Individual Alpha Frequency Research Articles

What a single electroencephalographic (EEG) channel can tell us about Alzheimer's disease patients with mild cognitive impairment

AbstractBackgroundAbnormalities in the neurophysiological oscillatory mechanisms generating dominant resting‐state eyes closed electroencephalographic (rsEEG) rhythms portray the Alzheimer’s disease (AD) continuum, from the preclinical to the dementia stage. Here, we tested whether these abnormalities may be reproducible by analyzing the rsEEG signals acquired in bipolar configuration with a montage consisting of only four centro‐parietal and parieto‐occipital channels (C3‐P3, C4‐P4, P3‐O1, and P4‐O2) in patients with mild cognitive impairment (MCI) due to AD (ADMCI).MethodTo evaluate the study hypotheses, clinical, neuropsychological, anthropometric, genetic, cerebrospinal fluid (CSF), MRI, and rsEEG data in 70 Nold and 75 ADMCI subjects from an international archive were used in the present study. The subgroups were matched for age, gender, and education. In all subjects, rsEEG recordings lasted about 3‐5 minutes. The rsEEG data were recorded with a sampling frequency of 128‐512 Hz and related antialiasing bandpass between 0.01 Hz and 60‐100 Hz. Electrode montage included 19 scalp monopolar sensors placed following 10‐20 System. The rsEEG rhythms were investigated at individual delta, theta, and alpha frequency bands as well as fixed beta (14‐30 Hz) and gamma (30‐40 Hz) bands.ResultResults confirmed previous evidence about the abnormalities of the delta, theta, and alpha rhythms in ADMCI patients compared to Nold subjects. Moreover, as compared to the Nold group, the ADMCI group showed increased delta power density and decreased alpha power density at the C3‐P3, C4‐P4, P3‐O1, and P4‐O2 bipolar channels. Increased theta power density for ADMCI patients was observed only at the C3‐P3 bipolar channel. Best classification accuracy between the ADMCI and Nold individuals reached 81% (area under the receiver operating characteristic curve) using Alpha2/Theta power density computed at the C3‐P3 bipolar channel.ConclusionThe current findings provide evidence in the potential use of rsEEG low‐channel portable devices as a topographic biomarker of cognitive decline within the extensive screening of in elderly population at risk of developing AD‐ or other dementia‐related disorders. Moreover, the confirmation of this hypothesis would have exciting applications in the framework of telehealth home monitoring of global brain functions.

Brain neural synchronization mechanisms are affected by aging in cognitively unimpaired seniors and patients with Alzheimer’s disease and mild cognitive impairment

AbstractBackgroundThe resting state eyes‐closed electroencephalographic (rsEEG) alpha (8‐12 Hz) rhythms reflect cortical neural synchronization mechanisms underpinning the inhibition of sensory, cognitive, and motor areas in parietal, temporal, and occipital cortex during a condition of low vigilance. Here we tested the hypothesis that age may diversely affect rsEEG alpha (8‐12 Hz) rhythms recorded in normal elderly (Nold) seniors and patients with Alzheimer’s disease and mild cognitive impairment (ADMCI).MethodClinical, magnetic resonance imaging (MRI) and rsEEG datasets in 63 ADMCI and 60 Nold individuals were taken from an international archive. The rsEEG rhythms were investigated at individual delta, theta, and alpha frequency bands as well as fixed beta (14‐30 Hz) and gamma (30‐40 Hz) bands. Each group was stratified into three subgroups based on age ranges (i.e., tertiles).ResultAs compared to the younger Nold subgroups, the older one showed greater reductions in the rsEEG alpha rhythms with major topographical effects in posterior regions (Figure 1). On the contrary, in relation to the younger ADMCI subgroups, the older one displayed lesser reduction in those rhythms (Figure 1). Furthermore, a decrease in the total grey matter (GM) volume and total cortical thickness as well as an increase in the white matter (WM) hypointensity were found in the older ADMCI subgroups compared to the younger ADMCI subgroups (Figure 2).ConclusionThe results of the present study suggest that in Nold seniors, the aging factor may significantly affect neurophysiological brain neural synchronization mechanisms underpinning the generation of dominant rsEEG alpha rhythms. In contrast, rsEEG alpha rhythms in ADMCI patients may be more affected by the disease variants, with more deleterious effects observed in early‐ than the late‐onset ADMCI patients. In the ADMCI patients, the mere effects of the aging factor may be hidden by dysfunctions in subcortical structures, including the cholinergic basal forebrain and thalamus.

Day-to-Day Individual Alpha Frequency Variability Measured by a Mobile EEG Device Relates to Anxiety.

The individual alpha frequency (IAF) has previously been identified as a unique neural signature within the 8-12 Hz alpha frequency band. However, the day-to-day variability of this feature is unknown. To accomplish this, healthy participants recorded their own brain activity daily at home using the Muse 2 headband, a low-cost consumer-grade mobile electroencephalography (EEG) device. Resting-state recordings of all participants using a high-density (HD) EEG were also collected in lab before and after the at-home data collection period. We found that the IAF extracted from the Muse 2 was comparable to that of location-matched HD-EEG electrodes. No significant difference was found between these IAF values before and after the at-home recording period for the HD-EEG device. Similarly, there was also no statistically significant difference between the beginning and end of the at-home recording period for the Muse 2 headband over one month. Despite the group-level stability of IAF, the individual-level day-to-day IAF variability carried mental health-relevant information: exploratory analyses revealed a relationship between IAF day-to-day variability and trait anxiety. We also noted that the IAF systematically varied across the scalp and although the Muse 2 electrodes do not cover the occipital lobe where alpha oscillations were the strongest, IAFs measured in the temporal lobe and occipital lobe were strongly correlated. Altogether, these results show that mobile EEG devices are useful for studying IAF variability. The relationship between day-to-day variability of region-specific IAF and the dynamics of psychiatric symptoms, particularly anxiety, should be further investigated.

Individual alpha frequency appears unrelated to the latency of early visual responses.

A large body of work has linked neural oscillations in the alpha-band (8-13 Hz) to visual perceptual outcomes. In particular, studies have found that alpha phase prior to stimulus onset predicts stimulus detection, and sensory responses and that the frequency of alpha can predict temporal properties of perception. These findings have bolstered the idea that alpha-band oscillations reflect rhythmic sampling of visual information, however the mechanisms of this are unclear. Recently two contrasting hypotheses have been proposed. According to the rhythmic perception account, alpha oscillations impose phasic inhibition on perceptual processing and primarily modulate the amplitude or strength of visual responses and thus the likelihood of stimulus detection. On the other hand, the discrete perception account proposes that alpha activity discretizes perceptual inputs thereby reorganizing the timing (not only the strength) of perceptual and neural processes. In this paper, we sought neural evidence for the discrete perception account by assessing the correlation between individual alpha frequencies (IAF) and the latency of early visual evoked event-related potential (ERP) components. If alpha cycles were responsible for shifting neural events in time, then we may expect higher alpha frequencies to be associated with earlier afferent visual ERPs. Participants viewed large checkerboard stimuli presented to either the upper or lower visual field that were designed to elicit a large C1 ERP response (thought to index feedforward primary visual cortex activation). We found no reliable correlation between IAF and the C1 latency, or subsequent ERP component latencies, suggesting that the timing of these visual-evoked potentials was not modulated by alpha frequency. Our results thus fail to find evidence for discrete perception at the level of early visual responses but leave open the possibility of rhythmic perception.

Age related changes and sex related differences of functional brain networks in childhood: A high-density EEG study

ObjectiveThe aim of this study was to explore functional network age-related changes and sex-related differences during the early lifespan with a high-density resting state electroencephalography (rs-EEG). MethodsWe analyzed two data sets of high-density rs-EEG in healthy children and adolescents. We recorded a 64-channel EEG and calculated functional connectomes in 27 participants aged 5–18 years. To validate our results, we used publicly available data and calculated functional connectomes in another 86 participants aged 6–18 years from a 128-channel rs-EEG. We were primarily interested in alpha frequency band, but we also analyzed theta and beta frequency bands. ResultsWe observed age-related increase of characteristic path, clustering coefficient and interhemispheric strength in the alpha frequency band of both data sets and in the beta frequency band of the larger validation data set. Age-related increase of global efficiency was seen in the theta band of the validation data set and in the alpha band of the test data set. Increase in small worldness was observed only in the alpha frequency band of the test data set. We also observed an increase of individual peak alpha frequency with age in both data sets. Sex-related differences were only observed in the beta frequency band of the larger validation data set, with females having higher values than same aged males. ConclusionsFunctional brain networks show indices of higher segregation, but also increasing global integration with maturation. Age-related changes are most prominent in the alpha frequency band. SignificanceTo the best of our knowledge, our study was the first to analyze maturation related changes and sex-related differences of functional brain networks with a high-density EEG and to compare functional connectomes generated from two diverse high-density EEG data sets. Understanding the age-related changes and sex-related differences of functional brain networks in healthy children and adolescents is crucial for identifying network abnormalities in different neurologic and psychiatric conditions, with the aim to identify possible markers for prognosis and treatment.

Test-retest reliability of resting-state EEG in young and older adults.

The quantification of resting-state electroencephalography (EEG) is associated with a variety of measures. These include power estimates at different frequencies, microstate analysis, and frequency-resolved source power and connectivity analyses. Resting-state EEG metrics have been widely used to delineate the manifestation of cognition and to identify psychophysiological indicators of age-related cognitive decline. The reliability of the utilized metrics is a prerequisite for establishing robust brain-behavior relationships and clinically relevant indicators of cognitive decline. To date, however, test-retest reliability examination of measures derived from resting human EEG, comparing different resting-state measures between young and older participants, within the same adequately powered dataset, is lacking. The present registered report examined test-retest reliability in a sample of 95 young (age range: 20-35 years) and 93 older (age range: 60-80 years) participants. A good-to-excellent test-retest reliability was confirmed in both age groups for power estimates on both scalp and source levels as well as for the individual alpha peak power and frequency. Partial confirmation was observed for hypotheses stating good-to-excellent reliability of microstates measures and connectivity. Equal levels of reliability between the age groups were confirmed for scalp-level power estimates and partially so for source-level power and connectivity. In total, five out of the nine postulated hypotheses were empirically supported and confirmed good-to-excellent reliability of the most commonly reported resting-state EEG metrics.

The impact of conversational interaction on users’ cognitive absorption in mobile news reading context: evidence from EEG

ABSTRACT From the perspective of the user experience of media products, the study primarily focuses on the influence of users’ interaction mode on cognitive absorption. Specifically, 80 participants were recruited and randomly assigned to different interactive modes: a conversational interactive news interface and a webpage-based interactive news interface. They needed to be recorded with an EEG during the interaction and completion of the cognitive absorption (CA) scale after the interaction. The results demonstrated that there were significant differences in CA between the webpage-based interaction group and the conversational interaction group. Meanwhile, the PSD of theta and delta bands under the conversational interaction group appeared to be significantly higher. Besides, the frontal EEG asymmetry in the conversational interaction group was significantly higher than in the webpage-based interaction group. In contrast, the individual alpha frequency of the webpage-based interaction group was higher than that of the conversational interaction group. These results suggest that conversational interaction reduces the user’s reading difficulty while also reduces the cognitive load in the process of task. This helps improve user’s level of being immersed, enjoyment, sense of control, and curiosity while also improving users’ cognitive absorption as they also exhibit stronger positive emotional experiences.

Neural and cognitive correlates of performance in dynamic multi-modal settings

The endeavour to understand human cognition has largely relied upon investigation of task-related brain activity. However, resting-state brain activity can also offer insights into individual information processing and performance capabilities. Previous research has identified electroencephalographic resting-state characteristics (most prominently: the individual alpha frequency; IAF) that predict cognitive function. However, it has largely overlooked a second component of electrophysiological signals: aperiodic 1/ƒ activity. The current study examined how both oscillatory and aperiodic resting-state EEG measures, alongside traditional cognitive tests, can predict performance in a dynamic and complex, semi-naturalistic cognitive task. Participants’ resting-state EEG was recorded prior to engaging in a Target Motion Analysis (TMA) task in a simulated submarine control room environment (CRUSE), which required participants to integrate dynamically changing information over time. We demonstrated that the relationship between IAF and cognitive performance extends from simple cognitive tasks (e.g., digit span) to complex, dynamic measures of information processing. Further, our results showed that individual 1/ƒ parameters (slope and intercept) differentially predicted performance across practice and testing sessions, whereby flatter slopes and higher intercepts were associated with improved performance during learning. In addition to the EEG predictors, we demonstrate a link between cognitive skills most closely related to the TMA task (i.e., spatial imagery) and subsequent performance. Overall, the current study highlights (1) how resting-state metrics – both oscillatory and aperiodic - have the potential to index higher-order cognitive capacity, while (2) emphasising the importance of examining these electrophysiological components within more dynamic settings and over time.

Alpha power modulation with tACS: a customized therapeutic approach

Abstract Among other electrophysiological biomarkers, power reduction in the alpha frequency band (8-12 Hz) is characteristic of Alzheimer’s Disease (AD). Restoring power in this band could help improve the performance of related functional networks and the cognitive state in AD patients. Transcranial alternate current stimulation (tACS) stands as a promising tool in this regard, given its capacity to entrain neural activity at a particular frequency. 27 healthy participants with ages ranging from (22 to 55 years/ 32.80 ± 8.52 ) were recruited for this study. After being randomly assigned to verum or sham group, each participant was stimulated through tACS at the Cz and Oz electrodes at his own Individual Alpha Frequency (IAF) for 20 minutes. The neurophysiological activity of each participant was initially captured by two successive 5-minute eyes-closed resting state MEG recordings, with a 10-minute time interval between the two sessions. After stimulation, a third MEG recording was extracted to measure the effects. After performing the CBPT analysis, the tACS group showed an increase of alpha power in a cluster of bilateral frontal, temporal and occipital cortical sources (p<0.01). Research Category and Technology and Methods Clinical Research: 5. Other Transcranial Electrical Stimulation (tES) Keywords: tACS, MCI, Alfa, Neurostimulation

Is it the frequency, cumulative dose, or both? A prospective study of the excitability enhancing effects of tACS at individual alpha or beta frequency

Is it the frequency, cumulative dose, or both? A prospective study of the excitability enhancing effects of tACS at individual alpha or beta frequency

Yield of EEG features as markers of disease severity in amyotrophic lateral sclerosis: a pilot study

Objective To clarify the role of electroencephalography (EEG) as a promising marker of severity in amyotrophic lateral sclerosis (ALS). We characterized the brain spatio-temporal patterns activity at rest by means of both spectral band powers and EEG microstates and correlated these features with clinical scores. Methods Eyes closed EEG was acquired in 15 patients with ALS and spectral band power was calculated in frequency bands, defined on the basis of individual alpha frequency (IAF): delta-theta band (1–7 Hz); low alpha (IAF − 2 Hz − IAF); high alpha (IAF − IAF + 2 Hz); beta (13 − 25 Hz). EEG microstate metrics (duration, occurrence, and coverage) were also evaluated. Spectral band powers and microstate metrics were correlated with several clinical scores of disabilities and disease progression. As a control group, 15 healthy volunteers were enrolled. Results The beta-band power in motor/frontal regions was higher in patients with higher disease burden, negatively correlated with clinical severity scores and positively correlated with disease progression. Overall microstate duration was longer and microstate occurrence was lower in patients than in controls. Longer duration was correlated with a worse clinical status. Conclusions Our results showed that beta-band power and microstate metrics may be good candidates of disease severity in ALS. Increased beta and longer microstate duration in clinically worse patients suggest a possible impairment of both motor and non-motor network activities to fast modify their status. This can be interpreted as an attempt in ALS patients to compensate the disability but resulting in an ineffective and probably maladaptive behavior.

One-year-later spontaneous EEG features predict visual exploratory human phenotypes

During visual exploration, eye movements are controlled by multiple stimulus- and goal-driven factors. We recently showed that the dynamics of eye movements –how/when the eye move– during natural scenes’ free viewing were similar across individuals and identified two viewing styles: static and dynamic, characterized respectively by longer or shorter fixations. Interestingly, these styles could be revealed at rest, in the absence of any visual stimulus. This result supports a role of intrinsic activity in eye movement dynamics. Here we hypothesize that these two viewing styles correspond to different spontaneous patterns of brain activity. One year after the behavioural experiments, static and dynamic viewers were called back to the lab to record high density EEG activity during eyes open and eyes closed. Static viewers show higher cortical inhibition, slower individual alpha frequency peak, and longer memory of alpha oscillations. The opposite holds for dynamic viewers. We conclude that some properties of spontaneous activity predict exploratory eye movement dynamics during free viewing.

What a Single Electroencephalographic (EEG) Channel Can Tell us About Alzheimer's Disease Patients With Mild Cognitive Impairment.

Abnormalities in cortical sources of resting-state eyes closed electroencephalographic (rsEEG) rhythms recorded by hospital settings (10-20 montage) with 19 scalp electrodes characterized Alzheimer's disease (AD) from preclinical to dementia stages. An intriguing rsEEG application is the monitoring and evaluation of AD progression in large populations with few electrodes in low-cost devices. Here we evaluated whether the above-mentioned abnormalities can be observed from fewer scalp electrodes in patients with mild cognitive impairment due to AD (ADMCI). Clinical and rsEEG data acquired in hospital settings (10-20 montage) from 75 ADMCI participants and 70 age-, education-, and sex-matched normal elderly controls (Nold) were available in an Italian-Turkish archive (PDWAVES Consortium; www.pdwaves.eu). Standard spectral fast fourier transform (FFT) analysis of rsEEG data for individual delta, theta, and alpha frequency bands was computed from 6 monopolar scalp electrodes to derive bipolar C3-P3, C4-P4, P3-O1, and P4-O2 markers. The ADMCI group showed increased delta and decreased alpha power density at the C3-P3, C4-P4, P3-O1, and P4-O2 bipolar channels compared to the Nold group. Increased theta power density for ADMCI patients was observed only at the C3-P3 bipolar channel. Best classification accuracy between the ADMCI and Nold individuals reached 81% (area under the receiver operating characteristic curve) using Alpha2/Theta power density computed at the C3-P3 bipolar channel. Standard rsEEG power density computed from six posterior bipolar channels characterized ADMCI status. These results may pave the way toward diffuse clinical applications in health monitoring of dementia using low-cost EEG systems with a strict number of electrodes in lower- and middle-income countries.

Transcranial alternating current stimulation ameliorates emotional attention through neural oscillations modulation

BackgroundNumerous clinical reports have suggested that psychopathy like schizophrenia, anxiety and depression is accompanied by early attentional abnormalities in emotional processing. Recently, the efficacy of transcranial alternating current stimulation (tACS) in changing emotional functioning has been repeatedly observed and demonstrated a causal relationship between endogenous oscillations and emotional processing.AimsUp to now, tACS effects on emotional attention have not yet been tested. To assess such ability, we delivered active-tACS at individual alpha frequency (IAF), 10 Hz or sham-tACS for 7 consecutive days in the bilaterally dorsolateral prefrontal cortex (dlPFC) to totally 79 healthy participants.ResultsIAF-tACS group showed significant alpha entrainment at-rest, especially in open state around stimulation area and showed an obvious advantage compared to 10 Hz-tACS. Event-related potential revealed a significant larger P200 amplitude after active-tACS and IAF group showed wider range of emotions than 10 Hz-tACS, indicating the attentional improvement in facial emotion processing. A notable positive correlation between alpha power and P200 amplitude provided an electrophysiological interpretation regarding the role of tACS in emotional attention modulation instead of somatosensory effects.ConclusionThese results support a seminal outcome for the effect of IAF-tACS on emotional attention modulation, demonstrating a feasible and individual-specific therapy for neuropsychiatric disorders related to emotion processing, especially regarding oscillatory disturbances.

Outcomes from Individual Alpha Frequency Guided Repetitive Transcranial Magnetic Stimulation in Children with Autism Spectrum Disorder – A Retrospective Chart Review

Aims and objectives: Individual alpha frequency (IAF) is a biomarker of neurophysiological functioning. The IAF-guided repetitive transcranial magnetic stimulation (α-rTMS) is increasingly explored in diverse neurological conditions. However, there is limited data on the efficacy and safety of α-rTMS in children with autism spectrum disorder (ASD). Materials and methods: The IAF, childhood autism rating scale (CARS), Pediatric Quality of Life Inventory 4.0 (PedsQLTM 4.0), and semi-structured interview data of patients that received 19 α-rTMS sessions (4 weeks) were aggregated and analysed using paired student t-test and descriptive method. Results: Data were retrieved from 28 patients (26 males, aged 3-9years (mean ± SD age: 6.1 ± 1.8years)). The post-α-rTMS data shows a significant improvement in IAF (9.4 Hz; p ≤ 0.025) towards 10 Hz. The CARS and PedsQLTM 4.0 surveys indicate that patients’ ASD symptoms and quality of life improved significantly. Specifically, reports from semi-structured interviews suggest improved sleep trouble – the most significant comorbidity. The experiences of minor side effects such as hyperactivity resolved within two hours following α-rTMS sessions. Conclusion: This study presents evidence on the efficacy and safety of α-rTMS in improving ASD symptoms, quality of life and comorbid sleep troubles in children. However, these findings should be interpreted as preliminary pending the presentation of double-blind, randomised clinical trials.

Learning at your brain's rhythm: individualized entrainment boosts learning for perceptual decisions.

Training is known to improve our ability to make decisions when interacting in complex environments. However, individuals vary in their ability to learn new tasks and acquire new skills in different settings. Here, we test whether this variability in learning ability relates to individual brain oscillatory states. We use a visual flicker paradigm to entrain individuals at their own brain rhythm (i.e. peak alpha frequency) as measured by resting-state electroencephalography (EEG). We demonstrate that this individual frequency-matched brain entrainment results in faster learning in a visual identification task (i.e. detecting targets embedded in background clutter) compared to entrainment that does not match an individual's alpha frequency. Further, we show that learning is specific to the phase relationship between the entraining flicker and the visual target stimulus. EEG during entrainment showed that individualized alpha entrainment boosts alpha power, induces phase alignment in the pre-stimulus period, and results in shorter latency of early visual evoked potentials, suggesting that brain entrainment facilitates early visual processing to support improved perceptual decisions. These findings suggest that individualized brain entrainment may boost perceptual learning by altering gain control mechanisms in the visual cortex, indicating a key role for individual neural oscillatory states in learning and brain plasticity.

What a single electroencephalographic (EEG) channel can tell us about patients with dementia due to Alzheimer's disease

Abnormalities in cortical sources of resting-state eyes-closed electroencephalographic (rsEEG) rhythms recorded by hospital settings (10–20 electrode montage) with 19 scalp electrodes provide useful markers of neurophysiological dysfunctions in the vigilance regulation in patients with Alzheimer's disease dementia (ADD). Here we tested whether these markers may be effective from a few scalp electrodes towards the use of low-cost recording devices.Clinical and rsEEG data acquired in hospital settings (10–20 electrode montage) from 88 ADD participants and 68 age-, education-, and sex-matched normal elderly controls (Nold) were available in an international Eurasian database. Standard spectral FFT analysis of rsEEG data for individual delta, theta, and alpha frequency bands was from C3-P3, C4-P4, P3-O1, and P4-O2 bipolar channels.As compared to the Nold group, the ADD group showed increased delta, theta, low-frequency alpha power density and decreased high-frequency alpha power density at all those bipolar channels. The highest classification accuracy between the ADD and Nold individuals reached 90 % (area under the receiver operating characteristic curve) using Alpha2/Theta power density computed at the C3-P3 bipolar channel.Standard rsEEG power density computed from a few posterior bipolar channels successfully classified Nold and ADD individuals, thus encouraging a massive prescreening of neurophysiological mechanisms underpinning the vigilance dysregulation in underserved old seniors.

Task-related, intrinsic oscillatory and aperiodic neural activity predict performance in naturalistic team-based training scenarios

Effective teams are essential for optimally functioning societies. However, little is known regarding the neural basis of two or more individuals engaging cooperatively in real-world tasks, such as in operational training environments. In this exploratory study, we recruited forty individuals paired as twenty dyads and recorded dual-EEG at rest and during realistic training scenarios of increasing complexity using virtual simulation systems. We estimated markers of intrinsic brain activity (i.e., individual alpha frequency and aperiodic activity), as well as task-related theta and alpha oscillations. Using nonlinear modelling and a logistic regression machine learning model, we found that resting-state EEG predicts performance and can also reliably differentiate between members within a dyad. Task-related theta and alpha activity during easy training tasks predicted later performance on complex training to a greater extent than prior behaviour. These findings complement laboratory-based research on both oscillatory and aperiodic activity in higher-order cognition and provide evidence that theta and alpha activity play a critical role in complex task performance in team environments.

Shifting Baselines: Longitudinal Reductions in EEG Beta Band Power Characterize Resting Brain Activity with Intensive Meditation

ObjectivesA core assumption of meditation training is that cognitive capacities developed during formal practice will transfer to other contexts or activities as expertise develops over time. This implies that meditation training might influence domain-general neurocognitive systems, the spontaneous activity of which should be reflected in the dynamics of the resting brain. Previous research has demonstrated that 3 months of meditation training led to reductions in EEG beta band power during mindfulness of breathing practice. The current study extends these findings to ask whether concomitant shifts in power are observed during 2 min of eyes closed rest, when participants are not explicitly engaged in formal meditation.MethodsExperienced meditation practitioners were randomly assigned to practice 3 months of focused attention meditation in a residential retreat, or to serve as waitlist controls. The waitlist controls later completed their own 3-month retreat. Permutation-based cluster analysis of 88-channel resting EEG data was used to test for spectral changes in spontaneous brain activity over the course of the retreats.ResultsLongitudinal reductions in EEG power in the beta frequency range were identified and replicated across the two independent training periods. Less robust reductions were also observed in the high alpha frequency range, and in individual peak alpha frequency. These changes closely mirror those previously observed during formal mindfulness of breathing meditation practice.ConclusionsThese findings suggest that the neurocognitive effects of meditation training can extend beyond the bounds of formal practice, influencing the spontaneous activity of the resting brain. Rather than serving as an invariant baseline, resting states might carry meaningful training-related effects, blurring the line between state and trait change.

Visual working memory recruits two functionally distinct alpha rhythms in posterior cortex.

Oscillatory activity in the human brain is dominated by posterior alpha oscillations (8–14 Hz), which have been shown to be functionally relevant in a wide variety of cognitive tasks. Although posterior alpha oscillations are commonly considered a single oscillator anchored at an individual alpha frequency (∼10 Hz), previous work suggests that individual alpha frequency reflects a spatial mixture of different brain rhythms. In this study, we assess whether independent component analysis (ICA) can disentangle functionally distinct posterior alpha rhythms in the context of visual short-term memory retention. Magnetoencephalography (MEG) was recorded in 33 subjects while performing a visual working memory task. Group analysis at sensor level suggested the existence of a single posterior alpha oscillator that increases in power and decreases in frequency during memory retention. Conversely, single-subject analysis of independent components revealed the existence of two dissociable alpha rhythms: one that increases in power during memory retention (Alpha1) and another one that decreases in power (Alpha2). Alpha1 and Alpha2 rhythms were differentially modulated by the presence of visual distractors (Alpha1 increased in power while Alpha2 decreased) and had an opposite relationship with accuracy (positive for Alpha1 and negative for Alpha2). In addition, Alpha1 rhythms showed a lower peak frequency, a narrower peak width, a greater relative peak amplitude and a more central source than Alpha2 rhythms. Together, our results demonstrate that modulations in posterior alpha oscillations during short-term memory retention reflect the dynamics of at least two distinct brain rhythms with different functions and spatiospectral characteristics.