Peak individual alpha frequency qualifies as a stable neurophysiological trait marker in healthy younger and older adults

Individual posterior alpha rhythms and cognitive reserve as possible early prognostic markers in people with subjective memory complaints

Subjective memory complaints (SMCs) are a memory disorder that often precedes mild cognitive impairment (MCI) or Alzheimer's disease (AD). Both individual alpha rhythms and cognitive reserve (CR) represent key features of SMCs and provide useful tools to characterize and predict the course of the disorder. We studied whether older people with SMCs may also present some abnormal resting state electroencephalogram (rsEEG) alpha rhythms, and whether alpha rhythms are associated with CR. To do this, eyes-closed rsEEG were recorded in 68 older people with and without SMCs. The individual alpha indexes alpha/theta transition frequency (TF) and individual alpha frequency peak (IAFp) were computed. TF and IAFp were also used to determine the alpha1, alpha2, and alpha3 power frequency. Results indicated no differences in TF or IAFp between older people with SMCs and controls. The SMCs group showed a reduction in alpha3 power in comparison with controls. Specifically, women with SMCs were characterized by a significant decrease in alpha3 power compared to control women. Furthermore, only in SMCs group, greater CR was associated with slow IAFp. In sum, these results suggest that TF and IAFp are two stable indexes that are not influenced by the presence of SMCs. However, the reduction in alpha3, as observed in women with SMCs, shows an abnormal posterior rsEEG at alpha power. Finally, the compensatory mechanisms of CR appear to interact with the neurophysiological mechanisms that underlie the regulation of alpha rhythms.

Aperiodic component of EEG power spectrum and cognitive performance are modulated by education in aging

Recent studies have shown a growing interest in the so-called "aperiodic" component of the EEG power spectrum, which describes the overall trend of the whole spectrum with a linear or exponential function. In the field of brain aging, this aperiodic component is associated both with age-related changes and performance on cognitive tasks. This study aims to elucidate the potential role of education in moderating the relationship between resting-state EEG features (including aperiodic component) and cognitive performance in aging. N = 179 healthy participants of the "Leipzig Study for Mind-Body-Emotion Interactions" (LEMON) dataset were divided into three groups based on age and education. Older adults exhibited lower exponent, offset (i.e. measures of aperiodic component), and Individual Alpha Peak Frequency (IAPF) as compared to younger adults. Moreover, visual attention and working memory were differently associated with the aperiodic component depending on education: in older adults with high education, higher exponent predicted slower processing speed and less working memory capacity, while an opposite trend was found in those with low education. While further investigation is needed, this study shows the potential modulatory role of education in the relationship between the aperiodic component of the EEG power spectrum and aging cognition.

Fungal Saprotrophic Promotion and Plant Pathogenic Suppression under Ditch-Buried Straw Return with Appropriate Burial Amount and Depth

Fungi as heterotrophs are key participants in the decomposition of organic materials and the transformation of nutrients in agroecosystems. Ditch-buried straw return as a novel conservation management strategy can improve soil fertility and alter hydrothermal processes. However, how ditch-buried straw return strategies affect the soil fungal community is still unclear. Herein, a 7-year field trial was conducted to test the influences of burial depth (0, 10, 20, 30, and 40 cm) and the amount of ditch-buried straw (half, full, double) on the diversity, composition, and predicted functions of a soil fungal community, as well as the activities of carbon-degraded enzymes. Under the full amount of straw burial, the abundance of phylum Ascomycota was 7.5% higher as compared to other burial amount treatments. This further increased the activity of cellobiohydrolase by 32%, as revealed by the positive correlation between Ascomycota and cellobiohydrolase. With deeper straw burial, however, the abundance of Ascomycota and β-D-glucopyranoside activity decreased. Moreover, genus Alternaria and Fusarium increased while Mortierella decreased with straw burial amount and depth. FUNgild prediction showed that plant fungal pathogens were 1- to 2-fold higher, whilst arbuscular mycorrhizal fungi were 64% lower under straw buried with double the amount and at a depth of 40 cm. Collectively, these findings suggest that ditch-buried straw return with a full amount and buried at a depth less than 30 cm could improve soil nutrient cycles and health and may be beneficial to subsequent crop production.

Differential roles of brain oscillations in numerical processing: evidence from resting-state EEG and mental number line

Recent works point to the importance of emotions in special-numerical associations. There remains a notable gap in understanding the electrophysiological underpinnings of such associations. Exploring resting-state (rs) EEG, particularly in frontal regions, could elucidate emotional aspects, while other EEG measures might offer insights into the cognitive dimensions correlating with behavioral performance. The present work investigated the relationship between rs-EEG measures (emotional and cognitive traits) and performance in the mental number line (MNL). EEG activity in theta (3-7 Hz), alpha (8-12 Hz, further subdivided into low-alpha and high-alpha), sensorimotor rhythm (SMR, 13-15 Hz), beta (16-25 Hz), and high-beta/gamma (28-40 Hz) bands was assessed. 76 university students participated in the study, undergoing EEG recordings at rest before engaging in a computerized number-to-position (CNP) task. Analysis revealed significant associations between frontal asymmetry, specific EEG frequencies, and MNL performance metrics (i.e., mean direction bias, mean absolute error, and mean reaction time). Notably, theta and beta asymmetries correlated with direction bias, while alpha peak frequency (APF) and beta activity related to absolute errors in numerical estimation. Moreover, the study identified significant correlations between relative amplitude indices (i.e., theta/beta ratio, theta/SMR ratio) and both absolute errors and reaction times (RTs). Our findings offer novel insights into the emotional and cognitive aspects of EEG patterns and their links to MNL performance.

Peak alpha frequency in schizophrenia, bipolar disorder, and healthy volunteers: Associations with visual information processing and cognition

BACKGROUND

Schizophrenia (SCZ) and bipolar disorder (BD) are associated with information processing abnormalities, including visual perceptual and cognitive impairments, that impact daily functioning. Recent work in healthy samples suggests that peak alpha frequency (PAF) is an electrophysiological index of visual information processing speed that is also correlated with cognitive ability. There is evidence that PAF is slowed in SCZ, but it remains unclear whether PAF is reduced in BD, or if slower PAF is associated with impaired visual perception and cognition in these clinical disorders.

METHODS

The current study recorded resting-state brain activity (both eyes open and closed) with electroencephalography (EEG) in 90 SCZ participants, 62 BD participants, and 69 healthy controls. Most participants also performed a visual perception task (backward masking) and cognitive testing (MATRICS Consensus Cognitive Battery).

RESULTS

We replicated previous findings of reduced PAF in SCZ compared with healthy controls. In contrast, PAF in BD did not significantly differ from healthy controls. Further, PAF was significantly correlated with performance on the perceptual and cognitive measures in SCZ, but not BD. PAF was also correlated with visual perception in the healthy control group, and showed a trend-level correlation with cognition.

CONCLUSIONS

Together, these results suggest that PAF deficits characterize SCZ, but not BD, and that individual differences in PAF relate to abnormalities in visual information processing and cognition in SCZ.

Augmenting complex and dynamic performance through mindfulness-based cognitive training: An evaluation of training adherence, trait mindfulness, personality and resting-state EEG

Human performance applications of mindfulness-based training have demonstrated its utility in enhancing cognitive functioning. Previous studies have illustrated how these interventions can improve performance on traditional cognitive tests, however, little investigation has explored the extent to which mindfulness-based training can optimise performance in more dynamic and complex contexts. Further, from a neuroscientific perspective, the underlying mechanisms responsible for performance enhancements remain largely undescribed. With this in mind, the following study aimed to investigate how a short-term mindfulness intervention (one week) augments performance on a dynamic and complex task (target motion analyst task; TMA) in young, healthy adults (n = 40, age range = 18-38). Linear mixed effect modelling revealed that increased adherence to the web-based mindfulness-based training regime (ranging from 0-21 sessions) was associated with improved performance in the second testing session of the TMA task, controlling for baseline performance. Analyses of resting-state electroencephalographic (EEG) metrics demonstrated no change across testing sessions. Investigations of additional individual factors demonstrated that enhancements associated with training adherence remained relatively consistent across varying levels of participants' resting-state EEG metrics, personality measures (i.e., trait mindfulness, neuroticism, conscientiousness), self-reported enjoyment and timing of intervention adherence. Our results thus indicate that mindfulness-based cognitive training leads to performance enhancements in distantly related tasks, irrespective of several individual differences. We also revealed nuances in the magnitude of cognitive enhancements contingent on the timing of adherence, regardless of total volume of training. Overall, our findings suggest that mindfulness-based training could be used in a myriad of settings to elicit transferable performance enhancements.

Lower individual alpha frequency in individuals with chronic low back pain and fear of movement

ABSTRACT

Significant progress has been made in linking measures of individual alpha frequency (IAF) and pain. A lower IAF has been associated with chronic neuropathic pain and with an increased sensitivity to pain in healthy young adults. However, the translation of these findings to chronic low back pain (cLBP) are sparse and inconsistent. To address this limitation, we assessed IAFs in a cohort of 70 individuals with cLBP, implemented 3 different IAF calculations, and separated cLBP subjects based on psychological variables. We hypothesized that a higher fear movement in cLBP is associated with a lower IAF at rest. A total of 10 minutes of resting data were collected from 128 electroencephalography channels. Our results offer 3 novel contributions to the literature. First, the high fear group had a significantly lower peak alpha frequency. The high fear group also reported higher pain and higher disability. Second, we calculated individual alpha frequency using 3 different but established methods; the effect of fear on individual alpha frequency was robust across all methods. Third, fear of movement, pain intensity, and disability highly correlated with each other and together significantly predicted IAF. Our findings are the first to show that individuals with cLBP and high fear have a lower peak alpha frequency.

Peak alpha frequency and electroencephalographic microstates are correlated with aggression in schizophrenia

Large scale retrospective studies have shown an association between schizophrenia and risk of violence. Overall, this increase in risk is small and does not justify or support stigmatizing public perceptions or media depictions of people with schizophrenia. Nonetheless, in some situations, some symptoms of schizophrenia can increase the risk of violent behavior. Prediction of this behavior would allow high impact preventive interventions. However, to date the neurobiological correlates of violent behavior in schizophrenia are not well understood, precluding the development of prognostic biomarkers. We used electroencephalography to measure alpha activity and microstates from 31 patients with schizophrenia and 18 age matched controls. Participants also completed multiple assessments of current aggressive tendencies and their lifetime history of aggressive acts. We found that individual alpha peak frequency was negatively correlated with aggression scores in both patients and controls (largest Spearman's r = -0.45). Furthermore, this result could be replicated in data taken from a single frontal channel suggesting that this may be possible to obtain in routine clinical settings (largest Spearman's r = -0.40). We also found that transitions between microstates corresponding to auditory and visual networks were inversely correlated with aggression scores. Finally, we found that, within patients, aggression was correlated with the degree of randomness between microstate transitions. This suggests that aggression is related to inappropriate switching between large scale brain networks and subsequent failure to appropriately integrate complicated environmental and internal stimuli. By elucidating some of the electrophysiological correlates of aggression, these data facilitate the development of prognostic biomarkers.

Individual Alpha Frequency Contributes to the Precision of Human Visual Processing

Brain oscillatory activity within the alpha band has been associated with a wide range of processes encompassing perception, memory, decision-making, and overall cognitive functioning. Individual alpha frequency (IAF) is a specific parameter accounting for the mean velocity of the alpha cycling activity, conventionally ranging between ∼7 and ∼13 Hz. One influential hypothesis has proposed a fundamental role of this cycling activity in the segmentation of sensory input and in the regulation of the speed of sensory processing, with faster alpha oscillations resulting in greater temporal resolution and more refined perceptual experience. However, although several recent theoretical and empirical studies would support this account, contradictory evidence suggests caution and more systematic approaches in the assessment and interpretation of this hypothesis. For example, it remains to be explored to what degree IAF shapes perceptual outcomes. In the present study, we investigated whether inter-individual differences in bias-free visual contrast detection threshold in a large sample of individuals in the general population (n = 122) could be explained by inter-individual differences in alpha pace. Our results show that the contrast needed to correctly identify target stimuli (individual perceptual threshold) is associated with alpha peak frequency (not amplitude). Specifically, individuals who require reduced contrast show higher IAF than individuals requiring higher contrasts. This suggests that inter-individual differences in alpha frequency contribute to performance variability in low-level perceptual tasks, supporting the hypothesis that IAF underlies a fundamental temporal sampling mechanism that shapes visual objective performance, with higher frequencies promoting enhanced sensory evidence per time unit.

Alpha-band Brain Dynamics and Temporal Processing: An Introduction to the Special Focus

For decades, the intriguing connection between the human alpha rhythm (an 8- to 13-Hz oscillation maximal over posterior cortex) and temporal processes in perception has furnished a rich landscape of proposals. The past decade, however, has seen a surge in interest in the topic, bringing new theoretical, analytic, and methodological developments alongside fresh controversies. This Special Focus on alpha-band dynamics and temporal processing provides an up-to-date snapshot of the playing field, with contributions from leading researchers in the field spanning original perspectives, new evidence, comprehensive reviews and meta-analyses, as well as discussion of ongoing controversies and paths forward. We hope that the perspectives captured here will help catalyze future research and shape the pathways toward a theoretically grounded and mechanistic account of the link between alpha dynamics and temporal properties of perception.

The search for the relationship between female hormonal status, alpha oscillations, and aperiodic features of resting state EEG

Fluctuations in sex steroid levels during the menstrual cycle and the use of hormonal contraceptives have been linked to changes in cognitive function and emotions in females. Such variations may be mediated by overall brain activity and excitability. We aimed to investigate the impact of female hormonal status on resting state EEG (rsEEG) parameters, including periodic (individual alpha frequency, alpha power) and aperiodic (1/f slope) features. rsEEG was recorded in healthy females (mean age 26.4 ± 4.6 years), who were naturally cycling in the early follicular (n = 33) or mid-luteal phases (n = 35), or who used either oral contraceptives (n = 35) or hormonal intrauterine devices (n = 28). Salivary concentrations of estradiol, progesterone, and testosterone were measured. Contrary to previous findings, this study did not reveal significant differences in rsEEG parameters between groups or significant relationships with hormonal levels. Age emerged as a covariate negatively related to the median 1/f slope. Based on these findings, we found no significant evidence to suggest that the periodic (alpha power and peak frequency) or aperiodic activity patterns in the brain during the resting state differ between the groups of females under investigation.

Resting EEG Periodic and Aperiodic Components Predict Cognitive Decline Over 10 Years

Measures of intrinsic brain function at rest show promise as predictors of cognitive decline in humans, including EEG metrics such as individual α peak frequency (IAPF) and the aperiodic exponent, reflecting the strongest frequency of α oscillations and the relative balance of excitatory/inhibitory neural activity, respectively. Both IAPF and the aperiodic exponent decrease with age and have been associated with worse executive function and working memory. However, few studies have jointly examined their associations with cognitive function, and none have examined their association with longitudinal cognitive decline rather than cross-sectional impairment. In a preregistered secondary analysis of data from the longitudinal Midlife in the United States (MIDUS) study, we tested whether IAPF and aperiodic exponent measured at rest predict cognitive function (N = 235; age at EEG recording M = 55.10, SD = 10.71) over 10 years. The IAPF and the aperiodic exponent interacted to predict decline in overall cognitive ability, even after controlling for age, sex, education, and lag between data collection time points. Post hoc tests showed that "mismatched" IAPF and aperiodic exponents (e.g., higher exponent with lower IAPF) predicted greater cognitive decline compared to "matching" IAPF and aperiodic exponents (e.g., higher exponent with higher IAPF; lower IAPF with lower aperiodic exponent). These effects were largely driven by measures of executive function. Our findings provide the first evidence that IAPF and the aperiodic exponent are joint predictors of cognitive decline from midlife into old age and thus may offer a useful clinical tool for predicting cognitive risk in aging.

Physical activity and verbal memory performance: Mediating effects of resting-state brain activity

Verbal short-term and long-term memory are crucial neuropsychological functions involved in core cognitive abilities. They constitute vital components of subjective well-being and academic achievement. To date, there is limited research on the association between regular physical activity and memory abilities during young adulthood. The Individual Alpha Peak Frequency (IAPF) contributes to various cognitive abilities and also appears to be sensitive to physical activity. Consequently, the IAPF has the potential to underlie the association between physical activity and verbal memory. We examined the direct relation of physical activity and verbal memory, and the potential indirect relation via IAPF in young adults. Regular physical activity was assessed via accelerometry on seven consecutive days in 115 participants (N=115, 48% female) aged 18-35 years (M=24.1, SD=3.8). In addition, verbal memory performance was assessed using an immediate and delayed free-recall task. Brain activity during rest was recorded with EEG, and IAPF was extracted for mediation analyses. Path analysis revealed pronounced sex differences in the association between physical activity, IAPF, and verbal memory performance. Exclusively in female participants, higher vigorous physical activity levels were associated with better recall performance. In contrast, no association of physical activity and memory was found in male participants. However, being more physically active was related to a higher IAPF exclusively in male participants. Physical activity shows differential associations between IAPF and verbal memory in male and female participants. However, the lack of a mediating role of IAPF suggests that this neurophysiological marker cannot explain these specific associations in young adults.

Resting EEG Periodic and Aperiodic Components Predict Cognitive Decline Over 10 Years

Measures of intrinsic brain function at rest show promise as predictors of cognitive decline in humans, including EEG metrics such as individual alpha peak frequency (IAPF) and the aperiodic exponent, reflecting the strongest frequency of alpha oscillations and the relative balance of excitatory:inhibitory neural activity, respectively. Both IAPF and the aperiodic exponent decrease with age and have been associated with worse executive function and working memory. However, few studies have jointly examined their associations with cognitive function, and none have examined their association with longitudinal cognitive decline rather than cross-sectional impairment. In a preregistered secondary analysis of data from the longitudinal Midlife in the United States (MIDUS) study, we tested whether IAPF and aperiodic exponent measured at rest predict cognitive function (N = 235; age at EEG recording M = 55.10, SD = 10.71) over 10 years. The IAPF and the aperiodic exponent interacted to predict decline in overall cognitive ability, even after controlling for age, sex, education, and lag between data collection timepoints. Post-hoc tests showed that "mismatched" IAPF and aperiodic exponents (e.g., higher exponent with lower IAPF) predicted greater cognitive decline compared to "matching" IAPF and aperiodic exponents (e.g., higher exponent with higher IAPF; lower IAPF with lower aperiodic exponent). These effects were largely driven by measures of executive function. Our findings provide the first evidence that IAPF and the aperiodic exponent are joint predictors of cognitive decline from midlife into old age and thus may offer a useful clinical tool for predicting cognitive risk in aging.

The emergence of the EEG dominant rhythm across the first year of life

The spectral composition of EEG provides important information on the function of the developing brain. For example, the frequency of the dominant rhythm, a salient features of EEG data, increases from infancy to adulthood. Changes of the dominant rhythm during infancy are yet to be fully characterized, in terms of their developmental trajectory and spectral characteristics. In this study, the development of dominant rhythm frequency was examined during a novel sustained attention task across 6-month-old (n = 39), 9-month-old (n = 30), and 12-month-old (n = 28) infants. During this task, computer-generated objects and faces floated down a computer screen for 10 s after a 5-second fixation cross. The peak frequency in the range between 5 and 9 Hz was calculated using center of gravity (CoG) and examined in response to faces and objects. Results indicated that peak frequency increased from 6 to 9 to 12 months of age in face and object conditions. We replicated the same result for the baseline. There was high reliability between the CoGs in the face, object, and baseline conditions across all channels. The developmental increase in CoG was more reliable than measures of mode frequency across different conditions. These findings suggest that CoG is a robust index of brain development across infancy.

Precision data-driven modeling of cortical dynamics reveals idiosyncratic mechanisms underlying canonical oscillations

Task-free brain activity affords unique insight into the functional structure of brain network dynamics and is a strong marker of individual differences. In this work, we present an algorithmic optimization framework that makes it possible to directly invert and parameterize brain-wide dynamical-systems models involving hundreds of interacting brain areas, from single-subject time-series recordings. This technique provides a powerful neurocomputational tool for interrogating mechanisms underlying individual brain dynamics ("precision brain models") and making quantitative predictions. We extensively validate the models' performance in forecasting future brain activity and predicting individual variability in key M/EEG markers. Lastly, we demonstrate the power of our technique in resolving individual differences in the generation of alpha and beta-frequency oscillations. We characterize subjects based upon model attractor topology and a dynamical-systems mechanism by which these topologies generate individual variation in the expression of alpha vs. beta rhythms. We trace these phenomena back to global variation in excitation-inhibition balance, highlighting the explanatory power of our framework in generating mechanistic insights.

Sleep spindle maturity promotes slow oscillation-spindle coupling across child and adolescent development

The synchronization of canonical fast sleep spindle activity (12.5-16 Hz, adult-like) precisely during the slow oscillation (0.5-1 Hz) up peak is considered an essential feature of adult non-rapid eye movement sleep. However, there is little knowledge on how this well-known coalescence between slow oscillations and sleep spindles develops. Leveraging individualized detection of single events, we first provide a detailed cross-sectional characterization of age-specific patterns of slow and fast sleep spindles, slow oscillations, and their coupling in children and adolescents aged 5-6, 8-11, and 14-18 years, and an adult sample of 20- to 26-year-olds. Critically, based on this, we then investigated how spindle and slow oscillation maturity substantiate age-related differences in their precise orchestration. While the predominant type of fast spindles was development-specific in that it was still nested in a frequency range below the canonical fast spindle range for the majority of children, the well-known slow oscillation-spindle coupling pattern was evident for sleep spindles in the adult-like canonical fast spindle range in all four age groups-but notably less precise in children. To corroborate these findings, we linked personalized measures of fast spindle maturity, which indicate the similarity between the prevailing development-specific and adult-like canonical fast spindles, and slow oscillation maturity, which reflects the extent to which slow oscillations show frontal dominance, with individual slow oscillation-spindle coupling patterns. Importantly, we found that fast spindle maturity was uniquely associated with enhanced slow oscillation-spindle coupling strength and temporal precision across the four age groups. Taken together, our results suggest that the increasing ability to generate adult-like canonical fast sleep spindles actuates precise slow oscillation-spindle coupling patterns from childhood through adolescence and into young adulthood.

A wearable EEG system for closed-loop neuromodulation of sleep-related oscillations

Objective.Healthy sleep plays a critical role in general well-being. Enhancement of slow-wave sleep by targeting acoustic stimuli to particular phases of delta (0.5-2 Hz) waves has shown promise as a non-invasive approach to improve sleep quality. Closed-loop stimulation during other sleep phases targeting oscillations at higher frequencies such as theta (4-7 Hz) or alpha (8-12 Hz) could be another approach to realize additional health benefits. However, systems to track and deliver stimulation relative to the instantaneous phase of electroencephalogram (EEG) signals at these higher frequencies have yet to be demonstrated outside of controlled laboratory settings.Approach.Here we examine the feasibility of using an endpoint-corrected version of the Hilbert transform (ecHT) algorithm implemented on a headband wearable device to measure alpha phase and deliver phase-locked auditory stimulation during the transition from wakefulness to sleep, during which alpha power is greatest. First, the ecHT algorithm is implementedin silicoto evaluate the performance characteristics of this algorithm across a range of sleep-related oscillatory frequencies. Secondly, a pilot sleep study tests feasibility to use the wearable device by users in the home setting for measurement of EEG activity during sleep and delivery of real-time phase-locked stimulation.Main results.The ecHT is capable of computing the instantaneous phase of oscillating signals with high precision, allowing auditory stimulation to be delivered at the intended phases of neural oscillations with low phase error. The wearable system was capable of measuring sleep-related neural activity with sufficient fidelity for sleep stage scoring during the at-home study, and phase-tracking performance matched simulated results. Users were able to successfully operate the system independently using the companion smartphone app to collect data and administer stimulation, and presentation of auditory stimuli during sleep initiation did not negatively impact sleep onset.Significance.This study demonstrates the feasibility of closed-loop real-time tracking and neuromodulation of a range of sleep-related oscillations using a wearable EEG device. Preliminary results suggest that this approach could be used to deliver non-invasive neuromodulation across all phases of sleep.

Resting EEG power spectra across middle to late life: associations with age, cognition, APOE-ɛ4 carriage, and cardiometabolic burden

We investigated how resting electroencephalography (EEG) measures are associated with risk factors for late-life cognitive impairment and dementia, including age, apolipoprotein E ɛ4 (APOE-ɛ4) carriage, and cardiometabolic burden. Resting EEG was recorded from 86 adults (50-80 years of age). Participants additionally completed the Addenbrooke's Cognitive Examination (ACE) III and had blood drawn to assess APOE-ɛ4 carriage status and cardiometabolic burden. EEG power spectra were decomposed into sources of periodic and aperiodic activity to derive measures of aperiodic component slope and alpha (7-14 Hz) and beta (15-30 Hz) peak power and peak frequency. Alpha and beta peak power measures were corrected for aperiodic activity. The aperiodic component slope was correlated with ACE-III scores but not age. Alpha peak frequency decreased with age. Individuals with higher cardiometabolic burden had lower alpha peak frequencies and lower beta peak power. APOE-ɛ4 carriers had lower beta peak frequencies. Our findings suggest that the slope of the aperiodic component of resting EEG power spectra is more closely associated with measures of cognitive performance rather than chronological age in older adults.

Reduced alpha2 power is associated with slowed information processing speed in multiple sclerosis

OBJECTIVE

Cognitive impairment is common in multiple sclerosis (MS), significantly impacts daily functioning, is time-consuming to assess, and is prone to practice effects. We examined whether the alpha band power measured with magnetoencephalography (MEG) is associated with the different cognitive domains affected by MS.

METHODS

Sixty-eight MS patients and 47 healthy controls underwent MEG, T1- and FLAIR-weighted magnetic resonance imaging (MRI), and neuropsychological testing. Alpha power in the occipital cortex was quantified in the alpha1 (8-10 Hz) and alpha2 (10-12 Hz) bands. Next, we performed best subset regression to assess the added value of neurophysiological measures to commonly available MRI measures.

RESULTS

Alpha2 power significantly correlated with information processing speed (p < 0.001) and was always retained in all multilinear models, whereas thalamic volume was retained in 80% of all models. Alpha1 power was correlated with visual memory (p < 0.001) but only retained in 38% of all models.

CONCLUSIONS

Alpha2 (10-12 Hz) power in rest is associated with IPS, independent of standard MRI parameters. This study stresses that a multimodal assessment, including structural and functional biomarkers, is likely required to characterize cognitive impairment in MS. Resting-state neurophysiology is thus a promising tool to understand and follow up changes in IPS.

Developmental changes in individual alpha frequency: Recording EEG data during public engagement events

Statistical power in cognitive neuroimaging experiments is often very low. Low sample size can reduce the likelihood of detecting real effects (false negatives) and increase the risk of detecting non-existing effects by chance (false positives). Here, we document our experience of leveraging a relatively unexplored method of collecting a large sample size for simple electroencephalography (EEG) studies: by recording EEG in the community during public engagement and outreach events. We collected data from 346 participants (189 females, age range 6-76 years) over 6 days, totalling 29 hours, at local science festivals. Alpha activity (6-15 Hz) was filtered from 30 seconds of signal, recorded from a single electrode placed between the occipital midline (Oz) and inion (Iz) while the participants rested with their eyes closed. A total of 289 good-quality datasets were obtained. Using this community-based approach, we were able to replicate controlled, lab-based findings: individual alpha frequency (IAF) increased during childhood, reaching a peak frequency of 10.28 Hz at 28.1 years old, and slowed again in middle and older age. Total alpha power decreased linearly, but the aperiodic-adjusted alpha power did not change over the lifespan. Aperiodic slopes and intercepts were highest in the youngest participants. There were no associations between these EEG indexes and self-reported fatigue, measured by the Multidimensional Fatigue Inventory. Finally, we present a set of important considerations for researchers who wish to collect EEG data within public engagement and outreach environments.

Slowed alpha oscillations and percept formation in psychotic psychopathology

Introduction

Psychosis is in part defined by disturbances in perception. Recent investigations have implicated the speed of alpha oscillations observed in brain electrical activity as reflective of a sampling rate of the visual environment and perception. Although both slowed alpha oscillations and aberrant percept formation are evident in disorders of psychotic psychopathology such as schizophrenia it is unclear whether slow alpha accounts for abnormal visual perception in these disorders.

Methods

To examine the role of the speed of alpha oscillations in perception in psychotic psychopathology we gathered resting-state magneto-encephalography data from probands with psychotic psychopathology (i.e., schizophrenia, schizoaffective disorder, and bipolar disorder with a history of psychosis), their biological siblings, and healthy controls. We appraised visual perceptual function without the confound of cognitive ability and effort through the use of a simple binocular rivalry task.

Results

We found a slowed pace of alpha oscillations in psychotic psychopathology that was associated with longer percept durations during binocular rivalry, consistent with the assertion that occipital alpha oscillations govern the rate of accumulation of visual information used to generate percepts. Alpha speed varied widely across individuals with psychotic psychopathology and was highly stable across several months indicating that it is likely a trait characteristic of neural function that is relevant to visual perception. Finally, a lower speed of alpha oscillation was associated with a lower IQ and greater disorder symptomatology implying that the effects of the endogenous neural oscillation on visual perception may have wider consequences for everyday functioning.

Discussion

Slowed alpha oscillations in individuals with psychotic psychopathology appear to reflect altered neural functions related to percept formation.

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

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

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.

Comparative analysis of acoustic therapies for tinnitus treatment based on auditory event-related potentials

Introduction

So far, Auditory Event-Related Potential (AERP) features have been used to characterize neural activity of patients with tinnitus. However, these EEG patterns could be used to evaluate tinnitus evolution as well. The aim of the present study is to propose a methodology based on AERPs to evaluate the effectiveness of four acoustic therapies for tinnitus treatment.

Methods

The acoustic therapies were: (1) Tinnitus Retraining Therapy (TRT), (2) Auditory Discrimination Therapy (ADT), (3) Therapy for Enriched Acoustic Environment (TEAE), and (4) Binaural Beats Therapy (BBT). In addition, relaxing music was included as a placebo for both: tinnitus sufferers and healthy individuals. To meet this aim, 103 participants were recruited, 53% were females and 47% were males. All the participants were treated for 8 weeks with one of these five sounds, which were moreover tuned in accordance with the acoustic features of their tinnitus (if applied) and hearing loss. They were electroencephalographically monitored before and after their acoustic therapy, and wherefrom AERPs were estimated. The sound effect of acoustic therapies was evaluated by examining the area under the curve of those AERPs. Two parameters were obtained: (1) amplitude and (2) topographical distribution.

Results

The findings of the investigation showed that after an 8-week treatment, TRT and ADT, respectively achieved significant neurophysiological changes over somatosensory and occipital regions. On one hand, TRT increased the tinnitus perception. On the other hand, ADT redirected the tinnitus attention, what in turn diminished the tinnitus perception. Tinnitus handicapped inventory outcomes verified these neurophysiological findings, revealing that 31% of patients in each group reported that TRT increased tinnitus perception, but ADT diminished it.

Discussion

Tinnitus has been identified as a multifactorial condition highly associated with hearing loss, age, sex, marital status, education, and even, employment. However, no conclusive evidence has been found yet. In this study, a significant (but low) correlation was found between tinnitus intensity and right ear hearing loss, left ear hearing loss, heart rate, area under the curve of AERPs, and acoustic therapy. This study raises the possibility to assign acoustic therapies by neurophysiological response of patient.

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.

Repetitive transcranial magnetic stimulation treatment of major depressive disorder and comorbid chronic pain: response rates and neurophysiologic biomarkers

BACKGROUND

Major depressive disorder (MDD) and chronic pain are highly comorbid, and pain symptoms are associated with a poorer response to antidepressant medication treatment. It is unclear whether comorbid pain also is associated with a poorer response to treatment with repetitive transcranial magnetic stimulation (rTMS).

METHODS

162 MDD subjects received 30 sessions of 10 Hz rTMS treatment administered to the left dorsolateral prefrontal cortex (DLPFC) with depression and pain symptoms measured before and after treatment. For a subset of 96 patients, a resting-state electroencephalogram (EEG) was recorded at baseline. Clinical outcome was compared between subjects with and without comorbid pain, and the relationships among outcome, pain severity, individual peak alpha frequency (PAF), and PAF phase-coherence in the EEG were examined.

RESULTS

64.8% of all subjects reported pain, and both depressive and pain symptoms were significantly reduced after rTMS treatment, irrespective of age or gender. Patients with severe pain were 27% less likely to respond to MDD treatment than pain-free individuals. PAF was positively associated with pain severity. PAF phase-coherence in the somatosensory and default mode networks was significantly lower for MDD subjects with pain who failed to respond to MDD treatment.

CONCLUSIONS

Pain symptoms improved after rTMS to left DLPFC in MDD irrespective of age or gender, although the presence of chronic pain symptoms reduced the likelihood of treatment response. Individual PAF and baseline phase-coherence in the sensorimotor and midline regions may represent predictors of rTMS treatment outcome in comorbid pain and MDD.

The posterior dominant rhythm: an electroencephalographic biomarker for cognitive recovery after general anaesthesia

BACKGROUND

The posterior dominant rhythm (PDR) was the first oscillatory pattern noted in the EEG. Evoked by wakeful eyelid closure, these oscillations dissipate over seconds during loss of arousal. The peak frequency of the PDR maintains stability over years, suggesting utility as a state biomarker in the surveillance of acute cognitive impairments. This EEG signature has not been systematically investigated for tracking cognitive dysfunction after anaesthetic-induced loss of consciousness.

METHODS

This substudy of Reconstructing Consciousness and Cognition (NCT01911195) investigated the PDR and cognitive function in 60 adult volunteers randomised to either 3 h of isoflurane general anaesthesia or resting wakefulness. Serial measurements of EEG power and cognitive task performance were assessed relative to pre-intervention baseline. Mixed-effects models allowed quantification of PDR and neurocognitive trajectories after return of responsiveness (ROR).

RESULTS

Individuals in the control group showed stability in the PDR peak frequency over several hours (median difference/inter-quartile range [IQR] of 0.02/0.20 Hz, P=0.39). After isoflurane general anaesthesia, the PDR peak frequency was initially reduced at ROR (median difference/IQR of 0.88/0.65 Hz, P<0.001). PDR peak frequency recovered at a rate of 0.20 Hz h-1. After ROR, the PDR peak frequency correlated with reaction time and accuracy on multiple cognitive tasks (P<0.001).

CONCLUSION

The temporal trajectory of the PDR peak frequency could be a useful perioperative marker for tracking cognitive dysfunction on the order of hours after surgery, particularly for cognitive domains of working memory, visuomotor speed, and executive function.

CLINICAL TRIAL REGISTRATION

NCT01911195.

Supplementation With Iron Syrup or Iron-Containing Multiple Micronutrient Powders Alters Resting Brain Activity in Bangladeshi Children

BACKGROUND

Anemia and iron deficiency have been associated with poor child cognitive development. A key rationale for the prevention of anemia using supplementation with iron has been the benefits to neurodevelopment. However, little causal evidence exists for these gains.

OBJECTIVES

We aimed to examine effects of supplementation with iron or multiple micronutrient powders (MNPs) on brain activity measures using resting electroencephalography (EEG).

METHODS

Children included in this neurocognitive substudy were randomly selected from the Benefits and Risks of Iron Supplementation in Children study, a double-blind, double-dummy, individually randomized, parallel-group trial in Bangladesh, in which children, starting at 8 mo of age, received 3 mo of daily iron syrup, MNPs, or placebo. Resting brain activity was recorded using EEG immediately after intervention (month 3) and after a further 9-month follow-up (month 12). We derived EEG band power measures for delta, theta, alpha, and beta frequency bands. Linear regression models were used to compare the effect of each intervention with that of placebo on the outcomes.

RESULTS

Data from 412 children at month 3 and 374 at month 12 were analyzed. At baseline, 43.9% were anemic and 26.7% were iron deficient. Immediately after intervention, iron syrup, but not MNPs, increased the mu alpha-band power, a measure that is associated with maturity and the production of motor actions (iron vs. placebo: mean difference = 0.30; 95% CI: 0.11, 0.50 μV²; P = 0.003; false discovery rate adjusted P = 0.015). Despite effects on hemoglobin and iron status, effects were not observed on the posterior alpha, beta, delta, and theta bands, nor were effects sustained at the 9-month follow-up.

CONCLUSIONS

The effect size for immediate effects on the mu alpha-band power is comparable in magnitude with psychosocial stimulation interventions and poverty reduction strategies. However, overall, we did not find evidence for long-lasting changes in resting EEG power spectra from iron interventions in young Bangladeshi children. This trial was registered at www.anzctr.org.au as ACTRN12617000660381.

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.

Neurofeedback training for children with ADHD using individual beta rhythm

Neurofeedback training (NFT) is a noninvasive neuromodulation method for children with attention-deficit/hyperactivity disorder (ADHD). Brain rhythms, the unique pattern in electroencephalogram (EEG), are widely used as the training target. Most of current studies used a fixed frequency division of brain rhythms, which ignores the individual developmental difference of each child. In this study, we validated the feasibility of NFT using individual beta rhythm. A total of 55 children with ADHD were divided into two groups using the relative power of individual or fixed beta rhythms as the training index. ADHD rating scale (ADHD-RS) was completed before and after NFT, and the EEG and behavioral features were extracted during the training process. After intervention, the attention ability of both groups was significantly improved, showing a significant increase in beta power, a decrease in scores of ADHD-RS and an improvement in behavioral and other EEG features. The training effect was significantly better with individualized beta training, showing more improvement in ADHD-RS scores. Furthermore, the distribution of brain rhythms moved towards high frequency after intervention. This study demonstrates the effectiveness of NFT based on individual beta rhythm for the intervention of children with ADHD. When designing a NFT protocol and the corresponding data analysis process, an individualized brain rhythm division should be applied to reflect the actual brain state and to accurately evaluate the effect of NFT.

Intellectually able adults with autism spectrum disorder show typical resting-state EEG activity

There is broad interest in discovering quantifiable physiological biomarkers for psychiatric disorders to aid diagnostic assessment. However, finding biomarkers for autism spectrum disorder (ASD) has proven particularly difficult, partly due to high heterogeneity. Here, we recorded five minutes eyes-closed rest electroencephalography (EEG) from 186 adults (51% with ASD and 49% without ASD) and investigated the potential of EEG biomarkers to classify ASD using three conventional machine learning models with two-layer cross-validation. Comprehensive characterization of spectral, temporal and spatial dimensions of source-modelled EEG resulted in 3443 biomarkers per recording. We found no significant group-mean or group-variance differences for any of the EEG features. Interestingly, we obtained validation accuracies above 80%; however, the best machine learning model merely distinguished ASD from the non-autistic comparison group with a mean balanced test accuracy of 56% on the entirely unseen test set. The large drop in model performance between validation and testing, stress the importance of rigorous model evaluation, and further highlights the high heterogeneity in ASD. Overall, the lack of significant differences and weak classification indicates that, at the group level, intellectually able adults with ASD show remarkably typical resting-state EEG.

Mental fatigue decreases complexity: Evidence from multiscale entropy analysis of instantaneous frequency variation in alpha rhythm

Mental fatigue (MF) jeopardizes performance and safety through a variety of cognitive impairments and according to the complexity loss theory, should represent "complexity loss" in electroencephalogram (EEG). However, the studies are few and inconsistent concerning the relationship between MF and loss of complexity, probably because of the susceptibility of brain waves to noise. In this study, MF was induced in thirteen male college students by a simulated flight task. Before and at the end of the task, spontaneous EEG and auditory steady-state response (ASSR) were recorded and instantaneous frequency variation (IFV) in alpha rhythm was extracted and analyzed by multiscale entropy (MSE) analysis. The results show that there were significant differences in IFV in alpha rhythm either from spontaneous EEG or from ASSR for all subjects. Therefore, the proposed method can be effective in revealing the complexity loss caused by MF in spontaneous EEG and ASSR, which may serve as a promising analyzing method to mark mild mental impairments.

Decreased resting-state alpha peak frequency in children and adolescents with fetal alcohol spectrum disorders or prenatal alcohol exposure

Prenatal alcohol exposure (PAE) can result in long-lasting changes to physical, behavioral, and cognitive functioning in children. PAE might result in decreased white matter integrity, corticothalamic tract integrity, and alpha cortical oscillations. Previous investigations of alpha oscillations in PAE/fetal alcohol spectrum disorder (FASD) have focused on average spectral power at specific ages; therefore, little is known about alpha peak frequency (APF) or its developmental trajectory making this research novel. Using resting-state MEG data, APF was determined from parietal/occipital regions in participants with PAE/FASD or typically developing controls (TDC). In total, MEG data from 157 infants, children, and adolescents ranging in age from 6 months to 17 years were used, including 17 individuals with PAE, 61 individuals with an FASD and 84 TDC. In line with our hypothesis, we found that individuals with PAE/FASD had significantly reduced APF relative to TDC. Both age and group were significantly related to APF with differences between TDC and PAE/FASD persisting throughout development. We did not find evidence that sex or socioeconomic status had additional impact on APF. Reduced APF in individuals with an FASD/PAE may represent a long-term deficit and demonstrates the detrimental impact prenatal alcohol exposure can have on neurophysiological processes.

The development of peak alpha frequency from infancy to adolescence and its role in visual temporal processing: A meta-analysis

While it has been shown that alpha frequency increases over development (Stroganova et al., 1999), a precise trajectory has not yet been specified, making it challenging to constrain theories linking alpha rhythms to perceptual development. We conducted a comprehensive review of studies measuring resting-state occipital peak alpha frequency (PAF, the frequency exhibiting maximum power) from birth to 18 years of age. From 889 potentially relevant studies, we identified 40 reporting PAF (109 samples; 3882 subjects). A nonlinear regression revealed that PAF increases quickly in early childhood (from 6.1 Hz at 6 months to 8.4 Hz at 5 years) and levels off in adolescence (9.7 Hz at 13 years), with an asymptote at 10.1 Hz. We found no effect of resting state procedure (eyes-open versus eyes-closed) or biological sex. PAF has been implicated as a clock on visual temporal processing, with faster frequencies associated with higher visual temporal resolution. Psychophysical studies have shown that temporal resolution reaches adult levels by 5 years of age (Freschl et al., 2019, 2020). The fact that PAF reaches the adult range of 8-12 Hz by that age strengthens the link between PAF and temporal resolution.

Evidence for a theta-band behavioural oscillation in rapid face detection

Theories of rhythmic perception propose that perceptual sampling operates in a periodic way, with alternating moments of high and low responsiveness to sensory inputs. This rhythmic sampling is linked to neural oscillations and thought to produce fluctuations in behavioural outcomes. Previous studies have revealed theta- and alpha-band behavioural oscillations in low-level visual tasks and object categorization. However, less is known about fluctuations in face perception, for which the human brain has developed a highly specialized network. To investigate this, we ran an online study (N = 179) incorporating the dense sampling technique with a dual-target rapid serial visual presentation (RSVP) paradigm. In each trial, a stream of object images was presented at 30 Hz and participants were tasked with detecting whether or not there was a face image in the sequence. On some trials, one or two (identical) face images (the target) were embedded in each stream. On dual-target trials, the targets were separated by an interstimulus interval (ISI) that varied between 0 to 633 ms. The task was to indicate the presence of the target and its gender if present. Performance varied as a function of ISI, with a significant behavioural oscillation in the face detection task at 7.5 Hz, driven mainly by the male target faces. This finding is consistent with a high theta-band-based fluctuation in visual processing. Such fluctuations might reflect rhythmic attentional sampling or, alternatively, feedback loops involved in updating top-down predictions.

Unveiling the Associations between EEG Indices and Cognitive Deficits in Schizophrenia-Spectrum Disorders: A Systematic Review

Cognitive dysfunctions represent a core feature of schizophrenia-spectrum disorders due to their presence throughout different illness stages and their impact on functioning. Abnormalities in electrophysiology (EEG) measures are highly related to these impairments, but the use of EEG indices in clinical practice is still limited. A systematic review of articles using Pubmed, Scopus and PsychINFO was undertaken in November 2021 to provide an overview of the relationships between EEG indices and cognitive impairment in schizophrenia-spectrum disorders. Out of 2433 screened records, 135 studies were included in a qualitative review. Although the results were heterogeneous, some significant correlations were identified. In particular, abnormalities in alpha, theta and gamma activity, as well as in MMN and P300, were associated with impairments in cognitive domains such as attention, working memory, visual and verbal learning and executive functioning during at-risk mental states, early and chronic stages of schizophrenia-spectrum disorders. The review suggests that machine learning approaches together with a careful selection of validated EEG and cognitive indices and characterization of clinical phenotypes might contribute to increase the use of EEG-based measures in clinical settings.

Rapid adaptation of predictive models during language comprehension: Aperiodic EEG slope, individual alpha frequency and idea density modulate individual differences in real-time model updating

Predictive coding provides a compelling, unified theory of neural information processing, including for language. However, there is insufficient understanding of how predictive models adapt to changing contextual and environmental demands and the extent to which such adaptive processes differ between individuals. Here, we used electroencephalography (EEG) to track prediction error responses during a naturalistic language processing paradigm. In Experiment 1, 45 native speakers of English listened to a series of short passages. Via a speaker manipulation, we introduced changing intra-experimental adjective order probabilities for two-adjective noun phrases embedded within the passages and investigated whether prediction error responses adapt to reflect these intra-experimental predictive contingencies. To this end, we calculated a novel measure of speaker-based, intra-experimental surprisal (“speaker-based surprisal”) as defined on a trial-by-trial basis and by clustering together adjectives with a similar meaning. N400 amplitude at the position of the critical second adjective was used as an outcome measure of prediction error. Results showed that N400 responses attuned to speaker-based surprisal over the course of the experiment, thus indicating that listeners rapidly adapt their predictive models to reflect local environmental contingencies (here: the probability of one type of adjective following another when uttered by a particular speaker). Strikingly, this occurs in spite of the wealth of prior linguistic experience that participants bring to the laboratory. Model adaptation effects were strongest for participants with a steep aperiodic (1/f) slope in resting EEG and low individual alpha frequency (IAF), with idea density (ID) showing a more complex pattern. These results were replicated in a separate sample of 40 participants in Experiment 2, which employed a highly similar design to Experiment 1. Overall, our results suggest that individuals with a steep aperiodic slope adapt their predictive models most strongly to context-specific probabilistic information. Steep aperiodic slope is thought to reflect low neural noise, which in turn may be associated with higher neural gain control and better cognitive control. Individuals with a steep aperiodic slope may thus be able to more effectively and dynamically reconfigure their prediction-related neural networks to meet current task demands. We conclude that predictive mechanisms in language are highly malleable and dynamic, reflecting both the affordances of the present environment as well as intrinsic information processing capabilities of the individual.

Peak frequency of the sensorimotor mu rhythm varies with autism-spectrum traits

Autism spectrum disorder (ASD) is a neurodevelopmental syndrome characterized by impairments in social perception and communication. Growing evidence suggests that the relationship between deficits in social perception and ASD may extend into the neurotypical population. In electroencephalography (EEG), high autism-spectrum traits in both ASD and neurotypical samples are associated with changes to the mu rhythm, an alpha-band (8–12 Hz) oscillation measured over sensorimotor cortex which typically shows reductions in spectral power during both one’s own movements and observation of others’ actions. This mu suppression is thought to reflect integration of perceptual and motor representations for understanding of others’ mental states, which may be disrupted in individuals with autism-spectrum traits. However, because spectral power is usually quantified at the group level, it has limited usefulness for characterizing individual variation in the mu rhythm, particularly with respect to autism-spectrum traits. Instead, individual peak frequency may provide a better measure of mu rhythm variability across participants. Previous developmental studies have linked ASD to slowing of individual peak frequency in the alpha band, or peak alpha frequency (PAF), predominantly associated with selective attention. Yet individual variability in the peak mu frequency (PMF) remains largely unexplored, particularly with respect to autism-spectrum traits. Here we quantified peak frequency of occipitoparietal alpha and sensorimotor mu rhythms across neurotypical individuals as a function of autism-spectrum traits. High-density 128-channel EEG data were collected from 60 participants while they completed two tasks previously reported to reliably index the sensorimotor mu rhythm: motor execution (bimanual finger tapping) and action observation (viewing of whole-body human movements). We found that individual measurement in the peak oscillatory frequency of the mu rhythm was highly reliable within participants, was not driven by resting vs. task states, and showed good correlation across action execution and observation tasks. Within our neurotypical sample, higher autism-spectrum traits were associated with slowing of the PMF, as predicted. This effect was not likely explained by volume conduction of the occipitoparietal PAF associated with attention. Together, these data support individual peak oscillatory alpha-band frequency as a correlate of autism-spectrum traits, warranting further research with larger samples and clinical populations.

Ultra-high-resolution time-frequency analysis of EEG to characterise brain functional connectivity with the application in Alzheimer's disease

OBJECTIVE

This study aims to explore the potential of high-resolution brain functional connectivity based on electroencephalogram (EEG), a non-invasive low-cost technique, to be translated into a long-overdue biomarker and a diagnostic method for Alzheimer's disease (AD).

APPROACH

The paper proposes a novel ultra-high-resolution time-frequency nonlinear cross-spectrum method to construct a promising biomarker of AD pathophysiology. Specifically, using the peak frequency estimated from a Revised Hilbert-Huang Transformation cross-spectrum as a biomarker, the Support Vector Machine classifier is used to distinguish AD from healthy controls (HC).

MAIN RESULTS

With the combinations of the proposed biomarker and machine learning, we achieved a promising accuracy of 89%. The proposed method performs better than the wavelet cross-spectrum and other functional connectivity measures in the temporal or frequency domain, particularly in the Full, Delta and Alpha bands. Besides, a novel visualisation approach developed from topography is introduced to represent the brain functional connectivity, with which the difference between AD and HCs can be clearly displayed. The interconnections between posterior and other brain regions are obviously affected in AD.

SIGNIFICANCE

Those findings imply that the proposed RHHT approach could better track dynamic and nonlinear functional connectivity information, paving the way for the development of a novel diagnostic approach.

Unraveling the Contribution of Serotonergic Polymorphisms, Prefrontal Alpha Asymmetry, and Individual Alpha Peak Frequency to the Emotion-Related Impulsivity Endophenotype

The unique contribution of the serotonin transporter-linked polymorphic region (5-HTTLPR), intronic region 2 (STin2), and monoamine oxidase A (MAO-A) genes to individual differences in personality traits has been widely explored, and research has shown that certain forms of these polymorphisms relate to impulsivity and impulsivity-related disorders. Humans showing these traits are also described as having an asymmetrical prefrontal cortical activity when compared to others. In this explorative study, we examine the relationship between serotonergic neurotransmission polymorphisms, cortical activity features (prefrontal alpha asymmetry, individual alpha peak frequency [iAPF]), emotion-related and non-emotion-related impulsivity in humans. 5-HTTLPR, MAO-A, and STin2 polymorphisms were assessed in blood taken from 91 participants with high emotion-related impulsivity levels. Sixty-seven participants completed resting electroencephalography and a more comprehensive impulsivity index. In univariate analyses, iAPF correlated with both forms of emotion-related impulsivity. In multiple linear regression models, 5-HTTLPR polymorphism (model 1, adj. R² = 15.2%) and iAPF were significant interacting predictors of emotion-related impulsivity, explaining a large share of the results’ variance (model 2, adj. R² = 21.2%). Carriers of the low transcriptional activity 5-HTTPLR and MAO-A phenotypes obtained higher emotion-related impulsivity scores than others did. No significant results were detected for non-emotion-related impulsivity or for a form of emotion-related impulsivity involving cognitive/motivational reactivity to emotion. Our findings support an endophenotypic approach to impulsivity, showing that tri-allelic 5-HTTLPR polymorphism, iAPF, and their interaction are relevant predictors of one form of emotion-related impulsivity.

Parietal Alpha Oscillatory Peak Frequency Mediates the Effect of Practice on Visuospatial Working Memory Performance

Visuospatial working memory (WM) requires the activity of a spread network, including right parietal regions, to sustain storage capacity, attentional deployment, and active manipulation of information. Notably, while the electrophysiological correlates of such regions have been explored using many different indices, evidence for a functional involvement of the individual frequency peaks in the alpha (IAF) and theta bands (ITF) is still poor despite their relevance in many influential theories regarding WM. Interestingly, there is also a parallel lack of literature about the effect of short-term practice on WM performance. Here, we aim to clarify whether the simple repetition of a change-detection task might be beneficial to WM performance and to which degree these effects could be predicted by IAF and ITF. For this purpose, 25 healthy participants performed a change-detection task at baseline and in a retest session, while IAF and ITF were also measured. Results show that task repetition improves WM performance. In addition, right parietal IAF, but not ITF, accounts for performance gain such that faster IAF predicts higher performance gain. Our findings align with recent literature suggesting that the faster the posterior alpha, the finer the perceptual sampling rate, and the higher the WM performance gain.

Theta oscillations shift towards optimal frequency for cognitive control

Cognitive control allows to flexibly guide behaviour in a complex and ever-changing environment. It is supported by theta band (4-7 Hz) neural oscillations that coordinate distant neural populations. However, little is known about the precise neural mechanisms permitting such flexible control. Most research has focused on theta amplitude, showing that it increases when control is needed, but a second essential aspect of theta oscillations, their peak frequency, has mostly been overlooked. Here, using computational modelling and behavioural and electrophysiological recordings, in three independent datasets, we show that theta oscillations adaptively shift towards optimal frequency depending on task demands. We provide evidence that theta frequency balances reliable set-up of task representation and gating of task-relevant sensory and motor information and that this frequency shift predicts behavioural performance. Our study presents a mechanism supporting flexible control and calls for a reevaluation of the mechanistic role of theta oscillations in adaptive behaviour.

Assessing the specificity of the relationship between brain alpha oscillations and tonic pain

Recent research proposed that the slowing of individual alpha frequency (IAF) could be an objective marker of pain. However, it is unclear whether this research can fully address the requirements of specificity and sensitivity of IAF to the pain experience. Here, we sought to develop a robust methodology for assessing the specificity of the relationship between alpha oscillations and acute tonic pain in healthy individuals. We recorded electroencephalography (EEG) of 36 volunteers during consecutive 5-minute sessions of painful hot water immersion, innocuous warm water immersion and aversive, non-painful auditory stimulus, matched by unpleasantness to the painful condition. Participants rated stimulus unpleasantness throughout each condition. We isolated two regions of the scalp displaying peak alpha activity across participants: centro-parietal (CP) and parieto-occipital (PO) ROI. In line with previous research our findings revealed decreased IAF during hot compared with warm stimulation, however the effect was not specific for pain as we found no difference between hot and sound in the CP ROI (compared to baseline). In contrast, the PO ROI reported the same pattern of differences, but their direction was opposite to the CP in that this ROI revealed faster frequency during hot condition than controls. Finally, we show that IAF in both ROIs did not mediate the relationship between the experimental manipulation and the affective experience. Altogether, these findings emphasize the importance of a robust methodological and analytical design to disclose the functional role of alpha oscillations during affective processing. Likewise, they suggest the absence of a causal role of IAF in the generation of acute pain experience in healthy individuals.

Effects of Pulsed-Wave Chromotherapy and Guided Relaxation on the Theta-Alpha Oscillation During Arrest Reaction

The search for the best wellness practice has promoted the development of devices integrating different technologies and guided meditation. However, the final effects on the electrical activity of the brain remain relatively sparse. Here, we have analyzed of the alpha and theta electroencephalographic oscillations during the realization of the arrest reaction (AR; eyes close/eyes open transition) when a chromotherapy session performed in a dedicated room [Rebalance (RB) device], with an ergonomic bed integrating pulsed-wave light (PWL) stimulation, guided breathing, and body scan exercises. We demonstrated that the PWL induced an evoked-related potential characterized by the N2-P3 components maximally recorded on the fronto-central areas and accompanied by an event-related synchronization (ERS) of the delta–theta–alpha oscillations. The power of the alpha and theta oscillations was analyzed during repeated ARs testing realized along with the whole RB session. We showed that the power of the alpha and theta oscillations was significantly increased during the session in comparison to their values recorded before. Of the 14 participants, 11 and 6 showed a significant power increase of the alpha and theta oscillations, respectively. These increased powers were not observed in two different control groups (n = 28) who stayed passively outside or inside the RB room but without any type of stimulation. These preliminary results suggest that PWL chromotherapy and guided relaxation induce measurable electrical brain changes that could be beneficial under neuropsychiatric perspectives.