On the Physiological Modulation and Potential Mechanisms Underlying Parieto-Occipital Alpha Oscillations

A comprehensive investigation of intracortical and corticothalamic models of the alpha rhythm

The electroencephalographic alpha rhythm is one of the most robustly observed and widely studied empirical phenomena in all of neuroscience. However, despite its extensive implication in a wide range of cognitive processes and clinical pathologies, the mechanisms underlying alpha generation in neural circuits remain poorly understood. In this paper we offer a renewed foundation for research on this question, by undertaking a systematic comparison and synthesis of the most prominent theoretical models of alpha rhythmogenesis in the published literature. We focus on four models, each studied intensively by multiple authors over the past three decades: (i) Jansen-Rit, (ii) Moran-David-Friston, (iii) Robinson-Rennie-Wright, and (iv) Liley-Wright. Several common elements are identified, such as the use of second-order differential equations and sigmoidal potential-to-rate operators to represent population-level neural activity. Major differences are seen in other features such as wiring topologies and conduction delays. Through a series of mathematical analyses and numerical simulations, we nevertheless demonstrate that the selected models can be meaningfully compared, by associating parameters and circuit motifs of analogous biological significance. With this established, we conduct explorations of rate constant and synaptic connectivity parameter spaces, with the aim of identifying common patterns in key behaviours, such as the role of excitatory-inhibitory interactions in the generation of oscillations. Finally, using linear stability analysis we identify two qualitatively different alpha-generating dynamical regimes across the models: (i) noise-driven fluctuations and (ii) self-sustained limit-cycle oscillations, emerging due to an Andronov-Hopf bifurcation. The comprehensive survey and synthesis developed here can, we suggest, be used to help guide future theoretical and experimental work aimed at disambiguating these and other candidate theories of alpha rhythmogenesis.

Neural sensitivity to the heartbeat is modulated by spontaneous fluctuations in subjective arousal during wakeful rest

Spontaneous thoughts, occupying much of one's awake time in daily time, are often colored by emotional qualities. While spontaneous thoughts have been associated with various neural correlates, the relationship between subjective qualities of ongoing experiences and the brain's sensitivity to bodily signals (i.e., interoception) remains largely unexplored. Given the well-established role of interoception in emotion, clarifying this relationship may elucidate how processes relevant to mental health, such as arousal and anxiety, are regulated. We used EEG and ECG to measure the heartbeat evoked potential (HEP), an index of interoceptive processing, while 51 adult participants (34 male, 20 female) visually fixated on a cross image and let their minds wander freely. At pseudo-random intervals, participants reported their momentary level of arousal. This measure of subjective arousal was highly variable within and between individuals but was statistically unrelated to several markers of physiological arousal, including heart rate, heart rate variability, time on task, and EEG alpha power at posterior electrodes. A cluster-based permutation analysis revealed that the HEP amplitude was increased during low relative to high subjective arousal in a set of frontal electrodes during the 0.328 s - 0.364 s window after heartbeat onset. This HEP effect was more pronounced in individuals who reported high, relative to low, levels of state anxiety. Together, our results offer novel evidence that at varying levels of state anxiety, the brain differentially modulates sensitivity to bodily signals in coordination with the momentary, spontaneous experience of subjective arousal-a mechanism that may operate independently of physiological arousal.

Significance Statement

Our findings highlight the relationships between spontaneous fluctuations in subjective arousal, brain-body interactions, and anxiety, offering new insights into how interoception fluctuates with changes in internal states. By showing that interoceptive processing is heightened during lower subjective arousal and that this effect is amplified in individuals with higher state anxiety, our study suggests the brain adaptively downregulates interoceptive sensitivity in response to fluctuating internal states. These results have implications for understanding how spontaneous thoughts shape interoception and emotion, particularly in clinical contexts where dysregulated interoception is linked to anxiety and mood disorders. More broadly, our work underscores the need to distinguish between different forms of arousal, advancing understanding of the taxonomy and ways of measuring arousal.

The Neurophysiological Costs of Learning in a Noisy Classroom: An Ecological Virtual Reality Study

Many real-life situations can be extremely noisy, which makes it difficult to understand what people say. Here, we introduce a novel audiovisual virtual reality experimental platform to study the behavioral and neurophysiological consequences of background noise on processing continuous speech in highly realistic environments. We focus on a context where the ability to understand speech is particularly important: the classroom. Participants (n = 32) experienced sitting in a virtual reality classroom and were told to pay attention to a virtual teacher giving a lecture. Trials were either quiet or contained background construction noise, emitted from outside the classroom window. Two realistic types of noise were used: continuous drilling and intermittent air hammers. Alongside behavioral outcomes, we measured several neurophysiological metrics, including neural activity (EEG), eye-gaze and skin conductance (galvanic skin response). Our results confirm the detrimental effect of background noise. Construction noise, and particularly intermittent noise, was associated with reduced behavioral performance, reduced neural tracking of the teacher's speech and an increase in skin conductance, although it did not have a significant effect on alpha-band oscillations or eye-gaze patterns. These results demonstrate the neurophysiological costs of learning in noisy environments and emphasize the role of temporal dynamics in speech-in-noise perception. The finding that intermittent noise was more disruptive than continuous noise supports a "habituation" rather than "glimpsing" hypothesis of speech-in-noise processing. These results also underscore the importance of increasing the ecologically relevance of neuroscientific research and considering acoustic, temporal, and semantic features of realistic stimuli as well as the cognitive demands of real-life environments.

Precision data-driven modeling of cortical dynamics reveals person-specific mechanisms underpinning brain electrophysiology

Task-free brain activity affords unique insight into the functional structure of brain network dynamics and has been used to identify neural markers of individual differences. In this work, we present an algorithmic optimization framework that directly inverts and parameterizes brain-wide dynamical-systems models involving hundreds of interacting neural populations, from single-subject M/EEG 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 metrics. Last, 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 excitatory-inhibitory balance, highlighting the explanatory power of our framework to generate mechanistic insights.

Resting-State EEG Oscillations in Amyotrophic Lateral Sclerosis (ALS): Toward Mechanistic Insights and Clinical Markers

Introduction: Amyotrophic lateral sclerosis (ALS) is a complex, progressive neurodegenerative disorder characterized by the degeneration of motor neurons in the brain, brainstem, and spinal cord. Several neuroimaging techniques can help reveal the pathophysiology of ALS. One of these is the electroencephalogram (EEG), a noninvasive and relatively inexpensive tool for examining electrical activity of the brain with excellent temporal precision. Methods: This mechanistic review examines the pattern of resting-state EEG activity. With a focus on publications published between January 1995 and October 2024, we carried out a comprehensive search in October 2024 across a number of databases, including PubMed/Medline, Research Gate, Google Scholar, and Cochrane. Results: The literature search yielded 17 studies included in this review. The studies varied significantly in their methodology and patient characteristics. Despite this, a common biomarker typical of ALS was found-reduced alpha power. Regarding other oscillations, the findings are less consistent and sometimes contradictory. As this is a mechanistic review, three possible explanations for this biomarker are provided. The main and most important one is increased cortical excitability. In addition, due to the limitations of the studies, recommendations for future research on this topic are outlined to enable a further and better understanding of EEG patterns in ALS. Conclusions: Most studies included in this review showed alpha power deficits in ALS patients, reflecting pathological hyperexcitability of the cerebral cortex. Future studies should address the methodological limitations identified in this review, including small sample sizes, inconsistent frequency-band definitions, and insufficient functional outcome measures, to solidify and extend current findings.

Reduced resting and task-related alpha activity in mine workers: Implications for occupational health and neurodegenerative risk

Underground mine workers face many risk factors at work sites that are known to affect the neural system. Observational studies report that these risk factors precede neuromuscular and neurodegenerative disorders, especially in old-age miners. Neurodegenerative disorders have electrophysiological, anatomical, and functional changes long before symptoms are seen in older adults. Therefore, this study investigated whether risks faced by miners at young ages were reflected in electrophysiological signals. Twenty-one underground miners and twenty-two above-ground workers matched with them in terms of age, education, and working duration were included in this study. Participants were recorded with a 20-channel EEG during the resting-state (eyes open and closed; EO-EC) and the perception of the International Affective Picture System Paradigm (IAPS). Time-frequency analyses were performed for alpha frequency. Rs-EEG results showed a statistically significant difference in alpha power between the EO and EC states in the control group. However, there was no statistical difference in alpha power between these two conditions in the miners. Additionally, we noted a more pronounced decrease in alpha responses in the posterior region during EC in the miners. The group's main effects were statistically significant in event-related alpha responses during emotional responses. Accordingly, event-related alpha responses of the miner group were lower than the control group in terms of both power spectrum and phase-locking. Underground mine workers are cognitively and emotionally affected by risks in the work environment. Electrophysiological changes seen in young underground workers may be a harbinger of neurodegenerative disorders in miners' old age. Our research findings may lead to the development of occupational neuroscience, social policies, and worker health, which are necessary to improve working conditions for mineworkers.

The Posterior Dominant Rhythm Remains Within Normal Limits in the Microgravity Environment

BACKGROUND

Electroencephalogram (EEG) biomarkers with adequate sensitivity and specificity to reflect the brain's health status can become indispensable for health monitoring during prolonged missions in space. The objective of our study was to assess whether the basic features of the posterior dominant rhythm (PDR) change under microgravity conditions compared to earth-based scalp EEG recordings.

METHODS

Three crew members during the 16-day AXIOM-1 mission to the International Space Station (ISS), underwent scalp EEG recordings before, during, and after the mission by means of a dry-electrode self-donning headgear designed to support long-term EEG recordings in space. Resting-state recordings were performed with eyes open and closed during relaxed wakefulness. The electrodes representative of EEG activity in each occipital lobe were used, and consecutive PDR oscillations were identified during periods of eye closure. In turn, cursor-based markers were placed at the negative peak of each sinusoidal wave of the PDR. Waveform averaging and time-frequency analysis were performed for all PDR samples for the respective pre-mission, mission, and post-mission EEGs.

RESULTS

No significant differences were found in the mean frequency of the PDR in any of the crew subjects between their EEG on the ISS and their pre- or post-mission EEG on ground level. The PDR oscillations varied over a ±1Hz standard deviation range. Similarly, no significant differences were found in PDR's power spectral density.

CONCLUSIONS

Our study shows that the spectral features of the PDR remain within normal limits in a short exposure to the microgravity environment, with its frequency manifesting within an acceptable ±1 Hz variation from the pre-mission mean. Further investigations for EEG features and markers reflecting the human brain neurophysiology during space missions are required.

Effects of continuous theta burst stimulation on contralateral primary motor cortex: a concurrent TMS-EEG study

Continuous theta burst stimulation (cTBS) is a noninvasive brain stimulation technique. cTBS modulation is an effective treatment for motor dysfunction rehabilitation in post-stroke patients. However, there's currently a lack of research on the effects of cTBS stimulation on the contralesional hemisphere. To better understand the role of cTBS in motor rehabilitation, we investigated the neuroregulatory mechanisms of cTBS in the contralateral cortex using transcranial magnetic stimulation-evoked electroencephalography (TMS-EEG). In this randomized, sham-controlled, single-blind study, 18 healthy subjects received two separate stimulation conditions: cTBS or sham stimulation applied to the left primary motor cortex (M1). TMS-EEG measurements were taken before and immediately after stimulation. We investigated the TMS-evoked potentials (TEPs), evoked oscillatory responses (EOR), and phase synchronization index (PSI) of TMS-EEG. The effects of cTBS were analyzed using two-way repeated-measures analysis of variance (RMANOVA). There was a significant "cTBS condition × time" interaction effect on the theta and gamma bands of EOR, and on interhemisphere PSI (inter-PSI) and global PSI in both cTBS stimulation conditions. (theta: F = 4.526, P = 0.041; gamma: F = 5.574, P = 0.024; inter-PSI: F = 5.028, P = 0.032; global PSI: F = 5.129, P = 0.030). After real cTBS modulation, the energy in the theta and gamma frequency bands was significantly higher than before (theta: F = 5.747, P = 0.022; gamma: F = 5.545, P = 0.024). The inter-PSI and global PSI significantly increased after real cTBS modulation (inter-PSI: F = 6.209, P = 0.018; global PSI: F = 6.530, P = 0.015). cTBS modulation significantly increased EOR and PSI in contralateral brain regions, thereby enhancing cortical excitability and cortical functional connectivity throughout the brain. This provides a theoretical basis for cTBS neuromodulation in patients with stroke.NEW & NOTEWORTHY In right-handed individuals, the left hemisphere exhibits higher excitability. According to hemispheric competition theory, applying continuous theta burst stimulation (cTBS) to inhibit excitability in the left hemisphere can reduce its inhibitory effect on the right, thereby promoting neural excitability. This study applied cTBS to the left M1 of healthy individuals and, for the first time, recorded transcranial magnetic stimulation-evoked electroencephalography (TMS-EEG) from the right M1 to analyze the effects of cTBS on cortical oscillations and network connectivity in the contralateral cortex.

Modulation of neural oscillations in escitalopram treatment: a Canadian biomarker integration network in depression study

Current pharmacological agents for depression have limited efficacy in achieving remission. Developing and validating new medications is challenging due to limited biological targets. This study aimed to link electrophysiological data and symptom improvement to better understand mechanisms underlying treatment response. Longitudinal changes in neural oscillations were assessed using resting-state electroencephalography (EEG) data from two Canadian Biomarker Integration Network in Depression studies, involving pharmacological and cognitive behavioral therapy (CBT) trials. Patients in the pharmacological trial received eight weeks of escitalopram, with treatment response defined as ≥ 50% decrease in Montgomery-Åsberg Depression Rating Scale (MADRS). Early (baseline to week 2) and late (baseline to week 8) changes in neural oscillation were investigated using relative power spectral measures. An association was found between an initial increase in theta and symptom improvement after 2 weeks. Additionally, late increases in delta and theta, along with a decrease in alpha, were linked to a reduction in MADRS after 8 weeks. These late changes were specifically observed in responders. To assess specificity, we extended our analysis to the independent CBT cohort. Responders exhibited an increase in delta and a decrease in alpha after 2 weeks. Furthermore, a late (baseline to week 16) decrease in alpha was associated with symptom improvement following CBT. Results suggest a common late decrease in alpha across both treatments, while modulatory effects in theta may be specific to escitalopram treatment. This study offers insights into electrophysiological markers indicating a favorable response to antidepressants, enhancing our comprehension of treatment response mechanisms in depression.

Implications of Aperiodic and Periodic EEG Components in Classification of Major Depressive Disorder from Source and Electrode Perspectives

Electroencephalography (EEG) is useful for studying brain activity in major depressive disorder (MDD), particularly focusing on theta and alpha frequency bands via power spectral density (PSD). However, PSD-based analysis has often produced inconsistent results due to difficulties in distinguishing between periodic and aperiodic components of EEG signals. We analyzed EEG data from 114 young adults, including 74 healthy controls (HCs) and 40 MDD patients, assessing periodic and aperiodic components alongside conventional PSD at both source and electrode levels. Machine learning algorithms classified MDD versus HC based on these features. Sensor-level analysis showed stronger Hedge's g effect sizes for parietal theta and frontal alpha activity than source-level analysis. MDD individuals exhibited reduced theta and alpha activity relative to HC. Logistic regression-based classifications showed that periodic components slightly outperformed PSD, with the best results achieved by combining periodic and aperiodic features (AUC = 0.82). Strong negative correlations were found between reduced periodic parietal theta and frontal alpha activities and higher scores on the Beck Depression Inventory, particularly for the anhedonia subscale. This study emphasizes the superiority of sensor-level over source-level analysis for detecting MDD-related changes and highlights the value of incorporating both periodic and aperiodic components for a more refined understanding of depressive disorders.

Substance specific EEG patterns in mice undergoing slow anesthesia induction

The exact mechanisms and the neural circuits involved in anesthesia induced unconsciousness are still not fully understood. To elucidate them valid animal models are necessary. Since the most commonly used species in neuroscience are mice, we established a murine model for commonly used anesthetics/sedatives and evaluated the epidural electroencephalographic (EEG) patterns during slow anesthesia induction and emergence. Forty-four mice underwent surgery in which we inserted a central venous catheter and implanted nine intracranial electrodes above the prefrontal, motor, sensory, and visual cortex. After at least one week of recovery, mice were anesthetized either by inhalational sevoflurane or intravenous propofol, ketamine, or dexmedetomidine. We evaluated the loss and return of righting reflex (LORR/RORR) and recorded the electrocorticogram. For spectral analysis we focused on the prefrontal and visual cortex. In addition to analyzing the power spectral density at specific time points we evaluated the changes in the spectral power distribution longitudinally. The median time to LORR after start anesthesia ranged from 1080 [1st quartile: 960; 3rd quartile: 1080]s under sevoflurane anesthesia to 1541 [1455; 1890]s with ketamine. Around LORR sevoflurane as well as propofol induced a decrease in the theta/alpha band and an increase in the beta/gamma band. Dexmedetomidine infusion resulted in a shift towards lower frequencies with an increase in the delta range. Ketamine induced stronger activity in the higher frequencies. Our results showed substance-specific changes in EEG patterns during slow anesthesia induction. These patterns were partially identical to previous observations in humans, but also included significant differences, especially in the low frequencies. Our study emphasizes strengths and limitations of murine models in neuroscience and provides an important basis for future studies investigating complex neurophysiological mechanisms.

EEG alpha reactivity on eyes opening discriminates patients with schizophrenia and schizoaffective disorder

OBJECTIVE

Alpha activity in the electroencephalogram (EEG) is typically dominant during rest with closed eyes but suppressed by visual stimulation. Previous research has shown that alpha-blockade is less pronounced in schizophrenia patients compared to healthy individuals, but no studies have examined it in schizoaffective disorder.

METHODS

A resting state EEG was used for the analysis of the alpha-reactivity between the eyes closed and the eyes opened conditions in overall (8 - 13 Hz), low (8 - 10 Hz) and high (10 - 13 Hz) alpha bands in three groups: schizophrenia patients (SC, n = 30), schizoaffective disorder (SA, n = 30), and healthy controls (HC, n = 36). All patients had their first psychotic episode and were receiving antipsychotic therapy.

RESULTS

A significant decrease in alpha power was noted across all subjects from the eyes-closed to eyes-open condition, spanning all regions. Alpha reactivity over the posterior regions was lower in SC compared to HC within overall and high alpha. SA showed a trend towards reduced alpha reactivity compared to HC, especially evident over the left posterior region within the overall alpha. Alpha reactivity was more pronounced over the middle and right posterior regions of SA as compared to SC, particularly in the high alpha. Alpha reactivity in SC and SA patients was associated with various negative symptoms.

CONCLUSIONS

Our findings imply distinct alterations in arousal mechanisms in SC and SA and their relation to negative symptomatology. Arousal is more preserved in SA.

SIGNIFICANCE

This study is the first to compare the EEG features of arousal in SC and SA.

Focal changes in alpha oscillations during short-term memorization of pain: a high-density electroencephalogram study with source localization

Memories of painful events constitute the basis for assessing patients' pain. This study explores the brain oscillatory activity during short-term memorization of a nociceptive stimulus. High-density EEG activity (128 electrodes) was recorded in 13 healthy subjects during a match-to-sample sensory discrimination task, whereby participants compared the intensity of a thumb-located electric shock (S2) with a prior stimulus to the same location (S1) delivered 8-10 s earlier. Stimuli were above or below the individual nociceptive threshold. EEG activity with intracortical source localization via LORETA source reconstruction was analysed during the inter-stimuli period and contrasted with a non-memory-related control task. The inter-stimulus memorization phase was characterized by a focal alpha-activity enhancement, significant during the nociceptive condition only, which progressed from bilateral occipital regions (cuneus and mid-occipital gyri) during the first encoding-memorization phase towards the right-superior and right mid-temporal gyri during the 2-4 s immediately preceding S2. Initial alpha enhancement in occipital areas/cuneus is consistent with rapid non-specific inhibition of task-irrelevant visual processing during initial stimulus encoding. Its transfer to the right-temporal regions was concomitant to the temporary upholding of the stimulus perceptual representation, previous to receiving S2, and suggests an active and local blockade of external interferences while these regions actively maintain internal information. These results add to a growing field indicating that alpha oscillations, while indicating local inhibitory processes, can also indirectly reveal active stimulus handling, including maintenance in short-term memory buffers, by objectivizing the filtering out of irrelevant and potentially disrupting inputs in brain regions engaged in internally driven operations.

Elevating understanding: Linking high-altitude hypoxia to brain aging through EEG functional connectivity and spectral analyses

High-altitude hypoxia triggers brain function changes reminiscent of those in healthy aging and Alzheimer's disease, compromising cognition and executive functions. Our study sought to validate high-altitude hypoxia as a model for assessing brain activity disruptions akin to aging. We collected EEG data from 16 healthy volunteers during acute high-altitude hypoxia (at 4,000 masl) and at sea level, focusing on relative changes in power and aperiodic slope of the EEG spectrum due to hypoxia. Additionally, we examined functional connectivity using wPLI, and functional segregation and integration using graph theory tools. High altitude led to slower brain oscillations, that is, increased δ and reduced α power, and flattened the 1/f aperiodic slope, indicating higher electrophysiological noise, akin to healthy aging. Notably, functional integration strengthened in the θ band, exhibiting unique topographical patterns at the subnetwork level, including increased frontocentral and reduced occipitoparietal integration. Moreover, we discovered significant correlations between subjects' age, 1/f slope, θ band integration, and observed robust effects of hypoxia after adjusting for age. Our findings shed light on how reduced oxygen levels at high altitudes influence brain activity patterns resembling those in neurodegenerative disorders and aging, making high-altitude hypoxia a promising model for comprehending the brain in health and disease.

Uncovering a stability signature of brain dynamics associated with meditation experience using massive time-series feature extraction

Previous research has examined resting electroencephalographic (EEG) data to explore brain activity related to meditation. However, previous research has mostly examined power in different frequency bands. The practical objective of this study was to comprehensively test whether other types of time-series analysis methods are better suited to characterize brain activity related to meditation. To achieve this, we compared >7000 time-series features of the EEG signal to comprehensively characterize brain activity differences in meditators, using many measures that are novel in meditation research. Eyes-closed resting-state EEG data from 49 meditators and 46 non-meditators was decomposed into the top eight principal components (PCs). We extracted 7381 time-series features from each PC and each participant and used them to train classification algorithms to identify meditators. Highly differentiating individual features from successful classifiers were analysed in detail. Only the third PC (which had a central-parietal maximum) showed above-chance classification accuracy (67 %, pFDR = 0.007), for which 405 features significantly distinguished meditators (all pFDR < 0.05). Top-performing features indicated that meditators exhibited more consistent statistical properties across shorter subsegments of their EEG time-series (higher stationarity) and displayed an altered distributional shape of values about the mean. By contrast, classifiers trained with traditional band-power measures did not distinguish the groups (pFDR > 0.05). Our novel analysis approach suggests the key signatures of meditators' brain activity are higher temporal stability and a distribution of time-series values suggestive of longer, larger, or more frequent non-outlying voltage deviations from the mean within the third PC of their EEG data. The higher temporal stability observed in this EEG component might underpin the higher attentional stability associated with meditation. The novel time-series properties identified here have considerable potential for future exploration in meditation research and the analysis of neural dynamics more broadly.

Resting-state EEG power differences in autism spectrum disorder: a systematic review and meta-analysis

Narrative reviews have described various resting-state EEG power differences in autism across all five canonical frequency bands, with increased power for low and high frequencies and reduced power for middle frequencies. However, these differences have yet to be quantified using effect sizes and probed robustly for consistency, which are critical next steps for clinical translation. Following PRISMA guidelines, we conducted a systematic review of published and gray literature on resting-state EEG power in autism. We performed 10 meta-analyses to synthesize and quantify differences in absolute and relative resting-state delta, theta, alpha, beta, and gamma EEG power in autism. We also conducted moderator analyses to determine whether demographic characteristics, methodological details, and risk-of-bias indicators might account for heterogeneous study effect sizes. Our literature search and study selection processes yielded 41 studies involving 1,246 autistic and 1,455 neurotypical individuals. Meta-analytic models of 135 effect sizes demonstrated that autistic individuals exhibited reduced relative alpha (g = -0.35) and increased gamma (absolute: g = 0.37, relative: g = 1.06) power, but similar delta (absolute: g = 0.06, relative: g = 0.10), theta (absolute: g = -0.03, relative: g = -0.15), absolute alpha (g = -0.17), and beta (absolute: g = 0.01, relative: g = 0.08) power. Substantial heterogeneity in effect sizes was observed across all absolute (I2: 36.1-81.9%) and relative (I2: 64.6-84.4%) frequency bands. Moderator analyses revealed that age, biological sex, IQ, referencing scheme, epoch duration, and use of gold-standard autism diagnostic instruments did not moderate study effect sizes. In contrast, resting-state paradigm type (eyes-closed versus eyes-open) moderated absolute beta, relative delta, and relative alpha power effect sizes, and resting-state recording duration moderated relative alpha power effect sizes. These findings support further investigation of resting-state alpha and gamma power as potential biomarkers for autism.

A genetic variation in the adenosine A2A receptor gene contributes to variability in oscillatory alpha power in wake and sleep EEG and A1 adenosine receptor availability in the human brain

The EEG alpha rhythm (∼ 8-13 Hz) is one of the most salient human brain activity rhythms, modulated by the level of attention and vigilance and related to cerebral energy metabolism. Spectral power in the alpha range in wakefulness and sleep strongly varies among individuals based on genetic predisposition. Knowledge about the underlying genes is scarce, yet small studies indicated that the variant rs5751876 of the gene encoding A2A adenosine receptors (ADORA2A) may contribute to the inter-individual variation. The neuromodulator adenosine is directly linked to energy metabolism as product of adenosine tri-phosphate breakdown and acts as a sleep promoting molecule by activating A1 and A2A adenosine receptors. We performed sleep and positron emission tomography studies in 59 healthy carriers of different rs5751876 alleles, and quantified EEG oscillatory alpha power in wakefulness and sleep, as well as A1 adenosine receptor availability with 18F-CPFPX. Oscillatory alpha power was higher in homozygous C-allele carriers (n = 27, 11 females) compared to heterozygous and homozygous carriers of the T-allele (n(C/T) = 23, n(T/T) = 5, 13 females) (F(18,37) = 2.35, p = 0.014, Wilk's Λ = 0.487). Furthermore, a modulatory effect of ADORA2A genotype on A1 adenosine receptor binding potential was found across all considered brain regions (F(18,40) = 2.62, p = 0.006, Wilk's Λ = 0.459), which remained significant for circumscribed occipital region of calcarine fissures after correction for multiple comparisons. In female participants, a correlation between individual differences in oscillatory alpha power and A1 receptor availability was observed. In conclusion, we confirmed that a genetic variant of ADORA2A affects individual alpha power, while a direct modulatory effect via A1 adenosine receptors in females is suggested.

A novel classification model based on cerebral 18F-FDG uptake pattern facilitates the diagnosis of acute/subacute seropositive autoimmune encephalitis

PURPOSE

To explore the intrinsic alteration of cerebral 18F-FDG metabolism in acute/subacute seropositive autoimmune encephalitis (AE) and to propose a universal classification model based on 18F-FDG metabolic patterns to predict AE.

METHODS

Cerebral 18F-FDG PET images of 42 acute/subacute seropositive AE patients and 45 healthy controls (HCs) were compared using voxelwise and region of interest (ROI)-based schemes. The mean standardized uptake value ratios (SUVRs) of 59 subregions according to a modified Automated Anatomical Labeling (AAL) atlas were compared using a t-test. Subjects were randomly divided into a training set (70%) and a testing set (30%). Logistic regression models were built based on the SUVRs and the models were evaluated by determining their predictive value in the training and testing sets.

RESULTS

The 18F-FDG uptake pattern in the AE group was characterized by increased SUVRs in the brainstem, cerebellum, basal ganglia, and temporal lobe, and decreased SUVRs in the occipital, and frontal regions with voxelwise analysis (false discovery rate [FDR] p<0.05). Utilizing ROI-based analysis, we identified 15 subareas that exhibited statistically significant changes in SUVRs among AE patients compared to HC (FDR p<0.05). Further, a logistic regression model incorporating SUVRs from the calcarine cortex, putamen, supramarginal gyrus, cerebelum_10, and hippocampus successfully enhanced the positive predictive value from 0.76 to 0.86 when compared to visual assessments. This model also demonstrated potent predictive ability, with AUC values of 0.94 and 0.91 observed for the training and testing sets, respectively.

CONCLUSIONS

During the acute/subacute stages of seropositive AE, alterations in SUVRs appear to be concentrated within physiologically significant regions, ultimately defining the general cerebral metabolic pattern. By incorporating these key regions into a new classification model, we have improved the overall diagnostic efficiency of AE.

Personalized repetitive transcranial magnetic stimulation (prtms®) for post-traumatic stress disorder (ptsd) in military combat veterans

Emerging data suggest that post-traumatic stress disorder (PTSD) arises from disrupted brain default mode network (DMN) activity manifested by dysregulated encephalogram (EEG) alpha oscillations. Hence, we pursued the treatment of combat veterans with PTSD (n = 185) using an expanded form of repetitive transcranial magnetic stimulation (rTMS) termed personalized-rTMS (PrTMS). In this treatment methodology spectral EEG based guidance is used to iteratively optimize symptom resolution via (1) stimulation of multiple motor sensory and frontal cortical sites at reduced power, and (2) adjustments of cortical treatment loci and stimulus frequency during treatment progression based on a proprietary frequency algorithm (PeakLogic, Inc. San Diego) identifying stimulation frequency in the DMN elements of the alpha oscillatory band. Following 4 - 6 weeks of PrTMS® therapy in addition to routine PTSD therapy, veterans exhibited significant clinical improvement accompanied by increased cortical alpha center frequency and alpha oscillatory synchronization. Full resolution of PTSD symptoms was attained in over 50% of patients. These data support DMN involvement in PTSD pathophysiology and suggest a role in therapeutic outcomes. Prospective, sham controlled PrTMS® trials may be warranted to validate our clinical findings and to examine the contribution of DMN targeting for novel preventive, diagnostic, and therapeutic strategies tailored to the unique needs of individual patients with both combat and non-combat PTSD.

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.

Dynamic cortical and tractography atlases of proactive and reactive alpha and high-gamma activities

Alpha waves-posterior dominant rhythms at 8-12 Hz reactive to eye opening and closure-are among the most fundamental EEG findings in clinical practice and research since Hans Berger first documented them in the early 20th century. Yet, the exact network dynamics of alpha waves in regard to eye movements remains unknown. High-gamma activity at 70-110 Hz is also reactive to eye movements and a summary measure of local cortical activation supporting sensorimotor or cognitive function. We aimed to build the first-ever brain atlases directly visualizing the network dynamics of eye movement-related alpha and high-gamma modulations, at cortical and white matter levels. We studied 28 patients (age: 5-20 years) who underwent intracranial EEG and electro-oculography recordings. We measured alpha and high-gamma modulations at 2167 electrode sites outside the seizure onset zone, interictal spike-generating areas and MRI-visible structural lesions. Dynamic tractography animated white matter streamlines modulated significantly and simultaneously beyond chance, on a millisecond scale. Before eye-closure onset, significant alpha augmentation occurred at the occipital and frontal cortices. After eye-closure onset, alpha-based functional connectivity was strengthened, while high gamma-based connectivity was weakened extensively in both intra-hemispheric and inter-hemispheric pathways involving the central visual areas. The inferior fronto-occipital fasciculus supported the strengthened alpha co-augmentation-based functional connectivity between occipital and frontal lobe regions, whereas the posterior corpus callosum supported the inter-hemispheric functional connectivity between the occipital lobes. After eye-opening offset, significant high-gamma augmentation and alpha attenuation occurred at occipital, fusiform and inferior parietal cortices. High gamma co-augmentation-based functional connectivity was strengthened, whereas alpha-based connectivity was weakened in the posterior inter-hemispheric and intra-hemispheric white matter pathways involving central and peripheral visual areas. Our results do not support the notion that eye closure-related alpha augmentation uniformly reflects feedforward or feedback rhythms propagating from lower to higher order visual cortex, or vice versa. Rather, proactive and reactive alpha waves involve extensive, distinct white matter networks that include the frontal lobe cortices, along with low- and high-order visual areas. High-gamma co-attenuation coupled to alpha co-augmentation in shared brain circuitry after eye closure supports the notion of an idling role for alpha waves during eye closure. These normative dynamic tractography atlases may improve understanding of the significance of EEG alpha waves in assessing the functional integrity of brain networks in clinical practice; they also may help elucidate the effects of eye movements on task-related brain network measures observed in cognitive neuroscience research.

Prediction of Behavioral Improvement Through Resting-State Electroencephalography and Clinical Severity in a Randomized Controlled Trial Testing Bumetanide in Autism Spectrum Disorder

BACKGROUND

Mechanism-based treatments such as bumetanide are being repurposed for autism spectrum disorder. We recently reported beneficial effects on repetitive behavioral symptoms that might be related to regulating excitation-inhibition (E/I) balance in the brain. Here, we tested the neurophysiological effects of bumetanide and the relationship to clinical outcome variability and investigated the potential for machine learning-based predictions of meaningful clinical improvement.

METHODS

Using modified linear mixed models applied to intention-to-treat population, we analyzed E/I-sensitive electroencephalography (EEG) measures before and after 91 days of treatment in the double-blind, randomized, placebo-controlled Bumetanide in Autism Medication and Biomarker study. Resting-state EEG of 82 subjects out of 92 participants (7-15 years) were available. Alpha frequency band absolute and relative power, central frequency, long-range temporal correlations, and functional E/I ratio treatment effects were related to the Repetitive Behavior Scale-Revised (RBS-R) and the Social Responsiveness Scale 2 as clinical outcomes.

RESULTS

We observed superior bumetanide effects on EEG, reflected in increased absolute and relative alpha power and functional E/I ratio and in decreased central frequency. Associations between EEG and clinical outcome change were restricted to subgroups with medium to high RBS-R improvement. Using machine learning, medium and high RBS-R improvement could be predicted by baseline RBS-R score and EEG measures with 80% and 92% accuracy, respectively.

CONCLUSIONS

Bumetanide exerts neurophysiological effects related to clinical changes in more responsive subsets, in whom prediction of improvement was feasible through EEG and clinical measures.

Dynamic causal modelling shows a prominent role of local inhibition in alpha power modulation in higher visual cortex

During resting-state EEG recordings, alpha activity is more prominent over the posterior cortex in eyes-closed (EC) conditions compared to eyes-open (EO). In this study, we characterized the difference in spectra between EO and EC conditions using dynamic causal modelling. Specifically, we investigated the role of intrinsic and extrinsic connectivity-within the visual cortex-in generating EC-EO alpha power differences over posterior electrodes. The primary visual cortex (V1) and the bilateral middle temporal visual areas (V5) were equipped with bidirectional extrinsic connections using a canonical microcircuit. The states of four intrinsically coupled subpopulations-within each occipital source-were also modelled. Using Bayesian model selection, we tested whether modulations of the intrinsic connections in V1, V5 or extrinsic connections (or a combination thereof) provided the best evidence for the data. In addition, using parametric empirical Bayes (PEB), we estimated group averages under the winning model. Bayesian model selection showed that the winning model contained both extrinsic connectivity modulations, as well as intrinsic connectivity modulations in all sources. The PEB analysis revealed increased extrinsic connectivity during EC. Overall, we found a reduction in the inhibitory intrinsic connections during EC. The results suggest that the intrinsic modulations in V5 played the most important role in producing EC-EO alpha differences, suggesting an intrinsic disinhibition in higher order visual cortex, during EC resting state.

Electroencephalography Signatures for Hepatic Encephalopathy in Cirrhosis Patients Treated with Proton Pump Inhibitors: An Exploratory Pilot Study

(1) Background: Hepatic encephalopathy (HE) is a common complication in cirrhosis patients, and recently, clinical evidence indicates that a higher risk of HE is associated with the usage of proton pump inhibitors. However, the cortical mechanism underlying this neurological disorder of HE remains unknown. (2) Methods: We review the medical recordings of 260 patients diagnosed with liver cirrhosis between January 2021 and March 2022 in one tertiary hospital. Logistic regression analyses were performed to identify the risk factor of HE development. To examine the relationship between cortical dynamics and the administration of proton pump inhibitors, resting-state electroencephalograms (EEGs) were conducted in cirrhosis patients who were treated with proton pump inhibitors. (3) Results: About 28.5% (74 out of 260) of participants developed secondary HE in this study. The logistics regression model indicated that multiple risk factors were associated with the incidence of secondary HE, including proton pump inhibitors usage, white blood cell and neutrophil counts, hemoglobin, prothrombin time activity, and blood urea nitrogen. A total of twelve cirrhosis patients who were scheduled to use proton pump inhibitors consented to performing electroencephalogram recordings upon admission, and eight of twelve participants were diagnosed with HE. Spectral analysis revealed that the decrease in alpha oscillation activities was potentially associated with the development of HE. (4) Conclusions: Our data support the susceptibility of secondary HE in cirrhosis patients treated by proton pump inhibitors. One potential cortical mechanism underlying the neurological disease is the suppression of alpha oscillations in the brain.

Frequency-specific neural signatures of perceptual content and perceptual stability

In the natural environment, we often form stable perceptual experiences from ambiguous and fleeting sensory inputs. Which neural activity underlies the content of perception and which neural activity supports perceptual stability remains an open question. We used a bistable perception paradigm involving ambiguous images to behaviorally dissociate perceptual content from perceptual stability, and magnetoencephalography to measure whole-brain neural dynamics in humans. Combining multivariate decoding and neural state-space analyses, we found frequency-band-specific neural signatures that underlie the content of perception and promote perceptual stability, respectively. Across different types of images, non-oscillatory neural activity in the slow cortical potential (<5 Hz) range supported the content of perception. Perceptual stability was additionally influenced by the amplitude of alpha and beta oscillations. In addition, neural activity underlying perceptual memory, which supports perceptual stability when sensory input is temporally removed from view, also encodes elapsed time. Together, these results reveal distinct neural mechanisms that support the content versus stability of visual perception.

Space-time resolved inference-based neurophysiological process imaging: application to resting-state alpha rhythm

Neural processes are complex and difficult to image. This paper presents a new space-time resolved brain imaging framework, called Neurophysiological Process Imaging (NPI), that identifies neurophysiological processes within cerebral cortex at the macroscopic scale. By fitting uncoupled neural mass models to each electromagnetic source time-series using a novel nonlinear inference method, population averaged membrane potentials and synaptic connection strengths are efficiently and accurately inferred and imaged across the whole cerebral cortex at a resolution afforded by source imaging. The efficiency of the framework enables return of the augmented source imaging results overnight using high performance computing. This suggests it can be used as a practical and novel imaging tool. To demonstrate the framework, it has been applied to resting-state magnetoencephalographic source estimates. The results suggest that endogenous inputs to cingulate, occipital, and inferior frontal cortex are essential modulators of resting-state alpha power. Moreover, endogenous input and inhibitory and excitatory neural populations play varied roles in mediating alpha power in different resting-state sub-networks. The framework can be applied to arbitrary neural mass models and has broad applicability to image neural processes in different brain states.

Cranial osteopathic techniques and electroencephalogram (EEG) alpha power: a controlled crossover trial

CONTEXT

Osteopathic tradition in the cranial field (OCF) stated that the primary respiratory mechanism (PRM) relies on the anatomical links between the occiput and sacrum. Few studies investigated this relationship with inconsistent results. No studies investigated the occiput-sacrum connection from a neurophysiological perspective.

OBJECTIVES

This study aims to determine whether the sacral technique (ST), compared to the compression of the fourth ventricle (CV4) technique, can affect brain alpha-band power (AABP) as an indicator of a neurophysiological connection between the occiput and sacrum.

METHODS

Healthy students, 22-30 years old for men and 20-30 years old for women, were enrolled in the study and randomized into eight interventions groups. Each group received a combination of active techniques (CV4 or ST) and the corresponding sham techniques (sham compression of the fourth ventricle [sCV4] or sham sacral technique [sST] ), organized in two experimental sessions divided by a 4 h washout period. AABP was continuously recorded by electroencephalogram (EEG) of the occipital area in the first 10 min of resting state, during each intervention (active technique time) and after 10 min (post-active technique time), for a total of approximately 50 min per session. Analysis was carried out utilizing a repeated-measure ANOVA within the linear general model framework, consisting of a within-subject factor of time and a within-subject factor of treatment (CV4/ST).

RESULTS

Forty healthy volunteers (mean age ± SD, 23.73±1.43 years; range, 21-26 years; 16 male and 24 female) were enrolled in the study and completed the study protocol. ANOVA revealed a time × treatment interaction effect statistically significant (F=791.4; p<0.001). A particularly high increase in mean AABP magnitude was recorded during the 10 min post-CV4, compared to both the CV4 and post-sCV4 application (p<0.001). During all the times analyzed for ST and sST application, no statistically significant differences were registered with respect to the resting state.

CONCLUSIONS

The ST does not produce immediate changes on occipital AABP brain activity. CV4, as previous evidence supported, generates immediate effects, suggesting that a different biological basis for OCF therapy's connection between the head and sacrum should be explored.

Response-related sensorimotor rhythms under scopolamine and MK-801 exposures in the touchscreen visual discrimination test in rats

The human mu rhythm has been suggested to represent an important function in information processing. Rodent homologue rhythms have been assumed though no study has investigated them from the cognitive aspect yet. As voluntary goal-directed movements induce the desynchronization of mu rhythm, we aimed at exploring whether the response-related brain activity during the touchscreen visual discrimination (VD) task is suitable to detect sensorimotor rhythms and their change under cognitive impairment. Different doses of scopolamine or MK-801 were injected subcutaneously to rats, and epidural electroencephalogram (EEG) was recorded during task performance. Arciform ~ 10 Hz oscillations appeared during visual processing, then two characteristic alpha/beta desynchronization-resynchronization patterns emerged mainly above the sensorimotor areas, serving presumably different motor functions. Beyond causing cognitive impairment, both drugs supressed the touch-related upper alpha (10–15 Hz) reactivity for desynchronization. Reaction time predominantly correlated positively with movement-related alpha and beta power both in normal and impaired conditions. These results support the existence of a mu homologue rodent rhythm whose upper alpha component appeared to be modulated by cholinergic and glutamatergic mechanisms and its power change might indicate a potential EEG correlate of processing speed. The VD task can be utilized for the investigation of sensorimotor rhythms in rats.

Bumetanide Effects on Resting-State EEG in Tuberous Sclerosis Complex in Relation to Clinical Outcome: An Open-Label Study

Neuronal excitation-inhibition (E/I) imbalances are considered an important pathophysiological mechanism in neurodevelopmental disorders. Preclinical studies on tuberous sclerosis complex (TSC), suggest that altered chloride homeostasis may impair GABAergic inhibition and thereby E/I-balance regulation. Correction of chloride homeostasis may thus constitute a treatment target to alleviate behavioral symptoms. Recently, we showed that bumetanide-a chloride-regulating agent-improved behavioral symptoms in the open-label study Bumetanide to Ameliorate Tuberous Sclerosis Complex Hyperexcitable Behaviors trial (BATSCH trial; Eudra-CT: 2016-002408-13). Here, we present resting-state EEG as secondary analysis of BATSCH to investigate associations between EEG measures sensitive to network-level changes in E/I balance and clinical response to bumetanide. EEGs of 10 participants with TSC (aged 8-21 years) were available. Spectral power, long-range temporal correlations (LRTC), and functional E/I ratio (fE/I) in the alpha-frequency band were compared before and after 91 days of treatment. Pre-treatment measures were compared against 29 typically developing children (TDC). EEG measures were correlated with the Aberrant Behavioral Checklist-Irritability subscale (ABC-I), the Social Responsiveness Scale-2 (SRS-2), and the Repetitive Behavior Scale-Revised (RBS-R). At baseline, TSC showed lower alpha-band absolute power and fE/I than TDC. Absolute power increased through bumetanide treatment, which showed a moderate, albeit non-significant, correlation with improvement in RBS-R. Interestingly, correlations between baseline EEG measures and clinical outcomes suggest that most responsiveness might be expected in children with network characteristics around the E/I balance point. In sum, E/I imbalances pointing toward an inhibition-dominated network are present in TSC. We established neurophysiological effects of bumetanide although with an inconclusive relationship with clinical improvement. Nonetheless, our results further indicate that baseline network characteristics might influence treatment response. These findings highlight the possible utility of E/I-sensitive EEG measures to accompany new treatment interventions for TSC.

Clinical Trial Registration

EU Clinical Trial Register, EudraCT 2016-002408-13 (www.clinicaltrialsregister.eu/ctr-search/trial/2016-002408-13/NL). Registered 25 July 2016.

Alpha blocking and 1/fβ spectral scaling in resting EEG can be accounted for by a sum of damped alpha band oscillatory processes

The dynamical and physiological basis of alpha band activity and 1/f^β noise in the EEG are the subject of continued speculation. Here we conjecture, on the basis of empirical data analysis, that both of these features may be economically accounted for through a single process if the resting EEG is conceived of being the sum of multiple stochastically perturbed alpha band damped linear oscillators with a distribution of dampings (relaxation rates). The modulation of alpha-band and 1/f^β noise activity by changes in damping is explored in eyes closed (EC) and eyes open (EO) resting state EEG. We aim to estimate the distribution of dampings by solving an inverse problem applied to EEG power spectra. The characteristics of the damping distribution are examined across subjects, sensors and recording condition (EC/EO). We find that there are robust changes in the damping distribution between EC and EO recording conditions across participants. The estimated damping distributions are found to be predominantly bimodal, with the number and position of the modes related to the sharpness of the alpha resonance and the scaling (β) of the power spectrum (1/f^β). The results suggest that there exists an intimate relationship between resting state alpha activity and 1/f^β noise with changes in both governed by changes to the damping of the underlying alpha oscillatory processes. In particular, alpha-blocking is observed to be the result of the most weakly damped distribution mode becoming more heavily damped. The results suggest a novel way of characterizing resting EEG power spectra and provides new insight into the central role that damped alpha-band activity may play in characterising the spatio-temporal features of resting state EEG.

The resting human electroencephalogram (EEG) exhibits two dominant spectral features: the alpha rhythm (8–13 Hz) and its associated attenuation between eyes-closed and eyes-open resting state (alpha blocking), and the 1/f^β scaling of the power spectrum. While these phenomena are well studied a thorough understanding of their respective generative processes remains elusive. By employing a theoretical approach that follows from neural population models of EEG we demonstrate that it is possible to economically account for both of these phenomena using a singular mechanistic framework: resting EEG is assumed to arise from the summed activity of multiple uncorrelated, stochastically driven, damped alpha band linear oscillatory processes having a distribution of relaxation rates or dampings. By numerically estimating these damping distributions from eyes-closed and eyes-open EEG data, in a total of 136 participants, it is found that such damping distributions are predominantly bimodal in shape. The most weakly damped mode is found to account for alpha band power, with alpha blocking being driven by an increase in the damping of this weakly damped mode, whereas the second, and more heavily damped mode, is able to explain 1/f^β scaling present in the resting state EEG spectra.

Identification of an optimal dose of intravenous ketamine for late-life treatment-resistant depression: a Bayesian adaptive randomization trial

Evidence supporting specific therapies for late-life treatment-resistant depression (LL-TRD) is necessary. This study used Bayesian adaptive randomization to determine the optimal dose for the probability of treatment response (≥50% improvement from baseline on the Montgomery-Åsberg Depression Rating Scale) 7 days after a 40 min intravenous (IV) infusion of ketamine 0.1 mg/kg (KET 0.1), 0.25 mg/kg (KET 0.25), or 0.5 mg/kg (KET 0.5), compared to midazolam 0.03 mg/kg (MID) as an active placebo. The goal of this study was to identify the best dose to carry forward into a larger clinical trial. Response durability at day 28, safety and tolerability, and effects on cortical excitation/inhibition (E/I) ratio using resting electroencephalography gamma and alpha power, were also determined. Thirty-three medication-free US military veterans (mean age 62; range: 55-72; 10 female) with LL-TRD were randomized double-blind. The trial was terminated when dose superiority was established. All interventions were safe and well-tolerated. Pre-specified decision rules terminated KET 0.1 (N = 4) and KET 0.25 (N = 5) for inferiority. Posterior probability was 0.89 that day-seven treatment response was superior for KET 0.5 (N = 11; response rate = 70%) compared to MID (N = 13; response rate = 46%). Persistent treatment response at day 28 was superior for KET 0.5 (response rate = 82%) compared to MID (response rate = 37%). KET 0.5 had high posterior probability of increased frontal gamma power (posterior probability = 0.99) and decreased posterior alpha power (0.89) during infusion, suggesting an acute increase in E/I ratio. These results suggest that 0.5 mg/kg is an effective initial IV ketamine dose in LL-TRD, although further studies in individuals older than 75 are required.

Electrocorticographic effects of acute ketamine on non-human primate brains

OBJECTIVE

Acute blockade of glutamate N-methyl-D-aspartate (NMDA) receptors by ketamine induces symptoms and electrophysiological changes similar to schizophrenia. Previous studies have shown that ketamine elicits aberrant gamma oscillations in several cortical areas and impairs coupling strength between the low-frequency phase and fast frequency amplitude (PAC), which plays an important role in integrating functional information.

APPROACH

This study utilized a customized wireless electrocorticography (ECoG) recording device to collect subdural signals from the somatosensory and primary auditory cortices in two monkeys. Ketamine was administered at a dose of 3 mg/kg (intramuscular) or 0.56 mg/kg (intravenous) to elicit brain oscillation reactions. We analyzed the raw data using methods such as power spectral density, time-frequency spectra, and PAC.

MAIN RESULTS

Acute ketamine triggered broadband gamma and high gamma oscillation power and decreased lower frequencies. The effect was stronger in the primary auditory cortex than in the somatosensory area. The coupling strength between the low phase of theta and the faster amplitude of gamma/high gamma bands was increased by a lower dose (0.56 mg/kg iv) and decreased with a higher dose (3 mg/kg im) ketamine.

SIGNIFICANCE

Our results showed that lower and higher doses of ketamine elicited differential effects on theta-gamma PAC. These findings support the utility of ECoG models as a translational platform for pharmacodynamic research in future research.

Neural oscillations promoting perceptual stability and perceptual memory during bistable perception

Ambiguous images elicit bistable perception, wherein periods of momentary perceptual stability are interrupted by sudden perceptual switches. When intermittently presented, ambiguous images trigger a perceptual memory trace in the intervening blank periods. Understanding the neural bases of perceptual stability and perceptual memory during bistable perception may hold clues for explaining the apparent stability of visual experience in the natural world, where ambiguous and fleeting images are prevalent. Motivated by recent work showing the involvement of the right inferior frontal gyrus (rIFG) in bistable perception, we conducted a transcranial direct-current stimulation (tDCS) study with a double-blind, within-subject cross-over design to test a potential causal role of rIFG in these processes. Subjects viewed ambiguous images presented continuously or intermittently while under EEG recording. We did not find any significant tDCS effect on perceptual behavior. However, the fluctuations of oscillatory power in the alpha and beta bands predicted perceptual stability, with higher power corresponding to longer percept durations. In addition, higher alpha and beta power predicted enhanced perceptual memory during intermittent viewing. These results reveal a unified neurophysiological mechanism sustaining perceptual stability and perceptual memory when the visual system is faced with ambiguous input.

The combination of acute exercise and eye closure has a synergistic effect on alpha activity

Acute aerobic exercise increases the brain cortical activity in alpha frequency. Eye closure also increases alpha activity. However, whether the two have an additive or a synergistic effect on alpha activity has never been explored. This study observed electroencephalography (EEG) from fifteen participants seated on the cycle ergometer before, during, and after a cycling exercise with the eyes open and with them closed. Exercise intensity was set to a target heart rate (120-130 bpm), corresponding to light-to-moderate intensity exercise. Each epoch was 6 min and the last 4 min (eyes closed in the first 2 min and eyes open in the second 2 min) were analyzed. The EEG power spectrum densities were calculated for alpha frequency band activity (8-13 Hz). At rest, alpha activity was significantly greater with the eyes closed than open. Exercise significantly increased alpha activity in both eye conditions. More importantly, in the occipital site, the alpha-increasing effect of their combination was significantly greater than the sum of the effect of each, showing a synergistic effect. We concluded that acute light-to-moderate intensity exercise with the eyes closed has a synergistic effect on alpha activity.

EEG Cortical Activities and Networks Altered by Watching 2D/3D Virtual Reality Videos

Abstract. Virtual reality (VR), which can represent real-life events and situations, is being increasingly applied to many fields, such as education, entertainment, and medical rehabilitation. Correspondingly, the neural information processing of VR has attracted attention. However, the underlying neural mechanisms of VR environments have not yet been fully revealed. The purpose of this study was to examine the possible differences in brain activities and networks between the less immersive 2D and the fully immersive 3D VR environments. 3D VR videos and the same 2D scenes were presented to the participants and the scalp electroencephalogram (EEG) was recorded, respectively. Power spectral density (PSD) and the functional connectivity of these EEG signals were analyzed. The results showed that 3D VR videos significantly enhanced the PSD of θ rhythm (4–7 Hz) in the frontal lobe; decreased the PSD of α rhythm (8–13 Hz) in the parietal and the occipital lobes; increased the PSD of β rhythm (14–30 Hz) in the frontal, the parietal, the temporal, and the occipital lobes, relative to 2D VR watching. Furthermore, 3D versus 2D VR-induced alterations in the patterns of brain networks were similar to the patterns of PSD. Specifically, for the θ rhythm, 3D VR significantly enhanced the frontal and the temporal brain functional connectivity; for the α rhythm, 3D VR increased the parietal and the occipital networks; for the β rhythm, 3D VR remarkably increased the frontal, the occipital, the frontal-temporal and the frontal-occipital brain functional connectivity, relative to 2D VR. These significant differences between 3D and 2D VR video-watching suggest that the neural information processing of cortical activities and networks is correlated to the degree of immersion. The present results, collected with previous researches, implicate that some visual-related information processes, such as visual attention, visual perception, and visual immersion are more robust in 3D VR environments.

Prolonged deficit of low gamma oscillations in the peri-infarct cortex of mice after stroke

Days and weeks after an ischemic stroke, the peri-infarct area adjacent to the necrotic tissue exhibits very intense synaptic reorganization aimed at regaining lost functions. In order to enhance functional recovery, it is important to understand the mechanisms supporting neural repair and neuroplasticity in the cortex surrounding the lesion. Brain oscillations of the local field potential (LFP) are rhythmic fluctuations of neuronal excitability that synchronize neuronal activity to organize information processing and plasticity. Although the oscillatory activity of the brain has been probed after stroke in both animals and humans using electroencephalography (EEG), the latter is ineffective to precisely map the oscillatory changes in the peri-infarct zone where synaptic plasticity potential is high. Here, we worked on the hypothesis that the brain oscillatory system is altered in the surviving peri-infarct cortex, which may slow down the functional repair and reduce the recovery. In order to document the relevance of this hypothesis, oscillatory power was measured at various distances from the necrotic core at 7 and 21 days after a permanent cortical ischemia induced in mice. Delta and theta oscillations remained at a normal power in the peri-infarct cortex, in contrast to low gamma oscillations that displayed a gradual decrease, when approaching the border of the lesion. A broadband increase of power was also observed in the homotopic contralateral sites. Thus, the proximal peri-infarct cortex could become a target of therapeutic interventions applied to correct the oscillatory regimen in order to boost post-stroke functional recovery.

Resting-state functional EEG connectivity in salience and default mode networks and their relationship to dissociative symptoms during NMDA receptor antagonism

N-methyl-d-aspartate receptor (NMDAR) antagonists administered to healthy humans results in schizophrenia-like symptoms, which are thought in part to be related to glutamatergically altered electrophysiological connectivity in large-scale intrinsic functional brain networks. Here, we examine resting-state source electroencephalographic (EEG) connectivity within and between the default mode (DMN: for self-related cognitive activity) and salience networks (SN: for detection of salient stimuli in internal and external environments) in 21 healthy volunteers administered a subanesthetic dose of the dissociative anesthetic and NMDAR antagonist, ketamine. In addition to provoking symptoms of dissociation, which are thought to originate from an altered sense of self that is common to schizophrenia, ketamine induces frequency-dependent increases and decreases in connectivity within and between DMN and SN. These altered interactive network couplings together with emergent dissociative symptoms tentatively support an NMDAR-hypofunction hypothesis of disturbed electrophysiologic connectivity in schizophrenia.

Altered Resting-State Neural Oscillations and Spectral Power in Children with Fetal Alcohol Spectrum Disorder

BACKGROUND

Consumption of alcohol during pregnancy impacts fetal development and may lead to a variety of physical, cognitive, and behavioral abnormalities in childhood collectively known as fetal alcohol spectrum disorder (FASD). The FASD spectrum includes children with fetal alcohol syndrome (FAS), partial fetal alcohol syndrome (pFAS), and alcohol-related neurodevelopmental disorder (ARND). Children with a FASD or prenatal alcohol exposure (PAE) have impaired white matter, reduced structural volumes, impaired resting-state functional connectivity when measured with fMRI, and spectral hypersynchrony as infants. Magnetoencephalography (MEG) provides high temporal resolution and good spatial precision for examining spectral power and connectivity patterns unique from fMRI. The impact of PAE on MEG resting-state spectral power in children remains unknown.

METHODS

We collected 2 minutes of eyes-open and eyes-closed resting-state data in 51 children (8 to 12 years of age) with 3 subgroups included: 10 ARND/PAE, 15 FAS/pFAS, and 26 controls (TDC). MEG data were collected on the Elekta Neuromag system. The following spectral metrics were compared between subgroups: power, normalized power, half power, 95% power, and Shannon spectral entropy (SSE). MEG spectral data were correlated with behavioral measures.

RESULTS

Our results indicate children with FAS/pFAS had reduced spectral power and normalized power, particularly within the alpha frequency band in sensor parietal and source superior parietal and lateral occipital regions, along with elevated half power, 95% power, and SSE. We also found select hemisphere specific effects further indicating reduced corpus callosum connectivity in children with a FASD. Interestingly, while the ARND/PAE subgroup had significant differences from the FAS/pFAS subgroup, in many cases spectral data were not significantly different from TDC.

CONCLUSIONS

Our results were consistent with previous studies and provide new insight into resting-state oscillatory differences both between children with FAS and TDC, and within FASD subgroups. Further understanding of these resting-state variations and their impact on cognitive function may help provide early targets for intervention and enhance outcomes for individuals with a FASD.

Age- and gender-specific characteristics of the resting-state brain activity: a magnetoencephalography study

Aging and gender influence regional brain activities. Although these biases should be considered during the clinical examinations using magnetoencephalography, they have yet to be standardized. In the present study, resting-state magnetoencephalography data were recorded from 54 healthy females and 48 males aged 22 to 75 years, who were controlled for cognitive performance. The regional oscillatory power was estimated for each frequency band (delta, theta, alpha, beta, low-gamma, and high-gamma) using the sLORETA-like algorithm and the biases of age and gender were evaluated, respectively. The results showed that faster oscillatory powers increased with age in the rostral regions and decreased in the caudal regions, while few slower oscillatory powers changed with age. Gender differences in oscillatory powers were found in a broad frequency range, mostly in the caudal brain regions. The present study characterized the effects of healthy aging and gender asymmetricity on the regional resting-state brain activity, with the aim to facilitate the accurate and efficient use of magnetoencephalography in clinical practice.

Inferring a simple mechanism for alpha-blocking by fitting a neural population model to EEG spectra

Alpha blocking, a phenomenon where the alpha rhythm is reduced by attention to a visual, auditory, tactile or cognitive stimulus, is one of the most prominent features of human electroencephalography (EEG) signals. Here we identify a simple physiological mechanism by which opening of the eyes causes attenuation of the alpha rhythm. We fit a neural population model to EEG spectra from 82 subjects, each showing a different degree of alpha blocking upon opening of their eyes. Though it has been notoriously difficult to estimate parameters by fitting such models, we show how, by regularizing the differences in parameter estimates between eyes-closed and eyes-open states, we can reduce the uncertainties in these differences without significantly compromising fit quality. From this emerges a parsimonious explanation for the spectral differences between states: Changes to just a single parameter, p_ei, corresponding to the strength of a tonic excitatory input to the inhibitory cortical population, are sufficient to explain the reduction in alpha rhythm upon opening of the eyes. We detect this by comparing the shift in each model parameter between eyes-closed and eyes-open states. Whereas changes in most parameters are weak or negligible and do not scale with the degree of alpha attenuation across subjects, the change in p_ei increases monotonically with the degree of alpha blocking observed. These results indicate that opening of the eyes reduces alpha activity by increasing external input to the inhibitory cortical population.

One of the most striking features of the human electroencephalogram (EEG) is the presence of neural oscillations in the range of 8-13 Hz. It is well known that attenuation of these alpha oscillations, a process known as alpha blocking, arises from opening of the eyes, though the cause has remained obscure. In this study we infer the mechanism underlying alpha blocking by fitting a neural population model to EEG spectra from 82 different individuals. Although such models have long held the promise of being able to relate macroscopic recordings of brain activity to microscopic neural parameters, their utility has been limited by the difficulty of inferring these parameters from fits to data. Our approach involves fitting eyes-open and eyes-closed EEG spectra in a way that minimizes unnecessary differences in model parameters between the two states. Surprisingly, we find that changes in just one parameter, the level of external input to the inhibitory neurons in cortex, is sufficient to explain the attenuation of alpha oscillations. This indicates that opening of the eyes reduces alpha activity simply by increasing external inputs to the inhibitory neurons in the cortex.

Impaired Coupling of the Brain's Default Network During Sleep Deprivation: A Resting-State EEG Study

INTRODUCTION

Sleep deprivation (SD) has a negative influence on mood and emotion processing, and previous studies have elucidated the impaired coupling within the default network (DN) after SD. However, the dynamic characteristic with high temporal precision was rarely investigated in the DN after SD.

METHODS

Here, the resting-state EEG after nocturnal sleep (NS) and SD was collected from 31 participants. The cortical electrical activities of the posterior cingulate cortex (PCC) and the anterior medial prefrontal cortex (aMPFC) were reconstructed applying the eLORETA, and the functional connectivity (FC) of PCC-aMPFC was calculated using the power envelope connectivity (PEC).

RESULTS

Compared with NS, the power spectrums of the PCC and the FC of PCC-aMPFC were significantly reduced in the α band after SD. Interestingly, the impaired PCC-aMPFC integration was positively correlated with the decreased positive affect, implying that the DN plays a critical role in the subjective mood state. Our moderation analysis further revealed that the intensity of the DN posterior-anterior interaction moderated sleep loss and positive affect.

DISCUSSION

Overall, the results reveal the strong relationship between the uncoupling of DN and the feeling down of mood. Our research may contribute towards a better understanding of the mood and cognition processing after sleep loss.

The Effect of Ketamine on Electrophysiological Connectivity in Major Depressive Disorder

Major depressive disorder (MDD) is highly prevalent and frequently disabling. Only about 30% of patients respond to a first-line antidepressant treatment, and around 30% of patients are classified as "treatment-resistant" after failing to respond to multiple adequate trials. While most antidepressants target monoaminergic targets, ketamine is an N-methyl-D-aspartate (NMDA) antagonist that has shown rapid antidepressant effects when delivered intravenously or intranasally. While there is evidence that ketamine exerts its effects via enhanced α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) throughput, its mechanism for relieving depressive symptoms is largely unknown. This study acquired resting-state magnetoencephalography (MEG) recordings after both ketamine and placebo infusions and investigated functional connectivity using a multilayer amplitude-amplitude correlation technique spanning the canonical frequency bands. Twenty-four healthy volunteers (HVs) and 27 unmedicated participants with MDD took part in a double-blind, placebo-controlled, crossover trial of 0.5 mg/kg IV ketamine. Order of infusion was randomized, and participants crossed over to receive the second infusion after two weeks. The results indicated widespread ketamine-induced reductions in connectivity in the alpha and beta bands that did not correlate with magnitude of antidepressant response. In contrast, the magnitude of ketamine's antidepressant effects in MDD participants was associated with cross-frequency connectivity for delta-alpha and delta-gamma bands, with HVs and ketamine non-responders showing connectivity decreases post-ketamine and ketamine responders demonstrating small increases in connectivity. These results may indicate functional subtypes of MDD and also suggest that neural responses to ketamine are fundamentally different between responders and non-responders.

Resting-State Magnetoencephalography Source Imaging Pilot Study in Children with Mild Traumatic Brain Injury

Mild traumatic brain injury (mTBI) accounts for the vast majority of all pediatric TBI. An important minority of children who have suffered an mTBI have enduring cognitive and emotional symptoms. However, the mechanisms of chronic symptoms in children with pediatric mTBI are not fully understood. This is in part due to the limited sensitivity of conventional neuroimaging technologies. The present study examined resting-state magnetoencephalography (rs-MEG) source images in 12 children who had mTBI and 12 age-matched control children. The rs-MEG exams were performed in children with mTBI 6 months after injury when they reported no clinically significant post-injury psychiatric changes and few if any somatic sensorimotor symptoms but did report cognitive symptoms. MEG source magnitude images were obtained for different frequency bands in alpha (8-12 Hz), beta (15-30 Hz), gamma (30-90 Hz), and low-frequency (1-7 Hz) bands. In contrast to the control participants, rs-MEG source imaging in the children with mTBI showed: 1) hyperactivity from the bilateral insular cortices in alpha, beta, and low-frequency bands, from the left amygdala in alpha band, and from the left precuneus in beta band; 2) hypoactivity from the bilateral dorsolateral prefrontal cortices (dlPFC) in alpha and beta bands, from the ventromedial prefrontal cortex (vmPFC) in beta band, from the ventrolateral prefrontal cortex (vlPFC) in gamma band, from the anterior cingulate cortex (ACC) in alpha band, and from the right precuneus in alpha band. The present study showed that MEG source imaging technique revealed abnormalities in the resting-state electromagnetic signals from the children with mTBI.

Evidence that alpha blocking is due to increases in system-level oscillatory damping not neuronal population desynchronisation

The attenuation of the alpha rhythm following eyes-opening (alpha blocking) is among the most robust features of the human electroencephalogram with the prevailing view being that it is caused by changes in neuronal population synchrony. To further study the basis for this phenomenon we use theoretically motivated fixed-order Auto-Regressive Moving-Average (ARMA) time series modelling to study the oscillatory dynamics of spontaneous alpha-band electroencephalographic activity in eyes-open and eyes-closed conditions and its modulation by the NMDA antagonist ketamine. We find that the reduction in alpha-band power between eyes-closed and eyes-open states is explicable in terms of an increase in the damping of stochastically perturbed alpha-band relaxation oscillatory activity. These changes in damping are putatively modified by the antagonism of NMDA-mediated glutamatergic neurotransmission but are not directly driven by changes in input to cortex nor by reductions in the phase synchronisation of populations of near identical oscillators. These results not only provide a direct challenge to the dominant view of the role that thalamus and neuronal population de-/synchronisation have in the genesis and modulation of alpha electro-/magnetoencephalographic activity but also suggest potentially important physiological determinants underlying its dynamical control and regulation.

Neurophenomenology of near-death experience memory in hypnotic recall: a within-subject EEG study

The neurobiological basis of near-death experiences (NDEs) is unknown, but a few studies attempted to investigate it by reproducing in laboratory settings phenomenological experiences that seem to closely resemble NDEs. So far, no study has induced NDE-like features via hypnotic modulation while simultaneously measuring changes in brain activity using high-density EEG. Five volunteers who previously had experienced a pleasant NDE were invited to re-experience the NDE memory and another pleasant autobiographical memory (dating to the same time period), in normal consciousness and with hypnosis. We compared the hypnosis-induced subjective experience with the one of the genuine experience memory. Continuous high-density EEG was recorded throughout. At a phenomenological level, we succeeded in recreating NDE-like features without any adverse effects. Absorption and dissociation levels were reported as higher during all hypnosis conditions as compared to normal consciousness conditions, suggesting that our hypnosis-based protocol increased the felt subjective experience in the recall of both memories. The recall of a NDE phenomenology was related to an increase of alpha activity in frontal and posterior regions. This study provides a proof-of-concept methodology for studying the phenomenon, enabling to prospectively explore the NDE-like features and associated EEG changes in controlled settings.

Parameter estimation and identifiability in a neural population model for electro-cortical activity

Electroencephalography (EEG) provides a non-invasive measure of brain electrical activity. Neural population models, where large numbers of interacting neurons are considered collectively as a macroscopic system, have long been used to understand features in EEG signals. By tuning dozens of input parameters describing the excitatory and inhibitory neuron populations, these models can reproduce prominent features of the EEG such as the alpha-rhythm. However, the inverse problem, of directly estimating the parameters from fits to EEG data, remains unsolved. Solving this multi-parameter non-linear fitting problem will potentially provide a real-time method for characterizing average neuronal properties in human subjects. Here we perform unbiased fits of a 22-parameter neural population model to EEG data from 82 individuals, using both particle swarm optimization and Markov chain Monte Carlo sampling. We estimate how much is learned about individual parameters by computing Kullback-Leibler divergences between posterior and prior distributions for each parameter. Results indicate that only a single parameter, that determining the dynamics of inhibitory synaptic activity, is directly identifiable, while other parameters have large, though correlated, uncertainties. We show that the eigenvalues of the Fisher information matrix are roughly uniformly spaced over a log scale, indicating that the model is sloppy, like many of the regulatory network models in systems biology. These eigenvalues indicate that the system can be modeled with a low effective dimensionality, with inhibitory synaptic activity being prominent in driving system behavior.

Connecting occipital alpha band peak frequency, visual temporal resolution, and occipital GABA levels in healthy participants and hepatic encephalopathy patients

Recent studies have proposed a connection between the individual alpha band peak frequency and the temporal resolution of visual perception in healthy human participants. This connection rests on animal studies describing oscillations in the alpha band as a mode of phasic thalamocortical information transfer for low-level visual stimuli, which critically relies on GABAergic interneurons. Here, we investigated the interplay of these parameters by measuring occipital alpha band peak frequency by means of magnetoencephalography, visual temporal resolution by means of behavioral testing, and occipital GABA levels by means of magnetic resonance spectroscopy. Importantly, we investigated a sample of healthy participants and patients with varying grades of hepatic encephalopathy, which are known to exhibit decreases in the investigated parameters, thus providing an increased parameter space. We found that occipital alpha band peak frequency and visual temporal resolution were positively correlated, i.e., higher occipital alpha band peak frequencies were on average related to a higher temporal resolution. Likewise, occipital alpha band peak frequency correlated positively with occipital GABA levels. However, correlations were significant only when both healthy participants and patients were included in the analysis, thereby indicating a connection of the measures on group level (instead of the individual level). These findings provide new insights into neurophysiological and neurochemical underpinnings of visual perception.