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

Oscillatory correlates of threat imminence during virtual navigation

The Predatory Imminence Continuum Theory proposes that defensive behaviors depend on the proximity of a threat. While the neural mechanisms underlying this proposal are well studied in animal models, it remains poorly understood in humans. To address this issue, we recorded EEG from 24 (15 female) young adults engaged in a first-person virtual reality Risk-Reward interaction task. On each trial, participants were placed in a virtual room and presented with either a threat or reward conditioned stimulus (CS) in the same room location (proximal) or different room location (distal). Behaviorally, all participants learned to avoid the threat-CS, with most using the optimal behavior to actively avoid the proximal threat-CS (88% accuracy) and passively avoid the distal threat-CS (69% accuracy). Similarly, participants learned to actively approach the distal reward-CS (82% accuracy) and to remain passive to the proximal reward-CS (72% accuracy). At an electrophysiological level, we observed a general increase in theta power (4-8 Hz) over the right posterior channel P8 across all conditions, with the proximal threat-CS evoking the largest theta response. By contrast, distal cues induced two bursts of gamma (30-60 Hz) power over midline-parietal channel Pz (200 msec post-cue) and right frontal channel Fp2 (300 msec post-cue). Interestingly, the first burst of gamma power was sensitive to the distal threat-CS and the second burst at channel Fp2 was sensitive to the distal reward-CS. Together, these findings demonstrate that oscillatory processes differentiate between the spatial proximity information during threat and reward encoding, likely optimizing the selection of the appropriate behavioral response.

Age-related changes in brain oscillatory patterns during an n-back task in children and adolescents

The development of brain oscillatory responses and their possible role in the working memory (WM) performance of children, adolescents and young adults was investigated. A set of 0- and 1-back tasks with letter stimuli were administered to a final sample of 131 subjects (between 6 and 20 years of age). A decrease in response times (RTs) and an increase of the sensitivity index d-prime (d') were seen with increased age. RTs increased and d' decreased with load, indicating higher difficulty for higher loads. Event-related synchronization (ERS) and event-related desynchronization (ERD) were obtained by the convolution of Morlet wavelets on the recorded EEG. Statistical analyses were performed of the absolute and relative power of brain oscillations defined by topography, frequency and latency. Posterior alpha and beta ERD, and frontocentral theta ERS, were induced by the stimuli presented during the n-back task. While relative theta ERS increased with age, absolute theta ERS, absolute and relative alpha and, absolute beta ERD, decreased with age. Age-related improvement in behavioral performance was mediated by relative theta. Alpha and beta ERD were more pronounced for the most difficult task (1-back) and for the target condition. Globally, there was high consistency of the effects of target type and task load across development. Theta ERS maturation is a crucial step for improving WM performance during development, while alpha and beta ERD maturation seem to be less critical for behavioral performance improvement with age, possibly due to a sufficient level of alpha-beta ERD for good performance in young children.

Do Miniature Eye Movements Affect Neurofeedback Training Performance? A Combined EEG-Eye Tracking Study

EEG-based neurofeedback is a prominent method to modulate one's own brain activity in a desired direction. However, the EEG signal can be disturbed by artifacts, e.g., eye movements, which can consequently confound the neurofeedback performance. Involuntary miniature eye movements can be hardly detected by conventional EEG correction methods such as recording the electro-oculogram (EOG) and subtracting EOG activity from the EEG signal. However, such miniature eye movements can influence EEG activity, especially in the Gamma frequency range, enormously. In the present study, we investigated whether power in different EEG frequencies can be effectively modulated by self-control of brain signals during neurofeedback training and/or whether changes in EEG power are provoked by miniature eye movements during the training. To this end, 24 participants performed one session of SMR and one session of Gamma neurofeedback training. Additionally, in each training session sham feedback was performed. An eye tracker was used to detect miniature eye movements (< 1°) during neurofeedback training. About two thirds of the participants were able to increase their SMR power over the course of NF training, while one third was able to increase Gamma power. Generally, miniature eye movements induced a strong Gamma power increase. The number of eye movements also increased numerically over the course of the NF training. However, we did not find a significant relationship with the NF training performance. This is a first indication that miniature saccades do not affect NF training performance, but should not be neglected during NF training. Our results have to be confirmed in future studies.

Why behaviour matters: Studying inter-brain coordination during child-caregiver interaction

Modern technology allows for simultaneous neuroimaging from interacting caregiver-child dyads. Whereas most analyses that examine the coordination between brain regions within an individual brain do so by measuring changes relative to observed events, studies that examine coordination between two interacting brains generally do this by measuring average intra-brain coordination across entire blocks or experimental conditions. In other words, they do not examine changes in inter-brain coordination relative to individual behavioural events. Here, we discuss the limitations of this approach. First, we present data suggesting that fine-grained temporal interdependencies in behaviour can leave residual artifact in neuroimaging data. We show how artifact can manifest as both power and (through that) phase synchrony effects in EEG and affect wavelet transform coherence in fNIRS analyses. Second, we discuss different possible mechanistic explanations of how inter-brain coordination is established and maintained. We argue that non-event-locked approaches struggle to differentiate between them. Instead, we contend that approaches which examine how interpersonal dynamics change around behavioural events have better potential for addressing possible artifactual confounds and for teasing apart the overlapping mechanisms that drive changes in inter-brain coordination.

Neurophenomenological Investigation of Mindfulness Meditation "Cessation" Experiences Using EEG Network Analysis in an Intensively Sampled Adept Meditator

Mindfulness meditation is a contemplative practice that is informed by Buddhism. It has been proven effective for improving mental and physical health in clinical and non-clinical contexts. To date, mainstream dialogue and scientific research on mindfulness has focused primarily on short-term mindfulness training and applications of mindfulness for reducing stress. Understanding advanced mindfulness practice has important implications for mental health and general wellbeing. According to Theravada Buddhist meditation, a "cessation" event is a dramatic experience of profound clarity and equanimity that involves a complete discontinuation in experience, and is evidence of mastery of mindfulness meditation. Thirty-seven cessation events were captured in a single intensively sampled advanced meditator (over 6,000 h of retreat mindfulness meditation training) while recording electroencephalography (EEG) in 29 sessions between November 12, 2019 and March 11, 2020. Functional connectivity and network integration were assessed from 40 s prior to cessations to 40 s after cessations. From 21 s prior to cessations there was a linear decrease in large-scale functional interactions at the whole-brain level in the alpha band. In the 40 s following cessations these interactions linearly returned to prior levels. No modulation of network integration was observed. The decrease in whole-brain functional connectivity was underlain by frontal to left temporal and to more posterior decreases in connectivity, while the increase was underlain by wide-spread increases in connectivity. These results provide neuroscientific evidence of large-scale modulation of brain activity related to cessation events that provides a foundation for future studies of advanced meditation.

Myogenic artifacts masquerade as neuroplasticity in the auditory frequency-following response (FFR)

The frequency-following response (FFR) is an evoked potential that provides a "neural fingerprint" of complex sound encoding in the brain. FFRs have been widely used to characterize speech and music processing, experience-dependent neuroplasticity (e.g., learning, musicianship), and biomarkers for hearing and language-based disorders that distort receptive communication abilities. It is widely assumed FFRs stem from a mixture of phase-locked neurogenic activity from brainstem and cortical structures along the hearing neuraxis. Here, we challenge this prevailing view by demonstrating upwards of ~50% of the FFR can originate from a non-neural source: contamination from the postauricular muscle (PAM) vestigial startle reflex. We first establish PAM artifact is present in all ears, varies with electrode proximity to the muscle, and can be experimentally manipulated by directing listeners' eye gaze toward the ear of sound stimulation. We then show this muscular noise easily confounds auditory FFRs, spuriously amplifying responses by 3-4x fold with tandem PAM contraction and even explaining putative FFR enhancements observed in highly skilled musicians. Our findings expose a new and unrecognized myogenic source to the FFR that drives its large inter-subject variability and cast doubt on whether changes in the response typically attributed to neuroplasticity/pathology are solely of brain origin.

Multi-Algorithm Artifact Correction (MAAC) procedure part one: Algorithm and example

The Multi-Algorithm Artifact Correction (MAAC) procedure is presented for electroencephalographic (EEG) data, as made freely available in the open-source EP Toolkit (Dien, 2010). First the major EEG artifact correction methods (regression, spatial filters, principal components analysis, and independent components analysis) are reviewed. Contrary to the dominant approach of picking one method that is thought to be most effective, this review concludes that none are globally superior, but rather each has strengths and weaknesses. Then each of the major artifact types are reviewed (Blink, Corneo-Retinal Dipole, Saccadic Spike Potential, and Movement). For each one, it is proposed that one of the major correction methods is best matched to address it, resulting in the MAAC procedure. The MAAC itself is then presented, as implemented in the EP Toolkit, in order to provide a sense of the user experience. The primary goal of this present paper is to make the conceptual argument for the MAAC approach.

Induced oscillatory brain responses under virtual reality conditions in the context of repetition priming

In the human electroencephalogram (EEG), induced oscillatory responses in various frequency bands are regarded as valuable indices to examine the neural mechanisms underlying human memory. While the advent of virtual reality (VR) drives the investigation of mnemonic processing under more lifelike settings, the joint application of VR and EEG methods is still in its infancy (e.g., due to technical limitations impeding the signal acquisition). The objective of the present EEG study was twofold. First, we examined whether the investigation of induced oscillations under VR conditions yields equivalent results compared to standard paradigms. Second, we aimed at obtaining further insights into basic memory-related brain mechanisms in VR. To these ends, we relied on a standard implicit memory design, namely repetition priming, for which the to-be-expected effects are well-documented for conventional studies. Congruently, we replicated a suppression of the evoked potential after stimulus onset. Regarding the induced responses, we observed a modulation of induced alphaband in response to a repeated stimulus. Importantly, our results revealed a repetition-related suppression of the high-frequency induced gammaband response (>30 Hz), indicating the sharpening of a cortical object representation fostering behavioral priming effects. Noteworthy, the analysis of the induced gammaband responses required a number of measures to minimize the influence of external and internal sources of artefacts (i.e., the electrical shielding of the technical equipment and the control for miniature eye movements). In conclusion, joint VR-EEG studies with a particular focus on induced oscillatory responses offer a promising advanced understanding of mnemonic processing under lifelike conditions.

The topology of interpersonal neural network in weak social ties

The strategies for social interaction between strangers differ from those between acquaintances, whereas the differences in neural basis of social interaction have not been fully elucidated. In this study, we examined the geometrical properties of interpersonal neural networks in pairs of strangers and acquaintances during antiphase joint tapping. Dual electroencephalogram (EEG) of 29 channels per participant was measured from 14 strangers and 13 acquaintance pairs.Intra-brain synchronizations were calculated using the weighted phase lag index (wPLI) for intra-brain electrode combinations, and inter-brain synchronizations were calculated using the phase locking value (PLV) for inter-brain electrode combinations in the theta, alpha, and beta frequency bands. For each participant pair, electrode combinations with larger wPLI/PLV than their surrogates were defined as the edges of the neural networks. We calculated global efficiency, local efficiency, and modularity derived from graph theory for the combined intra- and inter-brain networks of each pair. In the theta band networks, stranger pairs showed larger local efficiency than acquaintance pairs, indicating that the two brains of stranger pairs were more densely connected. Hence, weak social ties require extensive social interactions and result in high efficiency of information transfer between neighbors in neural network.

(Micro)saccade-related potentials during face recognition: A study combining EEG, eye-tracking, and deconvolution modeling

Under natural viewing conditions, complex stimuli such as human faces are typically looked at several times in succession, implying that their recognition may unfold across multiple eye fixations. Although electrophysiological (EEG) experiments on face recognition typically prohibit eye movements, participants still execute frequent (micro)saccades on the face, each of which generates its own visuocortical response. This finding raises the question of whether the fixation-related potentials (FRPs) evoked by these tiny gaze shifts also contain psychologically valuable information about face processing. Here, we investigated this question by corecording EEG and eye movements in an experiment with emotional faces (happy, angry, neutral). Deconvolution modeling was used to separate the stimulus ERPs to face onset from the FRPs generated by subsequent microsaccades-induced refixations on the face. As expected, stimulus ERPs exhibited typical emotion effects, with a larger early posterior negativity (EPN) for happy/angry compared with neutral faces. Eye tracking confirmed that participants made small saccades in 98% of the trials, which were often aimed at the left eye of the stimulus face. However, while each saccade produced a strong response over visual areas, this response was unaffected by the face's emotional expression, both for the first and for subsequent (micro)saccades. This finding suggests that the face's affective content is rapidly evaluated after stimulus onset, leading to only a short-lived sensory enhancement by arousing stimuli that does not repeat itself during immediate refixations. Methodologically, our work demonstrates how eye tracking and deconvolution modeling can be used to extract several brain responses from each EEG trial, providing insights into neural processing at different latencies after stimulus onset.

Enhancement of low gamma oscillations by volitional conditioning of local field potential in the primary motor and visual cortex of mice

Volitional control of local field potential oscillations in low gamma band via brain machine interface can not only uncover the relationship between low gamma oscillation and neural synchrony but also suggest a therapeutic potential to reverse abnormal local field potential oscillation in neurocognitive disorders. In nonhuman primates, the volitional control of low gamma oscillations has been demonstrated by brain machine interface techniques in the primary motor and visual cortex. However, it is not clear whether this holds in other brain regions and other species, for which gamma rhythms might involve in highly different neural processes. Here, we established a closed-loop brain-machine interface and succeeded in training mice to volitionally elevate low gamma power of local field potential in the primary motor and visual cortex. We found that the mice accomplished the task in a goal-directed manner and spiking activity exhibited phase-locking to the oscillation in local field potential in both areas. Moreover, long-term training made the power enhancement specific to direct and adjacent channel, and increased the transcriptional levels of NMDA receptors as well as that of hypoxia-inducible factor relevant to metabolism. Our results suggest that volitionally generated low gamma rhythms in different brain regions share similar mechanisms and pave the way for employing brain machine interface in therapy of neurocognitive disorders.

Effects of pupil size as manipulated through ipRGC activation on visual processing

The size of the eyes' pupils determines how much light enters the eye and also how well this light is focused. Through this route, pupil size shapes the earliest stages of visual processing. Yet causal effects of pupil size on vision are poorly understood and rarely studied. Here we introduce a new way to manipulate pupil size, which relies on activation of intrinsically photosensitive retinal ganglion cells (ipRGCs) to induce sustained pupil constriction. We report the effects of both experimentally induced and spontaneous changes in pupil size on visual processing as measured through EEG. We compare these to the effects of stimulus intensity and covert visual attention, because previous studies have shown that these factors all have comparable effects on some common measures of early visual processing, such as detection performance and steady-state visual evoked potentials; yet it is still unclear whether these are superficial similarities, or rather whether they reflect similar underlying processes. Using a mix of neural-network decoding, ERP analyses, and time-frequency analyses, we find that induced pupil size, spontaneous pupil size, stimulus intensity, and covert visual attention all affect EEG responses, mainly over occipital and parietal electrodes, but-crucially-that they do so in qualitatively different ways. Induced and spontaneous pupil-size changes mainly modulate activity patterns (but not overall power or intertrial coherence) in the high-frequency beta range; this may reflect an effect of pupil size on oculomotor activity and/ or visual processing. In addition, spontaneous (but not induced) pupil size tends to correlate positively with intertrial coherence in the alpha band; this may reflect a non-causal relationship, mediated by arousal. Taken together, our findings suggest that pupil size has qualitatively different effects on visual processing from stimulus intensity and covert visual attention. This shows that pupil size as manipulated through ipRGC activation strongly affects visual processing, and provides concrete starting points for further study of this important yet understudied earliest stage of visual processing.

Assessing focus through ear-EEG: a comparative study between conventional cap EEG and mobile in- and around-the-ear EEG systems

Introduction

As our attention is becoming a commodity that an ever-increasing number of applications are competing for, investing in modern day tools and devices that can detect our mental states and protect them from outside interruptions holds great value. Mental fatigue and distractions are impacting our ability to focus and can cause workplace injuries. Electroencephalography (EEG) may reflect concentration, and if EEG equipment became wearable and inconspicuous, innovative brain-computer interfaces (BCI) could be developed to monitor mental load in daily life situations. The purpose of this study is to investigate the potential of EEG recorded inside and around the human ear to determine levels of attention and focus.

Methods

In this study, mobile and wireless ear-EEG were concurrently recorded with conventional EEG (cap) systems to collect data during tasks related to focus: an N-back task to assess working memory and a mental arithmetic task to assess cognitive workload. The power spectral density (PSD) of the EEG signal was analyzed to isolate consistent differences between mental load conditions and classify epochs using step-wise linear discriminant analysis (swLDA).

Results and discussion

Results revealed that spectral features differed statistically between levels of cognitive load for both tasks. Classification algorithms were tested on spectral features from twelve and two selected channels, for the cap and the ear-EEG. A two-channel ear-EEG model evaluated the performance of two dry in-ear electrodes specifically. Single-trial classification for both tasks revealed above chance-level accuracies for all subjects, with mean accuracies of: 96% (cap-EEG) and 95% (ear-EEG) for the twelve-channel models, 76% (cap-EEG) and 74% (in-ear-EEG) for the two-channel model for the N-back task; and 82% (cap-EEG) and 85% (ear-EEG) for the twelve-channel, 70% (cap-EEG) and 69% (in-ear-EEG) for the two-channel model for the arithmetic task. These results suggest that neural oscillations recorded with ear-EEG can be used to reliably differentiate between levels of cognitive workload and working memory, in particular when multi-channel recordings are available, and could, in the near future, be integrated into wearable devices.

Pinprick-induced gamma-band oscillations are not a useful electrophysiological marker of pinprick hypersensitivity in humans

OBJECTIVE

This study aimed to investigate scalp gamma-band oscillations (GBOs) induced by mechanical stimuli activating skin nociceptors before and after the induction of mechanical hypersensitivity using high-frequency electrical stimulation (HFS) of the skin.

METHODS

In twenty healthy volunteers, we recorded the electroencephalogram during robot-controlled mechanical pinprick stimulation (512 mN) applied at the right ventral forearm before and after HFS.

RESULTS

HFS induced a significant increase in mechanical pinprick sensitivity, but this increased pinprick sensitivity was, at the group level, not accompanied by a significant increase in GBOs. Visual inspection of the individual data revealed that possible GBOs were present in eight out of twenty participants (40%) and the frequency of these GBOs varied substantially across participants.

CONCLUSIONS

Based on the low number of participants showing GBOs we question the (clinical) utility of mechanically-induced GBOs as an electrophysiological marker of pinprick hypersensitivity in humans.

SIGNIFICANCE

Mechanical pinprick-induced scalp GBOs are not useful for evaluating mechanical pinprick hypersensitivity in humans.

Altered neural oscillations underlying visuospatial processing in cerebral visual impairment

Visuospatial processing deficits are commonly observed in individuals with cerebral visual impairment, even in cases where visual acuity and visual field functions are intact. Cerebral visual impairment is a brain-based visual disorder associated with the maldevelopment of central visual pathways and structures. However, the neurophysiological basis underlying higher-order perceptual impairments in this condition has not been clearly identified, which in turn poses limits on developing rehabilitative interventions. Using combined eye tracking and EEG recordings, we assessed the profile and performance of visual search on a naturalistic virtual reality-based task. Participants with cerebral visual impairment and controls with neurotypical development were instructed to search, locate and fixate on a specific target placed among surrounding distractors at two levels of task difficulty. We analysed evoked (phase-locked) and induced (non-phase-locked) components of broadband (4-55 Hz) neural oscillations to uncover the neurophysiological basis of visuospatial processing. We found that visual search performance in cerebral visual impairment was impaired compared to controls (as indexed by outcomes of success rate, reaction time and gaze error). Analysis of neural oscillations revealed markedly reduced early-onset evoked theta [4-6 Hz] activity (within 0.5 s) regardless of task difficulty. Moreover, while induced alpha activity increased with task difficulty in controls, this modulation was absent in the cerebral visual impairment group identifying a potential neural correlate related to deficits with visual search and distractor suppression. Finally, cerebral visual impairment participants also showed a sustained induced gamma response [30-45 Hz]. We conclude that impaired visual search performance in cerebral visual impairment is associated with substantial alterations across a wide range of neural oscillation frequencies. This includes both evoked and induced components suggesting the involvement of feedforward and feedback processing as well as local and distributed levels of neural processing.

Mutual Information between EDA and EEG in Multiple Cognitive Tasks and Sleep Deprivation Conditions

Sleep deprivation, a widespread phenomenon that affects one-third of normal American adults, induces adverse changes in physical and cognitive performance, which in turn increases the occurrence of accidents. Sleep deprivation is known to increase resting blood pressure and decrease muscle sympathetic nerve activity. Monitoring changes in the interplay between the central and autonomic sympathetic nervous system can be a potential indicator of human's readiness to perform tasks that involve a certain level of cognitive load (e.g., driving). The electroencephalogram (EEG) is the standard to assess the brain's activity. The electrodermal activity (EDA) is a reflection of the general state of arousal regulated by the activation of the sympathetic nervous system through sweat gland stimulation. In this work, we calculated the mutual information between EDA and EEG recordings in order to consider linear and non-linear interactions and provide an insight of the relationship between brain activity and peripheral autonomic sympathetic activity. We analyzed EEG and EDA data from ten participants performing four cognitive tasks every two hours during 24 h (12 trials). We decomposed EEG data into delta, theta, alpha, beta, and gamma spectral components, and EDA into tonic and phasic components. The results demonstrate high values of mutual information between the EDA and delta component of EEG, mainly in working memory tasks. Additionally, we found an increase in the theta component of EEG in the presence of fatigue caused by sleep deprivation, the alpha component in tasks demanding inhibition and attention, and the delta component in working memory tasks. In terms of the location of brain activity, most of the tasks report high mutual information in frontal regions in the initial trials, with a trend to decrease and become uniform for all the nine analyzed EEG channels as a consequence of the sleep deprivation effect. Our results evidence the interplay between central and sympathetic nervous activity and can be used to mitigate the consequences of sleep deprivation.

Abnormal spectral and scale-free properties of resting-state EEG in girls with Rett syndrome

Spontaneous EEG contains important information about neuronal network properties that is valuable for understanding different neurological and psychiatric conditions. Rett syndrome (RTT) is a rare neurodevelopmental disorder, caused by mutation in the MECP2 gene. RTT is characterized by severe motor impairments that prevent adequate assessment of cognitive functions. Here we probe EEG parameters obtained in no visual input condition from a 28-channels system in 23 patients with Rett Syndrome and 38 their typically developing peers aged 3-17 years old. Confirming previous results, RTT showed a fronto-central theta power (4-6.25 Hz) increase that correlates with a progression of the disease. Alpha power (6.75-11.75 Hz) across multiple regions was, on the contrary, decreased in RTT, also corresponding to general background slowing reported previously. Among novel results we found an increase in gamma power (31-39.5 Hz) across frontal, central and temporal electrodes, suggesting elevated excitation/inhibition ratio. Long-range temporal correlation measured by detrended fluctuation analysis within 6-13 Hz was also increased, pointing to a more predictable oscillation pattern in RTT. Overall measured EEG parameters allow to differentiate groups with high accuracy, ROC AUC value of 0.92 ± 0.08, indicating clinical relevance.

Reliability and Validity of Transcranial Magnetic Stimulation-Electroencephalography Biomarkers

Noninvasive brain stimulation and neuroimaging have revolutionized human neuroscience with a multitude of applications, including diagnostic subtyping, treatment optimization, and relapse prediction. It is therefore particularly relevant to identify robust and clinically valuable brain biomarkers linking symptoms to their underlying neural mechanisms. Brain biomarkers must be reproducible (i.e., have internal reliability) across similar experiments within a laboratory and be generalizable (i.e., have external reliability) across experimental setups, laboratories, brain regions, and disease states. However, reliability (internal and external) is not alone sufficient; biomarkers also must have validity. Validity describes closeness to a true measure of the underlying neural signal or disease state. We propose that these metrics, reliability and validity, should be evaluated and optimized before any biomarker is used to inform treatment decisions. Here, we discuss these metrics with respect to causal brain connectivity biomarkers from coupling transcranial magnetic stimulation (TMS) with electroencephalography (EEG). We discuss controversies around TMS-EEG stemming from the multiple large off-target components (noise) and relatively weak genuine brain responses (signal), as is unfortunately often the case in noninvasive human neuroscience. We review the current state of TMS-EEG recordings, which consist of a mix of reliable noise and unreliable signal. We describe methods for evaluating TMS-EEG biomarkers, including how to assess internal and external reliability across facilities, cognitive states, brain networks, and disorders and how to validate these biomarkers using invasive neural recordings or treatment response. We provide recommendations to increase reliability and validity, discuss lessons learned, and suggest future directions for the field.

Comparative analysis of multifaceted neural effects associated with varying endogenous cognitive load

Contemporary neuroscience has firmly established that mental state variation concurs with changes in neural dynamic activity in a complex way that a one-to-one mapping cannot describe. To explore the scenario of the multifaceted changes in neural dynamics associated with simple mental state variation, we took cognitive load - a common cognitive manipulation in psychology - as a venue to characterize how multiple neural dynamic features are simultaneously altered by the manipulation and how their sensitivity differs. Electroencephalogram was collected from 152 participants performing stimulus-free tasks with different demands. The results show that task demand alters wide-ranging neural dynamic features, including band-specific oscillations across broad frequency bands, scale-free dynamics, and cross-frequency phase-amplitude coupling. The scale-free dynamics outperformed others in indexing cognitive load variation. This study demonstrates a complex relationship between cognitive dynamics and neural dynamics, which points to a necessity to integrate multifaceted neural dynamic features when studying mind-brain relationship in the future.

The role of brain-localized gamma and alpha oscillations in inattentional deafness: implications for understanding human attention

Introduction

The processes involved in how the attention system selectively focuses on perceptual and motor aspects related to a specific task, while suppressing features of other tasks and/or objects in the environment, are of considerable interest for cognitive neuroscience. The goal of this experiment was to investigate neural processes involved in selective attention and performance under multi-task situations. Several studies have suggested that attention-related gamma-band activity facilitates processing in task-specific modalities, while alpha-band activity inhibits processing in non-task-related modalities. However, investigations into the phenomenon of inattentional deafness/blindness (inability to observe stimuli in non-dominant task when primary task is demanding) have yet to observe gamma-band activity.

Methods

This EEG experiment utilizes an engaging whole-body perceptual motor task while carrying out a secondary auditory detection task to investigate neural correlates of inattentional deafness in natural immersive high workload conditions. Differences between hits and misses on the auditory detection task in the gamma (30-50 Hz) and alpha frequency (8-12 Hz) range were carried out at the cortical source level using LORETA.

Results

Participant auditory task performance correlated with an increase in gamma-band activity for hits over misses pre- and post-stimulus in left auditory processing regions. Alpha-band activity was greater for misses relative to hits in right auditory processing regions pre- and post-stimulus onset. These results are consistent with the facilitatory/inhibitory role of gamma/alpha-band activity for neural processing. Additional gamma- and alpha-band activity was found in frontal and parietal brain regions which are thought to reflect various attentional monitoring, selection, and switching processes.

Discussion

The results of this study help to elucidate the role of gamma and alpha frequency bands in frontal and modality-specific regions involved with selective attention in multi-task immersive situations.

Microsaccades transiently lateralise EEG alpha activity

The lateralisation of 8-12 Hz alpha activity is a canonical signature of human spatial cognition that is typically studied under strict fixation requirements. Yet, even during attempted fixation, the brain produces small involuntary eye movements known as microsaccades. Here we report how spontaneous microsaccades - made in the absence of incentives to look elsewhere - can themselves drive transient lateralisation of EEG alpha power according to microsaccade direction. This transient lateralisation of posterior alpha power occurs similarly following start and return microsaccades and is, at least for start microsaccades, driven by increased alpha power ipsilateral to microsaccade direction. This reveals new links between spontaneous microsaccades and human electrophysiological brain activity. It highlights how microsaccades are an important factor to consider in studies relating alpha activity - including spontaneous fluctuations in alpha activity - to spatial cognition, such as studies on visual attention, anticipation, and working memory.

Brain activity during cybersickness: a scoping review

Virtual reality (VR) experiences can cause a range of negative symptoms such as nausea, disorientation, and oculomotor discomfort, which is collectively called cybersickness. Previous studies have attempted to develop a reliable measure for detecting cybersickness instead of using questionnaires, and electroencephalogram (EEG) has been regarded as one of the possible alternatives. However, despite the increasing interest, little is known about which brain activities are consistently associated with cybersickness and what types of methods should be adopted for measuring discomfort through brain activity. We conducted a scoping review of 33 experimental studies in cybersickness and EEG found through database searches and screening. To understand these studies, we organized the pipeline of EEG analysis into four steps (preprocessing, feature extraction, feature selection, classification) and surveyed the characteristics of each step. The results showed that most studies performed frequency or time-frequency analysis for EEG feature extraction. A part of the studies applied a classification model to predict cybersickness indicating an accuracy between 79 and 100%. These studies tended to use HMD-based VR with a portable EEG headset for measuring brain activity. Most VR content shown was scenic views such as driving or navigating a road, and the age of participants was limited to people in their 20 s. This scoping review contributes to presenting an overview of cybersickness-related EEG research and establishing directions for future work.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10055-023-00795-y.

Saccadic modulation of neural excitability in auditory areas of the neocortex

In natural "active" vision, humans and other primates use eye movements (saccades) to sample bits of information from visual scenes. In the visual cortex, non-retinal signals linked to saccades shift visual cortical neurons into a high excitability state as each saccade ends. The extent of this saccadic modulation outside of the visual system is unknown. Here, we show that during natural viewing, saccades modulate excitability in numerous auditory cortical areas with a temporal pattern complementary to that seen in visual areas. Control somatosensory cortical recordings indicate that the temporal pattern is unique to auditory areas. Bidirectional functional connectivity patterns suggest that these effects may arise from regions involved in saccade generation. We propose that by using saccadic signals to yoke excitability states in auditory areas to those in visual areas, the brain can improve information processing in complex natural settings.

Neural bases of predictions during natural reading of known statements: An EEG and eye movements co-registration study

Predictions of incoming words performed during reading have an impact on how the reader moves their eyes and on the electrical brain potentials. Eye tracking (ET) experiments show that less predictable words are fixated for longer periods of times. Electroencephalography (EEG) experiments show that these words elicit a more negative potential around 400ms (N400) after the word onset when reading one word at a time (foveated reading). Nevertheless, there was no N400 potential during the foveated reading of previously known sentences (memory-encoded), which suggests that the prediction of words from memory-encoded sentences is based on different mechanisms than predictions performed on common sentences. Here, we performed an ET-EEG co-registration experiment where participants read common and memory-encoded sentences. Our results show that the N400 potential disappear when the reader recognises the sentence. Furthermore, time-frequency analyses show a larger alpha lateralisation and a beta power increase for memory-encoded sentences. This suggests a more distributed attention and an active maintenance of the cognitive set, in concordance to the predictive coding framework.

Motor-effector dependent modulation of sensory-motor processes identified by the multivariate pattern analysis of EEG activity

Sensory information received through sensory organs is constantly modulated by numerous non-sensory factors. Recent studies have demonstrated that the state of action can modulate sensory representations in cortical areas. Similarly, sensory information can be modulated by the type of action used to report perception; however, systematic investigation of this issue is scarce. In this study, we examined whether sensorimotor processes represented in electroencephalography (EEG) activities vary depending on the type of effector behavior. Nineteen participants performed motion direction discrimination tasks in which visual inputs were the same, and only the effector behaviors for reporting perceived motion directions were different (smooth pursuit, saccadic eye movement, or button press). We used multivariate pattern analysis to compare the EEG activities for identical sensory inputs under different effector behaviors. The EEG activity patterns for the identical sensory stimulus before any motor action varied across the effector behavior conditions, and the choice of motor effectors modulated the neural direction discrimination differently. We suggest that the motor-effector dependent modulation of EEG direction discrimination might be caused by effector-specific motor planning or preparation signals because it did not have functional relevance to behavioral direction discriminability.

RELAX part 2: A fully automated EEG data cleaning algorithm that is applicable to Event-Related-Potentials

OBJECTIVE

Electroencephalography (EEG) is often used to examine neural activity time-locked to stimuli presentation, referred to as Event-Related Potentials (ERP). However, EEG is influenced by non-neural artifacts, which can confound ERP comparisons. Artifact cleaning reduces artifacts, but often requires time-consuming manual decisions. Most automated methods filter frequencies <1 Hz out of the data, so are not recommended for ERPs (which contain frequencies <1 Hz). Our aim was to test the RELAX (Reduction of Electroencephalographic Artifacts) pre-processing pipeline for use on ERP data.

METHODS

The cleaning performance of multiple versions of RELAX were compared to four commonly used EEG cleaning pipelines across both artifact cleaning metrics and the amount of variance in ERPs explained by different conditions in a Go-Nogo task. Results RELAX with Multi-channel Wiener Filtering (MWF) and wavelet-enhanced independent component analysis applied to artifacts identified with ICLabel (wICA_ICLabel) cleaned data most effectively and produced amongst the most dependable ERP estimates. RELAX with wICA_ICLabel only or MWF_only may detect effects better for some ERPs.

CONCLUSIONS

RELAX shows high artifact cleaning performance even when data is high-pass filtered at 0.25 Hz (applicable to ERP analyses).

SIGNIFICANCE

RELAX is easy to implement via EEGLAB in MATLAB and freely available on GitHub. Given its performance and objectivity we recommend RELAX to improve artifact cleaning and consistency across ERP research.

Multivariate EEG activity reflects the Bayesian integration and the integrated Galilean relative velocity of sensory motion during sensorimotor behavior

Humans integrate multiple sources of information for action-taking, using the reliability of each source to allocate weight to the data. This reliability-weighted information integration is a crucial property of Bayesian inference. In this study, participants were asked to perform a smooth pursuit eye movement task in which we independently manipulated the reliability of pursuit target motion and the direction-of-motion cue. Through an analysis of pursuit initiation and multivariate electroencephalography activity, we found neural and behavioral evidence of Bayesian information integration: more attraction toward the cue direction was generated when the target motion was weak and unreliable. Furthermore, using mathematical modeling, we found that the neural signature of Bayesian information integration had extra-retinal origins, although most of the multivariate electroencephalography activity patterns during pursuit were best correlated with the retinal velocity errors accumulated over time. Our results demonstrated neural implementation of Bayesian inference in human oculomotor behavior.

Stimulus-induced narrow-band gamma oscillations in humans can be recorded using open-hardware low-cost EEG amplifier

Stimulus-induced narrow-band gamma oscillations (30-70 Hz) in human electro-encephalograph (EEG) have been linked to attentional and memory mechanisms and are abnormal in mental health conditions such as autism, schizophrenia and Alzheimer's Disease. However, since the absolute power in EEG decreases rapidly with increasing frequency following a "1/f" power law, and the gamma band includes line noise frequency, these oscillations are highly susceptible to instrument noise. Previous studies that recorded stimulus-induced gamma oscillations used expensive research-grade EEG amplifiers to address this issue. While low-cost EEG amplifiers have become popular in Brain Computer Interface applications that mainly rely on low-frequency oscillations (< 30 Hz) or steady-state-visually-evoked-potentials, whether they can also be used to measure stimulus-induced gamma oscillations is unknown. We recorded EEG signals using a low-cost, open-source amplifier (OpenBCI) and a traditional, research-grade amplifier (Brain Products GmbH), both connected to the OpenBCI cap, in male (N = 6) and female (N = 5) subjects (22-29 years) while they viewed full-screen static gratings that are known to induce two distinct gamma oscillations: slow and fast gamma, in a subset of subjects. While the EEG signals from OpenBCI were considerably noisier, we found that out of the seven subjects who showed a gamma response in Brain Products recordings, six showed a gamma response in OpenBCI as well. In spite of the noise in the OpenBCI setup, the spectral and temporal profiles of these responses in alpha (8-13 Hz) and gamma bands were highly correlated between OpenBCI and Brain Products recordings. These results suggest that low-cost amplifiers can potentially be used in stimulus-induced gamma response detection.

Removing ocular artifacts from magnetoencephalographic data on naturalistic reading of continuous texts

Naturalistic reading paradigms and stimuli consisting of long continuous texts are essential for characterizing the cortical basis of reading. Due to the highly dynamic nature of the reading process, electrophysiological brain imaging methods with high spatial and temporal resolution, such as magnetoencephalography (MEG), are ideal for tracking them. However, as electrophysiological recordings are sensitive to electromagnetic artifacts, data recorded during naturalistic reading is confounded by ocular artifacts. In this study, we evaluate two different pipelines for removing ocular artifacts from MEG data collected during continuous, naturalistic reading, with the focus on saccades and blinks. Both pipeline alternatives are based on blind source separation methods but differ fundamentally in their approach. The first alternative is a multi-part process, in which saccades are first extracted by applying Second-Order Blind Identification (SOBI) and, subsequently, FastICA is used to extract blinks. The other alternative uses a single powerful method, Adaptive Mixture ICA (AMICA), to remove all artifact types at once. The pipelines were tested, and their effects compared on MEG data recorded from 13 subjects in a naturalistic reading task where the subjects read texts with the length of multiple pages. Both pipelines performed well, extracting the artifacts in a single component per artifact type in most subjects. Signal power was reduced across the whole cortex in all studied frequency bands from 1 to 90 Hz, but especially in the frontal cortex and temporal pole. The results were largely similar for the two pipelines, with the exception that SOBI-FastICA reduced signal in the right frontal cortex in all studied frequency bands more than AMICA. However, there was considerable interindividual variation in the effects of the pipelines. As a holistic conclusion, we choose to recommend AMICA for removing artifacts from MEG data on naturalistic reading but note that the SOBI-FastICA pipeline has also various favorable characteristics.

EEG biomarker candidates for the identification of epilepsy

Electroencephalography (EEG) is one of the main pillars used for the diagnosis and study of epilepsy, readily employed after a possible first seizure has occurred. The most established biomarker of epilepsy, in case seizures are not recorded, are interictal epileptiform discharges (IEDs). In clinical practice, however, IEDs are not always present and the EEG may appear completely normal despite an underlying epileptic disorder, often leading to difficulties in the diagnosis of the disease. Thus, finding other biomarkers that reliably predict whether an individual suffers from epilepsy even in the absence of evident epileptic activity would be extremely helpful, since they could allow shortening the period of diagnostic uncertainty and consequently decreasing the risk of seizure. To date only a few EEG features other than IEDs seem to be promising candidates able to distinguish between epilepsy, i.e. > 60 % risk of recurrent seizures, or other (pathological) conditions. The aim of this narrative review is to provide an overview of the EEG-based biomarker candidates for epilepsy and the techniques employed for their identification.

Rhythms of human attention and memory: An embedded process perspective

It remains a dogma in cognitive neuroscience to separate human attention and memory into distinct modules and processes. Here we propose that brain rhythms reflect the embedded nature of these processes in the human brain, as evident from their shared neural signatures: gamma oscillations (30–90 Hz) reflect sensory information processing and activated neural representations (memory items). The theta rhythm (3–8 Hz) is a pacemaker of explicit control processes (central executive), structuring neural information processing, bit by bit, as reflected in the theta-gamma code. By representing memory items in a sequential and time-compressed manner the theta-gamma code is hypothesized to solve key problems of neural computation: (1) attentional sampling (integrating and segregating information processing), (2) mnemonic updating (implementing Hebbian learning), and (3) predictive coding (advancing information processing ahead of the real time to guide behavior). In this framework, reduced alpha oscillations (8–14 Hz) reflect activated semantic networks, involved in both explicit and implicit mnemonic processes. Linking recent theoretical accounts and empirical insights on neural rhythms to the embedded-process model advances our understanding of the integrated nature of attention and memory – as the bedrock of human cognition.

Extreme conditions affect neuronal oscillations of cerebral cortices in humans in the China Space Station and on Earth

Rhythmical oscillations of neural populations can reflect working memory performance. However, whether neuronal oscillations of the cerebral cortex change in extreme environments, especially in a space station, remains unclear. Here, we recorded electroencephalography (EEG) signals when volunteers and astronauts were executing a memory task in extreme working conditions. Our experiments showed that two extreme conditions affect neuronal oscillations of the cerebral cortex and manifest in different ways. Lengthy periods of mental work impairs the gating mechanism formed by theta-gamma phase-amplitude coupling of two cortical areas, and sleep deprivation disrupts synaptic homeostasis, as reflected by the substantial increase in theta wave activity in the cortical frontal-central area. In addition, we excluded the possibility that nutritional supply or psychological situations caused decoupled theta-gamma phase-amplitude coupling or an imbalance in theta wave activity increase. Therefore, we speculate that the decoupled theta-gamma phase-amplitude coupling detected in astronauts results from their lengthy periods of mental work in the China Space Station. Furthermore, comparing preflight and inflight experiments, we find that long-term spaceflight and other hazards in the space station could worsen this decoupling evolution. This particular neuronal oscillation mechanism in the cerebral cortex could guide countermeasures for the inadaptability of humans working in spaceflight.

Resting-state electroencephalographic correlates of cognitive reserve: Moderating the age-related worsening in cognitive function

This exploratory study aimed to investigate the resting-state electroencephalographic (rsEEG) correlates of the cognitive reserve from a life span perspective. Current source density (CSD) and lagged-linear connectivity (LLC) measures were assessed to this aim. We firstly explored the relationship between rsEEG measures for the different frequency bands and a socio-behavioral proxy of cognitive reserve, the Cognitive Reserve Index (CRI). Secondly, we applied moderation analyses to assess whether any of the correlated rsEEG measures showed a moderating role in the relationship between age and cognitive function. Moderate negative correlations were found between the CRI and occipital CSD of delta and beta 2. Moreover, inter- and intrahemispheric LLC measures were correlated with the CRI, showing a negative association with delta and positive associations with alpha 1, beta 1, and beta 2. Among those correlated measures, just two rsEEG variables were significant moderators of the relationship between age and cognition: occipital delta CSD and right hemispheric beta 2 LLC between occipital and limbic regions. The effect of age on cognitive performance was stronger for higher values of both measures. Therefore, lower values of occipital delta CSD and lower beta 2 LLC between right occipital and limbic regions might protect or compensate for the effects of age on cognition. Results of this exploratory study might be helpful to allocate more preventive efforts to curb the progression of cognitive decline in adults with less CR, possibly characterized by these rsEEG parameters at a neural level. However, given the exploratory nature of this study, more conclusive work on these rsEEG measures is needed to firmly establish their role in the cognition–age relationship, for example, verifying if these measures moderate the relationship between brain structure and cognition.

Sources of Variation in the Spectral Slope of the Sleep EEG

The 1/f spectral slope of the electroencephalogram (EEG) estimated in the γ frequency range has been proposed as an arousal marker that differentiates wake, nonrapid eye movement (NREM) sleep, and rapid eye movement (REM) sleep. Here, we sought to replicate and extend these findings in a large sample, providing a comprehensive characterization of how slope changes with age, sex, and its test-retest reliability as well as potential confounds that could affect the slope estimation. We used 10,255 whole-night polysomnograms (PSGs) from the National Sleep Research Resource (NSRR). All preprocessing steps were performed using an open-source Luna package and the spectral slope was estimated by fitting log-log linear regression models on the absolute power from 30 to 45 Hz separately for wake, NREM, and REM stages. We confirmed that the mean spectral slope grows steeper going from wake to NREM to REM sleep. We found that the choice of mastoid referencing scheme modulated the extent to which electromyogenic, or electrocardiographic artifacts were likely to bias 30- to 45-Hz slope estimates, as well as other sources of technical, device-specific bias. Nonetheless, within individuals, slope estimates were relatively stable over time. Both cross-sectionally and longitudinal, slopes tended to become shallower with increasing age, particularly for REM sleep; males tended to show flatter slopes than females across all states. Our findings support that spectral slope can be a valuable arousal marker for both clinical and research endeavors but also underscore the importance of considering interindividual variation and multiple methodological aspects related to its estimation.

Beyond mindfulness: Arousal-driven modulation of attentional control during arousal-based practices

Here we report meditative techniques, which modulate attentional control by arousal-driven influences and not by monitoring continuous thought processes as during mindfulness-related practices. We focus on Vajrayana (Tantric Buddhism) practices, during which a sequence of generation (self-visualization as a deity - Yidam) or completion with sign (inner heat -Tummo) stages necessarily precedes non-dual awareness (NDA) Tantric Mahamudra. We compared the electrocardiographic and electroencephalographic correlates of Mahamudra performed after rest (non-Tantric Mahamudra) with Mahamudra performed after Yidam (Tantric Mahamudra) in 16 highly experienced Vajrayana practitioners, 10 of whom also performed Tummo. Both Yidam and Tummo developed the state of PNS withdrawal (arousal) and phasic alertness, as reflected by HF HRV decreases and Alpha2 power increases, later neurophysiologically employed in Tantric Mahamudra. The latter led to the unique state of high cortical excitability, “non-selective” focused attention, and significantly reduced attentional control, quantified by power reductions in all frequency bands, except Theta. In contrast, similar to mindfulness-related practices, non-Tantric Mahamudra was performed in a state of PNS dominance (relaxation), tonic alertness, and active monitoring, as suggested by Alpha1 power increases and less pronounced decreases in other frequency bands. A neurobiological model of meditation is proposed, differentiating arousal-based and mindfulness-related practices.

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Arousal-based meditations involve the state of PNS withdrawal and phasic alertness.

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Top-down control during arousal-based practices is modulated by arousal.

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Mindfulness-based practices involve the state of PNS dominance and tonic alertness.

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Top-down control during mindfulness-based practices is regulated by monitoring.

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NDA practices aim at non-selectivity of attention and reduction of top-down control.

Deciphering the code: Identifying true gamma neural oscillations

Neural oscillatory activity occurring in the gamma frequency range (30-80 Hz) has been proposed to play essential roles in sensory and cognitive processing. Supporting this, abnormalities in gamma oscillations have been reported in patients with diverse neurological and neuropsychiatric disorders in which cognitive impairment is prominent. Understanding the mechanisms underpinning this relationship is the focus of extensive research. But while an increasing number of studies are investigating the intricate relationship between gamma oscillations and cognition, interpretation and generalisation of these studies is limited by the diverse, and at times questionable, methodologies used to analyse oscillatory activity. For example, a variety of different types of gamma oscillatory activity have been characterised, but all are generalised non-specifically as 'gamma oscillations'. This creates confusion, since distinct cellular and network mechanisms are likely responsible for generating these different types of rhythm. Moreover, in some instances, certain analytical measures of electrophysiological data are overinterpreted, with researchers pushing the boundaries of what would be considered rhythmic or oscillatory in nature. Here, we provide clarity on these issues, firstly presenting an overview of the different measures of gamma oscillatory activity, and describing common signal processing techniques used for analysis. Limitations of these techniques are discussed, and recommendations made on how future studies should optimise analyses, presentation and interpretation of gamma frequency oscillations. This is an essential progression in order to harmonise future studies, allowing us to gain a clearer understanding of the role of gamma oscillations in cognition, and in cognitive disorders.

Good scientific practice in EEG and MEG research: Progress and perspectives

Good scientific practice (GSP) refers to both explicit and implicit rules, recommendations, and guidelines that help scientists to produce work that is of the highest quality at any given time, and to efficiently share that work with the community for further scrutiny or utilization. For experimental research using magneto- and electroencephalography (MEEG), GSP includes specific standards and guidelines for technical competence, which are periodically updated and adapted to new findings. However, GSP also needs to be regularly revisited in a broader light. At the LiveMEEG 2020 conference, a reflection on GSP was fostered that included explicitly documented guidelines and technical advances, but also emphasized intangible GSP: a general awareness of personal, organizational, and societal realities and how they can influence MEEG research. This article provides an extensive report on most of the LiveMEEG contributions and new literature, with the additional aim to synthesize ongoing cultural changes in GSP. It first covers GSP with respect to cognitive biases and logical fallacies, pre-registration as a tool to avoid those and other early pitfalls, and a number of resources to enable collaborative and reproducible research as a general approach to minimize misconceptions. Second, it covers GSP with respect to data acquisition, analysis, reporting, and sharing, including new tools and frameworks to support collaborative work. Finally, GSP is considered in light of ethical implications of MEEG research and the resulting responsibility that scientists have to engage with societal challenges. Considering among other things the benefits of peer review and open access at all stages, the need to coordinate larger international projects, the complexity of MEEG subject matter, and today's prioritization of fairness, privacy, and the environment, we find that current GSP tends to favor collective and cooperative work, for both scientific and for societal reasons.

Functional but not obligatory link between microsaccades and neural modulation by covert spatial attention

Covert spatial attention is associated with spatial modulation of neural activity as well as with directional biases in fixational eye movements known as microsaccades. We studied how these two ‘fingerprints’ of attention are interrelated in humans. We investigated spatial modulation of 8-12 Hz EEG alpha activity and microsaccades when attention is directed internally within the spatial layout of visual working memory. Consistent with a common origin, spatial modulations of alpha activity and microsaccades co-vary: alpha lateralisation is stronger in trials with microsaccades toward versus away from the memorised location of the to-be-attended item and occurs earlier in trials with earlier microsaccades toward this item. Critically, however, trials without attention-driven microsaccades nevertheless show clear spatial modulation of alpha activity – comparable to trials with attention-driven microsaccades. Thus, directional biases in microsaccades correlate with neural signatures of spatial attention, but they are not necessary for neural modulation by spatial attention to be manifest.

Covert visual spatial attention modulates neural activity and biases the direction of small eye movements, known as microsaccades. Here, the authors show that these two markers co-vary, but that microsaccades are not necessary for neural modulation by attention to occur.

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.

Saccade rate is associated with recall of items in working memory

Working memory has been shown to rely on theta oscillations' phase synchronicity for item encoding and recall. At the same time, saccadic eye movements during visual exploration have been observed to trigger theta-phase resets, raising the question of whether the neuronal substrates of mnemonic processing rely on motor-evoked responses. To quantify the relationship between saccades and working memory load, we recorded eye tracking and behavioral data from human participants simultaneously performing an n-back Sternberg auditory task and a hue-based catch detection task. In addition to task-specific interference in performance, we also found that saccade rate was modulated by working memory load in the Sternberg task's preresponse stage. Our results support the possibility of interplay between saccades and hippocampal theta during working memory retrieval of items.

Integrating music-based interventions with Gamma-frequency stimulation: Implications for healthy ageing

In recent years, music-based interventions (MBIs) have risen in popularity as a non-invasive, sustainable form of care for treating dementia-related disorders, such as Mild Cognitive Impairment (MCI) and Alzheimer's disease (AD). Despite their clinical potential, evidence regarding the efficacy of MBIs on patient outcomes is mixed. Recently, a line of related research has begun to investigate the clinical impact of non-invasive Gamma-frequency (e.g., 40 Hz) sensory stimulation on dementia. Current work, using non-human-animal models of AD, suggests that non-invasive Gamma-frequency stimulation can remediate multiple pathophysiologies of dementia at the molecular, cellular and neural-systems scales, and, importantly, improve cognitive functioning. These findings suggest that the efficacy of MBIs could, in theory, be enhanced by incorporating Gamma-frequency stimulation into current MBI protocols. In the current review, we propose a novel clinical framework for non-invasively treating dementia-related disorders that combines previous MBIs with current approaches employing Gamma-frequency sensory stimulation. We theorize that combining MBIs with Gamma-frequency stimulation could increase the therapeutic power of MBIs by simultaneously targeting multiple biomarkers of dementia, restoring neural activity that underlies learning and memory (e.g., Gamma-frequency neural activity, Theta-Gamma coupling), and actively engaging auditory and reward networks in the brain to promote behavioural change.

Developmental organization of neural dynamics supporting auditory perception

Purpose:

A prominent view of language acquisition involves learning to ignore irrelevant auditory signals through functional reorganization, enabling more efficient processing of relevant information. Yet, few studies have characterized the neural spatiotemporal dynamics supporting rapid detection and subsequent disregard of irrelevant auditory information, in the developing brain. To address this unknown, the present study modeled the developmental acquisition of cost-efficient neural dynamics for auditory processing, using intracranial electrocorticographic responses measured in individuals receiving standard-of-care treatment for drug-resistant, focal epilepsy. We also provided evidence demonstrating the maturation of an anterior-to-posterior functional division within the superior-temporal gyrus (STG), which is known to exist in the adult STG.

Methods:

We studied 32 patients undergoing extraoperative electrocorticography (age range: eight months to 28 years) and analyzed 2,039 intracranial electrode sites outside the seizure onset zone, interictal spike-generating areas, and MRI lesions. Patients were given forward (normal) speech sounds, backward-played speech sounds, and signal-correlated noises during a task-free condition. We then quantified sound processing-related neural costs at given time windows using high-gamma amplitude at 70–110 Hz and animated the group-level high-gamma dynamics on a spatially normalized three-dimensional brain surface. Finally, we determined if age independently contributed to high-gamma dynamics across brain regions and time windows.

Results:

Group-level analysis of noise-related neural costs in the STG revealed developmental enhancement of early high-gamma augmentation and diminution of delayed augmentation. Analysis of speech-related high-gamma activity demonstrated an anterior-to-posterior functional parcellation in the STG. The left anterior STG showed sustained augmentation throughout stimulus presentation, whereas the left posterior STG showed transient augmentation after stimulus onset. We found a double dissociation between the locations and developmental changes in speech sound-related high-gamma dynamics. Early left anterior STG high-gamma augmentation (i.e., within 200 ms post-stimulus onset) showed developmental enhancement, whereas delayed left posterior STG high-gamma augmentation declined with development.

Conclusions:

Our observations support the model that, with age, the human STG refines neural dynamics to rapidly detect and subsequently disregard uninformative acoustic noises. Our study also supports the notion that the anterior-to-posterior functional division within the left STG is gradually strengthened for efficient speech sound perception after birth.

Neural Reinstatement of Overlapping Memories in Young and Older Adults

When we update our episodic memories with new information, mnemonic competition between old and new memories may result because of the presence of shared features. Behavioral studies suggest that this competition can lead to proactive interference, resulting in unsuccessful memory updating, particularly for older adults. It is difficult with behavioral data alone to measure the reactivation of old, overlapping memories during retrieval and its impact on memory for new memories. Here, we applied encoding-retrieval representational similarity (ERS) analysis to EEG data to estimate event-specific encoding-related neural reinstatement of old associations during the retrieval of new ones and its impact on memory for new associations in young and older adults. Our results showed that older adults' new associative memory performance was more negatively impacted by proactive interference from old memories than that of young adults. In both age groups, ERS for old associative memories was greater for trials for which new associative memories were forgotten than remembered. In contrast, ERS for new associative memories was greater when they were remembered than forgotten. In addition, older adults showed relatively attenuated target (i.e., new associates) and lure (i.e., old associates) ERS effects compared to younger adults. Collectively, these results suggest that the neural reinstatement of interfering memories during retrieval contributes to proactive interference across age, whereas overall attenuated ERS effect in older adults might reflect their reduced memory fidelity.

Recommendations and publication guidelines for studies using frequency domain and time-frequency domain analyses of neural time series

Since its beginnings in the early 20th century, the psychophysiological study of human brain function has included research into the spectral properties of electrical and magnetic brain signals. Now, dramatic advances in digital signal processing, biophysics, and computer science have enabled increasingly sophisticated methodology for neural time series analysis. Innovations in hardware and recording techniques have further expanded the range of tools available to researchers interested in measuring, quantifying, modeling, and altering the spectral properties of neural time series. These tools are increasingly used in the field, by a growing number of researchers who vary in their training, background, and research interests. Implementation and reporting standards also vary greatly in the published literature, causing challenges for authors, readers, reviewers, and editors alike. The present report addresses this issue by providing recommendations for the use of these methods, with a focus on foundational aspects of frequency domain and time-frequency analyses. It also provides publication guidelines, which aim to (1) foster replication and scientific rigor, (2) assist new researchers who wish to enter the field of brain oscillations, and (3) facilitate communication among authors, reviewers, and editors.

Interbrain synchrony: on wavy ground

In recent years the study of dynamic, between-brain coupling mechanisms has taken social neuroscience by storm. In particular, interbrain synchrony (IBS) is a putative neural mechanism said to promote social interactions by enabling the functional integration of multiple brains. In this article, I argue that this research is beset with three pervasive and interrelated problems. First, the field lacks a widely accepted definition of IBS. Second, IBS wants for theories that can guide the design and interpretation of experiments. Third, a potpourri of tasks and empirical methods permits undue flexibility when testing the hypothesis. These factors synergistically undermine IBS as a theoretical construct. I finish by recommending measures that can address these issues.

Power shift and connectivity changes in healthy aging during resting-state EEG

The neural activity of human brain changes in healthy individuals during aging. The most frequent variation in patterns of neural activity are a shift from posterior to anterior areas and a reduced asymmetry between hemispheres. These patterns are typically observed during task execution and by using functional magnetic resonance imaging data. In the present study we investigated whether analogous effects can also be detected during rest and by means of source-space time series reconstructed from electroencephalographic recordings. By analyzing oscillatory power distribution across the brain we indeed found a shift from posterior to anterior areas in older adults. We additionally examined this shift by evaluating connectivity and its changes with age. The findings indicated that inter-area connections among frontal, parietal and temporal areas were strengthened in older individuals. A more complex pattern was shown in intra-area connections, where age-related activity was enhanced in parietal and temporal areas, and reduced in frontal areas. Finally, the resulting network exhibits a loss of modularity with age. Overall, the results extend to resting-state condition the evidence of an age-related shift of brain activity from posterior to anterior areas, thus suggesting that this shift is a general feature of the aging brain rather than being task-specific. In addition, the connectivity results provide new information on the reorganization of resting-state brain activity in aging.

Naming-related spectral responses predict neuropsychological outcome after epilepsy surgery

This prospective study determined the use of intracranially recorded spectral responses during naming tasks in predicting neuropsychological performance following epilepsy surgery. We recruited 65 patients with drug-resistant focal epilepsy who underwent preoperative neuropsychological assessment and intracranial EEG recording. The Clinical Evaluation of Language Fundamentals evaluated the baseline and postoperative language function. During extra-operative intracranial EEG recording, we assigned patients to undergo auditory and picture naming tasks. Time-frequency analysis determined the spatiotemporal characteristics of naming-related amplitude modulations, including high gamma augmentation at 70-110 Hz. We surgically removed the presumed epileptogenic zone based on the intracranial EEG and MRI abnormalities while maximally preserving the eloquent areas defined by electrical stimulation mapping. The multivariate regression model incorporating auditory naming-related high gamma augmentation predicted the postoperative changes in Core Language Score with r2 of 0.37 and in Expressive Language Index with r2 of 0.32. Independently of the effects of epilepsy and neuroimaging profiles, higher high gamma augmentation at the resected language-dominant hemispheric area predicted a more severe postoperative decline in Core Language Score and Expressive Language Index. Conversely, the model incorporating picture naming-related high gamma augmentation predicted the change in Receptive Language Index with an r2 of 0.50. Higher high gamma augmentation independently predicted a more severe postoperative decline in Receptive Language Index. Ancillary regression analysis indicated that naming-related low gamma augmentation and alpha/beta attenuation likewise independently predicted a more severe Core Language Score decline. The machine learning-based prediction model suggested that naming-related high gamma augmentation, among all spectral responses used as predictors, most strongly contributed to the improved prediction of patients showing a >5-point Core Language Score decline (reflecting the lower 25th percentile among patients). We generated the model-based atlas visualizing sites, which, if resected, would lead to such a language decline. With a 5-fold cross-validation procedure, the auditory naming-based model predicted patients who had such a postoperative language decline with an accuracy of 0.80. The model indicated that virtual resection of an electrical stimulation mapping-defined language site would have increased the relative risk of the Core Language Score decline by 5.28 (95% confidence interval: 3.47-8.02). Especially, that of an electrical stimulation mapping-defined receptive language site would have maximized it to 15.90 (95% confidence interval: 9.59-26.33). In summary, naming-related spectral responses predict neuropsychological outcomes after epilepsy surgery. We have provided our prediction model as an open-source material, which will indicate the postoperative language function of future patients and facilitate external validation at tertiary epilepsy centres.

Naturalistic viewing conditions can increase task engagement and aesthetic preference but have only minimal impact on EEG quality

Free gaze and moving images are typically avoided in EEG experiments due to the expected generation of artifacts and noise. Yet for a growing number of research questions, loosening these rigorous restrictions would be beneficial. Among these is research on visual aesthetic experiences, which often involve open-ended exploration of highly variable stimuli. Here we systematically compare the effect of conservative vs. more liberal experimental settings on various measures of behavior, brain activity and physiology in an aesthetic rating task. Our primary aim was to assess EEG signal quality. 43 participants either maintained fixation or were allowed to gaze freely, and viewed either static images or dynamic (video) stimuli consisting of dance performances or nature scenes. A passive auditory background task (auditory steady-state response; ASSR) was added as a proxy measure for overall EEG recording quality. We recorded EEG, ECG and eyetracking data, and participants rated their aesthetic preference and state of boredom on each trial. Whereas both behavioral ratings and gaze behavior were affected by task and stimulus manipulations, EEG SNR was barely affected and generally robust across all conditions, despite only minimal preprocessing and no trial rejection. In particular, we show that using video stimuli does not necessarily result in lower EEG quality and can, on the contrary, significantly reduce eye movements while increasing both the participants' aesthetic response and general task engagement. We see these as encouraging results indicating that - at least in the lab - more liberal experimental conditions can be adopted without significant loss of signal quality.

Lucid dreaming occurs in activated rapid eye movement sleep, not a mixture of sleep and wakefulness

STUDY OBJECTIVES

(1) To critically test whether a previously reported increase in frontolateral 40 Hz power in lucid REM sleep, used to justify the claim that lucid dreaming is a "hybrid state" mixing sleep and wakefulness, is attributable to the saccadic spike potential (SP) artifact as a corollary of heightened REM density. (2) To replicate the finding that lucid dreams are associated with physiological activation, including heightened eye movement density, during REM sleep. (3) To conduct an exploratory analysis of changes in EEG features during lucid REM sleep.

METHODS

We analyzed 14 signal-verified lucid dreams (SVLDs) and baseline REM sleep segments from the same REM periods from six participants derived from the Stanford SVLD database. Participants marked lucidity onset with standard left-right-left-right-center (LR2c) eye-movement signals in polysomnography recordings.

RESULTS

Compared to baseline REM sleep, lucid REM sleep had higher REM density (β = 0.85, p = 0.002). Bayesian analysis supported the null hypothesis of no differences in frontolateral 40 Hz power after removal of the SP artifact (BH = 0.18) and ICA correction (BH = 0.01). Compared to the entire REM sleep period, lucid REM sleep showed small reductions in low-frequency and beta band spectral power as well as increased signal complexity (all p < 0.05), which were within the normal variance of baseline REM sleep.

CONCLUSIONS

Lucid dreams are associated with higher-than-average levels of physiological activation during REM sleep, including measures of both subcortical and cortical activation. Increases in 40 Hz power in periorbital channels reflect saccadic and microsaccadic SPs as a result of higher REM density accompanying heightened activation.

Transforming Discoveries About Cortical Microcircuits and Gamma Oscillations Into New Treatments for Cognitive Deficits in Schizophrenia

The major cause of disability in schizophrenia is cognitive impairment, which remains largely refractory to existing treatments. This reflects the fact that antipsychotics and other therapies have not been designed to address specific brain abnormalities that cause cognitive impairment. This overview proposes that understanding how specific cellular and synaptic loci within cortical microcircuits contribute to cortical gamma oscillations may reveal treatments for cognitive impairment. Gamma oscillations are rhythmic patterns of high frequency (∼30-100 Hz) neuronal activity that are synchronized within and across brain regions, generated by a class of inhibitory interneurons that express parvalbumin, and recruited during a variety of cognitive tasks. In schizophrenia, both parvalbumin interneuron function and task-evoked gamma oscillations are deficient. While it has long been controversial whether gamma oscillations are merely a biomarker of circuit function or actually contribute to information processing by neuronal networks, recent neurobiological studies in mice have shown that disrupting or enhancing synchronized gamma oscillations can reproduce or ameliorate cognitive deficits resembling those seen in schizophrenia. In fact, transiently enhancing the synchrony of parvalbumin interneuron-generated gamma oscillations can lead to long-lasting improvements in cognition in mice that model aspects of schizophrenia. Gamma oscillations emerge from specific patterns of connections between a variety of cell types within cortical microcircuits. Thus, a critical next step is to understand how specific cell types and synapses generate gamma oscillations, mediate the effects of gamma oscillations on information processing, and/or undergo plasticity following the induction of gamma oscillations. Modulating these circuit loci, potentially in combination with other approaches such as cognitive training and brain stimulation, may yield potent and selective interventions for enhancing cognition in schizophrenia.