Representations of imaginary scenes and their properties in cortical alpha activity.

Imagining natural scenes enables us to engage with a myriad of simulated environments. How do our brains generate such complex mental images? Recent research suggests that cortical alpha activity carries information about individual objects during visual imagery. However, it remains unclear if more complex imagined contents such as natural scenes are similarly represented in alpha activity. Here, we answer this question by decoding the contents of imagined scenes from rhythmic cortical activity patterns. In an EEG experiment, participants imagined natural scenes based on detailed written descriptions, which conveyed four complementary scene properties: openness, naturalness, clutter level and brightness. By conducting classification analyses on EEG power patterns across neural frequencies, we were able to decode both individual imagined scenes as well as their properties from the alpha band, showing that also the contents of complex visual images are represented in alpha rhythms. A cross-classification analysis between alpha power patterns during the imagery task and during a perception task, in which participants were presented images of the described scenes, showed that scene representations in the alpha band are partly shared between imagery and late stages of perception. This suggests that alpha activity mediates the top-down re-activation of scene-related visual contents during imagery.

A randomized controlled trial of alpha phase-locked auditory stimulation to treat symptoms of sleep onset insomnia.

Sleep onset insomnia is a pervasive problem that contributes significantly to the poor health outcomes associated with insufficient sleep. Auditory stimuli phase-locked to slow-wave sleep oscillations have been shown to augment deep sleep, but it is unknown whether a similar approach can be used to accelerate sleep onset. The present randomized controlled crossover trial enrolled adults with objectively verified sleep onset latencies (SOLs) greater than 30 min to test the effect of auditory stimuli delivered at specific phases of participants' alpha oscillations prior to sleep onset. During the intervention week, participants wore an electroencephalogram (EEG)-enabled headband that delivered acoustic pulses timed to arrive anti-phase with alpha for 30 min (Stimulation). During the Sham week, the headband silently recorded EEG. The primary outcome was SOL determined by blinded scoring of EEG records. For the 21 subjects included in the analyses, stimulation had a significant effect on SOL according to a linear mixed effects model (p = 0.0019), and weekly average SOL decreased by 10.5 ± 15.9 min (29.3 ± 44.4%). These data suggest that phase-locked acoustic stimulation can be a viable alternative to pharmaceuticals to accelerate sleep onset in individuals with prolonged sleep onset latencies. Trial Registration: This trial was first registered on clinicaltrials.gov on 24/02/2023 under the name Sounds Locked to ElectroEncephalogram Phase For the Acceleration of Sleep Onset Time (SLEEPFAST), and assigned registry number NCT05743114.

Theta and alpha oscillations may underlie improved attention and working memory in musically trained children.

INTRODUCTION: Attention and working memory are key cognitive functions that allow us to select and maintain information in our mind for a short time, being essential for our daily life and, in particular, for learning and academic performance. It has been shown that musical training can improve working memory performance, but it is still unclear if and how the neural mechanisms of working memory and particularly attention are implicated in this process. In this work, we aimed to identify the oscillatory signature of bimodal attention and working memory that contributes to improved working memory in musically trained children. MATERIALS AND METHODS: We recruited children with and without musical training and asked them to complete a bimodal (auditory/visual) attention and working memory task, whereas their brain activity was measured using electroencephalography. Behavioral, time-frequency, and source reconstruction analyses were made. RESULTS: Results showed that, overall, musically trained children performed better on the task than children without musical training. When comparing musically trained children with children without musical training, we found modulations in the alpha band pre-stimuli onset and the beginning of stimuli onset in the frontal and parietal regions. These correlated with correct responses to the attended modality. Moreover, during the end phase of stimuli presentation, we found modulations correlating with correct responses independent of attention condition in the theta and alpha bands, in the left frontal and right parietal regions. CONCLUSIONS: These results suggest that musically trained children have improved neuronal mechanisms for both attention allocation and memory encoding. Our results can be important for developing interventions for people with attention and working memory difficulties.

Modulation of EEG Signals by Visual and Auditory Distractors in Virtual Reality-Based Continuous Performance Tests.

Compared to traditional continuous performance tasks, virtual reality-based continuous performance tests (VR-CPT) offer higher ecological validity. While previous studies have primarily focused on behavioral outcomes in VR-CPT and incorporated various distractors to enhance ecological realism, little attention has been paid to the effects of distractors on EEG. Therefore, our study aimed to investigate the influence of distractors on EEG during VR-CPT. We studied visual distractors and auditory distractors separately, recruiting 68 subjects (M =20.82, SD =1.72) and asking each to complete four tasks. These tasks were categorized into four groups according to the presence or absence of visual and auditory distractors. We conducted paired t-tests on the mean relative power of the five electrodes in the ROI region across different frequency bands. Significant differences were found in theta waves between Group 3 (M =2.49, SD =2.02) and Group 4 (M =2.68, SD =2.39) (p < 0.05); in alpha waves between Group 3 (M =2.08, SD =3.73) and Group 4 (M =3.03, SD =4.60) (p < 0.001); and in beta waves between Group 1 (M = -4.44 , SD =2.29) and Group 2 (M = -5.03 , SD =2.48) (p < 0.001), as well as between Group 3 (M = -4.48 , SD =2.03) and Group 4 (M = -4.67 , SD =2.23) (p < 0.05). The incorporation of distractors in VR-CPT modulates EEG signals across different frequency bands, with visual distractors attenuating theta band activity, auditory distractors enhancing alpha band activity, and both types of distractors reducing beta oscillations following target stimuli. This insight holds significant promise for the rehabilitation of children and adolescents with attention deficits.

Alpha interbrain synchrony during mediated interpersonal touch.

Interpersonal touch plays a crucial role in human communication, development, and wellness. Mediated interpersonal touch (MIT), a technology to distance or virtually simulated interpersonal touch, has received significant attention to counteract the negative consequences of touch deprivation. Studies investigating the effectiveness of MIT have primarily focused on self-reporting or behavioral correlates. It is largely unknown how MIT affects neural processes such as interbrain functional connectivity during human interactions. Given how users exchange haptic information simultaneously during interpersonal touch, interbrain functional connectivity provides a more ecologically valid way of studying the neural correlates associated with MIT. In this study, a palm squeeze task is designed to examine interbrain synchrony associated with MIT using EEG-based hyperscanning methodology. The phase locking value (PLV) index is used to measure interbrain synchrony. Results demonstrate that MIT elicits a significant increase in alpha interbrain synchronization between participants' brains. Especially, there was a significant difference in the alpha PLV indices between no MIT and MIT conditions in the early stage (130-470 ms) of the interaction period (t-test, p < 0.05). Given the role that alpha interbrain synchrony plays during social interaction, a significant increase in PLV index during MIT interaction seems to indicate an effect of social coordination. The findings and limitations of this study are further discussed, and perspectives on future research are provided.

Neurovascular Coupling Analysis Based on Multivariate Variational Gaussian Process Convergent Cross-Mapping.

Neurovascular coupling (NVC) provides important insights into the intricate activity of brain functioning and may aid in the early diagnosis of brain diseases. Emerging evidences have shown that NVC could be assessed by the coupling between electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS). However, this endeavor presents significant challenges due to the absence of standardized methodologies and reliable techniques for coupling analysis of these two modalities. In this study, we introduced a novel method, i.e., the collaborative multi-output variational Gaussian process convergent cross-mapping (CMVGP-CCM) approach to advance coupling analysis of EEG and fNIRS. To validate the robustness and reliability of the CMVGP-CCM method, we conducted extensive experiments using chaotic time series models with varying noise levels, sequence lengths, and causal driving strengths. In addition, we employed the CMVGP-CCM method to explore the NVC between EEG and fNIRS signals collected from 26 healthy participants using a working memory (WM) task. Results revealed a significant causal effect of EEG signals, particularly the delta, theta, and alpha frequency bands, on the fNIRS signals during WM. This influence was notably observed in the frontal lobe, and its strength exhibited a decline as cognitive demands increased. This study illuminates the complex connections between brain electrical activity and cerebral blood flow, offering new insights into the underlying NVC mechanisms of WM.

Discriminating orientation information with phase consistency in alpha and low-gamma frequency bands: an EEG study.

Recent studies suggest that noninvasive imaging methods (EEG, MEG) in the human brain scalp can decode the content of visual features information (orientation, color, motion, etc.) in Visual-Working Memory (VWM). Previous work demonstrated that with the sustained low-frequency Event-Related Potential (ERP under 6 Hz) of scalp EEG distributions, it is possible to accurately decode the content of orientation information in VWM during the delay interval. In addition, previous studies showed that the raw data captured by a combination of the occi-parietal electrodes could be used to decode the orientation. However, it is unclear whether the orientation information is available in other frequency bands (higher than 6 Hz) or whether this information is feasible with fewer electrodes. Furthermore, the exploration of orientation information in the phase values of the signal has not been well-addressed. In this study, we propose that orientation information is also accessible through the phase consistency of the occipital region in the alpha band frequency. Our results reveal a significant difference between orientations within 200 ms after stimulus offset in early visual sensory processing, with no apparent effect in power and Event-Related Oscillation (ERO) during this period. Additionally, in later periods (420-500 ms after stimulus offset), a noticeable difference is observed in the phase consistency of low gamma-band activity in the occipital area. Importantly, our findings suggest that phase consistency between trials of the orientation feature in the occipital alpha and low gamma-band can serve as a measure to obtain orientation information in VWM. Furthermore, the study demonstrates that phase consistency in the alpha and low gamma band can reflect the distribution of orientation-selective neuron numbers in the four main orientations in the occipital area.

The relationship between T7-Fz alpha coherence and peak performance in self-paced sports: a meta-analytical review.

We examined whether the alpha-band coherence between the T7-Fz (verbal analytical-motor planning) brain areas were related to superior performance in sports. We searched for related papers across eight databases: ProQuest Central, ProQuest Psychology Journals, PsycARTICLES, PsycINFO, SPORTDiscus, MEDLINE, Scopus, and Web of Science using relevant keywords (i.e., EEG AND sports AND coherence). Seven studies, with a total of 194 participants, met our inclusion criteria and were shortlisted for statistical analysis. We compared EEG coherence data for both within-subject and between-subject experimental designs. Our analysis revealed that athletes had lower coherence in the T7-Fz brain pathway for alpha- band activation (Hedges' g = - 0.54; p = 0.03) when performing better. Theoretically, these results corroborate the notion that athletes become more "neurally efficient" as the verbal and motor areas of their brains function more independently, i.e., the neural efficiency hypothesis. Accordingly, athletes who can limit verbal interference are more likely to perform a sporting task successfully.

Neural oscillations guiding action during effects imagery.

Goal-directed acting requires the integration of sensory information but can also be performed without direct sensory input. Examples of this can be found in sports and can be conceptualized by feedforward processes. There is, however, still a lack of understanding of the temporal neural dynamics and neuroanatomical structures involved in such processes. In the current study, we used EEG beamforming methods and examined 37 healthy participants in two well-controlled experiments varying the necessity of anticipatory processes during goal-directed action. We found that alpha and beta activity in the medial and posterior cingulate cortex enabled feedforward predictions about the position of an object based on the latest sensorimotor state. On this basis, theta band activity seems more related to sensorimotor representations, while beta band activity would be more involved in setting up the structure of the neural representations themselves. Alpha band activity in sensory cortices reflects an intensified gating of the anticipated perceptual consequences of the to-be-executed action. Together, the findings indicate that goal-directed acting through the anticipation of the predicted state of an effector is based on accompanying processes in multiple frequency bands in midcingulate and sensory brain regions.

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

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

Alterations of the alpha rhythm in visual snow syndrome: a case-control study.

BACKGROUND: Visual snow syndrome is a disorder characterized by the combination of typical perceptual disturbances. The clinical picture suggests an impairment of visual filtering mechanisms and might involve primary and secondary visual brain areas, as well as higher-order attentional networks. On the level of cortical oscillations, the alpha rhythm is a prominent EEG pattern that is involved in the prioritisation of visual information. It can be regarded as a correlate of inhibitory modulation within the visual network. METHODS: Twenty-one patients with visual snow syndrome were compared to 21 controls matched for age, sex, and migraine. We analysed the resting-state alpha rhythm by identifying the individual alpha peak frequency using a Fast Fourier Transform and then calculating the power spectral density around the individual alpha peak (+/- 1 Hz). We anticipated a reduced power spectral density in the alpha band over the primary visual cortex in participants with visual snow syndrome. RESULTS: There were no significant differences in the power spectral density in the alpha band over the occipital electrodes (O1 and O2), leading to the rejection of our primary hypothesis. However, the power spectral density in the alpha band was significantly reduced over temporal and parietal electrodes. There was also a trend towards increased individual alpha peak frequency in the subgroup of participants without comorbid migraine. CONCLUSIONS: Our main finding was a decreased power spectral density in the alpha band over parietal and temporal brain regions corresponding to areas of the secondary visual cortex. These findings complement previous functional and structural imaging data at a electrophysiological level. They underscore the involvement of higher-order visual brain areas, and potentially reflect a disturbance in inhibitory top-down modulation. The alpha rhythm alterations might represent a novel target for specific neuromodulation. TRIAL REGISTRATION: we preregistered the study before preprocessing and data analysis on the platform osf.org (DOI: https://doi.org/10.17605/OSF.IO/XPQHF , date of registration: November 19th 2022).

The effect of age on alpha rhythms in the human brain derived from source localized resting-state electroencephalography.

With increasing age, peak alpha frequency (PAF) is slowed, and alpha power is reduced during resting-states with eyes closed. These age-related changes are evident across the whole scalp but remained unclear at the source level. The purpose of this study was to determine whether age impacts the power and frequency of the dominant alpha rhythm equally across source generators or whether the impact of age varies across sources. A total of 28 young adults and 26 elderly adults were recruited. High-density EEG was recorded for 10 mins with eyes closed. Single dipoles for each independent component were localized and clustered based on their anatomical label, resulting in 36 clusters. Meta-analyses were then conducted to assess effect sizes for PAF and power at PAF for all 36 clusters. Subgroup analyses were then implemented for frontal, sensorimotor, parietal, temporal, and occipital regions. The results of the meta-analyses showed that the elderly group exhibited slower PAF and less power at PAF compared to the young group. Subgroup analyses revealed age effects on PAF in parietal (g = 0.38), temporal (g = 0.65), and occipital regions (g = 1.04), with the largest effects observed in occipital regions. For power at PAF, age effects were observed in sensorimotor (g = 0.84) and parietal regions (g = 0.80), with the sensorimotor region showing the largest effect. Our findings show that age-related slowing and attenuation of the alpha rhythm manifests differentially across cortical regions, with sensorimotor and occipital regions most susceptible to age effects.

Functionally annotated electrophysiological neuromarkers of healthy ageing and memory function.

The unprecedented increase in life expectancy presents a unique opportunity and the necessity to explore both healthy and pathological aspects of ageing. Electroencephalography (EEG) has been widely used to identify neuromarkers of cognitive ageing due to its affordability and richness in information. However, despite the growing volume of data and methodological advancements, the abundance of contradictory and non-reproducible findings has hindered clinical translation. To address these challenges, our study introduces a comprehensive workflow expanding on previous EEG studies and investigates various static and dynamic power and connectivity estimates as potential neuromarkers of cognitive ageing in a large dataset. We also assess the robustness of our findings by testing their susceptibility to band specification. Finally, we characterise our findings using functionally annotated brain networks to improve their interpretability and multi-modal integration. Our analysis demonstrates the effect of methodological choices on findings and that dynamic rather than static neuromarkers are not only more sensitive but also more robust. Consequently, they emerge as strong candidates for cognitive ageing neuromarkers. Moreover, we were able to replicate the most established EEG findings in cognitive ageing, such as alpha oscillation slowing, increased beta power, reduced reactivity across multiple bands, and decreased delta connectivity. Additionally, when considering individual variations in the alpha band, we clarified that alpha power is characteristic of memory performance rather than ageing, highlighting its potential as a neuromarker for cognitive ageing. Finally, our approach using functionally annotated source reconstruction allowed us to provide insights into domain-specific electrophysiological mechanisms underlying memory performance and ageing. HIGHLIGHTS: We provide an open and reproducible pipeline with a comprehensive workflow to investigate static and dynamic EEG neuromarkers. Neuromarkers related to neural dynamics are sensitive and robust. Individualised alpha power characterises cognitive performance rather than ageing. Functional annotation allows cross-modal interpretation of EEG findings.

The relationship between cerebral asymmetry and measures of psychopathy in a non-clinical sample is moderated by both empathic challenge and biological sex.

This study investigated the relationship between psychopathy, as assessed by the Levenson Self-Report Psychopathy (LSRP) scale, and cerebral laterality. EEG recordings from frontal cortex (L3 and L4) were taken during both resting conditions and while viewing a video of an emergency field amputation, used as an empathic challenge. The ratio of alpha power from the two recording site was taken as an index of relative activity in the two hemispheres. Eighty three students from the University subject pool were recruited as participants. Male participants had a significantly higher mean LSRP score than did female participants. While LSRP scores were unrelated to cerebral laterality under resting conditions, there was both a significant linear and quadratic negative relationship between LSRP scores and relative left-hemisphere alpha activity. As alpha activity has been reported to be inversely related to brain or mental activity, a negative relationship can be inferred between LSRP scores and right hemisphere neural activity. The female participants had a much stronger quadratic relationship than did the combined sample, while the male sample showed only weak, non-significant relationships. Our data suggest that the relationship between psychopathy and cerebral laterality may be sexually dimorphic.

Revisiting alpha resting state dynamics underlying hallucinatory vulnerability: Insights from Hidden semi-Markov Modeling.

BACKGROUND: Resting state (RS) brain activity is inherently non-stationary. Hidden semi-Markov Models (HsMM) can characterize continuous RS data as a sequence of recurring and distinct brain states along with their spatio-temporal dynamics. NEW METHOD: Recent explorations suggest that HsMM state dynamics in the alpha frequency band link to auditory hallucination proneness (HP) in non-clinical individuals. The present study aimed to replicate these findings to elucidate robust neural correlates of hallucinatory vulnerability. Specifically, we aimed to investigate the reproducibility of HsMM states across different data sets and within-data set variants as well as the replicability of the association between alpha brain state dynamics and HP. RESULTS: We found that most brain states are reproducible in different data sets, confirming that the HsMM characterized robust and generalizable EEG RS dynamics on a sub-second timescale. Brain state topographies and temporal dynamics of different within-data set variants showed substantial similarities and were robust against reduced data length and number of electrodes. However, the association with HP was not directly reproducible across data sets. COMPARISON WITH EXISTING METHODS: The HsMM optimally leverages the high temporal resolution of EEG data and overcomes time-domain restrictions of other state allocation methods. CONCLUSION: The results indicate that the sensitivity of brain state dynamics to capture individual variability in HP may depend on the data recording characteristics and individual variability in RS cognition, such as mind wandering. Future studies should consider that the order in which eyes-open and eyes-closed RS data are acquired directly influences an individual's attentional state and generation of spontaneous thoughts, and thereby might mediate the link to hallucinatory vulnerability.

Disentangling periodic and aperiodic resting EEG correlates of personality.

Previous studies of resting electroencephalography (EEG) correlates of personality traits have conflated periodic and aperiodic sources of EEG signals. Because these are associated with different underlying neural dynamics, disentangling them can avoid measurement confounds and clarify findings. In a large sample (n = 300), we investigated how disentangling these activities impacts findings related to two research programs within personality neuroscience. In Study 1 we examined associations between Extraversion and two putative markers of reward sensitivity-Left Frontal Alpha asymmetry (LFA) and Frontal-Posterior Theta (FPT). In Study 2 we used machine learning to predict personality trait scores from resting EEG. In both studies, power within each EEG frequency bin was quantified as both total power and separate contributions of periodic and aperiodic activity. In Study 1, total power LFA and FPT correlated negatively with Extraversion (r ∼ -0.14), but there was no relation when LFA and FPT were derived only from periodic activity. In Study 2, all Big Five traits could be decoded from periodic power (r ∼ 0.20), and Agreeableness could also be decoded from total power and from aperiodic indices. Taken together, these results show how separation of periodic and aperiodic activity in resting EEG may clarify findings in personality neuroscience. Disentangling these signals allows for more reliable findings relating to periodic EEG markers of personality, and highlights novel aperiodic markers to be explored in future research.

Extracting Stress-Related EEG Patterns From Pre-Sleep EEG for Forecasting Slow-Wave Sleep Deficiency.

Sleep is vital to our daily activity. Lack of proper sleep can impair functionality and overall health. While stress is known for its detrimental impact on sleep quality, the precise effect of pre-sleep stress on subsequent sleep structure remains unknown. This study introduced a novel approach to study the pre-sleep stress effect on sleep structure, specifically slow-wave sleep (SWS) deficiency. To achieve this, we selected forehead resting EEG immediately before and upon sleep onset to extract stress-related neurological markers through power spectra and entropy analysis. These markers include beta/delta correlation, alpha asymmetry, fuzzy entropy (FuzzEn) and spectral entropy (SpEn). Fifteen subjects were included in this study. Our results showed that subjects lacking SWS often exhibited signs of stress in EEG, such as an increased beta/delta correlation, higher alpha asymmetry, and increased FuzzEn in frontal EEG. Conversely, individuals with ample SWS displayed a weak beta/delta correlation and reduced FuzzEn. Finally, we employed several supervised learning models and found that the selected neurological markers can predict subsequent SWS deficiency. Our investigation demonstrated that the classifiers could effectively predict varying levels of slow-wave sleep (SWS) from pre-sleep EEG segments, achieving a mean balanced accuracy surpassing 0.75. The SMOTE-Tomek resampling method could improve the performance to 0.77. This study suggests that stress-related neurological markers derived from pre-sleep EEG can effectively predict SWS deficiency. Such information can be integrated with existing sleep-improving techniques to provide a personalized sleep forecasting and improvement solution.

Frontal alpha asymmetry is associated with chronic stress and depression, but not with somatoform disorders.

Cardinal characteristics of somatoform disorders (SFDs) are worry of illness, and impaired affective processing. We used relative frontal alpha asymmetry (FAA), a method to measure functional lateralization of affective processing, to investigate psychobiological correlates of SFDs. With alpha activity being inversely related to cortical network activity, relative FAA refers to alpha activity on the right frontal lobe minus alpha activity on the left frontal lobe. Less relative left frontal activity, reflected by negative FAA scores, is associated with lower positive and greater negative affectivity, such as observed in depression. Due to its negative affective component (illness anxiety), we expected to find less relative left frontal activity pattern in SFDs, and positive associations with self-reported chronic stress and depression symptoms. We recorded resting-state EEG activity with 64 electrodes, placed in a 10-10 system in 26 patients with a primary SFD, 23 patients with a major depressive disorder and 25 healthy control participants. The groups did not differ in FAA. Nevertheless, across all participants, less relative left frontal activity was associated with chronic stress and depression symptoms. We concluded that FAA may not serve as an indicator of SFDs. As the relationship of FAA and depressive symptoms was fully mediated by chronic stress, future studies have to clarify whether the association between FAA and chronic stress may represent a shared underlying factor for the manifestation of mental health complaints, such as depression.

Live vs video interaction: sensorimotor and visual cortical oscillations during action observation.

Increasingly, in the field of communication, education, and business, people are switching to video interaction, and interlocutors frequently complain that the perception of nonverbal information and concentration suffer. We investigated this issue by analyzing electroencephalogram (EEG) oscillations of the sensorimotor (mu rhythm) and visual (alpha rhythm) cortex of the brain in an experiment with action observation live and on video. The mu rhythm reflects the activity of the mirror neuron system, and the occipital alpha rhythm shows the level of visual attention. We used 32-channel EEG recorded during live and video action observation in 83 healthy volunteers. The ICA method was used for selecting the mu- and alpha-components; the Fourier Transform was used to calculate the suppression index relative to the baseline (stationary demonstrator) of the rhythms. The main range of the mu rhythm was indeed sensitive to social movement and was highly dependent on the conditions of interaction-live or video. The upper mu-range appeared to be less sensitive to the conditions, but more sensitive to different movements. The alpha rhythm did not depend on the type of movement; however, a live performance initially caused a stronger concentration of visual attention. Thus, subtle social and nonverbal perceptions may suffer in remote video interactions.

Alpha event-related decreases during encoding in adults with ADHD - An investigation of sustained attention and working memory processes.

BACKGROUND: Executive functioning deficits are central to established neuropsychological models of ADHD. Oscillatory activity, particularly the alpha rhythm (8-12 Hz) has been associated with cognitive impairments in ADHD. However, most studies to date examined such neural mechanisms underlying executive dysfunction in children and adolescents with ADHD, raising the question of whether and to what extent those ADHD-related working memory impairments are still present in adults. To this end, the current study aimed to investigate the role of alpha event-related decreases (ERD) during working memory processes in adults with and without ADHD. METHODS: We collected electroencephalographic (EEG) data from 85 adults with a lifetime diagnosis of ADHD and 105 controls (aged 32-64), while they performed a continuous performance (CPT) and a spatial delayed response working memory task (SDRT). Time-frequency and independent component analysis (ICA) was used to identify alpha (8-12 Hz) clusters to examine group and condition effects during the temporal profile of sustained attention and working memory processes (encoding, maintenance, retrieval), loads (low and high) and trial type (go and nogo). RESULTS: Individuals with ADHD exhibited higher reaction time-variability in SDRT, and slower response times in SDRT and CPT, despite no differences in task accuracy. Although working memory load was associated with stronger alpha ERD in both tasks and both groups (ADHD, controls), we found no consistent evidence for attenuated alpha ERD in adults with ADHD, failing to replicate effects reported in children. In contrast, when looking at the whole sample, the correlations of alpha power during encoding with inattention and hyperactivity-impulsivity symptoms were significant, replicating prior findings in children with ADHD, but suggesting an alternate source for these effects in adults. CONCLUSIONS: Our results corroborate the robustness of alpha as a marker of visual attention and suggest that occipital alpha ERD normalizes in adulthood, but with unique contributions of centro-occipital alpha ERD, suggesting a secondary source. This implies that deviations in processes other than previously reported visuospatial cortex engagement may account for the persistent symptoms and cognitive deficits in adults with a history of ADHD.