We review both formal and informal descriptions of a range of such measures, suitable for the analysis of human brain electrophysiological data, principally electro- and magnetoencephalography. Methods are described in the space-time, space-frequency, and space-time-frequency domains. Signal processing and information theoretic measures are considered, and linear and nonlinear methods are distinguished. A novel set of cross-time-frequency measures is introduced, including a cross-time-frequency phase synchronization measure.

Influence of connection type on phase synchrony: analysis of a neural mass model

Empirical studies have demonstrated synchronized frontal and parietal electrophysiological signals at 22-34 Hz during a conjunctive visual search task and at 36-56 Hz during a pop-out visual search task. Bidirectional (conjunctive) versus unidirectional (pop-out) information transfer between neuronal populations is hypothesized to underly this difference in synchronization frequency. This study modeled the influence of connection type (i.e., unidirectional vs. bidirectional) on phase synchrony between two neural populations using a neural mass model. Phase-locking values (PLVs) were used as the measure of synchrony between populations. Consistent with the connectivity hypothesis, the model revealed greater PLVs at 22-34 Hz when the two populations were connected bidirectionally than unidirectionally, but greater PLVs at 34-52 Hz when connected unidirectionally than bidirectionally. The model suggests that inter-population connectivity also changes with bottom-up versus top-down control of attention.

Information processing in brain and dynamic patterns of transmission during working memory task by the SDTF function

We studied the dynamical pattern of transmission involved in the information processing during cognitive experiments engaging working memory. The ensemble averaging approach was used to fit a multichannel autoregressive model to the EEG signals recorded during the transitive reasoning task. The short-time directed transfer function was estimated for finding dynamical patterns of functional connectivity during the memory and reasoning task. The results indicated that there exist particular areas where information is processed as envisaged by transmissions between closely located electrodes. In case of reasoning task these local circuits were located in frontal and parietal regions. These areas (these local circuits) from time to time exchange information between each other‥

Deficits in fronto-posterior interactions point to inefficient resource allocation in schizophrenia

OBJECTIVE

Fronto-posterior networks have been implicated in various cognitive processes that are impaired in schizophrenia. This is the first study on time and frequency resolved fronto-posterior coherence during cognitive control in schizophrenia.

METHOD

We examined 16 schizophrenic/schizoaffective patients and 20 age-matched controls performing a choice-reaction task. Fronto-posterior coherence was analyzed for event-related increases with respect to the inter-trial interval. Furthermore, we compared the two groups for event-related coherence during the task-related time intervals which showed a significant coherence increase with respect to the inter-trial interval, as well as for absolute coherence during the inter-trial interval.

RESULTS

Event-related coherence was significantly reduced in patients during time intervals (0-250 ms poststimulus) when controls showed significant event-related coherence increases. However, patients showed significantly higher absolute coherence during the inter-trial interval. These results pointed to differential deficits in fronto-posterior connectivity during the inter-trial interval and task-related conditions in schizophrenia.

CONCLUSION

Cognitive deficits in schizophrenia might be driven by abnormal fronto-posterior communication. Task-related hypo-connectivity and inter-trial interval hyper-connectivity point to resource allocation deficits. The timing of cortico-cortical interactions during crucial task-related intervals may be impaired, while frontal and posterior areas may exhibit increased interactions between the trials.

Enhanced brain connectivity in math-gifted adolescents: An fMRI study using mental rotation

Mathematical giftedness is a form of intelligence related to enhanced mathematical reasoning that can be tested using a variety of numerical and spatial tasks. A number of neurobiological mechanisms related to exceptional mathematical reasoning ability have been postulated, including enhanced brain connectivity. We aimed to further investigate this possibility by comparing a group of mathematically gifted adolescents with an average math ability control group performing mental rotation of complex three-dimensional block figures. Functional magnetic resonance imaging (fMRI) data were collected and differences in intrahemispheric and interhemispheric connectivity between the groups were assessed using structural equation modeling (SEM). The math-gifted showed heightened intrahemispheric frontoparietal connectivity, as well as enhanced interhemispheric frontal connectivity between the dorsolateral prefrontal and premotor cortex. These enhanced connectivity patterns are consistent with previous studies linking increased activation of the frontal and parietal regions with high fluid intelligence, and may be a unique neural characteristic of the mathematically gifted brain.

Information transfer during a transitive reasoning task

For about two decades now, the localization of the brain regions involved in reasoning processes is being investigated through fMRI studies, and it is known that for a transitive form of reasoning the frontal and parietal regions are most active. In contrast, less is known about the information exchange during the performance of such complex tasks. In this study, the propagation of brain activity during a transitive reasoning task was investigated and compared to the propagation during a simple memory task. We studied EEG transmission patterns obtained for physiological indicators of brain activity and determined whether there are frequency bands specifically related to this type of cognitive operations. The analysis was performed by means of the directed transfer function. The transmission patterns were determined in the theta, alpha and gamma bands. The results show stronger transmissions in theta and alpha bands from frontal to parietal as well as within frontal regions in reasoning trials comparing to memory trials. The increase in theta and alpha transmissions was accompanied by flows in gamma band from right posterior to left posterior and anterior sites. These results are consistent with previous neuroimaging (fMRI) data concerning fronto-parietal regions involvement in reasoning and working memory processes and also provide new evidence for the executive role of frontal theta waves in organizing the cognition.

The application of graph theoretical analysis to complex networks in the brain

Considering the brain as a complex network of interacting dynamical systems offers new insights into higher level brain processes such as memory, planning, and abstract reasoning as well as various types of brain pathophysiology. This viewpoint provides the opportunity to apply new insights in network sciences, such as the discovery of small world and scale free networks, to data on anatomical and functional connectivity in the brain. In this review we start with some background knowledge on the history and recent advances in network theories in general. We emphasize the correlation between the structural properties of networks and the dynamics of these networks. We subsequently demonstrate through evidence from computational studies, in vivo experiments, and functional MRI, EEG and MEG studies in humans, that both the functional and anatomical connectivity of the healthy brain have many features of a small world network, but only to a limited extent of a scale free network. The small world structure of neural networks is hypothesized to reflect an optimal configuration associated with rapid synchronization and information transfer, minimal wiring costs, resilience to certain types of damage, as well as a balance between local processing and global integration. Eventually, we review the current knowledge on the effects of focal and diffuse brain disease on neural network characteristics, and demonstrate increasing evidence that both cognitive and psychiatric disturbances, as well as risk of epileptic seizures, are correlated with (changes in) functional network architectural features.

Large-Scale Gamma-Band Phase Synchronization and Selective Attention

Explaining the emergence of a coherent conscious percept and an intentional agent from the activity of distributed neurons is key to understanding how the brain produces higher cognitive processes. Gamma-band synchronization has been proposed to be a mechanism for the functional integration of neural populations that together form a transitory, large-scale, task- and/or percept-specific network. The operation of this mechanism in the context of attention orienting entails that cortical regions representing attended locations should show more gamma-band synchronization with other cortical areas than would those representing unattended locations. This increased synchronization should be apparent in the same time frame as that of the deployment of attention to a particular location. In order to observe this effect, we made electroencephalogram recordings while subjects attended to one side or the other of the visual field (which we confirmed by event-related potential analysis) and calculated phase-locking statistics between the signals recorded at relevant electrode pairs. We observed increased gamma-band phase synchronization between visual cortex contralateral to the attended location and other, widespread, cortical areas approximately 240-380 ms after the directional cue was presented, confirming the prediction of a large-scale gamma synchronous network oriented to the cued location.

Oscillatory gamma and theta activity during repeated mental manipulations of a visual image

Previous studies on mental manipulation have dealt with direct manipulation of a presented stimulus or a maintained image of a previously presented stimulus. Here, we investigated brain activity differences between successive maintenance and manipulation of the visual stimulus and the once transformed representations using electroencephalography (EEG) in a multi-stage sequential manipulation task. The task required the subjects to memorize a presented object which possessed four features (color, shape, direction and speed of motion) and transform the feature of the representation twice. Wavelet analysis showed strong gamma-band (>30 Hz) activity elicited in the frontal and parietal regions during two successive mental manipulation tasks of the visual stimulus. Interestingly, gamma activity in the frontal and parietal regions was stronger during the second manipulation. Our results suggest that successive mental manipulations of the once transformed representation may impose higher demand on the fronto-parietal networks. On the other hand, while the frontal theta activity was enhanced throughout maintenance and manipulation periods, the activity during maintenance of one-time manipulated representation was higher than that of the physically presented stimulus, suggesting that the frontal regions are further recruited in maintenance of manipulated images.

Suppression of early evoked gamma band response in male alcoholics during a visual oddball task

We investigated the early evoked gamma frequency band activity in alcoholics (n=122) and normal controls (n=72) during a visual oddball task. A time-frequency representation method was applied to EEG data in order to obtain phase-locked gamma band activity (29-45 Hz) and was analyzed within a 0-150 ms time window range. Significant reduction of the gamma band response in the frontal region during target stimulus processing was observed in alcoholic compared to control subjects. In contrast, significantly higher gamma band response for the non-target stimulus was observed in alcoholics compared to controls. It is suggested that the reduction in early evoked frontal gamma band response to targets may be associated with frontal lobe dysfunction commonly observed in alcoholics. This perhaps can be characterized by a deficient top-down processing mechanism.

Dynamic sculpting of brain functional connectivity and mental rotation aptitude

Changes in long-range synchronization are considered a key mechanism for the integration and segregation of cortical regions mediating cognitive processes. Such synchronization or functional connectivity is reflected in human electroencephalographic (EEG) coherence and in steady-state visually evoked potential (SSVEP) coherence. In this chapter, the relationship between cognitive proficiency in the mental rotation task (MRT) and functional connectivity reflected in SSVEP event-related partial coherence is described. The capacity to estimate changing levels of functional connectivity with a relatively high temporal resolution makes it possible to examine the relationship between functional connectivity at various points in time and aptitude. In the current study, the relationships between functional connectivity and two mental rotation aptitude measures, mental rotation speed and mental rotation accuracy, are described. We observed that functional connectivity was correlated with proficiency and that this correlation was both positive and negative for various regions and points in time. It is suggested that cognitive aptitude is related to the brain's capacity to enhance functional connectivity or communication between cortical regions that are relevant to the cognitive demands while attenuating irrelevant communication. This capacity is termed functional connectivity sculpting, and it is proposed that functional connectivity sculpting may constitute an important functional component of the neural substrate of learning and aptitude.

Nonlinear dynamical analysis of EEG and MEG: review of an emerging field

Many complex and interesting phenomena in nature are due to nonlinear phenomena. The theory of nonlinear dynamical systems, also called 'chaos theory', has now progressed to a stage, where it becomes possible to study self-organization and pattern formation in the complex neuronal networks of the brain. One approach to nonlinear time series analysis consists of reconstructing, from time series of EEG or MEG, an attractor of the underlying dynamical system, and characterizing it in terms of its dimension (an estimate of the degrees of freedom of the system), or its Lyapunov exponents and entropy (reflecting unpredictability of the dynamics due to the sensitive dependence on initial conditions). More recently developed nonlinear measures characterize other features of local brain dynamics (forecasting, time asymmetry, determinism) or the nonlinear synchronization between recordings from different brain regions. Nonlinear time series has been applied to EEG and MEG of healthy subjects during no-task resting states, perceptual processing, performance of cognitive tasks and different sleep stages. Many pathologic states have been examined as well, ranging from toxic states, seizures, and psychiatric disorders to Alzheimer's, Parkinson's and Cre1utzfeldt-Jakob's disease. Interpretation of these results in terms of 'functional sources' and 'functional networks' allows the identification of three basic patterns of brain dynamics: (i) normal, ongoing dynamics during a no-task, resting state in healthy subjects; this state is characterized by a high dimensional complexity and a relatively low and fluctuating level of synchronization of the neuronal networks; (ii) hypersynchronous, highly nonlinear dynamics of epileptic seizures; (iii) dynamics of degenerative encephalopathies with an abnormally low level of between area synchronization. Only intermediate levels of rapidly fluctuating synchronization, possibly due to critical dynamics near a phase transition, are associated with normal information processing, whereas both hyper-as well as hyposynchronous states result in impaired information processing and disturbed consciousness.

Spatial and temporal structure of phase synchronization of spontaneous alpha EEG activity

Spatiotemporal characteristics of spontaneous alpha EEG activity patterns are analyzed in terms of large-scale phase synchronization. During periods with strong phase synchronization over the entire scalp, phase patterns take either of two forms; one is a gradual phase shift between frontal and occipital regions and the other is a stepwise pattern with a sudden phase shift in the central region. The former is regarded as a traveling wave of electrocortical activity, of which the direction of propagation is predominantly from anterior to posterior in three out of four subjects, and opposite in the remaining one. The other activity pattern observed may correspond to a standing wave composed of two traveling waves propagating in opposite directions. The duration distributions of these patterns have similar forms within a subject, which suggests that they share the same mechanism for their generation.

Phase synchronization for the recognition of mental tasks in a brain-computer interface

Brain-computer interfaces (BCIs) may be a future communication channel for motor-disabled people. In surface electroencephalogram (EEG)-based BCIs, the extracted features are often derived from spectral estimates and autoregressive models. We examined the usefulness of synchronization between EEG signals for classifying mental tasks. To this end, we investigated the performance of features derived from the phase locking value (PLV) and from the spectral coherence and compared them to the classification rates resulting from the power densities in alpha, beta1, beta2, and 8-30-Hz frequency bands. Five recordings of 60 min, acquired from three subjects while performing three different mental tasks, were analyzed offline. No artifacts were removed or rejected. We noticed significant differences between PLV and mean spectral coherence. For sole use of synchronization measures, classification accuracies up to 62% were achieved. In general, the best result was obtained combining phase synchronization measures with alpha power spectral density estimates. The results demonstrate that phase synchronization provides relevant information for the classification of spontaneous EEG during mental tasks.

A post-processing/region of interest (ROI) method for discriminating patterns of activity in statistical maps of fMRI data

To combine functional neuroimaging studies across subjects, anatomical and functional data are typically either transformed to a common space or averaged across regions of interest (ROIs). However, if there are (1) anatomical variations within the subject pool (as in clinical or aging populations), (2) non-Gaussian distributions of task-related activity within a typical ROI or, (3) more ROIs than subjects, neither spatial transformation of the data to a common space nor averaging across all subjects' ROIs is suitable for standard discriminant analysis. To solve these problems, we describe a post-processing method that uses voxel-based statistics representing task-related activity (pooled within ROIs) to establish combinations of ROIs that maximally differentiate tasks across all subjects. The method involves randomized resampling from multiple ROIs within each subject, multivariate linear discriminant analysis across all subjects and validation with bootstrapping techniques. When applied to experimental data from healthy subjects performing two motor tasks, the method detected some brain regions, including the supplementary motor area (SMA), that participated in a distributed network differentially active between tasks. However there was not a significant difference in SMA activity when this region was examined in isolation. We suggest this method is a practical means to combine voxel-based statistics within anatomically defined ROIs across subjects.

Analysis of frequency components of cortical potentials evoked by progressive misalignment of Kanizsa squares

Cortical gamma oscillations (20-100 Hz) are thought to play an important role in encoding visual perception. If so they should emerge at about threshold. In the present investigation we examined the latter proposal. Visual responses were recorded in occipital, temporal and parietal areas (stimulus duration 512 ms). Oscillation strength and frequency were derived from FFT analysis and wavelet transforms. The specific goals of the present study are: 1: To examine the parallel between gamma oscillations and the psychometric threshold of perception of Kanizsa square (KS). The latter is gradually altered by a progressive misalignment of lower inducers (pacmen). Results show that the perception of the KS is altered by lateral displacements of the lower inducers as small as 0.1 to 0.2 degrees. In parallel, high frequency components of cortical responses gain in strength with misalignments. 2: Gamma oscillations emerge at or about the psychometric threshold. In addition, our data analysis demonstrates that gamma oscillations appear in short bursts (approx. 50 ms) in the time window between 200 and 500 ms after stimulus onset. Furthermore, controls indicated that these oscillations are of the induced-gamma type. Thus, our experiments suggest that gamma oscillations are associated with image structures and may be induced by local properties of the target.

Nonlinear synchronization in EEG and whole-head MEG recordings of healthy subjects

According to Friston, brain dynamics can be modelled as a large ensemble of coupled nonlinear dynamical subsystems with unstable and transient dynamics. In the present study, two predictions from this model (the existence of nonlinear synchronization between macroscopic field potentials and itinerant nonlinear dynamics) were investigated. The dependence of nonlinearity on the method of measuring brain activity (EEG vs. MEG) was also investigated. Dataset I consisted of 10 MEG recordings in 10 healthy subjects. Dataset II consisted of simultaneously recorded MEG (126 channels) and EEG (19 channels) in 5 healthy subjects. Nonlinear coupling was assessed with the synchronization likelihood S and dynamic itinerancy with the synchronization entropy Hs. Significance was assessed with a bootstrap procedure ("surrogate data testing"), comparing S and Hs with their distribution under the null hypothesis of stationary, linear dynamics. Significant nonlinear synchronization was detected in 14 of 15 subjects. The nonlinear dynamics were associated with a high index of itinerant behaviour. Nonlinear interdependence was significantly more apparent in MEG data than EEG. Synchronous oscillations in MEG and EEG recordings contain a significant nonlinear component that exhibits characteristics of unstable and itinerant behaviour. These findings are in line with Friston's proposal that the brain can be conceived as a large ensemble of coupled nonlinear dynamical subsystems with labile and unstable dynamics. The spatial scale and physical properties of MEG acquisition may increase the sensitivity of the data to underlying nonlinear structure.

Fronto-parietal evoked potential synchronization is increased during mental rotation

We used steady state visually evoked potential event related partial coherence (SSVEP-ERPC) to examine the SSVEP synchronization between brain regions while 22 males undertook a sequential version of the Shepard and Metzler mental rotation task. Compared to the 60 degrees rotation, the 180 degrees rotation was associated with increased synchronization between bilateral prefrontal and parieto-occipital sites, between left frontal and right parietal sites and between bilateral parietal and occipital sites. We suggest that the increased synchronization between prefrontal and parieto-occipital regions may be associated with the working memory components of the task, while the left frontal to right parietal synchronization may represent the increased interaction between these regions thought to occur in a variety of visuo-motor tasks.

Shadows of artistry: cortical synchrony during perception and imagery of visual art

Functional and topographical differences between two groups, artists and non-artists, during the performances of visual perception and imagery of paintings were presented by means of EEG phase synchrony analysis. In artists as compared with non-artists, significantly higher phase synchrony was found in the high frequency beta and gamma bands during the perception of the paintings; in the low frequency bands (primarily delta), phase synchrony was mostly enhanced during imagery. Strong decreases in phase synchrony of alpha were found primarily in artists for both tasks. The right hemisphere was found to present higher synchrony than the left in artists, whereas hemispheric asymmetry was less significant in non-artists. In the artists, enhanced synchrony in the high frequency band is most likely due to their enhanced binding capabilities of numerous visual attributes, and enhanced synchrony in the low frequency band seems to be due to the higher involvement of long-term visual memory mostly in imagery. Thus, the analysis of phase synchrony from EEG signals yields new information about the dynamical co-operation between neuronal assemblies during the cognition of visual art.

Universality in the brain while listening to music

The human brain, which is one of the most complex organic systems, involves billions of interacting physiological and chemical processes that give rise to experimentally observed neuroelectrical activity, which is called an electroencephalogram (EEG). The presence of non-stationarity and intermittency render standard available methods unsuitable for detecting hidden dynamical patterns in the EEG. In this paper, a method that is suitable for non-stationary signals and preserving the phase characteristics and that combines wavelet and Hilbert transforms was applied to multivariate EEG signals from human subjects at rest as well as in different cognitive states: listening to music, listening to text and performing spatial imagination. It was found that, if suitably rescaled, the gamma band EEG over distributed brain areas while listening to music can be described by a universal and homogeneous scaling, whereas this homogeneity in scale is reduced at resting conditions and also during listening to text and performing spatial imagination. The degree of universality is characterized by a Kullback-Leibler divergence measure. By statistical surrogate analysis, nonlinear phase interaction was found to play an important role in exhibiting universality among multiple cortical regions.