Transient Induced Gamma-Band Response in EEG as a Manifestation of Miniature Saccades

Auditory processing in noise is associated with complex patterns of disrupted functional connectivity in autism spectrum disorder

Autism spectrum disorder (ASD) is associated with difficulty in processing speech in a noisy background, but the neural mechanisms that underlie this deficit have not been mapped. To address this question, we used magnetoencephalography to compare the cortical responses between ASD and typically developing (TD) individuals to a passive mismatch paradigm. We repeated the paradigm twice, once in a quiet background, and once in the presence of background noise. We focused on both the evoked mismatch field (MMF) response in temporal and frontal cortical locations, and functional connectivity with spectral specificity between those locations. In the quiet condition, we found common neural sources of the MMF response in both groups, in the right temporal gyrus and inferior frontal gyrus (IFG). In the noise condition, the MMF response in the right IFG was preserved in the TD group, but reduced relative to the quiet condition in ASD group. The MMF response in the right IFG also correlated with severity of ASD. Moreover, in noise, we found significantly reduced normalized coherence (deviant normalized by standard) in ASD relative to TD, in the beta band (14-25 Hz), between left temporal and left inferior frontal sub-regions. However, unnormalized coherence (coherence during deviant or standard) was significantly increased in ASD relative to TD, in multiple frequency bands. Our findings suggest increased recruitment of neural resources in ASD irrespective of the task difficulty, alongside a reduction in top-down modulations, usually mediated by the beta band, needed to mitigate the impact of noise on auditory processing. Autism Res 2016,. © 2016 International Society for Autism Research, Wiley Periodicals, Inc. Autism Res 2017, 10: 631-647. © 2016 International Society for Autism Research, Wiley Periodicals, Inc.

Modulation of microsaccades by spatial frequency during object categorization

The organization of visual processing into a coarse-to-fine information processing based on the spatial frequency properties of the input forms an important facet of the object recognition process. During visual object categorization tasks, microsaccades occur frequently. One potential functional role of these eye movements is to resolve high spatial frequency information. To assess this hypothesis, we examined the rate, amplitude and speed of microsaccades in an object categorization task in which participants viewed object and non-object images and classified them as showing either natural objects, man-made objects or non-objects. Images were presented unfiltered (broadband; BB) or filtered to contain only low (LSF) or high spatial frequency (HSF) information. This allowed us to examine whether microsaccades were modulated independently by the presence of a high-level feature - the presence of an object - and by low-level stimulus characteristics - spatial frequency. We found a bimodal distribution of saccades based on their amplitude, with a split between smaller and larger microsaccades at 0.4° of visual angle. The rate of larger saccades (⩾0.4°) was higher for objects than non-objects, and higher for objects with high spatial frequency content (HSF and BB objects) than for LSF objects. No effects were observed for smaller microsaccades (<0.4°). This is consistent with a role for larger microsaccades in resolving HSF information for object identification, and previous evidence that more microsaccades are directed towards informative image regions.

Elevated midline-parietal gamma band noise power in schizophrenia but not in bipolar patients

Gamma oscillations are key in coordinating brain activity and seem to be altered in schizophrenia. In previous work, we studied the spatial distribution of a noise power measure (scalp-recorded electroencephalographic activity unlocked to stimuli) and found higher magnitudes in the gamma band related to symptoms and cognition in schizophrenia. In the current study, we sought to replicate those findings and to study its specificity for schizophrenia in a completely independent sample. A principal component analysis (PCA) was used to determine the factorial structure of gamma noise power acquired with an electroencephalographic recording during an odd-ball P300 paradigm in the 250- to 550-ms window in 70 patients with schizophrenia (16 patients with first episode), 45 bipolar patients and 65 healthy controls. Clinical and cognitive correlates of the resulting factors were also assessed. Three factors arose from the PCA. The first displayed a midline-parietal distribution (roughly corresponding to the default mode network), the second was centro-temporal and the third anterior-frontal. Schizophrenia but not bipolar patients showed higher gamma noise power loadings in the first factor in comparison with controls. Scores for this factor were significantly and directly associated with positive and total symptoms in patients and inversely associated with global cognition in all participants. The results of this study replicate those of our previous publication and suggest an elevated midline-parietal gamma noise power specific to schizophrenia. The gamma noise power measure seems to be a useful tool for studying background oscillatory activity during performance of cognitive tasks.

Electrophysiological responses to symmetry presented in the left or in the right visual hemifield

Symmetry is a highly salient feature in the visual world, abundant in both man-made and natural objects. In particular, humans find reflectional symmetry most salient. Electrophysiological work on symmetry perception has identified a difference wave known as the Sustained Posterior Negativity (SPN) originating from extrastriate areas. Amplitude is more negative for symmetrical than random patterns, from around 200 msec after stimulus onset. For the first time, we report responses to patterns presented exclusively in one hemifield. Participants were presented with reflection or random dot patterns to the left and right of fixation (3.2°). They judged whether the patterns were light red or dark red in colour. In Experiment 1, the pair always included one symmetrical and one random pattern. In Experiments 2 and 3 we varied the information presented contralaterally. The SPN was generated separately in each hemisphere in response to what was presented in the contralateral visual hemifield (a lateralised SPN). We conclude that a symmetry-sensitive network of extrastriate areas can be activated independently in each cerebral hemisphere.

Rapid gamma oscillations in the inferior occipital gyrus in response to eyes

Eyes are an indispensable communication medium for human social interactions. Although previous neuroscientific evidence suggests the activation of the inferior occipital gyrus (IOG) during eye processing, the temporal profile of this activation remains unclear. To investigate this issue, we analyzed intracranial electroencephalograms of the IOG during the presentation of eyes and mosaics, in either averted or straight directions. Time–frequency statistical parametric mapping analyses revealed greater gamma-band activation in the right IOG beginning at 114 ms in response to eyes relative to mosaics, irrespective of their averted or straight direction. These results suggest that gamma oscillations in the right IOG are involved in the early stages of eye processing, such as eye detection.

State-of-the-Art Analysis of High-Frequency (Gamma Range) Electroencephalography in Humans

Gamma oscillations (>30 Hz) in the brain are involved in attention, perception and memory. They are altered in various pathological states, as well as by neuropharmaceuticals, so that they are of interest in drug and clinical investigations. However, when the human electroencephalogram is recorded on the scalp, this neural high-frequency signal is buried under a range of other electrical signals such that, without careful handling, recordings of the high-frequency electroencephalogram cannot be considered reliable. The artefacts of concern originate from: power line noise, saccade-associated contraction of the extra-ocular muscles, activity of muscles in the scalp, face and neck, screen refresh artefacts and activity of the muscles associated with blinking. Recent progress in dealing with these artefacts is described, including either noise cancellation or phased noise template subtraction for power line noise, regression or independent component analysis for correcting extra-ocular muscle activity and mathematical modelling for reducing scalp, face and neck muscle activity. If the artefacts are properly addressed, the neural gamma signal can be uncovered.

Multimodal EEG Recordings, Psychometrics and Behavioural Analysis

High spatial and temporal resolution measurements of neuronal activity are preferably combined. In an overview on how this approach can take shape, multimodal electroencephalography (EEG) is treated in 2 main parts: by experiments without a task and in the experimentally cued working brain. It concentrates first on the alpha rhythm properties and next on data-driven search for patterns such as the default mode network. The high-resolution volumic distributions of neuronal metabolic indices result in distributed cortical regions and possibly relate to numerous nuclei, observable in a non-invasive manner in the central nervous system of humans. The second part deals with paradigms in which nowadays assessment of target-related networks can align level-dependent blood oxygenation, electrical responses and behaviour, taking the temporal resolution advantages of event-related potentials. Evidence-based electrical propagation in serial tasks during performance is now to a large extent attributed to interconnected pathways, particularly chronometry-dependent ones, throughout a chain including a dorsal stream, next ventral cortical areas taking the flow of information towards inferior temporal domains. The influence of aging is documented, and results of the first multimodal studies in neuropharmacology are consistent. Finally a scope on implementation of advanced clinical applications and personalized marker strategies in neuropsychiatry is indicated.

Do you see me? The role of visual fixation in chronic disorders of consciousness differential diagnosis

Visual fixation (VF) of a target is a possible, although atypical, feature of the Unresponsive Wakefulness Syndrome (UWS). Whether VF may indicate residual awareness in these patients is debatable, since it may simply subtend a series of reflex processes. Objective tools should therefore be used to identify aware VF, which depends on the integrity of visuomotor networks encompassing frontal-parietal-occipital areas. The aim of our study was to detect residual visuomotor network functionality potentially sustaining aware VF. To this end, we evaluated the visuomotor integration (VMI) and visual P300 patterns in a chronic Disorder of Consciousness (DOC) sample and a control group of healthy individuals (HC), using an associative stimulation protocol combining transcranial magnetic stimulation (TMS) with visual stimulation through transorbital alternating current stimulation. The Minimally Conscious State (MCS) patients showed preserved patterns of VMI and P300, whereas nearly all the UWS patients showed no significant VMI. Notably, the electrophysiological findings were correlated with the visual domain of the Coma Recovery Scale-Revised. Nonetheless, two fixating UWS individuals had a VMI similar to MCS patients. Our data suggest that some UWS patients showing VF could be aware, but unable to manifest it clearly, probably because of a severe motor output impairment, which is a condition compatible with the Functional Locked-In Syndrome.

Spatiotemporal properties of microsaccades: Model predictions and experimental tests

Microsaccades are involuntary and very small eye movements during fixation. Recently, the microsaccade-related neural dynamics have been extensively investigated both in experiments and by constructing neural network models. Experimentally, microsaccades also exhibit many behavioral properties. It's well known that the behavior properties imply the underlying neural dynamical mechanisms, and so are determined by neural dynamics. The behavioral properties resulted from neural responses to microsaccades, however, are not yet understood and are rarely studied theoretically. Linking neural dynamics to behavior is one of the central goals of neuroscience. In this paper, we provide behavior predictions on spatiotemporal properties of microsaccades according to microsaccade-induced neural dynamics in a cascading network model, which includes both retinal adaptation and short-term depression (STD) at thalamocortical synapses. We also successfully give experimental tests in the statistical sense. Our results provide the first behavior description of microsaccades based on neural dynamics induced by behaving activity, and so firstly link neural dynamics to behavior of microsaccades. These results indicate strongly that the cascading adaptations play an important role in the study of microsaccades. Our work may be useful for further investigations of the microsaccadic behavioral properties and of the underlying neural dynamical mechanisms responsible for the behavioral properties.

Oculomotor inhibition covaries with conscious detection

Saccadic eye movements occur frequently even during attempted fixation, but they halt momentarily when a new stimulus appears. Here, we demonstrate that this rapid, involuntary "oculomotor freezing" reflex is yoked to fluctuations in explicit visual perception. Human observers reported the presence or absence of a brief visual stimulus while we recorded microsaccades, small spontaneous eye movements. We found that microsaccades were reflexively inhibited if and only if the observer reported seeing the stimulus, even when none was present. By applying a novel Bayesian classification technique to patterns of microsaccades on individual trials, we were able to decode the reported state of perception more accurately than the state of the stimulus (present vs. absent). Moreover, explicit perceptual sensitivity and the oculomotor reflex were both susceptible to orientation-specific adaptation. The adaptation effects suggest that the freezing reflex is mediated by signals processed in the visual cortex before reaching oculomotor control centers rather than relying on a direct subcortical route, as some previous research has suggested. We conclude that the reflexive inhibition of microsaccades immediately and inadvertently reveals when the observer becomes aware of a change in the environment. By providing an objective measure of conscious perceptual detection that does not require explicit reports, this finding opens doors to clinical applications and further investigations of perceptual awareness.

Early suppression effect in human primary visual cortex during Kanizsa illusion processing: A magnetoencephalographic evidence

Detection of illusory contours (ICs) such as Kanizsa figures is known to depend primarily upon the lateral occipital complex. Yet there is no universal agreement on the role of the primary visual cortex in this process; some existing evidence hints that an early stage of the visual response in V1 may involve relative suppression to Kanizsa figures compared with controls. Iso-oriented luminance borders, which are responsible for Kanizsa illusion, may evoke surround suppression in V1 and adjacent areas leading to the reduction in the initial response to Kanizsa figures. We attempted to test the existence, as well as to find localization and timing of the early suppression effect produced by Kanizsa figures in adult nonclinical human participants. We used two sizes of visual stimuli (4.5 and 9.0°) in order to probe the effect at two different levels of eccentricity; the stimuli were presented centrally in passive viewing conditions. We recorded magnetoencephalogram, which is more sensitive than electroencephalogram to activity originating from V1 and V2 areas. We restricted our analysis to the medial occipital area and the occipital pole, and to a 40-120 ms time window after the stimulus onset. By applying threshold-free cluster enhancement technique in combination with permutation statistics, we were able to detect the inverted IC effect-a relative suppression of the response to the Kanizsa figures compared with the control stimuli. The current finding is highly compatible with the explanation involving surround suppression evoked by iso-oriented collinear borders. The effect may be related to the principle of sparse coding, according to which V1 suppresses representations of inner parts of collinear assemblies as being informationally redundant. Such a mechanism is likely to be an important preliminary step preceding object contour detection.

Steady-state visually evoked potential correlates of human body perception

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

Microsaccades Are Coupled to Heartbeat

During visual fixation, the eye generates microsaccades and slower components of fixational eye movements that are part of the visual processing strategy in humans. Here, we show that ongoing heartbeat is coupled to temporal rate variations in the generation of microsaccades. Using coregistration of eye recording and ECG in humans, we tested the hypothesis that microsaccade onsets are coupled to the relative phase of the R-R intervals in heartbeats. We observed significantly more microsaccades during the early phase after the R peak in the ECG. This form of coupling between heartbeat and eye movements was substantiated by the additional finding of a coupling between heart phase and motion activity in slow fixational eye movements; i.e., retinal image slip caused by physiological drift. Our findings therefore demonstrate a coupling of the oculomotor system and ongoing heartbeat, which provides further evidence for bodily influences on visuomotor functioning.

SIGNIFICANCE STATEMENT

In the present study, we show that microsaccades are coupled to heartbeat. Moreover, we revealed a strong modulation of slow eye movements around the R peak in the ECG. These results suggest that heartbeat as a basic physiological signal is related to statistical modulations of fixational eye movements, in particular, the generation of microsaccades. Therefore, our findings add a new perspective on the principles underlying the generation of fixational eye movements. Importantly, our study highlights the need to record eye movements when studying the influence of heartbeat in neuroscience to avoid misinterpretation of eye-movement-related artifacts as heart-evoked modulations of neural processing.

The relationship between oscillatory EEG activity and the laminar-specific BOLD signal

Electrophysiological recordings in animals have indicated that visual cortex γ-band oscillatory activity is predominantly observed in superficial cortical layers, whereas α- and β-band activity is stronger in deep layers. These rhythms, as well as the different cortical layers, have also been closely related to feedforward and feedback streams of information. Recently, it has become possible to measure laminar activity in humans with high-resolution functional MRI (fMRI). In this study, we investigated whether these different frequency bands show a differential relation with the laminar-resolved blood-oxygen level-dependent (BOLD) signal by combining data from simultaneously recorded EEG and fMRI from the early visual cortex. Our visual attention paradigm allowed us to investigate how variations in strength over trials and variations in the attention effect over subjects relate to each other in both modalities. We demonstrate that γ-band EEG power correlates positively with the superficial layers' BOLD signal and that β-power is negatively correlated to deep layer BOLD and α-power to both deep and superficial layer BOLD. These results provide a neurophysiological basis for human laminar fMRI and link human EEG and high-resolution fMRI to systems-level neuroscience in animals.

Hierarchy of prediction errors for auditory events in human temporal and frontal cortex

Predictive coding theories posit that neural networks learn statistical regularities in the environment for comparison with actual outcomes, signaling a prediction error (PE) when sensory deviation occurs. PE studies in audition have capitalized on low-frequency event-related potentials (LF-ERPs), such as the mismatch negativity. However, local cortical activity is well-indexed by higher-frequency bands [high-γ band (Hγ): 80-150 Hz]. We compared patterns of human Hγ and LF-ERPs in deviance detection using electrocorticographic recordings from subdural electrodes over frontal and temporal cortices. Patients listened to trains of task-irrelevant tones in two conditions differing in the predictability of a deviation from repetitive background stimuli (fully predictable vs. unpredictable deviants). We found deviance-related responses in both frequency bands over lateral temporal and inferior frontal cortex, with an earlier latency for Hγ than for LF-ERPs. Critically, frontal Hγ activity but not LF-ERPs discriminated between fully predictable and unpredictable changes, with frontal cortex sensitive to unpredictable events. The results highlight the role of frontal cortex and Hγ activity in deviance detection and PE generation.

Dysfunctional Patterns of Gamma-Band Activity in Response to Human Faces Compared to Non-Facial Stimuli in Patients with Schizophrenia

OBJECTIVE

Healthy individuals show stronger gamma-band activities (GBAs) for socially relevant stimuli (human faces) than for non-relevant ones. This study aimed to examine whether this gamma-band preference occurs in patients with schizophrenia.

METHODS

EEG was recorded for 24 patients with schizophrenia and 23 healthy controls while they viewed pictures of human faces, chairs, and nature scenes. The spectral powers of high-beta (20-30 Hz) and gamma (30-80 Hz) frequencies were analyzed along 3 midline cortical regions, and phase synchronization was calculated.

RESULTS

Compared to the response to non-facial stimuli, higher event related deactivation to facial stimuli was observed for the high-beta frequency across groups. For the gamma frequency, early-stage GBA was increased and late-stage GBA was decreased for all 3 stimuli in patients with schizophrenia compared to healthy controls. Preferential GBA patterns (100-200 and 200-300 ms) were found in healthy controls, but not in patients with schizophrenia. Significant correlation existed between negative symptoms and GBA in the frontal region for chair and scene stimuli. There was no significant intergroup difference in phase synchronization pattern.

CONCLUSION

Our results suggest that patients with schizophrenia have deficits in the preferential pattern of GBA for human faces and the deficits in the preferential pattern were mainly influenced by over-response to socially non-relevant stimuli.

Improvement of the Error-detection Mechanism in Adults with Dyslexia Following Reading Acceleration Training

The error-detection mechanism aids in preventing error repetition during a given task. Electroencephalography demonstrates that error detection involves two event-related potential components: error-related and correct-response negativities (ERN and CRN, respectively). Dyslexia is characterized by slow, inaccurate reading. In particular, individuals with dyslexia have a less active error-detection mechanism during reading than typical readers. In the current study, we examined whether a reading training programme could improve the ability to recognize words automatically (lexical representations) in adults with dyslexia, thereby resulting in more efficient error detection during reading. Behavioural and electrophysiological measures were obtained using a lexical decision task before and after participants trained with the reading acceleration programme. ERN amplitudes were smaller in individuals with dyslexia than in typical readers before training but increased following training, as did behavioural reading scores. Differences between the pre-training and post-training ERN and CRN components were larger in individuals with dyslexia than in typical readers. Also, the error-detection mechanism as represented by the ERN/CRN complex might serve as a biomarker for dyslexia and be used to evaluate the effectiveness of reading intervention programmes. Copyright © 2016 John Wiley & Sons, Ltd.

Automatic Sleep Stage Scoring Using Time-Frequency Analysis and Stacked Sparse Autoencoders

We developed a machine learning methodology for automatic sleep stage scoring. Our time-frequency analysis-based feature extraction is fine-tuned to capture sleep stage-specific signal features as described in the American Academy of Sleep Medicine manual that the human experts follow. We used ensemble learning with an ensemble of stacked sparse autoencoders for classifying the sleep stages. We used class-balanced random sampling across sleep stages for each model in the ensemble to avoid skewed performance in favor of the most represented sleep stages, and addressed the problem of misclassification errors due to class imbalance while significantly improving worst-stage classification. We used an openly available dataset from 20 healthy young adults for evaluation. We used a single channel of EEG from this dataset, which makes our method a suitable candidate for longitudinal monitoring using wearable EEG in real-world settings. Our method has both high overall accuracy (78%, range 75-80%), and high mean [Formula: see text]-score (84%, range 82-86%) and mean accuracy across individual sleep stages (86%, range 84-88%) over all subjects. The performance of our method appears to be uncorrelated with the sleep efficiency and percentage of transitional epochs in each recording.

Neuronal Oscillations in Various Frequency Bands Differ between Pain and Touch

Although humans are generally capable of distinguishing single events of pain or touch, recent research suggested that both modalities activate a network of similar brain regions. By contrast, less attention has been paid to which processes uniquely contribute to each modality. The present study investigated the neuronal oscillations that enable a subject to process pain and touch as well as to evaluate the intensity of both modalities by means of Electroencephalography. Nineteen healthy subjects were asked to rate the intensity of each stimulus at single trial level. By computing Linear mixed effects models (LME) encoding of both modalities was explored by relating stimulus intensities to brain responses. While the intensity of single touch trials is encoded only by theta activity, pain perception is encoded by theta, alpha and gamma activity. Beta activity in the tactile domain shows an on/off like characteristic in response to touch which was not observed in the pain domain. Our results enhance recent findings pointing to the contribution of different neuronal oscillations to the processing of nociceptive and tactile stimuli.

Hemodynamic signals in fNIRS

Near-infrared spectroscopy (NIRS) was originally designed for clinical monitoring of tissue oxygenation, and it has also been developed into a useful tool in neuroimaging studies, with the so-called functional NIRS (fNIRS). With NIRS, cerebral activation is detected by measuring the cerebral hemoglobin (Hb), where however, the precise correlation between NIRS signal and neural activity remains to be fully understood. This can in part be attributed to the situation that NIRS signals are inherently subject to contamination by signals arising from extracerebral tissue. In recent years, several approaches have been investigated to distinguish between NIRS signals originating in cerebral tissue and signals originating in extracerebral tissue. Selective measurements of cerebral Hb will enable a further evolution of fNIRS. This chapter is divided into six sections: first a summary of the basic theory of NIRS, NIRS signals arising in the activated areas, correlations between NIRS signals and fMRI signals, correlations between NIRS signals and neural activities, and the influence of a variety of extracerebral tissue on NIRS signals and approaches to this issue are reviewed. Finally, future prospects of fNIRS are described.

ERP C250 shows the elderly (cognitively normal, Alzheimer's disease) store more stimuli in short-term memory than Young Adults do

OBJECTIVE

To determine how aging and dementia affect the brain's initial storing of task-relevant and irrelevant information in short-term memory.

METHODS

We used brain Event-Related Potentials (ERPs) to measure short-term memory storage (ERP component C250) in 36 Young Adults, 36 Normal Elderly, and 36 early-stage AD subjects. Participants performed the Number-Letter task, a cognitive paradigm requiring memory storage of a first relevant stimulus to compare it with a second stimulus.

RESULTS

In Young Adults, C250 was more positive for the first task-relevant stimulus compared to all other stimuli. C250 in Normal Elderly and AD subjects was roughly the same to relevant and irrelevant stimuli in Intratrial Parts 1-3 but not 4. The AD group had lower C250 to relevant stimuli in part 1.

CONCLUSIONS

Both normal aging and dementia cause less differentiation of relevant from irrelevant information in initial storage. There was a large aging effect involving differences in the pattern of C250 responses of the Young Adult versus the Normal Elderly/AD groups. Also, a potential dementia effect was obtained.

SIGNIFICANCE

C250 is a candidate tool for measuring short-term memory performance on a biological level, as well as a potential marker for memory changes due to normal aging and dementia.

Effect of Reference Scheme on Power and Phase of the Local Field Potential

Brain signals are often analyzed in the spectral domain, where the power spectral density (PSD) and phase differences and consistency can reveal important information about the network. However, for proper interpretation, it is important to know whether these measures depend on stimulus/behavioral conditions or the reference scheme used to analyze data. We recorded local field potential (LFP) from an array of microelectrodes chronically implanted in area V1 of monkeys under different stimulus/behavioral conditions and computed PSD slopes, coherence, and phase difference between LFPs as a function of frequency and interelectrode distance while using four reference schemes: single wire, average, bipolar, and current source density. PSD slopes were dependent on reference scheme at low frequencies (below 200 Hz) but became invariant at higher frequencies. Average phase differences between sites also depended critically on referencing, switching from 0 degrees for single-wire to 180 degrees for average reference. Results were consistent across different stimulus/behavioral conditions. We were able to account for these results based on the coherence profile across sites and properties of the spectral estimator. Our results show that using different reference schemes can have drastic effects on phase differences and PSD slopes and therefore must be interpreted carefully to gain insights about network properties.

The visual gamma response to faces reflects the presence of sensory evidence and not awareness of the stimulus

It has been suggested that gamma (30-100 Hz) oscillations mediate awareness of visual stimuli, but tests of this hypothesis have produced differing results. We used phase scrambling to vary the perceptibility of face stimuli in order to determine whether gamma is indeed linked to perceptual awareness. Magnetoencephalography was used to measure the gamma response in 25 participants while viewing three conditions in which faces were presented either above, below or at the threshold for detection. In each of 400 trials (100 each for the sub- and suprathreshold conditions, 200 for the threshold condition), participants indicated whether they perceived a face in the stimulus. Gamma-band activity during the task was localized to bilateral ventral occipito-temporal cortex. For the threshold condition, we failed to find a significant difference in gamma amplitude between trials in which a face was perceived relative to those in which no face was perceived. However, we did find that gamma amplitude was significantly increased for threshold relative to subthreshold stimuli and for suprathreshold relative to threshold stimuli. This leads us to conclude that the gamma response to faces is primarily modulated by the presence of sensory evidence of a face rather by perceptual awareness.

Brain Oscillations in Sport: Toward EEG Biomarkers of Performance

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.

Source-space EEG neurofeedback links subjective experience with brain activity during effortless awareness meditation

BACKGROUND

Meditation is increasingly showing beneficial effects for psychiatric disorders. However, learning to meditate is not straightforward as there are no easily discernible outward signs of performance and thus no direct feedback is possible. As meditation has been found to correlate with posterior cingulate cortex (PCC) activity, we tested whether source-space EEG neurofeedback from the PCC followed the subjective experience of effortless awareness (a major component of meditation), and whether participants could volitionally control the signal.

METHODS

Sixteen novice meditators and sixteen experienced meditators participated in the study. Novice meditators were briefly trained to perform a basic meditation practice to induce the subjective experience of effortless awareness in a progressively more challenging neurofeedback test-battery. Experienced meditators performed a self-selected meditation practice to induce this state in the same test-battery. Neurofeedback was provided based on gamma-band (40-57Hz) PCC activity extracted using a beamformer algorithm. Associations between PCC activity and the subjective experience of effortless awareness were assessed by verbal probes.

RESULTS

Both groups reported that decreased PCC activity corresponded with effortless awareness (P<0.0025 for each group), with high median confidence ratings (novices: 8 on a 0-10 Likert scale; experienced: 9). Both groups showed high moment-to-moment median correspondence ratings between PCC activity and subjective experience of effortless awareness (novices: 8, experienced: 9). Both groups were able to volitionally control the PCC signal in the direction associated with effortless awareness by practicing effortless awareness meditation (novices: median % of time=77.97, P=0.001; experienced: 89.83, P<0.0005).

CONCLUSIONS

These findings support the feasibility of using EEG neurofeedback to link an objective measure of brain activity with the subjective experience of effortless awareness, and suggest potential utility of this paradigm as a tool for meditation training.

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

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

EEG Alpha and Gamma Modulators Mediate Motion Sickness-Related Spectral Responses

Motion sickness (MS) is a common experience of travelers. To provide insights into brain dynamics associated with MS, this study recruited 19 subjects to participate in an electroencephalogram (EEG) experiment in a virtual-reality driving environment. When riding on consecutive winding roads, subjects experienced postural instability and sensory conflict between visual and vestibular stimuli. Meanwhile, subjects rated their level of MS on a six-point scale. Independent component analysis (ICA) was used to separate the filtered EEG signals into maximally temporally independent components (ICs). Then, reduced logarithmic spectra of ICs of interest, using principal component analysis, were decomposed by ICA again to find spectrally fixed and temporally independent modulators (IMs). Results demonstrated that a higher degree of MS accompanied increased activation of alpha ([Formula: see text]) and gamma ([Formula: see text]) IMs across remote-independent brain processes, covering motor, parietal and occipital areas. This co-modulatory spectral change in alpha and gamma bands revealed the neurophysiological demand to regulate conflicts among multi-modal sensory systems during MS.

Unmasking local activity within local field potentials (LFPs) by removing distal electrical signals using independent component analysis

Local field potentials (LFPs) are commonly thought to reflect the aggregate dynamics in local neural circuits around recording electrodes. However, we show that when LFPs are recorded in awake behaving animals against a distal reference on the skull as commonly practiced, LFPs are significantly contaminated by non-local and non-neural sources arising from the reference electrode and from movement-related noise. In a data set with simultaneously recorded LFPs and electroencephalograms (EEGs) across multiple brain regions while rats perform an auditory oddball task, we used independent component analysis (ICA) to identify signals arising from electrical reference and from volume-conducted noise based on their distributed spatial pattern across multiple electrodes and distinct power spectral features. These sources of distal electrical signals collectively accounted for 23–77% of total variance in unprocessed LFPs, as well as most of the gamma oscillation responses to the target stimulus in EEGs. Gamma oscillation power was concentrated in volume-conducted noise and was tightly coupled with the onset of licking behavior, suggesting a likely origin of muscle activity associated with body movement or orofacial movement. The removal of distal signal contamination also selectively reduced correlations of LFP/EEG signals between distant brain regions but not within the same region. Finally, the removal of contamination from distal electrical signals preserved an event-related potential (ERP) response to auditory stimuli in the frontal cortex and also increased the coupling between the frontal ERP amplitude and neuronal activity in the basal forebrain, supporting the conclusion that removing distal electrical signals unmasked local activity within LFPs. Together, these results highlight the significant contamination of LFPs by distal electrical signals and caution against the straightforward interpretation of unprocessed LFPs. Our results provide a principled approach to identify and remove such contamination to unmask local LFPs.

Model predictions of features in microsaccade-related neural responses in a feedforward network with short-term synaptic depression

Recently, the significant microsaccade-induced neural responses have been extensively observed in experiments. To explore the underlying mechanisms of the observed neural responses, a feedforward network model with short-term synaptic depression has been proposed [Yuan, W.-J., Dimigen, O., Sommer, W. and Zhou, C. Front. Comput. Neurosci. 7, 47 (2013)]. The depression model not only gave an explanation for microsaccades in counteracting visual fading, but also successfully reproduced several microsaccade-related features in experimental findings. These results strongly suggest that, the depression model is very useful to investigate microsaccade-related neural responses. In this paper, by using the model, we extensively study and predict the dependance of microsaccade-related neural responses on several key parameters, which could be tuned in experiments. Particularly, we provide a significant prediction that microsaccade-related neural response also complies with the property "sharper is better" observed in many contexts in neuroscience. Importantly, the property exhibits a power-law relationship between the width of input signal and the responsive effectiveness, which is robust against many parameters in the model. By using mean field theory, we analytically investigate the robust power-law property. Our predictions would give theoretical guidance for further experimental investigations of the functional role of microsaccades in visual information processing.

Noise power associated with decreased task-induced variability of brain electrical activity in schizophrenia

In schizophrenia, both increased baseline metabolic and electroencephalographic (EEG) activities as well as decreased task-related modulation of neural dynamics have been reported. Noise power (NP) can measure the background EEG activity during task performance, and Shannon entropy (SE) is useful for quantifying the global modulation of EEG activity with a high temporal resolution. In this study, we have assessed the possible relationship between increased NP in theta and gamma bands and decreased SE modulation in 24 patients with schizophrenia and 26 controls over the parietal and central regions during a P300 task. SE modulation was calculated as the change from baseline to the active epoch (i.e., 150-550 ms following the target stimulus onset). Patients with schizophrenia displayed statistically significant higher NP values and lower SE modulation than healthy controls. We found a significant association between gamma NP and SE in all of the participants. Specifically, a NP increase in the gamma band was followed by a decrease in SE change. These results support the notion that an excess of gamma activity, unlocked to the task being performed, is accompanied by a decreased modulation of EEG activity in schizophrenia.

Metastability and Coherence: Extending the Communication through Coherence Hypothesis Using A Whole-Brain Computational Perspective

Understanding the mechanisms for communication in the brain remains one of the most challenging scientific questions. The communication through coherence (CTC) hypothesis was originally proposed 10 years ago, stating that two groups of neurons communicate most effectively when their excitability fluctuations are coordinated in time (i.e., coherent), and this control by cortical coherence is a fundamental brain mechanism for large-scale, distant communication. In light of new evidence from whole-brain computational modelling of multimodal neuroimaging data, we link CTC to the concept of metastability, which refers to a rich exploration of the functional repertoire made possible by the underlying structural whole-brain connectivity.

α Power Modulation and Event-Related Slow Wave Provide Dissociable Correlates of Visual Working Memory

Traditionally, electrophysiological correlates of visual working memory (VWM) capacity have been characterized using a lateralized VWM task in which participants had to remember items presented on the cued hemifield while ignoring the distractors presented on the other hemifield. Though this approach revealed a lateralized parieto-occipital negative slow wave (i.e., the contralateral delay activity) and lateralized α power modulation as neural correlates of VWM capacity that may be mechanistically related, recent evidence suggested that these measures might be reflecting individuals' ability to ignore distractors rather than their ability to maintain VWM representations. To better characterize the neural correlates of VWM capacity, we had human participants perform a whole-field VWM task in which they remembered all the items on the display. Here, we found that both the parieto-occipital negative slow wave and the α power suppression showed the characteristics of VWM capacity in the absence of distractors, suggesting that they reflect the maintenance of VWM representations rather than filtering of distractors. Furthermore, the two signals explained unique portions of variance in individual differences of VWM capacity and showed differential temporal characteristics. This pattern of results clearly suggests that individual differences in VWM capacity are determined by dissociable neural mechanisms reflected in the ERP and the oscillatory measures of VWM capacity.

SIGNIFICANCE STATEMENT

Our work demonstrates that there exist event-related potential and oscillatory correlates of visual working memory (VWM) capacity even in the absence of task-irrelevant distractors. This clearly shows that the two neural correlates are directly linked to maintenance of task-relevant information rather than filtering of task-irrelevant information. Furthermore, we found that these two correlates show differential temporal characteristics. These results are inconsistent with proposals that the two neural correlates are byproducts of asymmetric α power suppression and indicate that they reflect dissociable neural mechanisms subserving VWM.

Sparse time artifact removal

BACKGROUND

Muscle artifacts and electrode noise are an obstacle to interpretation of EEG and other electrophysiological signals. They are often channel-specific and do not fully benefit from component analysis techniques such as ICA, and their presence reduces the dimensionality needed by those techniques. Their high-frequency content may mask or masquerade as gamma band cortical activity.

NEW METHOD

The sparse time artifact removal (STAR) algorithm removes artifacts that are sparse in space and time. The time axis is partitioned into an artifact-free and an artifact-contaminated part, and the correlation structure of the data is estimated from the covariance matrix of the artifact-free part. Artifacts are then corrected by projection of each channel onto the subspace spanned by the other channels.

RESULTS

The method is evaluated with both simulated and real data, and found to be highly effective in removing or attenuating typical channel-specific artifacts.

COMPARISON WITH EXISTING METHODS

In contrast to the widespread practice of trial removal or channel removal or interpolation, very few data are lost. In contrast to ICA or other linear techniques, processing is local in time and affects only the artifact part, so most of the data are identical to the unprocessed data and the full dimensionality of the data is preserved.

CONCLUSIONS

STAR complements other linear component analysis techniques, and can enhance their ability to discover weak sources of interest by increasing the number of effective noise-free channels.

Age-Related Changes in 1/f Neural Electrophysiological Noise

Aging is associated with performance decrements across multiple cognitive domains. The neural noise hypothesis, a dominant view of the basis of this decline, posits that aging is accompanied by an increase in spontaneous, noisy baseline neural activity. Here we analyze data from two different groups of human subjects: intracranial electrocorticography from 15 participants over a 38 year age range (15-53 years) and scalp EEG data from healthy younger (20-30 years) and older (60-70 years) adults to test the neural noise hypothesis from a 1/f noise perspective. Many natural phenomena, including electrophysiology, are characterized by 1/f noise. The defining characteristic of 1/f is that the power of the signal frequency content decreases rapidly as a function of the frequency (f) itself. The slope of this decay, the noise exponent (χ), is often <-1 for electrophysiological data and has been shown to approach white noise (defined as χ = 0) with increasing task difficulty. We observed, in both electrophysiological datasets, that aging is associated with a flatter (more noisy) 1/f power spectral density, even at rest, and that visual cortical 1/f noise statistically mediates age-related impairments in visual working memory. These results provide electrophysiological support for the neural noise hypothesis of aging. Significance statement: Understanding the neurobiological origins of age-related cognitive decline is of critical scientific, medical, and public health importance, especially considering the rapid aging of the world's population. We find, in two separate human studies, that 1/f electrophysiological noise increases with aging. In addition, we observe that this age-related 1/f noise statistically mediates age-related working memory decline. These results significantly add to this understanding and contextualize a long-standing problem in cognition by encapsulating age-related cognitive decline within a neurocomputational model of 1/f noise-induced deficits in neural communication.

Areas V1 and V2 show microsaccade-related 3-4-Hz covariation in gamma power and frequency

Neuronal gamma-band synchronization (25-80 Hz) in visual cortex appears sustained and stable during prolonged visual stimulation when investigated with conventional averages across trials. However, recent studies in macaque visual cortex have used single-trial analyses to show that both power and frequency of gamma oscillations exhibit substantial moment-by-moment variation. This has raised the question of whether these apparently random variations might limit the functional role of gamma-band synchronization for neural processing. Here, we studied the moment-by-moment variation in gamma oscillation power and frequency, as well as inter-areal gamma synchronization, by simultaneously recording local field potentials in V1 and V2 of two macaque monkeys. We additionally analyzed electrocorticographic V1 data from a third monkey. Our analyses confirm that gamma-band synchronization is not stationary and sustained but undergoes moment-by-moment variations in power and frequency. However, those variations are neither random and nor a possible obstacle to neural communication. Instead, the gamma power and frequency variations are highly structured, shared between areas and shaped by a microsaccade-related 3-4-Hz theta rhythm. Our findings provide experimental support for the suggestion that cross-frequency coupling might structure and facilitate the information flow between brain regions.

Oscillatory neural responses evoked by natural vestibular stimuli in humans

While there have been numerous studies of the vestibular system in mammals, less is known about the brain mechanisms of vestibular processing in humans. In particular, of the studies that have been carried out in humans over the last 30 years, none has investigated how vestibular stimulation (VS) affects cortical oscillations. Here we recorded high-density electroencephalography (EEG) in healthy human subjects and a group of bilateral vestibular loss patients (BVPs) undergoing transient and constant-velocity passive whole body yaw rotations, focusing our analyses on the modulation of cortical oscillations in response to natural VS. The present approach overcame significant technical challenges associated with combining natural VS with human electrophysiology and reveals that both transient and constant-velocity VS are associated with a prominent suppression of alpha power (8-13 Hz). Alpha band suppression was localized over bilateral temporo-parietal scalp regions, and these alpha modulations were significantly smaller in BVPs. We propose that suppression of oscillations in the alpha band over temporo-parietal scalp regions reflects cortical vestibular processing, potentially comparable with alpha and mu oscillations in the visual and sensorimotor systems, respectively, opening the door to the investigation of human cortical processing under various experimental conditions during natural VS.

Accounting for microsaccadic artifacts in the EEG using independent component analysis and beamforming

Neuronal activity in the gamma-band range was long considered a marker of object representation. However, scalp-recorded EEG activity in this range is contaminated by a miniature saccade-related muscle artifact. Independent component analysis (ICA) has been proposed as a method of removal of such artifacts. Alternatively, beamforming, a source analysis method in which potential sources of activity across the whole brain are scanned independently through the use of adaptive spatial filters, offers a promising method of accounting for the artifact without relying on its explicit removal. We present here the application of ICA-based correction to a previously published dataset. Then, using beamforming, we examine the effect of ICA correction on the scalp-recorded EEG signal and the extent to which genuine activity is recoverable before and after ICA correction. We find that beamforming attributes much of the scalp-recorded gamma-band signal before correction to deep frontal sources, likely the eye muscles, which generate the artifact related to each miniature saccade. Beamforming confirms that what is removed by ICA is predominantly this artifactual signal, and that what remains after correction plausibly originates in the visual cortex. Thus, beamforming allows researchers to confirm whether their removal procedures successfully removed the artifact. Our results demonstrate that ICA-based correction brings about general improvements in signal-to-noise ratio suggesting it should be used along with, rather than be replaced by, beamforming.

Non-invasive brain mapping in epilepsy: Applications from magnetoencephalography

BACKGROUND

Non-invasive in vivo neurophysiological recordings with EEG/MEG are key to the diagnosis, classification, and further understanding of epilepsy. Historically the emphasis of these recordings has been the localisation of the putative sources of epileptic discharges. More recent developments see new techniques studying oscillatory dynamics, connectivity and network properties.

NEW METHOD

New analysis strategies for whole head MEG include the development of spatial filters or beamformers for source localisation, time-frequency analysis for cortical dynamics and graph theory applications for connectivity.

RESULTS

The idea of epilepsy as a network disorder is not new, and new applications of structural and functional brain imaging show differences in cortical and subcortical networks in patients with epilepsy compared to controls. Concepts of 'focal' and 'generalised' are challenged by evidence of focal onsets in generalised epileptic discharges, and widespread network changes in focal epilepsy. Spectral analyses can show differences in induced cortical response profiles, particularly in photosensitive epilepsy.

COMPARISON WITH EXISTING METHOD

This review focuses on the application of MEG in the study of epilepsy, starting with a brief historical perspective, followed by novel applications of source localisation, time-frequency and connectivity analyses.

CONCLUSION

Novel MEG analyses approaches show altered cortical dynamics and widespread network alterations in focal and generalised epilepsies, and identification of regional network abnormalities may have a role in epilepsy surgery evaluation.

Different coupling modes mediate cortical cross-frequency interactions

Cross-frequency coupling (CFC) has been suggested to constitute a highly flexible mechanism for cortical information gating and processing, giving rise to conscious perception and various higher cognitive functions in humans. In particular, it might provide an elegant tool for information integration across several spatiotemporal scales within nested or coupled neuronal networks. However, it is currently unknown whether low-frequency (theta/alpha) or high-frequency gamma oscillations orchestrate cross-frequency interactions, raising the question of who is master and who is slave. While correlative evidence suggested that at least two distinct CFC modes exist, namely, phase-amplitude-coupling (PAC) and amplitude-envelope correlations (AEC), it is currently unknown whether they subserve distinct cortical functions. Novel non-invasive brain stimulation tools, such as transcranial alternating current stimulation (tACS), now provide the unique opportunity to selectively entrain the low- or high-frequency component and study subsequent effects on CFC. Here, we demonstrate the differential modulation of CFC during selective entrainment of alpha or gamma oscillations. Our results reveal that entrainment of the low-frequency component increased PAC, where gamma power became preferentially locked to the trough of the alpha oscillation, while gamma-band entrainment enhanced AECs and reduced alpha power. These results provide causal evidence for the functional role of coupled alpha and gamma oscillations for visual processing.

Neurophysiological differences between patients clinically at high risk for schizophrenia and neurotypical controls--first steps in development of a biomarker

BACKGROUND

Schizophrenia is a severe, disabling and prevalent mental disorder without cure and with a variable, incomplete pharmacotherapeutic response. Prior to onset in adolescence or young adulthood a prodromal period of abnormal symptoms lasting weeks to years has been identified and operationalized as clinically high risk (CHR) for schizophrenia. However, only a minority of subjects prospectively identified with CHR convert to schizophrenia, thereby limiting enthusiasm for early intervention(s). This study utilized objective resting electroencephalogram (EEG) quantification to determine whether CHR constitutes a cohesive entity and an evoked potential to assess CHR cortical auditory processing.

METHODS

This study constitutes an EEG-based quantitative neurophysiological comparison between two unmedicated subject groups: 35 neurotypical controls (CON) and 22 CHR patients. After artifact management, principal component analysis (PCA) identified EEG spectral and spectral coherence factors described by associated loading patterns. Discriminant function analysis (DFA) determined factors' discrimination success between subjects in the CON and CHR groups. Loading patterns on DFA-selected factors described CHR-specific spectral and coherence differences when compared to controls. The frequency modulated auditory evoked response (FMAER) explored functional CON-CHR differences within the superior temporal gyri.

RESULTS

Variable reduction by PCA identified 40 coherence-based factors explaining 77.8% of the total variance and 40 spectral factors explaining 95.9% of the variance. DFA demonstrated significant CON-CHR group difference (P <0.00001) and successful jackknifed subject classification (CON, 85.7%; CHR, 86.4% correct). The population distribution plotted along the canonical discriminant variable was clearly bimodal. Coherence factors delineated loading patterns of altered connectivity primarily involving the bilateral posterior temporal electrodes. However, FMAER analysis showed no CON-CHR group differences.

CONCLUSIONS

CHR subjects form a cohesive group, significantly separable from CON subjects by EEG-derived indices. Symptoms of CHR may relate to altered connectivity with the posterior temporal regions but not to primary auditory processing abnormalities within these regions.

Impact of head modeling and sensor types in localizing human gamma-band oscillations

An effective mechanism in neuronal communication is oscillatory neuronal synchronization. The neuronal gamma-band (30-100 Hz) synchronization is associated with attention which is induced by a certain visual stimuli. Numerous studies have shown that the gamma-band activity is observed in the visual cortex. However, impact of different head modeling techniques and sensor types to localize gamma-band activity have not yet been reported. To do this, the brain activity was recorded using 306 magnetoencephalography (MEG) sensors, consisting of 102 magnetometers and 102 pairs of planar gradiometers (one measuring the derivative of the magnetic field along the latitude and the other along the longitude), and the data were analyzed with respect to time, frequency, and location of the strongest response. The spherical head models with a single-shell and overlapping spheres (local sphere) have been used as a forward model for calculating the external magnetic fields generated from the gamma-band activity. For each sensor type, the subject-specific frequency range of the gamma-band activity was obtained from the spectral analysis. The identified frequency range of interest with the highest gamma-band activity is then localized using a spatial-filtering technique known as dynamic imaging of coherent sources (DICS). The source analysis for all the subjects revealed that the gradiometer sensors which measure the derivative along the longitude, showed sources close to the visual cortex (cuneus) as compared to the other gradiometer sensors which measure the derivative along the latitude. However, using the magnetometer sensors, it was not possible to localize the sources in the region of interest. When comparing the two head models, the local-sphere model helps in localizing the source more focally as compared to the single-shell head model.