Theta-Alpha Connectivity in the Hippocampal-Entorhinal Circuit Predicts Working Memory Load.

Working memory (WM) maintenance relies on multiple brain regions and inter-regional communications. The hippocampus and entorhinal cortex (EC) are thought to support this operation. Besides, EC is the main gateway for information between the hippocampus and neocortex. However, the circuit-level mechanism of this interaction during WM maintenance remains unclear in humans. To address these questions, we recorded the intracranial electroencephalography from the hippocampus and EC while patients (N = 13, six females) performed WM tasks. We found that WM maintenance was accompanied by enhanced theta/alpha band (2-12 Hz) phase synchronization between the hippocampus to the EC. The Granger causality and phase slope index analyses consistently showed that WM maintenance was associated with theta/alpha band-coordinated unidirectional influence from the hippocampus to the EC. Besides, this unidirectional inter-regional communication increased with WM load and predicted WM load during memory maintenance. These findings demonstrate that WM maintenance in humans engages the hippocampal-entorhinal circuit, with the hippocampus influencing the EC in a load-dependent manner.

The neural oscillatory mechanism underlying human brain fingerprint recognition using a portable EEG acquisition device.

In recent years, brainprint recognition has emerged as a novel method of personal identity verification. Although studies have demonstrated the feasibility of this technology, some limitations hinder its further development into the society, such as insufficient efficiency (extended wear time for multi-channel EEG cap), complex experimental paradigms (more time in learning and completing experiments), and unclear neurobiological characteristics (lack of intuitive biomarkers and an inability to eliminate the impact of noise on individual differences). Overall, these limitations are due to the incomplete understanding of the underlying neural mechanisms. Therefore, this study aims to investigate the neural mechanisms behind brainwave recognition and simplify the operation process. We recorded prefrontal resting-state EEG data from 40 participants, which is followed up over nine months using a single-channel portable brainwave device. We found that portable devices can effectively and stably capture the characteristics of different subjects in the alpha band (8-13Hz) over long periods, as well as capturing their individual differences (no alpha peak, 1 alpha peak, or 2 alpha peaks). Through correlation analysis, alpha-band activity can reveal the uniqueness of the subjects compared to others within one minute. We further used a descriptive model to dissect the oscillatory and non-oscillatory components in the alpha band, demonstrating the different contributions of fine oscillatory features to individual differences (especially amplitude and bandwidth). Our study validated the feasibility of portable brainwave devices in brainwave recognition and the underlying neural oscillation mechanisms. The fine characteristics of various alpha oscillations will contribute to the accuracy of brainwave recognition, providing new insights for the development of future brainwave recognition technology.

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.

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.

Temporal expectation based on the duration variability modulates alpha oscillations during working memory retention.

While maintaining information over a delay of time, working memory (WM) also allows individuals to prepare the mnemonic contents for prospective utilisation. However, it remains unclear whether the expectation of the time of WM test could modulate neural responses during the retention interval of WM and subsequent performance. Here, we investigated whether temporal expectations based on the variability of delay duration can modulate 9-13 Hz alpha oscillations during WM retention and whether the expectation-induced alpha activity was associated with WM performance. Participants performed a retro-cueing WM task with magnetoencephalography (MEG) (Experiment 1) and a standard WM task with electroencephalography (EEG) (Experiment 2). The expectation of the timing of the WM test was manipulated by the temporal structure of the tasks with small or large variability in the delay durations. We showed that alpha oscillations during retention interval and WM performance varied with duration variability in both of the MEG and EEG experiments. The novel finding was greater alpha-power attenuation over the left frontal and parietal regions during WM retention when the duration variability was small and the test onset was predictable, compared to when the duration variability was large and the test onset was less predictable. Importantly, we observed a positive relationship in variability difference between the response benefit and alpha-power attenuation in the left posterior parietal regions at both MEG-source and EEG-electrode levels. Finally, we confirmed the behavioural benefit when a condition with a fixed delay-duration was included in a behavioural experiment (Experiment 3). When conjoined, the delay duration enables individuals to anticipate when the relevant information would be put to work, and alpha oscillations track the anticipatory states during WM maintenance.

Targeted rhythmic visual stimulation at individual participants' intrinsic alpha frequency causes selective increase of occipitoparietal BOLD-fMRI and EEG functional connectivity.

Neural oscillations in distinct frequency bands are ubiquitous in the brain and play a role in many cognitive processes. The "communication by coherence" hypothesis, poses that the synchronization through phase coupling of frequency-specific neural oscillations regulate information flow across distribute brain regions. Specifically, the posterior alpha frequency band (7-12 Hz) is thought to gate bottom-up visual information flow by inhibition during visual processing. Evidence shows that increased alpha phase coherency positively correlates with functional connectivity in resting state connectivity networks, supporting alpha mediates neural communication through coherency. However, these findings have mainly been derived from spontaneous changes in the ongoing alpha rhythm. In this study, we experimentally modulate the alpha rhythm by targeting individuals' intrinsic alpha frequency with sustained rhythmic light to investigate alpha-mediated synchronous cortical activity in both EEG and fMRI. We hypothesize increased alpha coherency and fMRI connectivity should arise from modulation of the intrinsic alpha frequency (IAF) as opposed to control frequencies in the alpha range. Sustained rhythmic and arrhythmic stimulation at the IAF and at neighboring frequencies within the alpha band range (7-12 Hz) was implemented and assessed in a separate EEG and fMRI study. We observed increased cortical alpha phase coherency in the visual cortex during rhythmic stimulation at the IAF as in comparison to rhythmic stimulation of control frequencies. In the fMRI, we found increased functional connectivity for stimulation at the IAF in visual and parietal areas as compared to other rhythmic control frequencies by correlating time courses from a set of regions of interest for the different stimulation conditions and applying network-based statistics. This suggests that rhythmic stimulation at the IAF frequency induces a higher degree of synchronicity of neural activity across the occipital and parietal cortex, which supports the role of the alpha oscillation in gating information flow during visual processing.

A neural oscillatory signature of sustained anxiety.

BACKGROUND: Anxiety is a sustained response to uncertain threats; yet few studies have explored sustained neurobiological activities underlying anxious states, particularly spontaneous neural oscillations. To address this gap, we reanalysed magnetoencephalographic (MEG) data recorded during induced anxiety to identify differences in sustained oscillatory activity between high- and low-anxiety states. METHODS: We combined data from three previous MEG studies in which healthy adults (total N = 51) were exposed to alternating periods of threat of unpredictable shock and safety while performing a range of cognitive tasks (passive oddball, mixed-saccade or stop-signal tasks). Spontaneous, band-limited, oscillatory activity was extracted from middle and late intervals of the threat and safe periods, and regional power distributions were reconstructed with adaptive beamforming. Conjunction analyses were used to identify regions showing overlapping spectral power differences between threat and safe periods across the three task paradigms. RESULTS: MEG source analyses revealed a robust and widespread reduction in beta (14-30 Hz) power during threat periods in bilateral sensorimotor cortices extending into right prefrontal regions. Alpha (8-13 Hz) power reductions during threat were more circumscribed, with notable peaks in left intraparietal sulcus and thalamus. CONCLUSIONS: Threat-induced anxiety is underpinned by a sustained reduction in spontaneous beta- and alpha-band activity in sensorimotor and parietal cortical regions. This general oscillatory pattern likely reflects a state of heightened action readiness and vigilance to cope with uncertain threats. Our findings provide a critical reference for which to identify abnormalities in cortical oscillatory activities in clinically anxious patients as well as evaluating the efficacy of anxiolytic treatments.

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.

The Analysis of Spontaneous Electroencephalogram (EEG) in Chronic Low Back Pain Patients Compared with Healthy Subjects.

Background: Quantitative electroencephalography (EEG) power spectra analysis was applied to assess brain activation during chronic pain. Although many studies have shown that there are some common characteristics among individuals suffering from various pain syndromes, the data remains inconclusive. The present study aimed to assess chronic low back pain (CLBP) based on functional brain changes with EEG in CLBP patients compared with healthy controls. Methods: Multichannel electroencephalogram data were recorded from 30 subjects with CLBP and 30 healthy controls under eye-open resting state conditions and active lumbar forward flexion, and their cortical oscillations were compared using electrode-level analysis. Data were analyzed using a pair t-test. Results: A total of 30 patients (19 men and 11 women in the case group (mean [SD] age, 35.23 [5.93] years) with 30 age and sex-match healthy controls participated in the study. A paired t-test was applied to identify whether there was any difference in the absolute and relative power of frequency spectra between CLBP patients and healthy controls. The results showed a significant increase in alpha relative power in CLBP patients compared with healthy controls in an open-eye resting state ( P < 0.050) and active lumbar forward flexion ( P < 0.050). Conclusion: The enhanced alpha relative power in CLBP patients could be relevant to attenuating sensory information gating and excessive integration of pain-related information. Increased power at the EEG seems to be one of the clinical characteristics of individuals with CLBP. EEG can be a simple and objective tool for studying the mechanisms involved in chronic pain and identifying specific characteristics of CLBP patients.

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.

Electrophysiological and behavioral correlates of cannabis use disorder.

Current research indicates deficits in cognitive function together with widespread changes in brain activity following long-term cannabis use. In particular, cannabis use has been associated with excessive spectral power of the alpha rhythm (8-12 Hz), which is also known to be modulated during attentional states. Recent neuroimaging studies have linked heavy cannabis use with structural and metabolic changes in the brain; however, the functional consequences of these changes are still not fully characterized. This study investigated the electrophysiological and behavioral correlates of cannabis dependence by comparing patients with a cannabis use disorder (CUD; N = 24) with cannabis nonuser controls (N = 24), using resting state electroencephalogram (EEG) source-imaging. In addition to evaluating mean differences between groups, we also explored whether particular EEG patterns were associated with individual cognitive-behavioral measures. First, we replicated historical findings of elevated levels of (relative) alpha rhythm in CUD patients compared with controls and located these abnormalities to mainly prefrontal cortical regions. Importantly, we observed a significant negative correlation between alpha spectral power in several cortical regions and individual attentional performance in the Go/NoGo task. Because such relationship was absent in the nonuser control group, our results suggest that reduced prefrontal cortical activation (indexed by increased relative alpha power) could be partly responsible for the reported cognitive impairments in CUD. Our findings support the use of electroencephalography as a noninvasive and cost-effective tool for biomarker discovery in substance abuse and have the potential of directly informing future intervention strategies.

Delineating between-subject heterogeneity in alpha networks with Spatio-Spectral Eigenmodes.

Between subject variability in the spatial and spectral structure of oscillatory networks can be highly informative but poses a considerable analytic challenge. Here, we describe a data-driven modal decomposition of a multivariate autoregressive model that simultaneously identifies oscillations by their peak frequency, damping time and network structure. We use this decomposition to define a set of Spatio-Spectral Eigenmodes (SSEs) providing a parsimonious description of oscillatory networks. We show that the multivariate system transfer function can be rewritten in these modal coordinates, and that the full transfer function is a linear superposition of all modes in the decomposition. The modal transfer function is a linear summation and therefore allows for single oscillatory signals to be isolated and analysed in terms of their spectral content, spatial distribution and network structure. We validate the method on simulated data and explore the structure of whole brain oscillatory networks in eyes-open resting state MEG data from the Human Connectome Project. We are able to show a wide between participant variability in peak frequency and network structure of alpha oscillations and show a distinction between occipital 'high-frequency alpha' and parietal 'low-frequency alpha'. The frequency difference between occipital and parietal alpha components is present within individual participants but is partially masked by larger between subject variability; a 10Hz oscillation may represent the high-frequency occipital component in one participant and the low-frequency parietal component in another. This rich characterisation of individual neural phenotypes has the potential to enhance analyses into the relationship between neural dynamics and a person's behavioural, cognitive or clinical state.

Neural dynamics of pain expression processing: Alpha-band synchronization to same-race pain but desynchronization to other-race pain.

Both electroencephalography and functional magnetic resonance imaging studies have revealed enhanced neural responses to perceived pain in same-race than other-race individuals. However, it remains unclear how neural responses in the sensorimotor, cognitive, and affective subsystems vary dynamically in the first few hundreds of milliseconds to generate racial ingroup favoritism in empathy for pain. We recorded magnetoencephalography signals to pain and neutral expressions of Asian and white faces from Chinese adults during judgments of racial identity of each face. We found that pain compared to neutral expressions of same-race faces induced early increased alpha oscillations in the precuneus/parietal cortices followed by increased alpha-band oscillations in the left anterior insula and temporoparietal junction. Pain compared to neutral expressions of other-race faces, however, induced early suppression of alpha-band oscillations in the bilateral sensorimotor cortices and left insular cortex. Moreover, decreased functional connectivity between the left sensorimotor cortex and left anterior insula predicted reduced subjective feelings of other-race suffering. Our results unraveled distinct patterns of modulations of neural dynamics of sensorimotor, affective, and cognitive components of empathy by interracial relationships between an observer and a target person, which provide possible brain mechanisms for understanding racial ingroup favoritism in social behavior.

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.

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.

Effect of brain alpha oscillation on the performance in laparoscopic skills simulator training.

BACKGROUND: Laparoscopic skill involves sensory processing and motor control, which is associated with high-level alpha oscillation of the brain. Neurofeedback (NF) has been reported effective in enhancing alpha oscillation. Our objectives were to assess the alpha oscillation during laparoscopic skills training, and to verify the usefulness of NF in improving the learning efficacy. METHODS: Sixty medical students without laparoscopic experience were recruited. Multi-channel electroencephalography (EEG) signals were recorded during training of peg transfer task. Training performance was assessed based on the task completion time. All subjects participated in the first experiment comprising eight training blocks and one testing block. Subjects were ranked based on performance: the top 20 subjects were classified as the good performance group and the bottom 20 subjects as the fair performance group. In the second experiment, the fair performance group were randomly divided into the NF and control groups. Spectral analysis of EEG signals was used to calculate alpha power and alpha band coherence. Training performance and EEG alpha powers were compared between the NF and control groups. RESULTS: In the first experiment, the completion time was significantly faster in the good performance group (62.5 ± 2.8 s) compared with the fair performance group (75.0 ± 5.6 s) (P < 0.05). EEG oscillations showed strong alpha power and alpha coherence in the posterior electrode clusters in the good performance group. In the second experiment, the NF group showed much stronger alpha activity power and coherence compared with the control group. Furthermore, the NF training led to a significant performance improvement from 75.1 ± 5.9 s in the first experiment to 64.3 ± 4.9 s in the second experiment (P = 0.003). CONCLUSIONS: The learning performance of laparoscopic skills varies among individuals. Subjects with good performance results had high alpha power and strong alpha coherence. The alpha enhancement NF increased alpha oscillations, leading to improved learning efficacy.

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.

Decomposing alpha and 1/f brain activities reveals their differential associations with cognitive processing speed.

Research in cognitive neuroscience has extensively demonstrated that the temporal dynamics of brain activity are associated with cognitive functioning. The temporal dynamics mainly include oscillatory and 1/f noise-like, non-oscillatory brain activities that coexist in many forms of brain activity and confound each other's variability. As such, observed functional associations of narrowband oscillations might have been confounded with the broadband 1/f component. Here, we investigated the relationship between resting-state EEG activity and the efficiency of cognitive functioning in N = 180 individuals. We show that 1/f brain activity plays an essential role in accounting for between-person variability in cognitive speed - a relationship that can be mistaken as originating from brain oscillations using conventional power spectrum analysis. At first glance, the power of alpha oscillations appeared to be predictive of cognitive speed. However, when dissociating pure alpha oscillations from 1/f brain activity, only the 1/f predicted cognitive speed, whereas the predictive power of alpha vanished. With this highly powered study, we disambiguate the functional relevance of the 1/f power law pattern in resting state neural activities and substantiate the necessity of isolating the 1/f component from oscillatory activities when studying the functional relevance of spontaneous brain activities.

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.