Localizing human visual gamma-band activity in frequency, time and space

Neurophysiological principles underlying predictive coding during dynamic perception-action integration

A major concept in cognitive neuroscience is that brains are "prediction machines". Yet, conceptual frameworks on how perception and action become integrated still lack the concept of predictability and it is unclear how neural processes may implement predictive coding during dynamic perception-action integration. We show that distinct neurophysiological mechanisms of nonlinearly directed connectivities in the theta and alpha band between cortical structures underlie these processes. During the integration of perception and motor codes, especially theta band activity in the insular cortex and temporo-hippocampal structures is modulated by the predictability of upcoming information. Here, the insular cortex seems to guide processes. Conversely, the retrieval of such integrated perception-action codes during actions heavily relies on alpha band activity. Here, directed top-down influence of alpha band activity from inferior frontal structures on insular and temporo-hippocampal structures is key. This suggests that these top-down effects reflect attentional shielding of retrieval processes operating in the same neuroanatomical structures previously involved in the integration of perceptual and motor codes. Through neurophysiology, the present study connects predictive coding mechanisms with frameworks specifying the dynamic integration of perception and action.

Challenges and Approaches in the Study of Neural Entrainment

When exposed to rhythmic stimulation, the human brain displays rhythmic activity across sensory modalities and regions. Given the ubiquity of this phenomenon, how sensory rhythms are transformed into neural rhythms remains surprisingly inconclusive. An influential model posits that endogenous oscillations entrain to external rhythms, thereby encoding environmental dynamics and shaping perception. However, research on neural entrainment faces multiple challenges, from ambiguous definitions to methodological difficulties when endogenous oscillations need to be identified and disentangled from other stimulus-related mechanisms that can lead to similar phase-locked responses. Yet, recent years have seen novel approaches to overcome these challenges, including computational modeling, insights from dynamical systems theory, sophisticated stimulus designs, and study of neuropsychological impairments. This review outlines key challenges in neural entrainment research, delineates state-of-the-art approaches, and integrates findings from human and animal neurophysiology to provide a broad perspective on the usefulness, validity, and constraints of oscillatory models in brain-environment interaction.

The gamma-band activity model of the near-death experience: a critique and a reinterpretation

Near-death experience (NDE) is a transcendent mental event of uncertain etiology that arises on the cusp of biological death. Since the discovery of NDE in the mid-1970s, multiple neuroscientific theories have been developed in an attempt to account for it in strictly materialistic or reductionistic terms. Therefore, in this conception, NDE is at most an extraordinary hallucination without any otherworldly, spiritual, or supernatural denotations. During the last decade or so, a number of animal and clinical studies have emerged which reported that about the time of death, there may be a surge of high frequency electroencephalogram (EEG) at a time when cortical electrical activity is otherwise at a very low ebb. This oscillatory rhythm falls within the range of the enigmatic brain wave-labelled gamma-band activity (GBA). Therefore, it has been proposed that this brief, paradoxical, and perimortem burst of the GBA may represent the neural foundation of the NDE. This study examines three separate but related questions concerning this phenomenon. The first problem pertains to the electrogenesis of standard GBA and the extent to which authentic cerebral activity has been contaminated by myogenic artifacts. The second problem involves the question of whether agents that can mimic NDE are also underlain by GBA. The third question concerns the electrogenesis of the surge in GBA itself. It has been contended that this is neither cortical nor myogenic in origin. Rather, it arises in a subcortical (amygdaloid) location but is recorded at the cortex via volume conduction, thereby mimicking standard GBA. Although this surge of GBA contains genuine electrophysiological activity and is an intriguing and provocative finding, there is little evidence to suggest that it could act as a kind of neurobiological skeleton for a phenomenon such as NDE.

A novel, robust, and portable platform for magnetoencephalography using optically-pumped magnetometers

Magnetoencephalography (MEG) measures brain function via assessment of magnetic fields generated by neural currents. Conventional MEG uses superconducting sensors, which place significant limitations on performance, practicality, and deployment; however, the field has been revolutionised in recent years by the introduction of optically-pumped magnetometers (OPMs). OPMs enable measurement of the MEG signal without cryogenics, and consequently the conception of "OPM-MEG" systems which ostensibly allow increased sensitivity and resolution, lifespan compliance, free subject movement, and lower cost. However, OPM-MEG is in its infancy with existing limitations on both sensor and system design. Here, we report a new OPM-MEG design with miniaturised and integrated electronic control, a high level of portability, and improved sensor dynamic range. We show that this system produces equivalent measures compared with an established OPM-MEG instrument; specifically, when measuring task-induced beta-band, gamma-band, and evoked neuro-electrical responses, source localisations from the two systems were comparable and temporal correlation of measured brain responses was >0.7 at the individual level and >0.9 for groups. Using an electromagnetic phantom, we demonstrate improved dynamic range by running the system in background fields up to 8 nT. We show that the system is effective in gathering data during free movement (including a sitting-to-standing paradigm) and that it is compatible with simultaneous electroencephalography (EEG). Finally, we demonstrate portability by moving the system between two laboratories. Overall, our new system is shown to be a significant step forward for OPM-MEG and offers an attractive platform for next generation functional medical imaging.

Alterations in resting-state gamma-activity is adults with autism spectrum disorder: A High-Density EEG study

Autism spectrum disorder (ASD) is a neurodevelopmental disorder with a wide range of symptoms that include deficits in social cognition and difficulties with social interactions. Neural oscillations in the EEG gamma band have been proposed as an important candidate neurobiological marker of higher order cognitive processes and social interactions. We investigated resting-state gamma-activity of patients with ASD (n=23) in order to delineate alterations as compared to typically developing (TD) subjects (n=24). EEG absolute power was examined in the gamma (30-100Hz) frequency band. We found significantly reduced spectral power across the entire gamma range in the ASD group. The decrease was most pronounced over the inferior-frontal and temporo-parietal junction areas. We also found a significant decrease in gamma-activity over the dorsolateral prefrontal cortex, especially in the left side. Since these brain areas have been associated with social functioning, the reduced gamma-activity in ASD may represent a cortical dysfunction that could underlie a diminished capacity to interpret socially important information, thereby interfering with social functioning. The alterations we found may lend support for an improved diagnosis. Furthermore, they can lead to focused therapies, by targeting the dysfunctional brain activity to improve social cognitive and interaction abilities that are compromised in ASD.

Distinct oscillatory patterns differentiate between segregation and integration processes in perceptual grouping

Recently, there has been a resurgence in experimental and conceptual efforts to understand how brain rhythms can serve to organize visual information. Oscillations can provide temporal structure for neuronal processing and form a basis for integrating information across brain areas. Here, we use a bistable paradigm and a data-driven approach to test the hypothesis that oscillatory modulations associate with the integration or segregation of visual elements. Spectral signatures of perception of bound and unbound configurations of visual moving stimuli were studied using magnetoencephalography (MEG) in ambiguous and unambiguous conditions. Using a 2 × 2 design, we were able to isolate correlates from visual integration, either perceptual or stimulus-driven, from attentional and ambiguity-related activity. Two frequency bands were found to be modulated by visual integration: an alpha/beta frequency and a higher frequency gamma-band. Alpha/beta power was increased in several early visual cortical and dorsal visual areas during visual integration, while gamma-band power was surprisingly increased in the extrastriate visual cortex during segregation. This points to an integrative role for alpha/beta activity, likely from top-down signals maintaining a single visual representation. On the other hand, when more representations have to be processed in parallel gamma-band activity is increased, which is at odds with the notion that gamma oscillations are related to perceptual coherence. These modulations were confirmed in intracranial EEG recordings and partially originate from distinct brain areas. Our MEG and stereo-EEG data confirms predictions of binding mechanisms depending on low-frequency activity for long-range integration and for organizing visual processing while refuting a straightforward correlation between gamma-activity and perceptual binding. PRACTITIONER POINTS: Distinct neurophysiological signals underlie competing bistable percepts. Increased alpha/beta activity correlate with visual integration while gamma correlates with segmentation. Ambiguous percepts drive alpha/beta activity in the posterior cingulate cortex.

Establishing the relationship between subjective perception and neural responses: Insights from correlation analysis and representational similarity analysis

Exploring the relationship between sensory perception and brain responses holds important theoretical and clinical implications. However, commonly used methodologies like correlation analysis performed either intra- or inter- individually often yield inconsistent results across studies, limiting their generalizability. Representational similarity analysis (RSA), a method that assesses the perception-response relationship by calculating the correlation between behavioral and neural patterns, may offer a fresh perspective to reveal novel findings. Here, we delivered a series of graded sensory stimuli of four modalities (i.e., nociceptive somatosensory, non-nociceptive somatosensory, visual, and auditory) to/near the left or right hand of 107 healthy subjects and collected their single-trial perceptual ratings and electroencephalographic (EEG) responses. We examined the relationship between sensory perception and brain responses using within- and between-subject correlation analysis and RSA, and assessed their stability across different numbers of subjects and trials. We found that within-subject and between-subject correlations yielded distinct results: within-subject correlation revealed strong and reliable correlations between perceptual ratings and most brain responses, while between-subject correlation showed weak correlations that were vulnerable to the change of subject number. In addition to verifying the correlation results, RSA revealed some novel findings, i.e., correlations between behavioral and neural patterns were observed in some additional neural responses, such as "γ-ERS" in the visual modality. RSA results were sensitive to the trial number, but not to the subject number, suggesting that consistent results could be obtained for studies with relatively small sample sizes. In conclusion, our study provides a novel perspective on establishing the relationship between behavior and brain activity, emphasizing that RSA holds promise as a method for exploring this pattern relationship in future research.

Spontaneous cortical activity is altered in persons with HIV and related to domain-specific cognitive function

Whilst the average lifespan of persons with HIV now approximates that of the general population, these individuals are at a much higher risk of developing cognitive impairment with ∼35-70% experiencing at least subtle cognitive deficits. Previous works suggest that HIV impacts both low-level primary sensory regions and higher-level association cortices. Notably, multiple neuroHIV studies have reported elevated levels of spontaneous cortical activity during the pre-stimulus baseline period of task-based experiments, but only a few have examined such activity during resting-state conditions. In the current study, we examined such spontaneous cortical activity using magnetoencephalography in 79 persons with HIV and 83 demographically matched seronegative controls and related this neural activity to performance on neuropsychological assessments of cognitive function. Consistent with previous works, persons with HIV exhibited stronger spontaneous gamma activity, particularly in inferior parietal, prefrontal and superior temporal cortices. In addition, serostatus moderated the relationship between spontaneous beta activity and attention, motor and processing speed scores, with controls but not persons with HIV showing stronger beta activity with better performance. The current results suggest that HIV predominantly impacts spontaneous activity in association cortices, consistent with alterations in higher-order brain function, and may be attributable to deficient GABAergic signalling, given its known role in the generation of gamma and beta oscillations. Overall, these effects align with previous studies showing aberrant spontaneous activity in persons with HIV and provide a critical new linkage to domain-specific cognitive dysfunction.

A Role for Bottom-Up Alpha Oscillations in Temporal Integration

Neural oscillations in the 8-12 Hz alpha band are thought to represent top-down inhibitory control and to influence temporal resolution: Individuals with faster peak frequencies segregate stimuli appearing closer in time. Recently, this theory has been challenged. Here, we investigate a special case in which alpha does not correlate with temporal resolution: when stimuli are presented amidst strong visual drive. Based on findings regarding alpha rhythmogenesis and wave spatial propagation, we suggest that stimulus-induced, bottom-up alpha oscillations play a role in temporal integration. We propose a theoretical model, informed by visual persistence, lateral inhibition, and network refractory periods, and simulate physiologically plausible scenarios of the interaction between bottom-up alpha and the temporal segregation. Our simulations reveal that different features of oscillations, including frequency, phase, and power, can influence temporal perception and provide a theoretically informed starting point for future empirical studies.

Sensory Drive Modifies Brain Dynamics and the Temporal Integration Window

Perception is suggested to occur in discrete temporal windows, clocked by cycles of neural oscillations. An important testable prediction of this theory is that individuals' peak frequencies of oscillations should correlate with their ability to segregate the appearance of two successive stimuli. An influential study tested this prediction and showed that individual peak frequency of spontaneously occurring alpha (8-12 Hz) correlated with the temporal segregation threshold between two successive flashes of light [Samaha, J., & Postle, B. R. The speed of alpha-band oscillations predicts the temporal resolution of visual perception. Current Biology, 25, 2985-2990, 2015]. However, these findings were recently challenged [Buergers, S., & Noppeney, U. The role of alpha oscillations in temporal binding within and across the senses. Nature Human Behaviour, 6, 732-742, 2022]. To advance our understanding of the link between oscillations and temporal segregation, we devised a novel experimental approach. Rather than relying entirely on spontaneous brain dynamics, we presented a visual grating before the flash stimuli that is known to induce continuous oscillations in the gamma band (45-65 Hz). By manipulating the contrast of the grating, we found that high contrast induces a stronger gamma response and a shorter temporal segregation threshold, compared to low-contrast trials. In addition, we used a novel tool to characterize sustained oscillations and found that, for half of the participants, both the low- and high-contrast gratings were accompanied by a sustained and phase-locked alpha oscillation. These participants tended to have longer temporal segregation thresholds. Our results suggest that visual stimulus drive, reflected by oscillations in specific bands, is related to the temporal resolution of visual perception.

A Novel, Robust, and Portable Platform for Magnetoencephalography using Optically Pumped Magnetometers

Magnetoencephalography (MEG) measures brain function via assessment of magnetic fields generated by neural currents. Conventional MEG uses superconducting sensors, which place significant limitations on performance, practicality, and deployment; however, the field has been revolutionised in recent years by the introduction of optically-pumped-magnetometers (OPMs). OPMs enable measurement of the MEG signal without cryogenics, and consequently the conception of 'OPM-MEG' systems which ostensibly allow increased sensitivity and resolution, lifespan compliance, free subject movement, and lower cost. However, OPM-MEG remains in its infancy with limitations on both sensor and system design. Here, we report a new OPM-MEG design with miniaturised and integrated electronic control, a high level of portability, and improved sensor dynamic range (arguably the biggest limitation of existing instrumentation). We show that this system produces equivalent measures when compared to an established instrument; specifically, when measuring task-induced beta-band, gamma-band and evoked neuro-electrical responses, source localisations from the two systems were highly comparable and temporal correlation was >0.7 at the individual level and >0.9 for groups. Using an electromagnetic phantom, we demonstrate improved dynamic range by running the system in background fields up to 8 nT. We show that the system is effective in gathering data during free movement (including a sitting-to-standing paradigm) and that it is compatible with simultaneous electroencephalography (EEG - the clinical standard). Finally, we demonstrate portability by moving the system between two laboratories. Overall, our new system is shown to be a significant step forward for OPM-MEG technology and offers an attractive platform for next generation functional medical imaging.

Rodents' visual gamma as a biomarker of pathological neural conditions

Neural gamma oscillations (indicatively 30-100 Hz) are ubiquitous: they are associated with a broad range of functions in multiple cortical areas and across many animal species. Experimental and computational works established gamma rhythms as a global emergent property of neuronal networks generated by the balanced and coordinated interaction of excitation and inhibition. Coherently, gamma activity is strongly influenced by the alterations of synaptic dynamics which are often associated with pathological neural dysfunctions. We argue therefore that these oscillations are an optimal biomarker for probing the mechanism of cortical dysfunctions. Gamma oscillations are also highly sensitive to external stimuli in sensory cortices, especially the primary visual cortex (V1), where the stimulus dependence of gamma oscillations has been thoroughly investigated. Gamma manipulation by visual stimuli tuning is particularly easy in rodents, which have become a standard animal model for investigating the effects of network alterations on gamma oscillations. Overall, gamma in the rodents' visual cortex offers an accessible probe on dysfunctional information processing in pathological conditions. Beyond vision-related dysfunctions, alterations of gamma oscillations in rodents were indeed also reported in neural deficits such as migraine, epilepsy and neurodegenerative or neuropsychiatric conditions such as Alzheimer's, schizophrenia and autism spectrum disorders. Altogether, the connections between visual cortical gamma activity and physio-pathological conditions in rodent models underscore the potential of gamma oscillations as markers of neuronal (dys)functioning.

Brain activity characteristics of RGB stimulus: an EEG study

The perception of color is a fundamental cognitive feature of our psychological experience, with an essential role in many aspects of human behavior. Several studies used magnetoencephalography, functional magnetic resonance imaging, and electroencephalography (EEG) approaches to investigate color perception. Their methods includes the event-related potential and spectral power activity of different color spaces, such as Derrington-Krauskopf-Lennie and red-green-blue (RGB), in addition to exploring the psychological and emotional effects of colors. However, we found insufficient studies in RGB space that considered combining all aspects of EEG signals. Thus, in the present study, focusing on RGB stimuli and using a data-driven approach, we investigated significant differences in the perception of colors. Our findings show that beta oscillation of green compared to red and blue colors occurs in early sensory periods with a latency shifting in the occipital region. Furthermore, in the occipital region, the theta power of the blue color decreases noticeably compared to the other colors. Concurrently, in the prefrontal area, we observed an increase in phase consistency in response to the green color, while the blue color showed a decrease. Therefore, our results can be used to interpret the brain activity mechanism of color perception in RGB color space and to choose suitable colors for more efficient performance in cognitive activities.

The coupling between the spatial and temporal scales of neural processes revealed by a joint time-vertex connectome spectral analysis

Brain oscillations are produced by the coordinated activity of large groups of neurons and different rhythms are thought to reflect different modes of information processing. These modes, in turn, are known to occur at different spatial scales. Nevertheless, how these rhythms support different spatial modes of information processing at the brain scale is not yet fully understood. Here we use "Joint Time-Vertex Spectral Analysis" to characterize the joint spectral content of brain activity both in time (temporal frequencies) and in space over the connectivity graph (spatial connectome harmonics). This method allows us to characterize the relationship between spatially localized or distributed neural processes on one side and their respective temporal frequency bands in source-reconstructed M/EEG signals. We explore this approach on two different datasets, an auditory steady-state response (ASSR) and a visual grating task. Our results suggest that different information processing mechanisms are carried out at different frequency bands: while spatially distributed activity (which may also be interpreted as integration) specifically occurs at low temporal frequencies (alpha and theta) and low graph spatial frequencies, localized electrical activity (i.e., segregation) is observed at high temporal frequencies (high and low gamma) over restricted high spatial graph frequencies. Crucially, the estimated contribution of the distributed and localized neural activity predicts performance in a behavioral task, demonstrating the neurophysiological relevance of the joint time-vertex spectral representation.

A guide towards optimal detection of transient oscillatory bursts with unknown parameters

Objectives. Recent event-based analyses of transient neural activities have characterized the oscillatory bursts as a neural signature that bridges dynamic neural states to cognition and behaviors. Following this insight, our study aimed to (1) compare the efficacy of common burst detection algorithms under varying signal-to-noise ratios and event durations using synthetic signals and (2) establish a strategic guideline for selecting the optimal algorithm for real datasets with undefined properties.Approach.We tested the robustness of burst detection algorithms using a simulation dataset comprising bursts of multiple frequencies. To systematically assess their performance, we used a metric called 'detection confidence', quantifying classification accuracy and temporal precision in a balanced manner. Given that burst properties in empirical data are often unknown in advance, we then proposed a selection rule to identify an optimal algorithm for a given dataset and validated its application on local field potentials of basolateral amygdala recorded from male mice (n=8) exposed to a natural threat.Main Results.Our simulation-based evaluation demonstrated that burst detection is contingent upon event duration, whereas accurately pinpointing burst onsets is more susceptible to noise level. For real data, the algorithm chosen based on the selection rule exhibited superior detection and temporal accuracy, although its statistical significance differed across frequency bands. Notably, the algorithm chosen by human visual screening differed from the one recommended by the rule, implying a potential misalignment between human priors and mathematical assumptions of the algorithms.Significance.Therefore, our findings underscore that the precise detection of transient bursts is fundamentally influenced by the chosen algorithm. The proposed algorithm-selection rule suggests a potentially viable solution, while also emphasizing the inherent limitations originating from algorithmic design and volatile performances across datasets. Consequently, this study cautions against relying solely on heuristic-based approaches, advocating for a careful algorithm selection in burst detection studies.

Excitation-Inhibition Imbalance in Migraine: From Neurotransmitters to Brain Oscillations

Migraine is among the most common and debilitating neurological disorders typically affecting people of working age. It is characterised by a unilateral, pulsating headache often associated with severe pain. Despite the intensive research, there is still little understanding of the pathophysiology of migraine. At the electrophysiological level, altered oscillatory parameters have been reported within the alpha and gamma bands. At the molecular level, altered glutamate and GABA concentrations have been reported. However, there has been little cross-talk between these lines of research. Thus, the relationship between oscillatory activity and neurotransmitter concentrations remains to be empirically traced. Importantly, how these indices link back to altered sensory processing has to be clearly established as yet. Accordingly, pharmacologic treatments have been mostly symptom-based, and yet sometimes proving ineffective in resolving pain or related issues. This review provides an integrative theoretical framework of excitation-inhibition imbalance for the understanding of current evidence and to address outstanding questions concerning the pathophysiology of migraine. We propose the use of computational modelling for the rigorous formulation of testable hypotheses on mechanisms of homeostatic imbalance and for the development of mechanism-based pharmacological treatments and neurostimulation interventions.

Relating neural oscillations to laminar fMRI connectivity in visual cortex

Laminar functional magnetic resonance imaging (fMRI) holds the potential to study connectivity at the laminar level in humans. Here we analyze simultaneously recorded electroencephalography (EEG) and high-resolution fMRI data to investigate how EEG power modulations, induced by a task with an attentional component, relate to changes in fMRI laminar connectivity between and within brain regions in visual cortex. Our results indicate that our task-induced decrease in beta power relates to an increase in deep-to-deep layer coupling between regions and to an increase in deep/middle-to-superficial layer connectivity within brain regions. The attention-related alpha power decrease predominantly relates to reduced connectivity between deep and superficial layers within brain regions, since, unlike beta power, alpha power was found to be positively correlated to connectivity. We observed no strong relation between laminar connectivity and gamma band oscillations. These results indicate that especially beta band, and to a lesser extent, alpha band oscillations relate to laminar-specific fMRI connectivity. The differential effects for alpha and beta bands indicate that they relate to different feedback-related neural processes that are differentially expressed in intra-region laminar fMRI-based connectivity.

Gamma oscillations point to the role of primary visual cortex in atypical motion processing in autism

Neurophysiological studies suggest that abnormal neural inhibition may explain a range of sensory processing differences in autism spectrum disorders (ASD). In particular, the impaired ability of people with ASD to visually discriminate the motion direction of small-size objects and their reduced perceptual suppression of background-like visual motion may stem from deficient surround inhibition within the primary visual cortex (V1) and/or its atypical top-down modulation by higher-tier cortical areas. In this study, we estimate the contribution of abnormal surround inhibition to the motion-processing deficit in ASD. For this purpose, we used a putative correlate of surround inhibition-suppression of the magnetoencephalographic (MEG) gamma response (GR) caused by an increase in the drift rate of a large annular high-contrast grating. The motion direction discrimination thresholds for the gratings of different angular sizes (1° and 12°) were assessed in a separate psychophysical paradigm. The MEG data were collected in 42 boys with ASD and 37 typically developing (TD) boys aged 7-15 years. Psychophysical data were available in 33 and 34 of these participants, respectively. The results showed that the GR suppression in V1 was reduced in boys with ASD, while their ability to detect the direction of motion was compromised only in the case of small stimuli. In TD boys, the GR suppression directly correlated with perceptual suppression caused by increasing stimulus size, thus suggesting the role of the top-down modulations of V1 in surround inhibition. In ASD, weaker GR suppression was associated with the poor directional sensitivity to small stimuli, but not with perceptual suppression. These results strongly suggest that a local inhibitory deficit in V1 plays an important role in the reduction of directional sensitivity in ASD and that this perceptual deficit cannot be explained exclusively by atypical top-down modulation of V1 by higher-tier cortical areas.

Altered visual cortex excitability in premenstrual dysphoric disorder: Evidence from magnetoencephalographic gamma oscillations and perceptual suppression

Premenstrual dysphoric disorder (PMDD) is a psychiatric condition characterized by extreme mood shifts during the luteal phase of the menstrual cycle (MC) due to abnormal sensitivity to neurosteroids and unbalanced neural excitation/inhibition (E/I) ratio. We hypothesized that in women with PMDD in the luteal phase, these factors would alter the frequency of magnetoencephalographic visual gamma oscillations, affect modulation of their power by excitatory drive, and decrease perceptual spatial suppression. Women with PMDD and control women were examined twice-during the follicular and luteal phases of their MC. We recorded visual gamma response (GR) while modulating the excitatory drive by increasing the drift rate of the high-contrast grating (static, 'slow', 'medium', and 'fast'). Contrary to our expectations, GR frequency was not affected in women with PMDD in either phase of the MC. GR power suppression, which is normally associated with a switch from the 'optimal' for GR slow drift rate to the medium drift rate, was reduced in women with PMDD and was the only GR parameter that distinguished them from control participants specifically in the luteal phase and predicted severity of their premenstrual symptoms. Over and above the atypical luteal GR suppression, in both phases of the MC women with PMDD had abnormally strong GR facilitation caused by a switch from the 'suboptimal' static to the 'optimal' slow drift rate. Perceptual spatial suppression did not differ between the groups but decreased from the follicular to the luteal phase only in PMDD women. The atypical modulation of GR power suggests that neuronal excitability in the visual cortex is constitutively elevated in PMDD and that this E/I imbalance is further exacerbated during the luteal phase. However, the unaltered GR frequency does not support the hypothesis of inhibitory neuron dysfunction in PMDD.

Oscillatory Neural Signatures of Visual Perception Across Developmental Stages in Individuals With 22q11.2 Deletion Syndrome

BACKGROUND

Numerous behavioral studies have highlighted the contribution of visual perceptual deficits to the nonverbal cognitive profile of individuals with 22q11.2 deletion syndrome. However, the neurobiological processes underlying these widespread behavioral alterations are yet to be fully understood. Thus, in this paper, we investigated the role of neural oscillations toward visuoperceptual deficits to elucidate the neurobiology of sensory impairments in deletion carriers.

METHODS

We acquired 125 high-density electroencephalography recordings during a visual grating task in a group of 62 deletion carriers and 63 control subjects. Stimulus-elicited oscillatory responses were analyzed with 1) time-frequency analysis using wavelets decomposition at sensor and source level, 2) intertrial phase coherence, and 3) Granger causality connectivity in source space. Additional analyses examined the development of neural oscillations across age bins.

RESULTS

Deletion carriers had decreased theta-band (4-8 Hz) and gamma-band (58-68 Hz) spectral power compared with control subjects in response to the visual stimuli, with an absence of age-related increase of theta- and gamma-band responses. Moreover, adult deletion carriers had decreased gamma- and theta-band responses but increased alpha/beta desynchronization (10-25 Hz) that correlated with behavioral performance. Granger causality estimates reflected an increased frontal-occipital connectivity in the beta range (22-40 Hz).

CONCLUSIONS

Deletion carriers exhibited decreased theta- and gamma-band responses to visual stimuli, while alpha/beta desynchronization was preserved. Overall, the lack of age-related changes in deletion carriers implicates developmental impairments in circuit mechanisms underlying neural oscillations. The dissociation between the maturation of theta/gamma- and alpha/beta-band responses may indicate a selective impairment in supragranular cortical layers, leading to compensatory top-down connectivity.

Eyes-closed versus eyes-open differences in spontaneous neural dynamics during development

BACKGROUND

Assessing brain activity during rest has become a widely used approach in developmental neuroscience. Extant literature has measured resting brain activity both during eyes-open and eyes-closed conditions, but the difference between these conditions has not yet been well characterized. Studies, limited to fMRI and EEG, have suggested that eyes-open versus -closed conditions may differentially impact neural activity, especially in visual cortices.

METHODS

Spontaneous cortical activity was recorded using MEG from 108 typically developing youth (9-15 years-old; 55 female) during separate sessions of eyes-open and eyes-closed rest. MEG source images were computed, and the strength of spontaneous neural activity was estimated in the canonical delta, theta, alpha, beta, and gamma bands, respectively. Power spectral density maps for eyes-open were subtracted from eyes-closed rest, and then submitted to vertex-wise regression models to identify spatially specific differences between conditions and as a function of age and sex.

RESULTS

Relative alpha power was weaker in the eyes-open compared to -closed condition, but otherwise eyes-open was stronger in all frequency bands, with differences concentrated in the occipital cortex. Relative theta power became stronger in the eyes-open compared to the eyes-closed condition with increasing age in frontal cortex. No differences were observed between males and females.

CONCLUSIONS

The differences in relative power from eyes-closed to -open conditions are consistent with changes observed in task-based visual sensory responses. Age differences occurred in relatively late developing frontal regions, consistent with canonical attention regions, suggesting that these differences could be reflective of developmental changes in attention processes during puberty. Taken together, resting-state paradigms using eyes-open versus -closed produce distinct results and, in fact, can help pinpoint sensory related brain activity.

The Spatial Reach of Neuronal Coherence and Spike-Field Coupling across the Human Neocortex

Neuronal coherence is thought to be a fundamental mechanism of communication in the brain, where synchronized field potentials coordinate synaptic and spiking events to support plasticity and learning. Although the spread of field potentials has garnered great interest, little is known about the spatial reach of phase synchronization, or neuronal coherence. Functional connectivity between different brain regions is known to occur across long distances, but the locality of synchronization across the neocortex is understudied. Here we used simultaneous recordings from electrocorticography (ECoG) grids and high-density microelectrode arrays to estimate the spatial reach of neuronal coherence and spike-field coherence (SFC) across frontal, temporal, and occipital cortices during cognitive tasks in humans. We observed the strongest coherence within a 2-3 cm distance from the microelectrode arrays, potentially defining an effective range for local communication. This range was relatively consistent across brain regions, spectral frequencies, and cognitive tasks. The magnitude of coherence showed power law decay with increasing distance from the microelectrode arrays, where the highest coherence occurred between ECoG contacts, followed by coherence between ECoG and deep cortical local field potential (LFP), and then SFC (i.e., ECoG > LFP > SFC). The spectral frequency of coherence also affected its magnitude. Alpha coherence (8-14 Hz) was generally higher than other frequencies for signals nearest the microelectrode arrays, whereas delta coherence (1-3 Hz) was higher for signals that were farther away. Action potentials in all brain regions were most coherent with the phase of alpha oscillations, which suggests that alpha waves could play a larger, more spatially local role in spike timing than other frequencies. These findings provide a deeper understanding of the spatial and spectral dynamics of neuronal synchronization, further advancing knowledge about how activity propagates across the human brain.SIGNIFICANCE STATEMENT Coherence is theorized to facilitate information transfer across cerebral space by providing a convenient electrophysiological mechanism to modulate membrane potentials in spatiotemporally complex patterns. Our work uses a multiscale approach to evaluate the spatial reach of phase coherence and spike-field coherence during cognitive tasks in humans. Locally, coherence can reach up to 3 cm around a given area of neocortex. The spectral properties of coherence revealed that alpha phase-field and spike-field coherence were higher within ranges <2 cm, whereas lower-frequency delta coherence was higher for contacts farther away. Spatiotemporally shared information (i.e., coherence) across neocortex seems to reach farther than field potentials alone.

FLUX: A pipeline for MEG analysis

Magnetoencephalography (MEG) allows for quantifying modulations of human neuronal activity on a millisecond time scale while also making it possible to estimate the location of the underlying neuronal sources. The technique relies heavily on signal processing and source modelling. To this end, there are several open-source toolboxes developed by the community. While these toolboxes are powerful as they provide a wealth of options for analyses, the many options also pose a challenge for reproducible research as well as for researchers new to the field. The FLUX pipeline aims to make the analyses steps and setting explicit for standard analysis done in cognitive neuroscience. It focuses on quantifying and source localization of oscillatory brain activity, but it can also be used for event-related fields and multivariate pattern analysis. The pipeline is derived from the Cogitate consortium addressing a set of concrete cognitive neuroscience questions. Specifically, the pipeline including documented code is defined for MNE Python (a Python toolbox) and FieldTrip (a Matlab toolbox), and a data set on visuospatial attention is used to illustrate the steps. The scripts are provided as notebooks implemented in Jupyter Notebook and MATLAB Live Editor providing explanations, justifications and graphical outputs for the essential steps. Furthermore, we also provide suggestions for text and parameter settings to be used in registrations and publications to improve replicability and facilitate pre-registrations. The FLUX can be used for education either in self-studies or guided workshops. We expect that the FLUX pipeline will strengthen the field of MEG by providing some standardization on the basic analysis steps and by aligning approaches across toolboxes. Furthermore, we also aim to support new researchers entering the field by providing education and training. The FLUX pipeline is not meant to be static; it will evolve with the development of the toolboxes and with new insights. Furthermore, with the anticipated increase in MEG systems based on the Optically Pumped Magnetometers, the pipeline will also evolve to embrace these developments.

Human visual gamma for color stimuli

Strong gamma-band oscillations in primate early visual cortex can be induced by homogeneous color surfaces (Peter et al., 2019; Shirhatti and Ray, 2018). Compared to other hues, particularly strong gamma oscillations have been reported for red stimuli. However, precortical color processing and the resultant strength of input to V1 have often not been fully controlled for. Therefore, stronger responses to red might be due to differences in V1 input strength. We presented stimuli that had equal luminance and cone contrast levels in a color coordinate system based on responses of the lateral geniculate nucleus, the main input source for area V1. With these stimuli, we recorded magnetoencephalography in 30 human participants. We found gamma oscillations in early visual cortex which, contrary to previous reports, did not differ between red and green stimuli of equal L-M cone contrast. Notably, blue stimuli with contrast exclusively on the S-cone axis induced very weak gamma responses, as well as smaller event-related fields and poorer change-detection performance. The strength of human color gamma responses for stimuli on the L-M axis could be well explained by L-M cone contrast and did not show a clear red bias when L-M cone contrast was properly equalized.

Longitudinal study of infants receiving extra motor stimulation, full‐term control infants, and infants born preterm: High‐density EEG analyses of cortical activity in response to visual motion

Electroencephalography was used to investigate the effects of extrastimulation and preterm birth on the development of visual motion perception during early infancy. Infants receiving extra motor stimulation in the form of baby swimming, a traditionally raised control group, and preterm born infants were presented with an optic flow pattern simulating forward and reversed self‐motion and unstructured random visual motion before and after they achieved self‐produced locomotion. Extrastimulated infants started crawling earlier and displayed significantly shorter N2 latencies in response to visual motion than their full‐term and preterm peers. Preterm infants could not differentiate between visual motion conditions, nor did they significantly decrease their latencies with age and locomotor experience. Differences in induced activities were also observed with desynchronized theta‐band activity in all infants, but with more mature synchronized alpha–beta band activity only in extrastimulated infants after they had become mobile. Compared with the other infants, preterm infants showed more widespread desynchronized oscillatory activities at lower frequencies at the age of 1 year (corrected for prematurity). The overall advanced performance of extrastimulated infants was attributed to their enriched motor stimulation. The poorer responses in the preterm infants could be related to impairment of the dorsal visual stream that is specialized in the processing of visual motion.

Using OPM-MEG in contrasting magnetic environments

Magnetoencephalography (MEG) has been revolutionised by optically pumped magnetometers (OPMs). "OPM-MEG" offers higher sensitivity, better spatial resolution, and lower cost than conventional instrumentation based on superconducting quantum interference devices (SQUIDs). Moreover, because OPMs are small, lightweight, and portable they offer the possibility of lifespan compliance and (with control of background field) motion robustness, dramatically expanding the range of MEG applications. However, OPM-MEG remains nascent technology; it places stringent requirements on magnetic shielding, and whilst a number of viable systems exist, most are custom made and there have been no cross-site investigations showing the reliability of data. In this paper, we undertake the first cross-site OPM-MEG comparison, using near identical commercial systems scanning the same participant. The two sites are deliberately contrasting, with different magnetic environments: a "green field" campus university site with an OPM-optimised shielded room (low interference) and a city centre hospital site with a "standard" (non-optimised) MSR (higher interference). We show that despite a 20-fold difference in background field, and a 30-fold difference in low frequency interference, using dynamic field control and software-based suppression of interference we can generate comparable noise floors at both sites. In human data recorded during a visuo-motor task and a face processing paradigm, we were able to generate similar data, with source localisation showing that brain regions could be pinpointed with just ∼10 mm spatial discrepancy and temporal correlations of > 80%. Overall, our study demonstrates that, with appropriate field control, OPM-MEG systems can be sited even in city centre hospital locations. The methods presented pave the way for wider deployment of OPM-MEG.

State anxiety alters the neural oscillatory correlates of predictions and prediction errors during reward-based learning

Anxiety influences how the brain estimates and responds to uncertainty. The consequences of these processes on behaviour have been described in theoretical and empirical studies, yet the associated neural correlates remain unclear. Rhythm-based accounts of Bayesian predictive coding propose that predictions in generative models of perception are represented in alpha (8-12 Hz) and beta oscillations (13-30 Hz). Updates to predictions are driven by prediction errors weighted by precision (inverse variance) encoded in gamma oscillations (>30 Hz) and associated with the suppression of beta activity. We tested whether state anxiety alters the neural oscillatory activity associated with predictions and precision-weighted prediction errors (pwPE) during learning. Healthy human participants performed a probabilistic reward-based learning task in a volatile environment. In our previous work, we described learning behaviour in this task using a hierarchical Bayesian model, revealing more precise (biased) beliefs about the tendency of the reward contingency in state anxiety, consistent with reduced learning in this group. The model provided trajectories of predictions and pwPEs for the current study, allowing us to assess their parametric effects on the time-frequency representations of EEG data. Using convolution modelling for oscillatory responses, we found that, relative to a control group, state anxiety increased beta activity in frontal and sensorimotor regions during processing of pwPE, and in fronto-parietal regions during encoding of predictions. No effects of state anxiety on gamma modulation were found. Our findings expand prior evidence on the oscillatory representations of predictions and pwPEs into the reward-based learning domain. The results suggest that state anxiety modulates beta-band oscillatory correlates of pwPE and predictions in generative models, providing insights into the neural processes associated with biased belief updating and poorer learning.

Stimulus-induced narrowband gamma oscillations are test–retest reliable in human EEG

Visual stimulus-induced gamma oscillations in electroencephalogram (EEG) recordings have been recently shown to be compromised in subjects with preclinical Alzheimer’s Disease (AD), suggesting that gamma could be an inexpensive biomarker for AD diagnosis provided its characteristics remain consistent across multiple recordings. Previous magnetoencephalography studies in young subjects have reported consistent gamma power over recordings separated by a few weeks to months. Here, we assessed the consistency of stimulus-induced slow (20–35 Hz) and fast gamma (36–66 Hz) oscillations in subjects (n = 40) (age: 50–88 years) in EEG recordings separated by a year, and tested the consistency in the magnitude of gamma power, its temporal evolution and spectral profile. Gamma had distinct spectral/temporal characteristics across subjects, which remained consistent across recordings (average intraclass correlation of ~0.7). Alpha (8–12 Hz) and steady-state-visually evoked-potentials were also reliable. We further tested how EEG features can be used to identify 2 recordings as belonging to the same versus different subjects and found high classifier performance (AUC of ~0.89), with temporal evolution of slow gamma and spectral profile being most informative. These results suggest that EEG gamma oscillations are reliable across sessions separated over long durations and can also be a potential tool for subject identification.

Holo-Hilbert spectral-based noise removal method for EEG high-frequency bands

Simultaneous EEG-fMRI is a growing and promising field, as it has great potential to further our understanding of the spatiotemporal dynamics of brain function in health and disease. In particular, there is much interest in understanding the fMRI correlates of brain activity in the gamma band (> 30 Hz), as these frequencies are thought to be associated with cognitive processes involving perception, attention, and memory, as well as with disorders such as schizophrenia and autism. However, progress in this area has been limited due to issues such as MR-induced artifacts in EEG recordings, which seem to be more problematic for gamma frequencies. This paper presents a noise removal method for the gamma band of EEG that is based on the Holo-Hilbert spectral analysis (HHSA), but with a new implementation strategy. HHSA uses a nested empirical mode decomposition (EMD) to identify amplitude and frequency modulations (AM and FM, respectively) by averaging over frequencies with high and significant powers. Our method examines gamma band by applying two layers of EMD to the FM and AM components, removing components with very low power based on the power-instantaneous frequency spectrum, and subsequently reconstructs the denoised gamma-band signal from the remaining components. Simulations demonstrate that our proposed method efficiently reduces artifacts while preserving the original gamma signal which is especially critical for simultaneous EEG/fMRI studies.

Cortical oscillatory dysrhythmias in visual snow syndrome: a magnetoencephalography study

Visual snow refers to the persistent visual experience of static in the whole visual field of both eyes. It is often reported by patients with migraine and co-occurs with conditions such as tinnitus and tremor. The underlying pathophysiology of the condition is poorly understood. Previously, we hypothesized that visual snow syndrome may be characterized by disruptions to rhythmical activity within the visual system. To test this, data from 18 patients diagnosed with visual snow syndrome, and 16 matched controls, were acquired using magnetoencephalography. Participants were presented with visual grating stimuli, known to elicit decreases in alpha-band (8–13 Hz) power and increases in gamma-band power (40–70 Hz). Data were mapped to source-space using a beamformer. Across both groups, decreased alpha power and increased gamma power localized to early visual cortex. Data from the primary visual cortex were compared between groups. No differences were found in either alpha or gamma peak frequency or the magnitude of alpha power, p > 0.05. However, compared with controls, our visual snow syndrome cohort displayed significantly increased primary visual cortex gamma power, p = 0.035. This new electromagnetic finding concurs with previous functional MRI and PET findings, suggesting that in visual snow syndrome, the visual cortex is hyperexcitable. The coupling of alpha-phase to gamma amplitude within the primary visual cortex was also quantified. Compared with controls, the visual snow syndrome group had significantly reduced alpha–gamma phase–amplitude coupling, p < 0.05, indicating a potential excitation–inhibition imbalance in visual snow syndrome, as well as a potential disruption to top-down ‘noise-cancellation’ mechanisms. Overall, these results suggest that rhythmical brain activity in the primary visual cortex is both hyperexcitable and disorganized in visual snow syndrome, consistent with this being a condition of thalamocortical dysrhythmia.

Genetic risk for schizophrenia is associated with altered visually-induced gamma band activity: evidence from a population sample stratified polygenic risk

Gamma oscillations (30-90 Hz) have been proposed as a signature of cortical visual information processing, particularly the balance between excitation and inhibition, and as a biomarker of neuropsychiatric diseases. Magnetoencephalography (MEG) provides highly reliable visual-induced gamma oscillation estimates, both at sensor and source level. Recent studies have reported a deficit of visual gamma activity in schizophrenia patients, in medication naive subjects, and high-risk clinical participants, but the genetic contribution to such a deficit has remained unresolved. Here, for the first time, we use a genetic risk score approach to assess the relationship between genetic risk for schizophrenia and visual gamma activity in a population-based sample drawn from a birth cohort. We compared visual gamma activity in a group (N = 104) with a high genetic risk profile score for schizophrenia (SCZ-PRS) to a group with low SCZ-PRS (N = 99). Source-reconstructed V1 activity was extracted using beamformer analysis applied to MEG recordings using individual MRI scans. No group differences were found in the induced gamma peak amplitude or peak frequency. However, a non-parametric statistical contrast of the response spectrum revealed more robust group differences in the amplitude of high-beta/gamma power across the frequency range, suggesting that overall spectral shape carries important biological information beyond the individual frequency peak. Our findings show that changes in gamma band activity correlate with liability to schizophrenia and suggest that the index changes to synaptic function and neuronal firing patterns that are of pathophysiological relevance rather than consequences of the disorder.

Can the causal role of brain oscillations be studied through rhythmic brain stimulation?

Many studies have investigated the causal relevance of brain oscillations using rhythmic stimulation, either through direct-brain or sensory stimulation. Yet, how intrinsic rhythms interact with the externally generated rhythm is largely unknown. We presented a flickered (60 Hz) visual grating or its correspondent unflickered stimulus in a psychophysical change detection task during simultaneous magnetoencephalography recordings to humans to test the effect of visual entrainment on induced gamma oscillations. Notably, we generally observed the coexistence of the broadband induced gamma rhythm with the entrained flicker rhythm (reliably measured in each participant), with the peak frequency of the induced response remaining unaltered in approximately half of participants—relatively independently of their native frequency. However, flicker increased broadband induced gamma power, and this was stronger in participants with a native frequency closer to the flicker frequency (resonance) and led to strong phase entrainment. Presence of flicker did not change behavior itself but profoundly altered brain behavior correlates across the sample: While broadband induced gamma oscillations correlated with reaction times for unflickered stimuli (as known previously), for the flicker, the amplitude of the entrained flicker rhythm (but no more the induced oscillation) correlated with reaction times. This, however, strongly depended on whether a participant's peak frequency shifted to the entrained rhythm. Our results suggests that rhythmic brain stimulation leads to a coexistence of two partially independent oscillations with heterogeneous effects across participants on the downstream relevance of these rhythms for behavior. This may explain the inconsistency of findings related to external entrainment of brain oscillations and poses further questions toward causal manipulations of brain oscillations in general.

No Evidence for Entrainment: Endogenous Gamma Oscillations and Rhythmic Flicker Responses Coexist in Visual Cortex

Over the past decades, numerous studies have linked cortical gamma oscillations (∼30-100 Hz) to neurocomputational mechanisms. Their functional relevance, however, is still passionately debated. Here, we asked whether endogenous gamma oscillations in the human brain can be entrained by a rhythmic photic drive >50 Hz. Such a noninvasive modulation of endogenous brain rhythms would allow conclusions about their causal involvement in neurocognition. To this end, we systematically investigated oscillatory responses to a rapid sinusoidal flicker in the absence and presence of endogenous gamma oscillations using magnetoencephalography (MEG) in combination with a high-frequency projector. The photic drive produced a robust response over visual cortex to stimulation frequencies of up to 80 Hz. Strong, endogenous gamma oscillations were induced using moving grating stimuli as repeatedly done in previous research. When superimposing the flicker and the gratings, there was no evidence for phase or frequency entrainment of the endogenous gamma oscillations by the photic drive. Unexpectedly, we did not observe an amplification of the flicker response around participants' individual gamma frequencies (IGFs); rather, the magnitude of the response decreased monotonically with increasing frequency. Source reconstruction suggests that the flicker response and the gamma oscillations were produced by separate, coexistent generators in visual cortex. The presented findings challenge the notion that cortical gamma oscillations can be entrained by rhythmic visual stimulation. Instead, the mechanism generating endogenous gamma oscillations seems to be resilient to external perturbation.SIGNIFICANCE STATEMENT We aimed to investigate to what extent ongoing, high-frequency oscillations in the gamma-band (30-100 Hz) in the human brain can be entrained by a visual flicker. Gamma oscillations have long been suggested to coordinate neuronal firing and enable interregional communication. Our results demonstrate that rhythmic visual stimulation cannot hijack the dynamics of ongoing gamma oscillations; rather, the flicker response and the endogenous gamma oscillations coexist in different visual areas. Therefore, while a visual flicker evokes a strong neuronal response even at high frequencies in the gamma-band, it does not entrain endogenous gamma oscillations in visual cortex. This has important implications for interpreting studies investigating the causal and neuroprotective effects of rhythmic sensory stimulation in the gamma-band.

Brain networks and cognitive impairment in Parkinson's disease

Aim The aim of the present study is to investigate the relations between both functional connectivity and brain networks with cognitive decline, in patients with Parkinson's disease (PD). Introduction PD phenotype is not limited to motor impairment but, rather, a wide range of non-motor disturbances can occur, cognitive impairment being one of the commonest. However, how the large-scale organization of brain activity differs in cognitively impaired patients, as opposed to cognitively preserved ones, remains poorly understood. Methods Starting from source-reconstructed resting-state magnetoencephalography data, we applied the PLM to estimate functional connectivity, globally and between brain areas, in PD patients with and without cognitive impairment (respectively PD-CI and PD-NC), as compared to healthy subjects (HS). Furthermore, using graph analysis, we characterized the alterations in brain network topology and related these, as well as the functional connectivity, to cognitive performance. Results We found reduced global and nodal PLM in several temporal (fusiform gyrus, Heschl's gyrus and inferior temporal gyrus), parietal (postcentral gyrus), and occipital (lingual gyrus) areas within the left hemisphere, in the gamma band, in PD-CI patients, as compared to PD-NC and HS. With regard to the global topological features, PD-CI patients, as compared to HS and PD-NC patients, showed differences in multi frequencies bands (delta, alpha, gamma) in the Leaf fraction, Tree hierarchy (both higher in PD-CI) and Diameter (lower in PD-CI). Finally, we found statistically significant correlations between the MoCA test and both the Diameter in delta band and the Tree Hierarchy in the alpha band. Conclusion Our work points to specific large-scale rearrangements that occur selectively in cognitively compromised PD patients and correlated to cognitive impairment.

Visual gamma oscillations predict sensory sensitivity in females as they do in males

Gamma oscillations are driven by local cortical excitatory (E)-inhibitory (I) loops and may help to characterize neural processing involving excitatory-inhibitory interactions. In the visual cortex reliable gamma oscillations can be recorded with magnetoencephalography (MEG) in the majority of individuals, which makes visual gamma an attractive candidate for biomarkers of brain disorders associated with E/I imbalance. Little is known, however, about if/how these oscillations reflect individual differences in neural excitability and associated sensory/perceptual phenomena. The power of visual gamma response (GR) changes nonlinearly with increasing stimulation intensity: it increases with transition from static to slowly drifting high-contrast grating and then attenuates with further increase in the drift rate. In a recent MEG study we found that the GR attenuation predicted sensitivity to sensory stimuli in everyday life in neurotypical adult men and in men with autism spectrum disorders. Here, we replicated these results in neurotypical female participants. The GR enhancement with transition from static to slowly drifting grating did not correlate significantly with the sensory sensitivity measures. These findings suggest that weak velocity-related attenuation of the GR is a reliable neural concomitant of visual hypersensitivity and that the degree of GR attenuation may provide useful information about E/I balance in the visual cortex.

The visual cortex produces gamma band echo in response to broadband visual flicker

The aim of this study is to uncover the network dynamics of the human visual cortex by driving it with a broadband random visual flicker. We here applied a broadband flicker (1-720 Hz) while measuring the MEG and then estimated the temporal response function (TRF) between the visual input and the MEG response. This TRF revealed an early response in the 40-60 Hz gamma range as well as in the 8-12 Hz alpha band. While the gamma band response is novel, the latter has been termed the alpha band perceptual echo. The gamma echo preceded the alpha perceptual echo. The dominant frequency of the gamma echo was subject-specific thereby reflecting the individual dynamical properties of the early visual cortex. To understand the neuronal mechanisms generating the gamma echo, we implemented a pyramidal-interneuron gamma (PING) model that produces gamma oscillations in the presence of constant input currents. Applying a broadband input current mimicking the visual stimulation allowed us to estimate TRF between the input current and the population response (akin to the local field potentials). The TRF revealed a gamma echo that was similar to the one we observed in the MEG data. Our results suggest that the visual gamma echo can be explained by the dynamics of the PING model even in the absence of sustained gamma oscillations.

Sexually dimorphic development in the cortical oscillatory dynamics serving early visual processing

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Visual processing dynamics continue to develop throughout childhood and adolescence.

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Visual alpha response power differed between males and females.

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Sex and age interacted to modulate visual gamma responses.

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Peak frequency predicted response power above and beyond the effects of age and sex.

Successful interaction with one’s visual environment is paramount to developing and performing many basic and complex mental functions. Although major aspects of visual development are completed at an early age, other structural and functional components of visual processing appear to be dynamically changing across a much more protracted period extending into late childhood and adolescence. However, the underlying neurophysiological changes and cortical oscillatory dynamics that support maturation of the visual system during this developmental period remain poorly understood. The present study utilized magnetoencephalography (MEG) to investigate maturational changes in the neural dynamics serving basic visual processing during childhood and adolescence (ages 9–15, n = 69). Our key results included robust sex differences in alpha oscillatory activity within the left posterior parietal cortex, and sex-by-age interactions in gamma activity in the right lingual gyrus and superior parietal lobule. Hierarchical regression revealed that the peak frequency of both the alpha and gamma responses predicted response power in parietal regions above and beyond the noted effects of age and sex. These findings affirm the view that neural oscillations supporting visual processing develop over a much more protracted period, and illustrate that these maturational trajectories are influenced by numerous elements, including age, sex, and individual variation.

Reviewing Evidence for the Relationship of EEG Abnormalities and RTT Phenotype Paralleled by Insights from Animal Studies

Rett syndrome (RTT) is a rare neurodevelopmental disorder that is usually caused by mutations of the MECP2 gene. Patients with RTT suffer from severe deficits in motor, perceptual and cognitive domains. Electroencephalogram (EEG) has provided useful information to clinicians and scientists, from the very first descriptions of RTT, and yet no reliable neurophysiological biomarkers related to the pathophysiology of the disorder or symptom severity have been identified to date. To identify consistently observed and potentially informative EEG characteristics of RTT pathophysiology, and ascertain areas most worthy of further systematic investigation, here we review the literature for EEG abnormalities reported in patients with RTT and in its disease models. While pointing to some promising potential EEG biomarkers of RTT, our review identify areas of need to realize the potential of EEG including (1) quantitative investigation of promising clinical-EEG observations in RTT, e.g., shift of mu rhythm frequency and EEG during sleep; (2) closer alignment of approaches between patients with RTT and its animal models to strengthen the translational significance of the work (e.g., EEG measurements and behavioral states); (3) establishment of large-scale consortium research, to provide adequate Ns to investigate age and genotype effects.

Age differences in resting state EEG and their relation to eye movements and cognitive performance

Prior research has focused on EEG differences across age or EEG differences across cognitive tasks/eye tracking. There are few studies linking age differences in EEG to age differences in behavioural performance which is necessary to establish how neuroactivity corresponds to successful and impaired ageing. Eighty-six healthy participants completed a battery of cognitive tests and eye-tracking measures. Resting state EEG (n = 75, 31 young, 44 older adults) was measured for delta, theta, alpha and beta power as well as for alpha peak frequency. Age deficits in cognition were aligned with the literature, showing working memory and inhibitory deficits along with an older adult advantage in vocabulary. Older adults showed poorer eye movement accuracy and response times, but we did not replicate literature showing a greater age deficit for antisaccades than for prosaccades. We replicated EEG literature showing lower alpha peak frequency in older adults but not literature showing lower alpha power. Older adults also showed higher beta power and less parietal alpha power asymmetry than young adults. Interaction effects showed that better prosaccade performance was related to lower beta power in young adults but not in older adults. Performance at the trail making test part B (measuring task switching and inhibition) was improved for older adults with higher resting state delta power but did not depend on delta power for young adults. It is argued that individuals with higher slow-wave resting EEG may be more resilient to age deficits in tasks that utilise cross-cortical processing.

40-Hz Auditory Steady-State Response (ASSR) as a Biomarker of Genetic Defects in the SHANK3 Gene: A Case Report of 15-Year-Old Girl with a Rare Partial SHANK3 Duplication

SHANK3 encodes a scaffold protein involved in postsynaptic receptor density in glutamatergic synapses, including those in the parvalbumin (PV)+ inhibitory neurons—the key players in the generation of sensory gamma oscillations, such as 40-Hz auditory steady-state response (ASSR). However, 40-Hz ASSR was not studied in relation to SHANK3 functioning. Here, we present a 15-year-old girl (SH01) with previously unreported duplication of the first seven exons of the SHANK3 gene (22q13.33). SH01’s electroencephalogram (EEG) during 40-Hz click trains of 500 ms duration binaurally presented with inter-trial intervals of 500–800 ms were compared with those from typically developing children (n = 32). SH01 was diagnosed with mild mental retardation and learning disabilities (F70.88), dysgraphia, dyslexia, and smaller vocabulary than typically developing (TD) peers. Her clinical phenotype resembled the phenotype of previously described patients with 22q13.33 microduplications (≈30 reported so far). SH01 had mild autistic symptoms but below the threshold for ASD diagnosis and microcephaly. No seizures or MRI abnormalities were reported. While SH01 had relatively preserved auditory event-related potential (ERP) with slightly attenuated P1, her 40-Hz ASSR was totally absent significantly deviating from TD’s ASSR. The absence of 40-Hz ASSR in patients with microduplication, which affected the SHANK3 gene, indicates deficient temporal resolution of the auditory system, which might underlie language problems and represent a neurophysiological biomarker of SHANK3 abnormalities.

Measuring functional connectivity with wearable MEG

Optically-pumped magnetometers (OPMs) offer the potential for a step change in magnetoencephalography (MEG) enabling wearable systems that provide improved data quality, accommodate any subject group, allow data capture during movement and potentially reduce cost. However, OPM-MEG is a nascent technology and, to realise its potential, it must be shown to facilitate key neuroscientific measurements, such as the characterisation of brain networks. Networks, and the connectivities that underlie them, have become a core area of neuroscientific investigation, and their importance is underscored by many demonstrations of their disruption in brain disorders. Consequently, a demonstration of network measurements using OPM-MEG would be a significant step forward. Here, we aimed to show that a wearable 50-channel OPM-MEG system enables characterisation of the electrophysiological connectome. To this end, we measured connectivity in the resting state and during a visuo-motor task, using both OPM-MEG and a state-of-the-art 275-channel cryogenic MEG device. Our results show that resting-state connectome matrices from OPM and cryogenic systems exhibit a high degree of similarity, with correlation values >70%. In addition, in task data, similar differences in connectivity between individuals (scanned multiple times) were observed in cryogenic and OPM-MEG data, again demonstrating the fidelity of the OPM-MEG device. This is the first demonstration of network connectivity measured using OPM-MEG, and results add weight to the argument that OPMs will ultimately supersede cryogenic sensors for MEG measurement.

Narrowband multivariate source separation for semi-blind discovery of experiment contrasts

BACKGROUND

Electrophysiological recordings contain mixtures of signals from distinct neural sources, impeding a straightforward interpretation of the sensor-level data. This mixing is particularly detrimental when distinct sources resonate in overlapping frequencies. Fortunately, the mixing is linear and instantaneous. Multivariate source separation methods may therefore successfully separate statistical sources, even with overlapping spatial distributions.

NEW METHOD

We demonstrate a feature-guided multivariate source separation method that is tuned to narrowband frequency content as well as binary condition differences. This method - comparison scanning generalized eigendecomposition, csGED - harnesses the covariance structure of multichannel data to find directions (i.e., eigenvectors) that maximally separate two subsets of data. To drive condition specificity and frequency specificity, our data subsets were taken from different task conditions and narrowband-filtered prior to applying GED.

RESULTS

To validate the method, we simulated MEG data in two conditions with shared noise characteristics and unique signal. csGED outperformed the best sensor at reconstructing the ground truth signals, even in the presence of large amounts of noise. We next applied csGED to a published empirical MEG dataset on visual perception vs. imagery. csGED identified sources in alpha, beta, and gamma bands, and successfully separated distinct networks in the same frequency band.

COMPARISON WITH EXISTING METHOD(S)

GED is a flexible feature-guided decomposition method that has previously successfully been applied. Our combined frequency- and condition-tuning is a novel adaptation that extends the power of GED in cognitive electrophysiology.

CONCLUSIONS

We demonstrate successful condition-specific source separation by applying csGED to simulated and empirical data.

The gamma response to colour hue in humans: Evidence from MEG

It has recently been demonstrated through invasive electrophysiology that visual stimulation with extended patches of uniform colour generates pronounced gamma oscillations in the visual cortex of both macaques and humans. In this study we sought to discover if this oscillatory response to colour can be measured non-invasively in humans using magnetoencephalography. We were able to demonstrate increased gamma (40–70 Hz) power in response to full-screen stimulation with four different colour hues and found that the gamma response is particularly strong for long wavelength (i.e. red) stimulation, as was found in previous studies. However, we also found that gamma power in response to colour was generally weaker than the response to an identically sized luminance-defined grating. We also observed two additional responses in the gamma frequency: a lower frequency response around 25–35 Hz that showed fewer clear differences between conditions than the gamma response, and a higher frequency response around 70–100 Hz that was present for red stimulation but not for other colours. In a second experiment we sought to test whether differences in the gamma response between colour hues could be explained by their chromatic separation from the preceding display. We presented stimuli that alternated between each of the three pairings of the three primary colours (red, green, blue) at two levels of chromatic separation defined in the CIELUV colour space. We observed that the gamma response was significantly greater to high relative to low chromatic separation, but that at each level of separation the response was greater for both red-blue and red-green than for blue-green stimulation. Our findings suggest that the stronger gamma response to red stimulation cannot be wholly explained by the chromatic separation of the stimuli.

Neural Oscillations: Understanding a Neural Code of Pain

Neural oscillations play an important role in the integration and segregation of brain regions that are important for brain functions, including pain. Disturbances in oscillatory activity are associated with several disease states, including chronic pain. Studies of neural oscillations related to pain have identified several functional bands, especially alpha, beta, and gamma bands, implicated in nociceptive processing. In this review, we introduce several properties of neural oscillations that are important to understand the role of brain oscillations in nociceptive processing. We also discuss the role of neural oscillations in the maintenance of efficient communication in the brain. Finally, we discuss the role of neural oscillations in healthy and chronic pain nociceptive processing. These data and concepts illustrate the key role of regional and interregional neural oscillations in nociceptive processing underlying acute and chronic pains.

Mental rotation ability and spontaneous brain activity: a magnetoencephalography study

We performed experiments using magnetoencephalography to clarify the relationship between three-dimensional visuospatial abilities and spontaneous visual thinking characteristics. Subjects were divided into two groups based on the rate of correct answers to mental rotation tasks: those with good performances (Group G) and those with bad performances (Group B). We found the followings: (1) in the mental rotation tasks, the 25-35 Hz lower γ band activities in the superior parietal lobule/intraparietal sulcus regions and in the occipitotemporal region were significantly larger in Group G than in Group B and (2) in the spontaneous mental imagery tasks, the 20-Hz band activity in the left premotor cortex and the 35-Hz band activity in the supplementary motor area were significantly larger in Group G.

Association of Magnetoencephalographically Measured High-Frequency Oscillations in Visual Cortex With Circuit Dysfunctions in Local and Large-scale Networks During Emerging Psychosis

IMPORTANCE

Psychotic disorders are characterized by impairments in neural oscillations, but the nature of the deficit, the trajectory across illness stages, and functional relevance remain unclear.

OBJECTIVES

To examine whether changes in spectral power, phase locking, and functional connectivity in visual cortex are present during emerging psychosis and whether these abnormalities are associated with clinical outcomes.

DESIGN, SETTING, AND PARTICIPANTS

In this cross-sectional study, participants meeting clinical high-risk criteria for psychosis, participants with first-episode psychosis, participants with affective disorders and substance abuse, and a group of control participants were recruited. Participants underwent measurements with magnetoencephalography and magnetic resonance imaging. Data analysis was carried out between 2018 and 2019.

MAIN OUTCOMES AND MEASURES

Magnetoencephalographical activity was examined in the 1- to 90-Hz frequency range in combination with source reconstruction during a visual grating task. Event-related fields, power modulation, intertrial phase consistency, and connectivity measures in visual and frontal cortices were associated with neuropsychological scores, psychosocial functioning, and clinical symptoms as well as persistence of subthreshold psychotic symptoms at 12 months.

RESULTS

The study participants included those meeting clinical high-risk criteria for psychosis (n = 119; mean [SD] age, 22 [4.4] years; 32 men), 26 patients with first-episode psychosis (mean [SD] age, 24 [4.2] years; 16 men), 38 participants with affective disorders and substance abuse (mean [SD] age, 23 [4.7] years; 11 men), and 49 control participants (mean age [SD], 23 [3.6] years; 16 men). Clinical high-risk participants and patients with first-episode psychosis were characterized by reduced phase consistency of β/γ-band oscillations in visual cortex (d = 0.63/d = 0.93). Moreover, the first-episode psychosis group was also characterized by reduced occipital γ-band power (d = 1.14) and altered visual cortex connectivity (d = 0.74-0.84). Impaired fronto-occipital connectivity was present in both clinical high-risk participants (d = 0.54) and patients with first-episode psychosis (d = 0.84). Importantly, reductions in intertrial phase coherence predicted persistence of subthreshold psychosis in clinical high-risk participants (receiver operating characteristic area under curve = 0.728; 95% CI, 0.612-0.841; P = .001).

CONCLUSIONS AND RELEVANCE

High-frequency oscillations are impaired in the visual cortex during emerging psychosis and may be linked to behavioral and clinical impairments. Impaired phase consistency of γ-band oscillations was also associated with the persistence of subthreshold psychosis, suggesting that magnetoencephalographical measured neural oscillations could constitute a biomarker for clinical staging of emerging psychosis.

Development and sex modulate visuospatial oscillatory dynamics in typically-developing children and adolescents

Visuospatial processing is a cognitive function that is critical to navigating one's surroundings and begins to develop during infancy. Extensive research has examined visuospatial processing in adults, but far less work has investigated how visuospatial processing and the underlying neurophysiology changes from childhood to early adolescence, which is a critical period of human development that is marked by the onset of puberty. In the current study, we examined behavioral performance and the oscillatory dynamics serving visuospatial processing using magnetoencephalography (MEG) in a cohort of 70 children and young adolescents aged 8-15 years. All participants performed a visuospatial processing task during MEG, and the resulting oscillatory responses were imaged using a beamformer and probed for developmental and sex-related differences. Our findings indicated that reaction time on the task was negatively correlated with age, and that the amplitude of theta oscillations in the medial occipital cortices increased with age. Significant sex-by-age interactions were also detected, with female participants exhibiting increased theta oscillatory activity in the right prefrontal cortex with increasing age, while male participants exhibited theta increases in the left parietal lobe/left precuneus and left supplementary motor area with increasing age. These data indicate that different nodes of the visuospatial processing network develop earlier in males compared to females (and vice versa) in this age range, which may have major implications for the developmental trajectory of behavioral performance and executive function more generally during the transition through puberty.

Intracranial Recordings Reveal Unique Shape and Timing of Responses in Human Visual Cortex during Illusory Visual Events

During binocular rivalry, perception spontaneously changes without any alteration to the visual stimulus. What neural events bring about this illusion that a constant stimulus is changing? We recorded from intracranial electrodes placed on the occipital and posterior temporal cortex of two patients with epilepsy while they experienced illusory changes of a face-house binocular-rivalry stimulus or observed a control stimulus that physically changed. We performed within-patient comparisons of broadband high-frequency responses, focusing on single epochs recorded along the ventral processing stream. We found transient face- and house-selective responses localized to the same electrodes for illusory and physical changes, but the temporal characteristics of these responses markedly differed. In comparison with physical changes, responses to illusory changes were longer lasting, in particular exhibiting a characteristic slow rise. Furthermore, the temporal order of responses across the visual hierarchy was reversed for illusory as compared to physical changes: for illusory changes, higher order fusiform and parahippocampal regions responded before lower order occipital regions. Our tentative interpretation of these findings is that two stages underlie the initiation of illusory changes: a destabilization stage in which activity associated with the impending change gradually accumulates across the visual hierarchy, ultimately graduating in a top-down cascade of activity that may stabilize the new perceptual interpretation of the stimulus.