Online and offline effects of parietal 10 Hz repetitive transcranial magnetic stimulation on working memory in healthy controls

Parietal alpha activity shows a specific pattern of phasic changes during working memory. It decreases during the encoding and recall phases but increases during the maintenance phase. This study tested whether online rTMS delivered to the parietal cortex during the maintenance phase of a working memory task would increase alpha activity and hence improve working memory. Then, 46 healthy volunteers were randomly assigned to two groups to receive 3-day parietal 10 Hz online rTMS (either real or sham, 3600 pulses in total) that were time-locked to the maintenance phase of a spatial span task (180 trials in total). Behavioral performance on another spatial span task and EEG signals during a change detection task were recorded on the day before the first rTMS (pretest) and the day after the last rTMS (posttest). We found that rTMS improved performance on both online and offline spatial span tasks. For the offline change detection task, rTMS enhanced alpha activity within the maintenance phase and improved interference control of working memory at both behavioral (K score) and neural (contralateral delay activity) levels. These results suggested that rTMS with alpha frequency time-locked to the maintenance phase is a promising way to boost working memory.

Low Atmospheric Oxygen Attenuates Alpha Oscillations in the Primary Motor Cortex of Awake Rats

Oxygen is pivotal for survival of animals. Their cellular activity and cognitive behavior are impaired when atmospheric oxygen is insufficient, called hypoxia. However, concurrent effects of hypoxia on physiological signals are poorly understood. To address this question, we simultaneously recorded local field potentials in the primary motor cortex, primary somatosensory, and anterior cingulate cortex, electrocardiograms, electroolfactograms, and electromyograms of rats under acute hypoxic conditions (i.e., 5.0% O2). Exposure to acute hypoxia significantly attenuated alpha oscillations alone in the primary motor cortex, while we failed to find any effects of acute hypoxia on the oscillatory power in the somatosensory cortex or anterior cingulate cortex. These area- and frequency-specific effects by hypoxia may be accounted for by neural innervation from the brainstem to each cortical area via thalamic relay nuclei. Moreover, we found that heart rate and respiratory rate were increased during acute hypoxia and high heart rate was maintained even after the oxygen level returned to the baseline. Altogether, our study characterizes a systemic effect of atmospheric hypoxia on neural and peripheral signals from physiological viewpoints, leading to bridging a gap between cellular and behavioral levels.

Modulating Individual Alpha Frequency through Short-Term Neurofeedback for Cognitive Enhancement in Healthy Young Adults

Human alpha oscillation (7-13 Hz) has been extensively studied over the years for its connection with cognition. The individual alpha frequency (IAF), defined as the frequency that provides the highest power in the alpha band, shows a positive correlation with cognitive processes. The modulation of alpha activities has been accomplished through various approaches aimed at improving cognitive performance. However, very few studies focused on the direct modulation of IAF by shifting the peak frequency, and the understanding of IAF modulation remains highly limited. In this study, IAFs of healthy young adults were up-regulated through short-term neurofeedback training using haptic feedback. The results suggest that IAFs have good trainability and are up-regulated, also that IAFs are correlated with the enhanced cognitive performance in mental rotation and n-back tests compared to sham-neurofeedback control. This study demonstrates the feasibility of self-regulating IAF for cognition enhancement and provides potential therapeutic benefits for cognitive-impaired patients.

Slope of the power spectral density flattens at low frequencies (<150 Hz) with healthy aging but also steepens at higher frequency (>200 Hz) in human electroencephalogram

The power spectral density (PSD) of the brain signals is characterized by two distinct features: oscillations, which are represented as distinct "bumps," and broadband aperiodic activity, that reduces in power with increasing frequency and is characterized by the slope of the power falloff. Recent studies have shown a change in the slope of the aperiodic activity with healthy aging and mental disorders. However, these studies analyzed slopes over a limited frequency range (<100 Hz). To test whether the PSD slope is affected over a wider frequency range with aging and mental disorder, we analyzed the slope till 800 Hz in electroencephalogram data recorded from elderly subjects (>49 years) who were healthy (n = 217) or had mild cognitive impairment (MCI; n = 11) or Alzheimer's Disease (AD; n = 5). Although the slope reduced up to ~ 150 Hz with healthy aging (as shown previously), surprisingly, at higher frequencies (>200 Hz), it increased with age. These results were observed in all electrodes, for both eyes open and eyes closed conditions, and for different reference schemes. However, slopes were not significantly different in MCI/AD subjects compared with healthy controls. Overall, our results constrain the biophysical mechanisms that are reflected in the PSD slopes in healthy and pathological aging.

Breakdown of long-range spatial correlations of infraslow amplitude fluctuations of EEG oscillations in patients with current and past major depressive disorder

Introduction

Identifying biomarkers for depression from brain activity is important for the diagnosis and treatment of depression disorders. We investigated spatial correlations of the amplitude fluctuations of electroencephalography (EEG) oscillations as a potential biomarker of depression. The amplitude fluctuations of EEG oscillations intrinsically reveal both temporal and spatial correlations, indicating rapid and functional organization of the brain networks. Amid these correlations, long-range temporal correlations are reportedly impaired in patients with depression, exhibiting amplitude fluctuations closer to a random process. Based on this occurrence, we hypothesized that the spatial correlations of amplitude fluctuations would also be altered by depression.

Methods

In the present study, we extracted the amplitude fluctuations of EEG oscillations by filtering them through infraslow frequency band (0.05-0.1 Hz).

Results

We found that the amplitude fluctuations of theta oscillations during eye-closed rest depicted lower levels of spatial correlation in patients with major depressive disorder (MDD) compared to control individuals. This breakdown of spatial correlations was most prominent in the left fronto - temporal network, specifically in patients with current MDD rather than in those with past MDD. We also found that the amplitude fluctuations of alpha oscillations during eye-open rest exhibited lower levels of spatial correlation in patients with past MDD compared to control individuals or patients with current MDD.

Discussion

Our results suggest that breakdown of long-range spatial correlations may offer a biomarker for the diagnosis of depression (current MDD), as well as the tracking of the recovery from depression (past MDD).

The neurovascular couplings between electrophysiological and hemodynamic activities in anticipatory selective attention

Selective attention is thought to involve target enhancement and distractor inhibition processes. Here, we recorded simultaneous electroencephalographic (EEG) and functional near-infrared spectroscopy (fNIRS) data from human adults when they were pre-cued by the visual field of coming target, distractor, or both of them. From the EEG data, we found alpha power relatively decreased contralaterally to the to-be-attended target, as reflected by the positive-going alpha modulation index. Late alpha power relatively increased contralaterally to the to-be-suppressed distractor, as reflected by the negative-going alpha modulation index. From the fNIRS data, we found enhancements of hemodynamic activity over the contralateral hemisphere in response to both the target and the distractor anticipation but within nonoverlapping posterior brain regions. More importantly, we described the specific neurovascular modulation between alpha power and oxygenated hemoglobin signal, which showed a positive coupling effect during target anticipation and a negative coupling effect during distractor anticipation. Such flexible neurovascular couplings between EEG oscillation and hemodynamic activity seem to play an essential role in the final behavioral outcomes. These results provide unique neurovascular evidence for the dissociation of the mechanisms of target enhancement and distractor inhibition. Individual behavioral differences can be related to individual differences in neurovascular coupling.

Retrosplenial and Hippocampal Synchrony during Retrieval of Old Memories in Macaques

Memory for events from the distant past relies on multiple brain regions, but little is known about the underlying neural dynamics that give rise to such abilities. We recorded neural activity in the hippocampus and retrosplenial cortex of two female rhesus macaques as they visually selected targets in year-old and newly acquired object-scene associations. Whereas hippocampal activity was unchanging with memory age, the retrosplenial cortex responded with greater magnitude alpha oscillations (10-15 Hz) and greater phase locking to memory-guided eye movements during retrieval of old events. A similar old-memory enhancement was observed in the anterior cingulate cortex but in a beta2/gamma band (28-35 Hz). In contrast, remote retrieval was associated with decreased gamma-band synchrony between the hippocampus and each neocortical area. The increasing retrosplenial alpha oscillation and decreasing hippocampocortical synchrony with memory age may signify a shift in frank memory allocation or, alternatively, changes in selection among distributed memory representations in the primate brain.SIGNIFICANCE STATEMENT Memory depends on multiple brain regions, whose involvement is thought to change with time. Here, we recorded neuronal population activity from the hippocampus and retrosplenial cortex as nonhuman primates searched for objects embedded in scenes. These memoranda were either newly presented or a year old. Remembering old material drove stronger oscillations in the retrosplenial cortex and led to a greater locking of neural activity to search movements. Remembering new material revealed stronger oscillatory synchrony between the hippocampus and retrosplenial cortex. These results suggest that with age, memories may come to rely more exclusively on neocortical oscillations for retrieval and search guidance and less on long-range coupling with the hippocampus.

Alpha Oscillations Track Content-Specific Working Memory Capacity

Although the neural basis of working memory (WM) capacity is often studied by exploiting interindividual differences, capacity may also differ across memory materials within a given individual. Here, we exploit the content dependence of WM capacity as a novel approach to investigate the oscillatory correlates of WM capacity, focusing on posterior 9-12 Hz alpha activity during retention. We recorded scalp electroencephalography (EEG) while male and female human participants performed WM tasks with varying memory loads (two vs. four items) and materials (English letters vs. regular shapes vs. abstract shapes). First, behavioral data confirmed that memory capacity was fundamentally content dependent; capacity for abstract shapes plateaued at around two, whereas the participants could remember more letters and regular shapes. Critically, content-specific capacity was paralleled in the degree of attenuation of EEG-alpha activity that plateaued in a similar content-specific manner. Although we observed greater alpha attenuation for higher loads for all materials, we found larger load effects for letters and regular shapes than for abstract shapes, which is consistent with our behavioral data showing a lower capacity plateau for abstract shapes. Moreover, when only considering two-item trials, alpha attenuation was greater for abstract shapes where two items were close to the capacity plateau than for other materials. Multivariate decoding of alpha activity patterns reinforced these findings. Finally, for each material, load effects on capacity (K) and alpha attenuation were correlated across individuals. Our results demonstrate that alpha oscillations track memory capacity in a content-specific manner and track not just the number of items but also their complexity.SIGNIFICANCE STATEMENT WM is limited in its capacity. We show that capacity is not fixed for an individual but is rather memory-content dependent. Moreover, we used this as a novel approach to investigate the neural basis of WM capacity with EEG. We found that both behavioral capacity estimates and neural oscillations in the alpha band varied with memory loads and materials. The critical finding is a capacity plateau of approximately two items only for the more complex materials, accompanied by a similar plateau in the EEG alpha attenuation. The load effects on capacity and alpha attenuation were furthermore correlated across individuals for each of the materials. Our results demonstrate that alpha oscillations track the content-specific nature of WM capacity.

Pre-Stimulus Alpha-Band Phase Gates Early Visual Cortex Responses

Alpha-band (8-13 Hz) oscillations have been shown to phasically inhibit perceptual reports in human observers, yet the underlying physiological mechanism of this effect is debated. According to contrasting models, based primarily on animal experiments, alpha activity is thought to either originate from specialized cells in the visual thalamus and periodically inhibit the relay of visual information to the primary visual cortex (V1) in a feedforward manner, or to propagate from higher visual areas back to V1 in a feedback manner. Human neurophysiological evidence in favor of either hypothesis, both, or neither, has been limited. To help address this issue, we explored the link between pre-stimulus alpha phase and visual electroencephalography (EEG) responses thought to arise from afferent input onto human V1. Specially-designed visual stimuli were used to elicit large amplitude C1 event-related potentials (ERP), with polarity, topography, and timing indicative of striate genesis. Single-trial circular-linear associations between pre-stimulus phase and post-stimulus global field power (GFP) during the C1 time window revealed significant effects peaking in the alpha frequency band. Control analyses ruling out the potential confound of post-stimulus data bleeding into the pre-stimulus window demonstrated that GFP amplitude decreases as pre-stimulus alpha phase deviates from an individual's preferred phase. These findings demonstrate an early locus - suggesting that the phase of pre-stimulus alpha oscillations could modulate visual processing by gating the feedforward flow of sensory input between the thalamus and V1, although other models are potentially compatible.

Visual thalamocortical mechanisms of waking state-dependent activity and alpha oscillations

The brain exhibits distinct patterns of recurrent activity closely related to behavioral state. The neural mechanisms that underlie state-dependent activity in the awake animal are incompletely understood. Here, we demonstrate that two types of state-dependent activity, rapid arousal/movement-related signals and a 3-5 Hz alpha-like rhythm, in the primary visual cortex (V1) of mice strongly correlate with activity in the visual thalamus. Inactivation of V1 does not interrupt arousal/movement signals in most visual thalamic neurons, but it abolishes the 3-5 Hz oscillation. Silencing of the visual thalamus similarly eradicates the alpha-like rhythm and perturbs arousal/movement-related activation in V1. Intracellular recordings in thalamic neurons reveal the 3-5 Hz oscillation to be associated with rhythmic low-threshold Ca²⁺ spikes. Our results indicate that thalamocortical interactions through ionotropic signaling, together with cell-intrinsic properties of thalamocortical cells, play a crucial role in shaping state-dependent activity in V1 of the awake animal.

Neurofeedback Training of the Control Network Improves Children's Performance with an SSVEP-based BCI

In the past 20 years, neural engineering has made unprecedented progress in the interpretation of brain information (e.g., brain-computer interfaces) and in neuromodulation (e.g., electromagnetic stimulation and neurofeedback). However, there has been little research aiming to improve the performance of brain-computer interfaces (BCIs) using neuromodulation. The present study presents a novel design for a neurofeedback training (NFT) method to improve the operation of a steady-state visual evoked potential (SSVEP)-based BCI and further explores its underlying mechanisms. The use of NFT to upregulate alpha-band power in the user's parietal lobe is presented in this study as a new neuromodulation method to improve SSVEP-based BCI in this study. After users completed this NFT intervention, the signal-to-noise ratio (SNR), accuracy, and information transfer rate (ITR) of the SSVEP-based BCI were increased by 5.8%, 4.7%, and 15.6%, respectively. However, no improvement was observed in the control group in which the subjects did not participate in NFT. Moreover, a general reinforcement of the information flow from the parietal lobe to the occipital lobe was observed. Evidence from a network analysis and an attention test further indicates that NFT improves attention by developing the control capacity of the parietal lobe and then enhances the above SSVEP indicators. Upregulating the amplitude of parietal alpha oscillations using NFT significantly improves the SSVEP-based BCI performance by modulating the control network. The study validates an effective neuromodulation method and possibly contributes to explaining the function of the parietal lobe in the control network.

Social-Specific Impairment of Negative Emotion Perception in Alexithymia

Alexithymia has been characterized as an impaired ability of emotion processing and regulation. The definition of alexithymia does not include a social component. However, there is some evidence that social cognition may be compromised in individuals with alexithymia. Hence, emotional impairments associated with alexithymia may extend to socially relevant information. Here, we recorded electrophysiological responses of individuals meeting the clinically relevant cutoff for alexithymia (ALEX; n = 24) and individuals without alexithymia (NonALEX; n = 23) while they viewed affective scenes that varied on the dimensions of sociality and emotional valence during a rapid serial visual presentation task. We found that ALEX exhibited lower accuracy and larger N2 than NonALEX in the perception of social negative scenes. Source reconstruction revealed that the group difference in N2 was localized at the dorsal anterior cingulate cortex. Irrespective of emotional valence, ALEX showed stronger alpha power than NonALEX in social but not non-social conditions. Our findings support the hypothesis of social processing being selectively affected by alexithymia, especially for stimuli with negative valence. Electrophysiological evidence suggests altered deployment of attentional resources in the perception of social-specific emotional information in alexithymia. This work sheds light on the neuropsychopathology of alexithymia and alexithymia-related disorders.

Explosive sound without external stimuli following electroencephalography kappa rhythm fluctuation: A case report

BACKGROUND

The pathology underlying exploding head syndrome, a parasomnia causing a loud sound/sense of explosion, is not well understood. Kappa rhythm is a type of electroencephalogram alpha band activity with maximum potential between contralateral temporal electrodes We report a case of preceding kappa activity before exploding head syndrome attacks.

CASE REPORT

A 57-year-old woman complained of explosive sounds for 2 months; a loud sound would transpire every day before sleep onset. She was diagnosed with exploding head syndrome. During polysomnography and the multiple sleep latency test, the exploding head syndrome attacks occurred six times. A kappa wave with activity disappearing a few seconds before most exploding head syndrome attacks was observed. The alpha band power in T3-T4 derivation gradually waxed followed by termination around the attacks.

CONCLUSION

This case demonstrated that the dynamics of kappa activity precede exploding head syndrome attacks. Finding ways to modulate electroencephalogram oscillation could elucidate their causality and lead to therapeutic intervention.

Examining motor evoked potential amplitude and short-interval intracortical inhibition on the up-going and down-going phases of a transcranial alternating current stimulation (tacs) imposed alpha oscillation

Many brain regions exhibit rhythmical activity thought to reflect the summed behaviour of large populations of neurons. The endogenous alpha rhythm has been associated with phase-dependent modulation of corticospinal excitability. However, whether exogenous alpha rhythm, induced using transcranial alternating current stimulation (tACS) also has a phase-dependent effect on corticospinal excitability remains unknown. Here, we triggered transcranial magnetic stimuli (TMS) on the up- or down-going phase of a tACS-imposed alpha oscillation and measured motor evoked potential (MEP) amplitude and short-interval intracortical inhibition (SICI). There was no significant difference in MEP amplitude or SICI when TMS was triggered on the up- or down-going phase of the tACS-imposed alpha oscillation. The current study provides no evidence of differences in corticospinal excitability or GABAergic inhibition when targeting the up-going (peak) and down-going (trough) phase of the tACS-imposed oscillation.

Real-Time Implementation of EEG Oscillatory Phase-Informed Visual Stimulation Using a Least Mean Square-Based AR Model

It is a technically challenging problem to assess the instantaneous brain state using electroencephalography (EEG) in a real-time closed-loop setup because the prediction of future signals is required to define the current state, such as the instantaneous phase and amplitude. To accomplish this in real-time, a conventional Yule–Walker (YW)-based autoregressive (AR) model has been used. However, the brain state-dependent real-time implementation of a closed-loop system employing an adaptive method has not yet been explored. Our primary purpose was to investigate whether time-series forward prediction using an adaptive least mean square (LMS)-based AR model would be implementable in a real-time closed-loop system or not. EEG state-dependent triggers synchronized with the EEG peaks and troughs of alpha oscillations in both an open-eyes resting state and a visual task. For the resting and visual conditions, statistical results showed that the proposed method succeeded in giving triggers at a specific phase of EEG oscillations for all participants. These individual results showed that the LMS-based AR model was successfully implemented in a real-time closed-loop system targeting specific phases of alpha oscillations and can be used as an adaptive alternative to the conventional and machine-learning approaches with a low computational load.

Distinguishing vigilance decrement and low task demands from mind-wandering: A machine learning analysis of EEG

Mind‐wandering is a ubiquitous mental phenomenon that is defined as self‐generated thought irrelevant to the ongoing task. Mind‐wandering tends to occur when people are in a low‐vigilance state or when they are performing a very easy task. In the current study, we investigated whether mind‐wandering is completely dependent on vigilance and current task demands, or whether it is an independent phenomenon. To this end, we trained support vector machine (SVM) classifiers on EEG data in conditions of low and high vigilance, as well as under conditions of low and high task demands, and subsequently tested those classifiers on participants' self‐reported mind‐wandering. Participants' momentary mental state was measured by means of intermittent thought probes in which they reported on their current mental state. The results showed that neither the vigilance classifier nor the task demands classifier could predict mind‐wandering above‐chance level, while a classifier trained on self‐reports of mind‐wandering was able to do so. This suggests that mind‐wandering is a mental state different from low vigilance or performing tasks with low demands—both which could be discriminated from the EEG above chance. Furthermore, we used dipole fitting to source‐localize the neural correlates of the most import features in each of the three classifiers, indeed finding a few distinct neural structures between the three phenomena. Our study demonstrates the value of machine‐learning classifiers in unveiling patterns in neural data and uncovering the associated neural structures by combining it with an EEG source analysis technique.

Brainwaves Oscillations as a Potential Biomarker for Major Depression Disorder Risk

Major depressive disorder (MDD) is a multidimensional disorder that is characterized by the presence of alterations in mood, cognitive capacity, sensorimotor, and homeostatic functions. Given that about half of the patients diagnosed with MDD do not respond to the various current treatments, new techniques are being sought to predict not only the course of the disease but also the characteristics that differentiate responders from non-responders. Using the electroencephalogram, a noninvasive and inexpensive tool, most studies have proposed that patients with MDD have some lateralization in brain electrical activity, with alterations in alpha and theta rhythms being observed, which would be related to dysfunctions in emotional capacity such as the absence or presence of responses to the different existing treatments. These alterations help in the identification of subjects at high risk of suffering from depression, in the differentiation into responders and nonresponders to various therapies (pharmacological, electroconvulsive therapy, and so on), as well as to establish in which period of the disease the treatment will be more effective. Although the data are still inconclusive and more research is needed, these alpha and theta neurophysiological markers could support future clinical practice when it comes to establishing an early diagnosis and treating state disorders more successfully and accurately of mood disorders.

Decomposed Temporal Complexity Analysis of Neural Oscillations and Machine Learning Applied to Alzheimer's Disease Diagnosis

Despite growing evidence of aberrant neuronal complexity in Alzheimer's disease (AD), it remains unclear how this variation arises. Neural oscillations reportedly comprise different functions depending on their own properties. Therefore, in this study, we investigated details of the complexity of neural oscillations by decomposing the oscillations into frequency, amplitude, and phase for AD patients. We applied resting-state magnetoencephalography (MEG) to 17 AD patients and 21 healthy control subjects. We first decomposed the source time series of the MEG signal into five intrinsic mode functions using ensemble empirical mode decomposition. We then analyzed the temporal complexities of these time series using multiscale entropy. Results demonstrated that AD patients had lower complexity on short time scales and higher complexity on long time scales in the alpha band in temporal regions of the brain. We evaluated the alpha band complexity further by decomposing it into amplitude and phase using Hilbert spectral analysis. Consequently, we found lower amplitude complexity and higher phase complexity in AD patients. Correlation analyses between spectral complexity and decomposed complexities revealed scale-dependency. Specifically, amplitude complexity was positively correlated with spectral complexity on short time scales, whereas phase complexity was positively correlated with spectral complexity on long time scales. Regarding the relevance of cognitive function to the complexity measures, the phase complexity on the long time scale was found to be correlated significantly with the Mini-Mental State Examination score. Additionally, we examined the diagnostic utility of the complexity characteristics using machine learning (ML) methods. We prepared a feature pool using multiple sparse autoencoders (SAEs), chose some discriminating features, and applied them to a support vector machine (SVM). Compared to the simple SVM and the SVM after feature selection (FS + SVM), the SVM with multiple SAEs (SAE + FS + SVM) had improved diagnostic accuracy. Through this study, we 1) advanced the understanding of neuronal complexity in AD patients using decomposed temporal complexity analysis and 2) demonstrated the effectiveness of combining ML methods with information about signal complexity for the diagnosis of AD.

Pulsed Facilitation of Corticospinal Excitability by the Sensorimotor μ-Alpha Rhythm

Alpha oscillations (8-14 Hz) are assumed to gate information flow in the brain by means of pulsed inhibition; that is, the phasic suppression of cortical excitability and information processing once per alpha cycle, resulting in stronger net suppression for larger alpha amplitudes due to the assumed amplitude asymmetry of the oscillation. While there is evidence for this hypothesis regarding occipital alpha oscillations, it is less clear for the central sensorimotor μ-alpha rhythm. Probing corticospinal excitability via transcranial magnetic stimulation (TMS) of the primary motor cortex and the measurement of motor evoked potentials (MEPs), we have previously demonstrated that corticospinal excitability is modulated by both amplitude and phase of the sensorimotor μ-alpha rhythm. However, the direction of this modulation, its proposed asymmetry, and its underlying mechanisms remained unclear. We therefore used real-time EEG-triggered single- and paired-pulse TMS in healthy humans of both sexes to assess corticospinal excitability and GABA-A-receptor mediated short-latency intracortical inhibition (SICI) at rest during spontaneous high amplitude μ-alpha waves at different phase angles (peaks, troughs, rising and falling flanks) and compared them to periods of low amplitude (desynchronized) μ-alpha. MEP amplitude was facilitated during troughs and rising flanks, but no phasic suppression was observed at any time, nor any modulation of SICI. These results are best compatible with sensorimotor μ-alpha reflecting asymmetric pulsed facilitation but not pulsed inhibition of motor cortical excitability. The asymmetric excitability with respect to rising and falling flanks of the μ-alpha cycle further reveals that voltage differences alone cannot explain the impact of phase.SIGNIFICANCE STATEMENT The pulsed inhibition hypothesis, which assumes that alpha oscillations actively inhibit neuronal processing in a phasic manner, is highly influential and has substantially shaped our understanding of these oscillations. However, some of its basic assumptions, in particular its asymmetry and inhibitory nature, have rarely been tested directly. Here, we explicitly investigated the asymmetry of modulation and its direction for the human sensorimotor μ-alpha rhythm. We found clear evidence of pulsed facilitation, but not inhibition, in the human motor cortex, challenging the generalizability of the pulsed inhibition hypothesis and advising caution when interpreting sensorimotor μ-alpha changes in the sensorimotor system. This study also demonstrates how specific assumptions about the neurophysiological underpinnings of cortical oscillations can be experimentally tested noninvasively in humans.

Anticipatory alpha oscillation predicts attentional selection and hemodynamic response

In covert visual attention, one fundamental question is how advance knowledge facilitates subsequent neural processing and behavioral performance. In this study, with a rapid event-related simultaneous electroencephalography (EEG) and functional near infrared spectroscopy recording in humans, we explored the potential contribution of anticipatory electrophysiological activation and hemodynamic activation by examining how anticipatory low-frequency oscillations and changes in oxygenated hemoglobin (HbO) concentration influence the subsequent event-related potential (ERP) marker of attentional selection. We found that expecting a target led to both a posterior lateralization of alpha-band (8-12 Hz) oscillation power and a lateralization of HbO response over the visual cortex. Importantly, the magnitude of cue-induced alpha lateralization was positively correlated with the nearby HbO lateralization in the visual cortex, and such a cue-induced alpha lateralization predicted the subsequent target-evoked N2pc amplitudes assumed to reflect attentional selection. Our results suggest that each individual's attentional selection biomarker as reflected by N2pc is predictable in advance via the anticipation-induced alpha lateralization, and such cue-induced alpha lateralization seems to play an important role in the functional coupling effects between the low-frequency EEG and the nearby hemodynamic activation.

Repetitive Passive Finger Movement Modulates Primary Somatosensory Cortex Excitability

Somatosensory inputs induced by repetitive passive movement (RPM) modulate primary motor cortex (M1) excitability; however, it is unclear whether RPM affects primary somatosensory cortex (S1) excitability. In this study, we investigated whether RPM affects somatosensory evoked potentials (SEPs) and resting state brain oscillation, including alpha and beta bands, depend on RPM frequency. Nineteen healthy subjects participated in this study, and SEPs elicited by peripheral nerve electrical stimulation were recorded from the C3’ area in order to assess S1 excitability (Exp. 1: n = 15). We focused on prominent SEP components such as N20, P25 and P45-reflecting S1 activities. In addition, resting electroencephalograms (EEGs) were recorded from C3’ area to assess the internal state of the brain network at rest (Exp. 2: n = 15). Passive abduction/adduction of the right index finger was applied for 10 min at frequencies of 0.5, 1.0, 3.0, and 5.0 Hz in Exp. 1, and 1.0, 3.0, and 5.0 Hz in Exp. 2. No changes in N20 or P25 components were observed following RPM. The 3.0 Hz-RPM decreased the P45 component for 20 min (p < 0.05), but otherwise did not affect the P45 component. There was no difference in the alpha and beta bands before and after any RPM; however, a negative correlation was observed between the rate of change of beta power and P45 component at 3.0 Hz-RPM. Our findings indicated that the P45 component changes depending on the RPM frequency, suggesting that somatosensory inputs induced by RPM influences S1 excitability. Additionally, beta power enhancement appears to contribute to the P45 component depression in 3.0 Hz-RPM.

Neural Activity Is Dynamically Modulated by Memory Load During the Maintenance of Spatial Objects

Visuospatial working memory (WM) is a fundamental but severely limited ability to temporarily remember selected stimuli. Several studies have investigated the underlying neural mechanisms of maintaining various visuospatial stimuli simultaneously (i.e., WM load, the number of representations that need to be maintained in WM). However, two confounding factors, namely verbal representation and encoding load (the number of items that need to be encoded into WM), have not been well controlled in previous studies. In this study, we developed a novel delayed-match-to-sample task (DMST) controlling for these two confounding factors and recorded scalp EEG signals during the task. We found that behavioral performance deteriorated severely as memory load increased. Neural activity was modulated by WM load in a dynamic manner. Specifically, higher memory load induced stronger amplitude in occipital and central channel-clusters during the early delay period, while the inverse trend was observed in central and frontal channel-clusters during late delay. In addition, the same inverse memory load effect, that was lower memory load induced stronger amplitude, was observed in occipital channel-cluster alpha power during late delay. Finally, significant correlations between neural activity and individual reaction time showed a role of late-delay central and frontal channel-cluster amplitude in predicting behavioral performance. Because the occipital cortex is important for visual information maintenance, the decrease in alpha oscillation was consistent with the cognitive role that is “gating by inhibition.” Together, our results from a well-controlled DMST suggest that WM load not exerted constant but dynamic effect on neural activity during maintenance of visuospatial objects.

Alpha Oscillations Are Causally Linked to Inhibitory Abilities in Ageing

Aging adults typically show reduced ability to ignore task-irrelevant information, an essential skill for optimal performance in many cognitive operations, including those requiring working memory (WM) resources. In a first experiment, young and elderly human participants of both genders performed an established WM paradigm probing inhibitory abilities by means of valid, invalid, and neutral retro-cues. Elderly participants showed an overall cost, especially in performing invalid trials, whereas younger participants' general performance was comparatively higher, as expected.Inhibitory abilities have been linked to alpha brain oscillations but it is yet unknown whether in aging these oscillations (also typically impoverished) and inhibitory abilities are causally linked. To probe this possible causal link in aging, we compared in a second experiment parietal alpha-transcranial alternating current stimulation (tACS) with either no stimulation (Sham) or with two control stimulation frequencies (theta- and gamma-tACS) in the elderly group while performing the same WM paradigm. Alpha- (but not theta- or gamma-) tACS selectively and significantly improved performance (now comparable to younger adults' performance in the first experiment), particularly for invalid cues where initially elderly showed the highest costs. Alpha oscillations are therefore causally linked to inhibitory abilities and frequency-tuned alpha-tACS interventions can selectively change these abilities in the elderly.SIGNIFICANCE STATEMENT Ignoring task-irrelevant information, an ability associated to rhythmic brain activity in the alpha frequency band, is fundamental for optimal performance. Indeed, impoverished inhibitory abilities contribute to age-related decline in cognitive functions like working memory (WM), the capacity to briefly hold information in mind. Whether in aging adults alpha oscillations and inhibitory abilities are causally linked is yet unknown. We experimentally manipulated frequency-tuned brain activity using transcranial alternating current stimulation (tACS), combined with a retro-cue paradigm assessing WM and inhibition. We found that alpha-tACS induced a significant improvement in target responses and misbinding errors, two indexes of inhibition. We concluded that in aging alpha oscillations are causally linked to inhibitory abilities, and that despite being impoverished, these abilities are still malleable.

Corrigendum: Placebo Analgesia Changes Alpha Oscillations Induced by Tonic Muscle Pain: EEG Frequency Analysis Including Data during Pain Evaluation

[This corrects the article on p. 45 in vol. 10, PMID: 27242501.].

Competition in the Brain. The Contribution of EEG and fNIRS Modulation and Personality Effects in Social Ranking

In the present study, the social ranking perception in competition was explored. Brain response (alpha band oscillations, EEG; hemodynamic activity, O2Hb), as well as self-perception of social ranking, cognitive performance, and personality trait (Behavioral Activation System, BAS) were considered during a competitive joint-action. Subjects were required to develop a strategy to obtain a better outcome than a competitor (C) (in term of error rate, and response time, RT). A pre-feedback (without a specific feedback on the performance) and a post-feedback condition (which reinforced the improved performance) were provided. It was found that higher-BAS participants responded in greater measure to perceived higher cognitive performance (post-feedback condition), with increased left prefrontal activity, higher ranking perception, and a better real performance (reduced RTs). These results were explained in term of increased sense of self-efficacy and social position, probably based on higher-BAS sensitivity to reinforcing conditions. In addition, the hemispheric effect in favor of the left side characterized the competitive behavior, showing an imbalance for high-BAS in comparison to low-BAS in the case of a rewarding (post-feedback) context. Therefore, the present results confirmed the significance of BAS in modulating brain responsiveness, self-perceived social position, and real performance during an interpersonal competitive action which is considered highly relevant for social status.

Placebo Analgesia Changes Alpha Oscillations Induced by Tonic Muscle Pain: EEG Frequency Analysis Including Data during Pain Evaluation

Placebo exhibits beneficial effects on pain perception in human experimental studies. Most of these studies demonstrate that placebo significantly decreased neural activities in pain modulatory brain regions and pain-evoked potentials. This study examined placebo analgesia-related effects on spontaneous brain oscillations. We examined placebo effects on four order-fixed 20-min conditions in two sessions: isotonic saline-induced control conditions (with/without placebo) followed by hypertonic saline-induced tonic muscle pain conditions (with/without placebo) in 19 subjects using continuous electroencephalography (EEG) recording. Placebo treatment exerted significant analgesic effects in 14 placebo responders, as subjective intensity of pain perception decreased. Frequency analyses were performed on whole continuous EEG data, data during pain perception rating and data after rating. The results in the first two cases revealed that placebo induced significant increases and a trend toward significant increases in the amplitude of alpha oscillation during tonic muscle pain compared to control conditions in frontal-central regions of the brain, respectively. Placebo-induced decreases in the subjective intensity of pain perception significantly and positively correlated with the increases in the amplitude of alpha oscillations during pain conditions. In conclusion, the modulation effect of placebo treatment was captured when the pain perception evaluating period was included. The strong correlation between the placebo effect on reported pain perception and alpha amplitude suggest that alpha oscillations in frontal-central regions serve as a cortical oscillatory basis of the placebo effect on tonic muscle pain. These results provide important evidence for the investigation of objective indicators of the placebo effect.

Wake High-Density Electroencephalographic Spatiospectral Signatures of Insomnia

STUDY OBJECTIVES

Although daytime complaints are a defining characteristic of insomnia, most EEG studies evaluated sleep only. We used high-density electroencephalography to investigate wake resting state oscillations characteristic of insomnia disorder (ID) at a fine-grained spatiospectral resolution.

METHODS

A case-control assessment during eyes open (EO) and eyes closed (EC) was performed in a laboratory for human physiology. Participants (n = 94, 74 female, 21-70 y) were recruited through www.sleepregistry.nl: 51 with ID, according to DSM-5 and 43 matched controls. Exclusion criteria were any somatic, neurological or psychiatric condition. Group differences in the spectral power topographies across multiple frequencies (1.5 to 40 Hz) were evaluated using permutation-based inference with Threshold-Free Cluster-Enhancement, to correct for multiple comparisons.

RESULTS

As compared to controls, participants with ID showed less power in a narrow upper alpha band (11-12.7 Hz, peak: 11.7 Hz) over bilateral frontal and left temporal regions during EO, and more power in a broad beta frequency range (16.3-40 Hz, peak: 19 Hz) globally during EC. Source estimates suggested global rather than cortically localized group differences.

CONCLUSIONS

The widespread high power in a broad beta band reported previously during sleep in insomnia is present as well during eyes closed wakefulness, suggestive of a round-the-clock hyperarousal. Low power in the upper alpha band during eyes open is consistent with low cortical inhibition and attentional filtering. The fine-grained HD-EEG findings suggest that, while more feasible than PSG, wake EEG of short duration with a few well-chosen electrodes and frequency bands, can provide valuable features of insomnia.

Attentional modulation of the inner ear: a combined otoacoustic emission and EEG study

Attending to a single stimulus in a complex multisensory environment requires the ability to select relevant information while ignoring distracting input. The underlying mechanism and involved neuronal levels of this attentional gain control are still a matter of debate. Here, we investigated the influence of intermodal attention on different levels of auditory processing in humans. It is known that the activity of the cochlear amplifier can be modulated by efferent neurons of the medial olivocochlear complex. We used distortion product otoacoustic emission (DPOAE) measurements to monitor cochlear activity during an intermodal cueing paradigm. Simultaneously, central auditory processing was assessed by electroencephalography (EEG) with a steady-state paradigm targeting early cortical responses and analysis of alpha oscillations reflecting higher cognitive control of attentional modulation. We found effects of selective attention at all measured levels of the auditory processing: DPOAE levels differed significantly between periods of visual and auditory attention, showing a reduction during visual attention, but no change during auditory attention. Primary auditory cortex activity, as measured by the auditory steady-state response (ASSR), differed between conditions, with higher ASSRs during auditory than visual attention. Furthermore, the analysis of cortical oscillatory activity revealed increased alpha power over occipitoparietal and frontal regions during auditory compared with visual attention, putatively reflecting suppression of visual processing. In conclusion, this study showed both enhanced processing of attended acoustic stimuli in early sensory cortex and reduced processing of distracting input, both at higher cortical levels and at the most peripheral level of the hearing system, the cochlea.