EEG Oscillations Research Articles

Involvement of muscarinic acetylcholine receptor-mediated cholinergic neurotransmission in TMS–EEG responses

The combination of transcranial magnetic stimulation and electroencephalography (TMS–EEG) is emerging as a valuable tool for investigating brain functions in health and disease. However, the detailed neural mechanisms underlying TMS–EEG responses, including TMS-evoked EEG potentials (TEPs) and TMS-induced EEG oscillations (TIOs), remain largely unknown. Combining TMS–EEG with pharmacological interventions provides a unique opportunity to elucidate the roles of specific receptor-mediated neurotransmissions in these responses. Here, we investigated the involvement of muscarinic acetylcholine receptor (mAChR)-mediated cholinergic neurotransmission in TMS–EEG responses by evaluating the effects of mAChR antagonists on TEPs and TIOs in twenty-four healthy participants using a randomized, placebo-controlled crossover design. TEPs and TIOs were measured before and after administering a single oral dose of scopolamine (a non-selective mAChR antagonist), biperiden (an M1 mAChR antagonist), or placebo, with TMS targeting the left medial prefrontal cortex (mPFC), angular gyrus (AG), and supplementary motor area (SMA). The results indicated that mAChR-mediated cholinergic neurotransmission played a role in TEPs, but not TIOs, in a target-specific manner. Specifically, scopolamine significantly increased the amplitude of a local TEP component between approximately 40 and 63 ms post-stimulus when TMS was applied to the SMA, but not the mPFC or AG. Biperiden produced a similar but less pronounced effect. Importantly, the effects of these mAChR antagonists on TEPs were independent of those on sensory-evoked EEG potentials caused by TMS-associated sensory stimulation. These findings expand our understanding of TMS–EEG physiology, providing insights for its application in physiological and clinical research.

Music therapy with adult burn patients in the intensive care unit: short-term analysis of electrophysiological signals during music-assisted relaxation

Burn patients often face elevated pain, anxiety, and depression levels. Music therapy adds to integrative care in burn patients, but research including electrophysiological measures is limited. This study reports electrophysiological signals analysis during Music-Assisted Relaxation (MAR) with burn patients in the Intensive Care Unit (ICU). This study is a sub-analysis of an ongoing trial of music therapy with burn patients in the ICU. Electroencephalogram (EEG), electrocardiogram (ECG), and electromyogram (EMG) were recorded during MAR with nine burn patients. Additionally, background pain levels (VAS) and anxiety and depression levels (HADS) were assessed. EEG oscillation power showed statistically significant changes in the delta (p < 0.05), theta (p = 0.01), beta (p < 0.05), and alpha (p = 0.05) bands during music therapy. Heart rate variability tachograms high-frequencies increased (p = 0.014), and low-frequencies decreased (p = 0.046). Facial EMG mean frequency decreased (p = 0.01). VAS and HADS scores decreased − 0.76 (p = 0.4) and − 3.375 points (p = 0.37) respectively. Our results indicate parasympathetic system activity, attention shifts, reduced muscle tone, and a relaxed state of mind during MAR. This hints at potential mechanisms of music therapy but needs to be confirmed in larger studies. Electrophysiological changes during music therapy highlight its clinical relevance as a complementary treatment for ICU burn patients.Trial registration: Clinicaltrials.gov (NCT04571255). Registered September 24th, 2020. https//classic.clinicaltrials.gov/ct2/show/NCT04571255.

EEG Oscillations in Recent Suicide Attempters: Assessing Responses to Positive and Negative Future Imagination Tasks

Background: Our goal is to uncover Electroencephalography (EEG) power spectrum patterns during imagination tasks in individuals who attempted suicide within the past 1-4 weeks, addressing gaps in understanding the neural correlates of future imagination in suicidal behavior. Methods: This case-control study comprised a total of 60 participants, consisting of 47 females and 13 males. The sample comprised three groups: Attempted Suicide + Major Depressive Disorder (SA+MDD), Major Depressive Disorder (MDD), and Healthy Controls (HC). To assess participants' future imagination, a unique approach called the Positive and Negative Future Imagination Task was designed, which involved scenario visualization concurrent with EEG recording. Statistical analyses included ANOVA with post-hoc pairwise comparisons to compare EEG power spectrum between three groups. Results: It was observed that the SA+MDD group experienced significantly increased theta frequency band in the right frontocentral regions when compared to the MDD group during both positive and negative imagination tasks (P-value< 0.05). Furthermore, increased gamma activity was observed in the SA+MDD group compared to the HC group, predominantly in the right frontocentral areas during both imagination tasks. Conclusion: The results of this study indicate that individuals who have recently attempted suicide exhibit heightened neural activity in the frontocentral regions of the right hemisphere of the brain, specifically in theta and gamma band frequencies, when contemplating both positive and negative aspects of the future. These findings, in the context of behavioral tasks may indicate a decrease in the ability to envision a positive future and an increase in visualizing a negative future.

Oscillatory and nonoscillatory sleep electroencephalographic biomarkers of the epileptic network.

In addition to the oscillatory brain activity, the nonoscillatory (scale-free) components of the background electroencephalogram (EEG) may provide further information about the complexity of the underlying neuronal network. As epilepsy is considered a network disease, such scale-free metrics might help to delineate the epileptic network. Here, we performed an analysis of the sleep oscillatory (spindle, slow wave, and rhythmic spectral power) and nonoscillatory (H exponent) intracranial EEG using multiple interictal features to estimate whether and how they deviate from normalcy in 38 adults with drug-resistant epilepsy. To quantify intracranial EEG abnormalities within and outside the seizure onset areas, patients' values were adjusted based on normative maps derived from the open-access Montreal Neurological Institute open iEEG Atlas. In a subset of 29 patients who underwent resective surgery, we estimated the predictive value of these features to identify the epileptogenic zone in those with a good postsurgical outcome. We found that distinct sleep oscillatory and nonoscillatory metrics behave differently across the epileptic network, with the strongest differences observed for (1) a reduction in spindle activity (spindle rates and rhythmic sigma power in the 10-16 Hz band), (2) a higher rhythmic gamma power (30-80 Hz), and (3) a higher H exponent (steeper 1/f slope). As expected, epileptic spikes were also highest in the seizure onset areas. Furthermore, in surgical patients, the H exponent achieved the highest performance (balanced accuracy of .76) for classifying resected versus nonresected channels in good outcome patients. This work suggests that nonoscillatory components of the intracranial EEG signal could serve as promising interictal sleep candidates of epileptogenicity in patients with drug-resistant epilepsy. Our findings further advance the understanding of epilepsy as a disease, whereby absence or loss of sleep physiology may provide information complementary to pathological epileptic processes.

Enhanced network synchronization connectivity following transcranial direct current stimulation (tDCS) in bipolar depression: Effects on EEG oscillations and deep learning-based predictors of clinical remission

AimTo investigate oscillatory networks in bipolar depression, effects of a home-based tDCS treatment protocol, and potential predictors of clinical response. Methods20 participants (14 women) with bipolar disorder, mean age 50.75 ± 10.46 years, in a depressive episode of severe severity (mean Montgomery-Åsberg Rating Scale (MADRS) score 24.60 ± 2.87) received home-based transcranial direct current stimulation (tDCS) treatment for 6 weeks. Clinical remission defined as MADRS score < 10. Resting-state EEG data were acquired at baseline, prior to the start of treatment, and at the end of treatment, using a portable 4-channel EEG device (electrode positions: AF7, AF8, TP9, TP10). EEG band power was extracted for each electrode and phase locking value (PLV) was computed as a functional connectivity measure of phase synchronization. Deep learning was applied to pre-treatment PLV features to examine potential predictors of clinical remission. ResultsFollowing treatment, 11 participants (9 women) attained clinical remission. A significant positive correlation was observed with improvements in depressive symptoms and delta band PLV in frontal and temporoparietal regional channel pairs. An interaction effect in network synchronization was observed in beta band PLV in temporoparietal regions, in which participants who attained clinical remission showed increased synchronization following tDCS treatment, which was decreased in participants who did not achieve clinical remission. Main effects of clinical remission status were observed in several PLV bands: clinical remission following tDCS treatment was associated with increased PLV in frontal and temporal regions and in several frequency bands, including delta, theta, alpha and beta, as compared to participants who did not achieve clinical remission. The highest deep learning prediction accuracy 69.45 % (sensitivity 71.68 %, specificity 66.72 %) was obtained from PLV features combined from theta, beta, and gamma bands. ConclusionstDCS treatment enhances network synchronization, potentially increasing inhibitory control, which underscores improvement in depressive symptoms. Baseline EEG-based measures might aid predicting clinical response.

Dissociable Decoding of Predictive Sensory Processing from EEG Oscillations

Dissociable Decoding of Predictive Sensory Processing from EEG Oscillations

The cognitive triad network - oscillation - behaviour links individual differences in EEG theta frequency with task performance and effective connectivity

We reconcile two significant lines of Cognitive Neuroscience research: the relationship between the structural and functional architecture of the brain and behaviour on the one hand and the functional significance of oscillatory brain processes to behavioural performance on the other. Network neuroscience proposes that the three elements, behavioural performance, EEG oscillation frequency, and network connectivity should be tightly connected at the individual level. Young and old healthy adults were recruited as a proxy for performance variation. An auditory inhibitory control task was used to demonstrate that task performance correlates with the individual EEG frontal theta frequency. Older adults had a significantly slower theta frequency, and both theta frequency and task performance correlated with the strengths of two network connections that involve the main areas of inhibitory control and speech processing. The results suggest that both the recruited functional network and the oscillation frequency induced by the task are specific to the task, are inseparable, and mark individual differences that directly link structure and function to behaviour in health and disease.

Electroencephalogram-Based Anesthesia Indices Differently React to Modulations of Alpha-Oscillatory Activity.

The electroencephalographic (EEG) provides the anesthesiologist with information regarding the level of anesthesia. Processed EEG indices are available that reflect the level of anesthesia as a single number. Strong oscillatory EEG activity in the alpha-band may be associated with an adequate level of anesthesia and a lower incidence of cognitive sequelae. So far, we do not know how the processed indices would react to changes in the alpha-band activity. Hence, we modulated the alpha-oscillatory activity of intraoperative EEG to assess possible index changes. We performed our analyses based on data from 2 studies. Intraoperative EEG was extracted, and we isolated the alpha-band activity by band-pass filtering (8-12 Hz). We added or subtracted this activity to the original EEG in different steps with different amplifications of the alpha signal. We then replayed these signals to the bispectral index (BIS), the Entropy Module (state entropy [SE]), the CONOX (qCON), and the SEDLine (patient state index [PSI]); and evaluated the alpha-band modulation's impact on the respective index. The indices behaved differently to the modulation. In general, indices decreased with stronger alpha-band activity, but the rate of change was different with SE showing the strongest change (9% per step) and PSI and BIS (<5% per step) showing the weakest change. A simple regression analysis revealed a decrease of 0.02 to 0.09 index points with increasing alpha amplification. While the alpha-band in the intraoperative EEG seems to carry information regarding the quality of anesthesia, changes in the alpha-band activity do neither strongly nor uniformly influence processed EEG indices. Hence, to assess alpha-oscillatory activity's strength, the user needs to focus on the raw EEG or its spectral representation also displayed on the monitoring systems.

Brain wave modulation and EEG power changes during auditory beats stimulation

Auditory beats stimulation (ABS) has received increased attention for its potential to modulate neural oscillations through a phenomenon described as brain entrainment (i.e synchronization of brain’s electrocortical activity to external stimuli at a specific frequency). Recently, a new form of ABS has emerged, inspired by isochronic tones stimulation (ITd).This study investigated neural oscillatory responses induced by ITd in comparison with formerly well-established ABS protocols, such as gamma-binaural beats (BB) and white noise (WN).We recorded the electroencephalographic brain activity in 28 participants during 4 min of BB, ITd, and WN presentation.Data demonstrated that while both BB and WN enhanced oscillatory power on the EEG gamma band, consistently with the expected brain entrainment effect, ITd yielded greater changes in EEG power (p < 0.001). This was confirmed by time-based analysis, which showed a progressive increase in normalized EEG power within the ITd window compared to BB (p < 0.05). Findings also revealed that ITd elicited acute changes in the alpha band of EEG oscillations, through a progressive decrease in power over time, which was distinctly different from the pattern observed while listening BB and WN. Such dual alpha-gamma effects underline the promising and unique potential of ITd to modulate neural oscillations which selectively differ from BB and WN.This study contributes to the evolution of ABS research, highlighting the promise of ITd for cognitive enhancement and clinical applications.

Conflicting Sensory Information Sharpens the Neural Representations of Early Selective Visuospatial Attention.

Adaptive behaviors require the ability to resolve conflicting information caused by the processing of incompatible sensory inputs. Prominent theories of attention have posited that early selective attention helps mitigate cognitive interference caused by conflicting sensory information by facilitating the processing of task-relevant sensory inputs and filtering out behaviorally irrelevant information. Surprisingly, many recent studies that investigated the role of early selective attention on conflict mitigation have failed to provide positive evidence. Here, we examined changes in the selectivity of early visuospatial attention in male and female human subjects performing an attention-cueing Eriksen flanker task, where they discriminated the shape of a visual target surrounded by congruent or incongruent distractors. We used the inverted encoding model to reconstruct spatial representations of visual selective attention from the topographical patterns of amplitude modulations in alpha band oscillations in scalp EEG (∼8-12 Hz). We found that the fidelity of the alpha-based spatial reconstruction was significantly higher in the incongruent compared with the congruent condition. Importantly, these conflict-related modulations in the reconstruction fidelity occurred at a much earlier time window than those of the lateralized posterior event-related potentials associated with target selection and distractor suppression processes, as well as conflict-related modulations in the frontocentral negative-going wave and midline-frontal theta oscillations (∼3-7 Hz), thought to track executive control functions. Taken together, our data suggest that conflict resolution is supported by the cascade of neural processes underlying early selective visuospatial attention and frontal executive functions that unfold over time.

The stability of slow-wave sleep and EEG oscillations across two consecutive nights of laboratory polysomnography in cognitively normal older adults.

Laboratory polysomnography provides gold-standard measures of sleep physiology, but multi-night investigations are resource intensive. We assessed the night-to-night stability via reproducibility metrics for sleep macrostructure and electroencephalography oscillations in a group of cognitively normal adults attending two consecutive polysomnographies. Electroencephalographies were analysed using an automatic algorithm for detection of slow-wave activity, spindle and K-complex densities. Average differences between nights for sleep macrostructure, electroencephalography oscillations and sleep apnea severity were assessed, and test-retest reliability was determined using two-way intraclass correlations. Agreement was calculated using the smallest real differences between nights for all measures. Night 2 polysomnographies showed significantly greater time in bed, total sleep time (6.3 hr versus 6.8 hr, p < 0.001) and percentage of rapid eye movement sleep (17.5 versus 19.7, p < 0.001). Intraclass correlations were low for total sleep time, percentage of rapid eye movement sleep and sleep efficiency, moderate for percentage of slow-wave sleep and percentage of non-rapid eye movement 2 sleep, good for slow-wave activity and K-complex densities, and excellent for spindles and apnea-hypopnea index with hypopneas defined according to 4% oxygen desaturation criteria only. The smallest real difference values were proportionally high for most sleep macrostructure measures, indicating moderate agreement, and proportionally lower for most electroencephalography microstructure variables. Slow waves, K-complexes, spindles and apnea severity indices are highly reproducible across two consecutive nights of polysomnography. In contrast, sleep macrostructure measures all demonstrated poor reproducibility as indicated by low intraclass correlation values and moderate agreement. Although there were average differences in percentage of rapid eye movement sleep and total sleep time, these were numerically small and perhaps functionally or clinically less significant. One night of in-laboratory polysomnography is enough to provide stable, reproducible estimates of an individual's sleep concerning measures of slow-wave activity, spindles, K-complex densities and apnea severity.

Adaptive and Compensatory Neural Signatures in Fibromyalgia: An Analysis of Resting-State and Stimulus-Evoked EEG Oscillations.

This study aimed to investigate clinical and physiological predictors of brain oscillatory activity in patients with fibromyalgia (FM), assessing resting-state power, event-related desynchronization (ERD), and event-related synchronization (ERS) during tasks. We performed a cross-sectional analysis, including clinical and neurophysiological data from 78 subjects with FM. Multivariate regression models were built to explore predictors of electroencephalography bands. Our findings show a negative correlation between beta oscillations and pain intensity; fibromyalgia duration is positively associated with increased oscillatory power at low frequencies and in the beta band; ERS oscillations in the theta and alpha bands seem to be correlated with better symptoms of FM; fatigue has a signature in the alpha band-a positive relationship in resting-state and a negative relationship in ERS oscillations. Specific neural signatures lead to potential clusters of neural adaptation, in which beta oscillatory activity in the resting state represents a more adaptive activity when pain levels are low and stimulus-evoked oscillations at lower frequencies are likely brain compensatory mechanisms. These neurophysiological changes may help to understand the impact of long-term chronic pain in the central nervous system and the descending inhibitory system in fibromyalgia subjects.

Effects of Single-Session Practice Structure on Motor Skill Acquisition and Alpha and Beta EEG Oscillations

Background: Although it is known that practicing a motor skill updates the associated internal model, it is still unclear as to how cortical oscillations linked with the motor skill change under differing practice schedules. The current study investigated α- and β-power changes associated with motor skill acquisition. Objectives: Firstly, we investigated the behavioral effects of practice on motor learning and retention during repetitive (RP) and variable (VP) practice schedules on an anticipation timing task. Secondly, we investigated changes in cortical α (10 - 13 Hz) and β (15 - 30 Hz) event-related synchronization and desynchronization (ERS/ERD) under RP and VP during early (EP) and late (LP) stages of practice. Methods: To investigate the behavioral effects of practice on learning and retention, participants were pretested, post-tested at 5 min (retention), and tested twice at 30 min (one for longer retention, one for transfer to a novel velocity). To investigate electroencephalography (EEG) α and β power changes, data were collected from electrode sites T7, T8, C3, C4, CP3, CP4, FCz, AFz, and Pz. Results: Based on a 2 × 4 (practice group × test block) ANOVA, results indicated a significant learning effect for both group participants, with VP participants performing better on the 30-min transfer test. To investigate EEG α and β power changes, data were analyzed using separate, 2 × 2 repeated measures ANOVA (group [RP and VP] × practice trial blocks [EP and LP]). Power analyses revealed (1) attenuated α ERD at T7 (cognitive/verbal rehearsal), C3 (motor cortex), CP3, CP4, and FCz (pooled data representing premotor cortices), and AFz (frontal cortex and attentional processes) during LP, with greater changes observed in premotor activity (PMA), T7, and AFz electrode sites in RP participants. β frequency analysis, using beta modulation depth (BMD), revealed that participants in both groups had increased BMD at premotor, motor, and frontal electrode sites at LP, with RP participants exhibiting greater changes. Conclusions: Results are in accordance with previous research indicating that practicing under a VP schedule leads to superior motor skill transfer than practicing under an RP schedule. Moreover, lesser changes in α ERD along and lower BMD observed in VP participants might be responsible for a more adaptable and flexible motor program, allowing for greater skill retention and transfer in individuals practicing under VP conditions.

Development of EEG alpha and theta oscillations in the maintenance stage of working memory

Several studies have shown developmental changes in EEG oscillations during working memory tasks. Although the load-modulated theta and alpha activities in adults are well-documented, the findings are inconsistent if children possess the adult-like brain oscillations that are similarly modulated by memory load. The present study compares children’s and adults’ true theta and alpha EEG oscillations, separated from aperiodic components, in the maintenance stage of working memory. The EEG was recorded in 25 Chinese-speaking children (14 male, Mage = 9.4 yrs) and 31 adults (19 male, Mage = 20.8 yrs) in Hong Kong while they performed an n-back task that included four conditions differing in load (1- vs. 2-back) and stimulus type (Chinese character vs. visual pattern). The results show that aperiodic activities (i.e., broadband power and slope) during the maintenance stage in the n-back task were significantly higher in children than adults. The periodic theta and alpha oscillations also changed with age. More importantly, adults showed significant periodic theta increase with memory load, whereas such an effect was absent in children. Regardless of age, there was a significant alpha power decrease with load increase, and a significant theta power enhancement when maintaining visual patterns than Chinese characters. In adults, load-modulated alpha peak shift (towards higher frequency) was linked to higher behavioral efficiency in the n-back task. In children, higher load-modulated theta enhancement was linked to better behavioral efficiency. The findings suggest that the load-modulated theta power during working memory maintenance matures from childhood to adulthood.

A thin line between conflict and reaction time effects on EEG and fMRI brain signals

Abstract The last two decades of electrophysiological and neuroimaging research converged that the activity in the medial frontal cortex plays a pivotal role in cognitive control processes. Notably, the midfrontal theta (MFT) oscillatory EEG power as well as activity in the anterior midcingulate cortex (aMCC) or pre-supplementary motor area (preSMA) were consistently proclaimed as markers of conflict processing. However, these brain signals are strongly correlated with response time (RT) variability in various non-conflict tasks, which overshadows the true nature of their involvement. Our previous study (Beldzik et al., 2022) successfully identified these brain signals during a simultaneous EEG-fMRI experiment implementing Stroop and Simon tasks. Based on the assumption that overcoming the habitual prepotent response during high interference trials requires additional neural resources beyond simple decision variable represented in RTs, here we aim to verify if these markers exhibit a congruency effect beyond RT variations. Furthermore, we explored if these brain signals represent either proactive or reactive cognitive control mechanisms by investigating two widely known behavioral phenomena observed in conflict tasks: proportion congruency and congruency sequence effects. The results revealed partially null findings for MFT activity, yet a distinct cognitive control specialization between aMCC and preSMA. Our study provides novel evidence that the former is involved in proactive control mechanisms, possibly contingency learning, whereas the latter reflects reactive control mechanisms by exhibiting a strong congruency effect regardless of RT variation and responding to adaptive behavior.

Extended wakefulness alters the relationship between EEG oscillations and performance in a sustained attention task.

During drowsiness, maintaining consistent attention becomes difficult, leading to behavioural lapses. Bursts of oscillations in the electroencephalogram (EEG) might predict such lapses, given that alpha bursts increase during inattention and theta bursts increase with time spent awake. Paradoxically, however, alpha bursts decrease with time awake and theta bursts increase during focussed attention and cognitive tasks. Therefore, we investigated to what extent theta and alpha bursts predicted performance in a sustained attention task, either when well rested (baseline, BL) or following 20 h of extended wakefulness (EW). High-density EEG was measured in 18 young adults, and the timing of bursts was related to trial outcomes (fast, slow, and lapse trials). To increase the likelihood of lapses, the task was performed under soporific conditions. Against expectations, alpha bursts were more likely before fast trials and less likely before lapses at baseline, although the effect was substantially reduced during extended wakefulness. Theta bursts showed no significant relationship to behavioural outcome either at baseline or extended wakefulness. However, following exploratory analyses, we found that large-amplitude theta and alpha bursts were more likely to be followed by lapse trials during extended wakefulness but not baseline. In summary, alpha bursts during baseline anticipated better trial outcomes, whereas large-amplitude theta and alpha bursts during extended wakefulness anticipated worse outcomes. Therefore, neither theta nor alpha bursts maintain a consistent relationship with behaviour under different levels of overall vigilance.

414 Post-stroke Cognitive deficits are associated with reduced cognitive conflict evoked mid-frontal EEG theta oscillations and can be potentially improved with prefrontal transcranial electrical stimulation

OBJECTIVES/GOALS: Cognitive dysfunction and/or depressionfollowing ischemic stroke results in loss of independence in daily functioning. The objective of this work is to assess neural correlates of post-stroke cognitive deficits and the effect of left frontal transcranial electrical stimulation on cognitive control and associated brain rhythms. METHODS/STUDY POPULATION: We recorded midfrontal scalp EEG from 15 healthy and 13 participants with stroke while they performed a multi-source interference task (MSIT). The stroke cohort also performed additional MSIT sessions where they received active and sham transcranial direct current stimulation (tDCS) on the left prefrontal cortex (PFC). The EEG was pre-processed to get rid of eye movement and other channel noise artifacts and filtered to retain 0.5-55 Hz components. A Morlet wavelet was used to estimate power in theta (4-8 Hz), alpha (8-15 Hz) and gamma (35-50 Hz) frequency bands over a period of 2 seconds following MSIT image presentation. A generalized linear mixed effects model was used to find effect of group on behavior and EEG oscillations. A GLME was also used to find effects of active tDCS on behavior and EEG. RESULTS/ANTICIPATED RESULTS: We found Group (healthy v stroke) as a significant predictor of both response time (behavior) and conflict evoked theta power in the frontal channels (F1-Fz, F2-Fz). We also found that active tDCS significantly improved MSIT performance as compared to sham, after accounting for cognitive load. Active tDCS also induced low frequency oscillations in frontal EEG channels compared to sham. Preliminary results indicate that mid-frontal theta oscillations are a potential neural correlate of post-stroke cognitive deficit and tDCS of the left PFC might be a promising therapeutic intervention to ameliorate this. DISCUSSION/SIGNIFICANCE: Current therapeutic approaches often do not alleviate post stroke executive dysfunction, hence a better understanding of the brain network changes underlying such deficit can elucidate neural correlates of post stroke cognitive deficit to inform the development of neuromodulation interventions.

Personalized repetitive transcranial magnetic stimulation guided by the spectral electroencephalogram may enhance and democratize therapy for autism spectrum disorder

Autism spectrum disorder (ASD) is a genetically heterogeneous group of neurodevelopmental disorders that affect 1 in 36 children (CDC data) and have recognizable core deficits in common, including repetitive stereotyped behaviors and difficulties in social interaction and communication. Pharmacological interventions moderate some ASD comorbidities, but do not alleviate core deficits and have significant side effects. While many behavioral therapies are inadequate, a very intensive form called applied behavioral analysis (ABA) is demonstrably effective. ABA is based on graded progression and immediate feedback. ABA has raised concerns over its intensive nature and has triggered unease about being too harsh. One solution may derive from a widespread hypothesis of ASD pathogenesis, which posits that the brain in ASD is overexcited, i.e., excitation dominates over inhibition, and electroencephalographic (EEG) alpha band oscillatory activity is altered, which degrades sensory input and task management. This may also disrupt the brain mesolimbic dopaminergic reward cascade causing social interactions to be unrewarding, leading to deleterious social behavior and poor communication. We hypothesize that a comprehensive, personalized form of spectral EEG guided repetitive transcranial magnetic stimulation that we term PrTMS, can normalize alpha EEG oscillations, E/I balance, and dopaminergic reward signaling, to facilitate improved psychosocial behavior. The goal is for PrTMS to synergize with behavioral interventions, so that ABA for example, could be less intensive. This may hold the promise of making self-determination more readily attainable for ASD persons, and could also democratize ASD therapy by rendering it more affordable.

Role of GABAB receptors in cognition and EEG activity in aged APP and PS1 transgenic mice

Alzheimer's disease (AD) is the most common cause of dementia in the elderly. Recent evidence suggests that gamma-aminobutyric acid B (GABAB) receptor-mediated inhibition is a major contributor to AD pathobiology, and GABAB receptors have been hypothesized to be a potential target for AD treatment. The aim of this study is to determine how GABAB regulation alters cognitive function and brain activity in an AD mouse model. Early, middle and late stage (8–23 months) amyloid precursor protein (APP) and presenilin 1 (PS1) transgenic mice were used for the study. The GABAB agonist baclofen (1 and 2.5 mg/kg, i. p.) and the antagonist phaclofen (0.5 mg/kg, i. p.) were used. Primarily, we found that GABAB activation was able to improve spatial and/or working memory performance in early and late stage AD animals. In addition, GABAB activation and inhibition could regulate global and local EEG oscillations in AD animals, with activation mainly regulating low-frequency activity (delta-theta bands) and inhibition mainly regulating mid- and high-frequency activity (alpha-gamma bands), although the regulated magnitude at some frequencies was reduced in AD. The cognitive improvements in AD animals may be explained by the reduced EEG activity in the theta frequency band (2–4 Hz). This study provides evidence for a potential therapeutic effect of baclofen in the elderly AD brain and for GABAB receptor-mediated inhibition as a potential therapeutic target for AD.

Context Modulates Perceived Fairness in Altruistic Punishment: Neural Signatures from ERPs and EEG Oscillations.

Social norms and altruistic punitive behaviours are both based on the integration of information from multiple contexts. Individual behavioural performance can be altered by loss and gain contexts, which produce different mental states and subjective perceptions. In this study, we used event-related potential and time-frequency techniques to examine performance on a third-party punishment task and to explore the neural mechanisms underlying context-dependent differences in punishment decisions. The results indicated that individuals were more likely to reject unfairness in the context of loss (vs. gain) and to increase punishment as unfairness increased. In contrast, fairness appeared to cause an early increase in cognitive control signal enhancement, as indicated by the P2 amplitude and theta oscillations, and a later increase in emotional and motivational salience during decision-making in gain vs. loss contexts, as indicated by the medial frontal negativity and beta oscillations. In summary, individuals were more willing to sanction violations of social norms in the loss context than in the gain context and rejecting unfair losses induced more equity-related cognitive conflict than accepting unfair gains, highlighting the importance of context (i.e., gain vs. loss) in equity-related social decision-making processes.