Relationship Between Alpha Rhythm and the Default Mode Network: An EEG-fMRI Study

A retrospective chart review to assess the impact of alpha-guided transcranial magnetic stimulation on symptoms of PTSD and depression in active-duty special operations service members

Introduction

Special Operations Forces service members (SOF) are regularly exposed to traumatic and concussive events, increasing the prevalence of symptoms of post-traumatic stress disorder (PTSD) and depression, shortening potential years of service.

Methods

This retrospective chart review presents preliminary data on a Human Performance Optimization (HPO) program that provided an average of 30 sessions of individualized alpha frequency repetitive transcranial magnetic stimulation (α-rTMS) to active-duty SOF as to reduce symptoms of PTSD and depression following traumatic brain injury. Scores from the PTSD Checklist for DSM-5, PROMIS Depression short form and Perceived Deficits Questionnaire (PDQ) were reviewed.

Results

Significant reductions were noted after the HPO program in all clinical scales with an average 37% decrease in PCL-5 (p<.01), 11.3% reduction in PROMIS depression T-scores (p<.01), and 45.5% reduction in PDQ scales by session 30 (p<.01), with side effects matching those commonly reported in rTMS. Importantly, the average PCL-5 score decreased from 42.9 to 27 by end of the treatment program, which is below the clinical threshold of 33 for presence of PTSD. For those with depression symptoms scores greater than cut off clinical thresholds at baseline, 46% resolved following treatment.

Conclusion

This data provides preliminary support for safe application of α-rTMS for symptom reduction in active-duty special operations military personnel.

Effect of Forward Head Posture on Resting State Brain Function

Forward head posture (FHP) is a common postural problem experienced by most people. However, its effect on brain activity is still unknown. Accordingly, we aimed to observe changes in brain waves at rest to determine the effect of FHP on the nervous systems. A total of 33 computer users (Male = 17; Female = 16; age = 22.18 ± 1.88) were examined in both FHP and neutral posture. For each session, brain waves were measured for 5 min, and then muscle mechanical properties and cranio-vertebral angle (CVA) were measured. Changes in brain waves between the neutral posture and FHP were prominent in gamma waves. A notable increase was confirmed in the frontal and parietal lobes. That is, eight channels in the frontal lobe and all channels in the parietal lobe showed a significant increase in FHP compared to neutral posture. Additionally, FHP changes were associated with a decrease in CVA (p < 0.001), an increase in levator scapulae tone (Right, p = 0.014; Left, p = 0.001), and an increase in right sternocleidomastoid stiffness (p = 0.002), and a decrease in platysma elasticity (Right, p = 0.039; Left, p = 0.017). The change in CVA was found to have a negative correlation with the gamma activity (P7, p = 0.044; P8, p = 0.004). Therefore, increased gamma wave activity in FHP appears to be related to CVA decrease due to external force that was applied to the nervous system and cervical spine.

Judgments of Learning Reactively Improve Memory by Enhancing Learning Engagement and Inducing Elaborative Processing: Evidence from an EEG Study

Making judgments of learning (JOLs) can reactively alter memory itself, a phenomenon termed the reactivity effect. The current study recorded electroencephalography (EEG) signals during the encoding phase of a word list learning task to explore the neurocognitive features associated with JOL reactivity. The behavioral results show that making JOLs reactively enhances recognition performance. The EEG results reveal that, compared with not making JOLs, making JOLs increases P200 and LPC amplitudes and decreases alpha and beta power. Additionally, the signals of event-related potentials (ERPs) and event-related desynchronizations (ERDs) partially mediate the reactivity effect. These findings support the enhanced learning engagement theory and the elaborative processing explanation to account for the JOL reactivity effect.

Exploring the correlation and causation between alpha oscillations and one-second time perception through EEG and tACS

Alpha oscillations have been implicated in time perception, yet a consensus on their precise role remains elusive. This study directly investigates this relationship by examining the impact of alpha oscillations on time perception. Resting-state EEG recordings were used to extract peak alpha frequency (PAF) and peak alpha power (PAP) characteristics. Participants then performed a time generalization task under transcranial alternating current stimulation (tACS) at frequencies of PAF-2, PAF, and PAF+2, as well as a sham condition. Results revealed a significant correlation between PAP and accuracy, and between PAF and precision of one-second time perception in the sham condition. This suggests that alpha oscillations may influence one-second time perception by modulating their frequency and power. Interestingly, these correlations weakened with real tACS stimulations, particularly at higher frequencies. A second analysis aimed to establish a causal relationship between alpha peak modulation by tACS and time perception using repeated measures ANOVAs, but no significant effect was observed. Results were interpreted according to the state-dependent networks and internal clock model.

EEG-based neurophysiological indices for expert psychomotor performance - a review

A primary objective of current human neuropsychological performance research is to define the physiological correlates of adaptive knowledge utilization, in order to support the enhanced execution of both simple and complex tasks. Within the present article, electroencephalography-based neurophysiological indices characterizing expert psychomotor performance, will be explored. As a means of characterizing fundamental processes underlying efficient psychometric performance, the neural efficiency model will be evaluated in terms of alpha-wave-based selective cortical processes. Cognitive and motor domains will initially be explored independently, which will act to encapsulate the task-related neuronal adaptive requirements for enhanced psychomotor performance associating with the neural efficiency model. Moderating variables impacting the practical application of such neuropsychological model, will also be investigated. As a result, the aim of this review is to provide insight into detectable task-related modulation involved in developed neurocognitive strategies which support heightened psychomotor performance, for the implementation within practical settings requiring a high degree of expert performance (such as sports or military operational settings).

Towards an electroencephalographic measure of awareness based on the reactivity of oscillatory macrostates to hearing a subject's own name

We proposed that the brain's electrical activity is composed of a sequence of alternating states with repeating topographic spectral distributions on scalp electroencephalogram (EEG), referred to as oscillatory macrostates. The macrostate showing the largest decrease in the probability of occurrence, measured as a percentage (reactivity), during sensory stimulation was labelled as the default EEG macrostate (DEM). This study aimed to assess the influence of awareness on DEM reactivity (DER). We included 11 middle cerebral artery ischaemic stroke patients with impaired awareness having a median Glasgow Coma Scale (GCS) of 6/15 and a group of 11 matched healthy controls. EEG recordings were carried out during auditory 1 min stimulation epochs repeating either the subject's own name (SON) or the SON in reverse (rSON). The DEM was identified across three SON epochs alternating with three rSON epochs. Compared with the patients, the DEM of controls contained more posterior theta activity reflecting source dipoles that could be mapped in the posterior cingulate cortex. The DER was measured from the 1 min quiet baseline preceding each stimulation epoch. The difference in mean DER between the SON and rSON epochs was measured by the salient EEG reactivity (SER) theoretically ranging from -100% to 100%. The SER was 12.4 ± 2.7% (Mean ± standard error of the mean) in controls and only 1.3 ± 1.9% in the patient group (P < 0.01). The patient SER decreased with the Glasgow Coma Scale. Our data suggest that awareness increases DER to SON as measured by SER.

Effects of task context on EEG correlates of mind-wandering

This study was designed to examine how mind-wandering and its neural correlates vary across tasks with different attentional demands, motivated by the context regulation hypothesis of mind-wandering. Participants (n = 59 undergraduates) completed the sustained attention to response task (SART) and the Stroop selective attention task in counterbalanced order while EEG was recorded. The tasks included experience-sampling probes to identify self-reported episodes of mind-wandering, along with retrospective reports. Participants reported more mind-wandering during the SART than the Stroop and during whichever task was presented second during the session, compared with first. Replicating previous findings, EEG data (n = 37 usable participants) indicated increased alpha oscillations during episodes of mind-wandering, compared with on-task episodes, for both the SART and Stroop tasks. ERP data, focused on the P2 component reflecting perceptual processing, found that mind-wandering was associated with increased P2 amplitudes during the Stroop task, counter to predictions from the perceptual decoupling theory. Overall, the study found that self-report and neural correlates of mind-wandering are sensitive to task context. This line of research can further the understanding of how mechanisms of mind-wandering are adapted to varied tasks and situations.

Oscillatory network markers of subcallosal cingulate deep brain stimulation for depression

Identifying functional biomarkers related to treatment success can aid in expediting therapy optimization, as well as contribute to a better understanding of the neural mechanisms of the treatment-resistant depression (TRD) and subcallosal cingulate deep brain stimulation (SCC-DBS). Magnetoencephalography data were obtained from 16 individuals with SCC-DBS for TRD and 25 healthy subjects. The first objective of the study was to identify region-specific oscillatory modulations that both (i) discriminate individuals with TRD (with SCC-DBS OFF) from healthy controls, and (ii) discriminate TRD treatment responders from non-responders (with SCC-DBS ON). The second objective of this work was to further explore the effects of stimulation intensity and frequency on oscillatory activity in the identified brain regions of interest. Oscillatory power analyses led to the identification of brain regions that differentiated responders from non-responders based on modulations of increased alpha (8-12 Hz) and decreased gamma (32-116 Hz) power within nodes of the default mode, central executive, and somatomotor networks, Broca's area, and lingual gyrus. Within these nodes, it was also found that low stimulation frequency had stronger effects on oscillatory modulation than increased stimulation intensity. The identified functional network biomarkers implicate modulation of TRD-related activity in brain regions involved in emotional control/processing, motor control, and the interaction between speech, vision, and memory, which have all been implicated in depression. These electrophysiological biomarkers have the potential to be used as functional proxies for therapy optimization. Additional stimulation parameter analyses revealed that oscillatory modulations can be strengthened by increasing stimulation intensity or reducing frequency, which may represent potential avenues of direction in non-responders.

Pain-free default mode network connectivity contributes to tonic experimental pain intensity beyond the role of negative mood and other pain-related factors

BACKGROUND

Alterations in the default mode network (DMN) connectivity across pain stages suggest a possible DMN involvement in the transition to persistent pain.

AIM

This study examined whether pain-free DMN connectivity at lower alpha oscillations (8-10 Hz) accounts for a unique variation in experimental peak pain intensity beyond the contribution of factors known to influence pain intensity.

METHODS

Pain-free DMN connectivity was measured with electroencephalography prior to 1 h of capsaicin-evoked pain using a topical capsaicin patch on the right forearm. Pain intensity was assessed on a (0-10) numerical rating scale and the association between peak pain intensity and baseline measurements was examined using hierarchical multiple regression in 52 healthy volunteers (26 women). The baseline measurements consisted of catastrophizing (helplessness, rumination, magnification), vigilance, depression, negative and positive affect, sex, age, sleep, fatigue, thermal and mechanical pain thresholds and DMN connectivity (medial prefrontal cortex [mPFC]-posterior cingulate cortex [PCC], mPFC-right angular gyrus [rAG], mPFC-left Angular gyrus [lAG], rAG-mPFC and rAG-PCC).

RESULTS

Pain-free DMN connectivity increased the explained variance in peak pain intensity beyond the contribution of other factors (ΔR2  = 0.10, p = 0.003), with the final model explaining 66% of the variation (R2  = 0.66, ANOVA: p < 0.001). In this model, negative affect (β = 0.51, p < 0.001), helplessness (β = 0.49, p = 0.007), pain-free mPFC-lAG connectivity (β = 0.36, p = 0.003) and depression (β = -0.39, p = 0.009) correlated significantly with peak pain intensity. Interestingly, negative affect and depression, albeit both being negative mood indices, showed opposing relationships with peak pain intensity.

CONCLUSIONS

This work suggests that pain-free mPFC-lAG connectivity (at lower alpha) may contribute to individual variations in pain-related vulnerability.

SIGNIFICANCE

These findings could potentially lead the way for investigations in which DMN connectivity is used in identifying individuals more likely to develop chronic pain.

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.

Cognition is entangled with metabolism: relevance for resting-state EEG-fMRI

The brain is a living organ with distinct metabolic constraints. However, these constraints are typically considered as secondary or supportive of information processing which is primarily performed by neurons. The default operational definition of neural information processing is that (1) it is ultimately encoded as a change in individual neuronal firing rate as this correlates with the presentation of a peripheral stimulus, motor action or cognitive task. Two additional assumptions are associated with this default interpretation: (2) that the incessant background firing activity against which changes in activity are measured plays no role in assigning significance to the extrinsically evoked change in neural firing, and (3) that the metabolic energy that sustains this background activity and which correlates with differences in neuronal firing rate is merely a response to an evoked change in neuronal activity. These assumptions underlie the design, implementation, and interpretation of neuroimaging studies, particularly fMRI, which relies on changes in blood oxygen as an indirect measure of neural activity. In this article we reconsider all three of these assumptions in light of recent evidence. We suggest that by combining EEG with fMRI, new experimental work can reconcile emerging controversies in neurovascular coupling and the significance of ongoing, background activity during resting-state paradigms. A new conceptual framework for neuroimaging paradigms is developed to investigate how ongoing neural activity is "entangled" with metabolism. That is, in addition to being recruited to support locally evoked neuronal activity (the traditional hemodynamic response), changes in metabolic support may be independently "invoked" by non-local brain regions, yielding flexible neurovascular coupling dynamics that inform the cognitive context. This framework demonstrates how multimodal neuroimaging is necessary to probe the neurometabolic foundations of cognition, with implications for the study of neuropsychiatric disorders.

Decomposing age effects in EEG alpha power

Increasing life expectancy is prompting the need to understand how the brain changes during healthy aging. Research utilizing electroencephalography (EEG) has found that the power of alpha oscillations decrease from adulthood on. However, non-oscillatory (aperiodic) components in the data may confound results and thus require re-investigation of these findings. Thus, the present report analyzed a pilot and two additional independent samples (total N = 533) of resting-state EEG from healthy young and elderly individuals. A newly developed algorithm was utilized that allows the decomposition of the measured signal into periodic and aperiodic signal components. By using multivariate sequential Bayesian updating of the age effect in each signal component, evidence across the datasets was accumulated. It was hypothesized that previously reported age-related alpha power differences will largely diminish when total power is adjusted for the aperiodic signal component. First, the age-related decrease in total alpha power was replicated. Concurrently, decreases of the intercept and slope (i.e. exponent) of the aperiodic signal component were observed. Findings on aperiodic-adjusted alpha power indicated that this general shift of the power spectrum leads to an overestimation of the true age effects in conventional analyses of total alpha power. Thus, the importance of separating neural power spectra into periodic and aperiodic signal components is highlighted. However, also after accounting for these confounding factors, the sequential Bayesian updating analysis provided robust evidence that aging is associated with decreased aperiodic-adjusted alpha power. While the relation of the aperiodic component and aperiodic-adjusted alpha power to cognitive decline demands further investigation, the consistent findings on age effects across independent datasets and high test-retest reliabilities support that these newly emerging measures are reliable markers of the aging brain. Hence, previous interpretations of age-related decreases in alpha power are reevaluated, incorporating changes in the aperiodic signal.

EEG Resting-State Functional Networks in Amnestic Mild Cognitive Impairment

Background. Alzheimer's cognitive-behavioral syndrome is the result of impaired connectivity between nerve cells, due to misfolded proteins, which accumulate and disrupt specific brain networks. Electroencephalography, because of its excellent temporal resolution, is an optimal approach for assessing the communication between functionally related brain regions. Objective. To detect and compare EEG resting-state networks (RSNs) in patients with amnesic mild cognitive impairment (aMCI), and healthy elderly (HE). Methods. We recruited 125 aMCI patients and 70 healthy elderly subjects. One hundred and twenty seconds of artifact-free EEG data were selected and compared between patients with aMCI and HE. We applied standard low-resolution brain electromagnetic tomography (sLORETA)-independent component analysis (ICA) to assess resting-state networks. Each network consisted of a set of images, one for each frequency (delta, theta, alpha1/2, beta1/2). Results. The functional ICA analysis revealed 17 networks common to groups. The statistical procedure demonstrated that aMCI used some networks differently than HE. The most relevant findings were as follows. Amnesic-MCI had: i) increased delta/beta activity in the superior frontal gyrus and decreased alpha1 activity in the paracentral lobule (ie, default mode network); ii) greater delta/theta/alpha/beta in the superior frontal gyrus (i.e, attention network); iii) lower alpha in the left superior parietal lobe, as well as a lower delta/theta and beta, respectively in post-central, and in superior frontal gyrus(ie, attention network). Conclusions. Our study confirms sLORETA-ICA method is effective in detecting functional resting-state networks, as well as between-groups connectivity differences. The findings provide support to the Alzheimer's network disconnection hypothesis.

Decreased Default Mode Network Connectivity Following 24 Hours of Capsaicin-induced Pain Persists During Immediate Pain Relief and Facilitation

Prolonged experimental pain models can help assess cortical mechanisms underlying the transition from acute to chronic pain such as resting-state functional connectivity (rsFC), especially in early stages. This crossover study determined the effects of 24-hour-capsaicin-induced pain on the default mode network rsFC, a major network in the dynamic pain connectome. Electroencephalographic rsFC measured by Granger causality was acquired from 24 healthy volunteers (12 women) at baseline, 1hour, and 24hours following the application of a control or capsaicin patch on the right forearm. The control patch was received maximum 1 week before the capsaicin patch. Following 24hours, the patch was cooled and later heated to assess rsFC changes in response to pain relief and facilitation, respectively. Compared to baseline, decreased rsFC at alpha oscillations (8-10Hz) was found following 1hour and 24hours of capsaicin application for connections projecting from medial prefrontal cortex (mPFC) and right angular gyrus (rAG) but not left angular gyrus (lAG) or posterior cingulate cortex (PCC): mPFC-PCC (1hour:P < .001, 24hours:P = .002), mPFC-rAG (1hour:P < .001, 24hours:P = .001), rAG-mPFC (1hour:P < .001, 24hours:P = .001), rAG-PCC (1hour:P < .001, 24hours:P = .004). Comparable decreased rsFC following 1hour and 24hours (P≤0.008) was found at beta oscillations, however, decreased projections from PCC were also found: PCC-rAG (P≤0.005) and PCC-lAG (P≤0.006). Pain NRS scores following 24hours (3.7±0.4) was reduced by cooling (0.3±0.1, P = .004) and increased by heating (4.8±0.6, P = .016). However, neither cooling nor heating altered rsFC. This study shows that 24hours of experimental pain induces a robust decrease in DMN connectivity that persists during pain relief or facilitation suggesting a possible shift to attentional and emotional processing in persistent pain. PERSPECTIVE: This article shows decreased DMN connectivity that might reflect possible attentional and emotional changes during acute and prolonged pain. Understanding these changes could potentially help clinicians in developing therapeutic methods that can better target these attentional and emotional processes before developing into more persistent states.

Extracting electrophysiological correlates of functional magnetic resonance imaging data using the canonical polyadic decomposition

The relation between electrophysiology and BOLD-fMRI requires further elucidation. One approach for studying this relation is to find time-frequency features from electrophysiology that explain the variance of BOLD time-series. Convolution of these features with a canonical hemodynamic response function (HRF) is often required to model neurovascular coupling mechanisms and thus account for time shifts between electrophysiological and BOLD-fMRI data. We propose a framework for extracting the spatial distribution of these time-frequency features while also estimating more flexible, region-specific HRFs. The core component of this method is the decomposition of a tensor containing impulse response functions using the Canonical Polyadic Decomposition. The outputs of this decomposition provide insight into the relation between electrophysiology and BOLD-fMRI and can be used to construct estimates of BOLD time-series. We demonstrated the performance of this method on simulated data while also examining the effects of simulated measurement noise and physiological confounds. Afterwards, we validated our method on publicly available task-based and resting-state EEG-fMRI data. We adjusted our method to accommodate the multisubject nature of these datasets, enabling the investigation of inter-subject variability with regards to EEG-to-BOLD neurovascular coupling mechanisms. We thus also demonstrate how EEG features for modelling the BOLD signal differ across subjects.

Diagnostic delay in functional seizures is associated with abnormal processing of facial emotions

PURPOSE

In patients with functional seizures (FS), delay in diagnosis (DD) may negatively affect outcomes. Altered brain responses to emotional stimuli have been shown in adults with FS. We hypothesized that DD would be associated with differential fMRI activation in emotion processing circuits.

METHODS

Fifty-two adults (38 females) with video-EEG confirmed FS prospectively completed assessments related to symptoms of depression (BDI-II), anxiety (BAI), post-traumatic stress disorder (PCL-S), a measure of how their symptoms affect day-to-day life (GAF), and fMRI at 3T with emotional faces task (EFT). During fMRI, subjects indicated "male" or "female" via button press while implicitly processing happy, sad, fearful, and neutral faces. Functional magnetic resonance imaging (FMRI) response to each emotion was modeled and group analyses were performed in AFNI within pre-specified regions-of-interest involved in emotion processing. A median split (507 days) defined short- (s-DD) and long-delay diagnosis (l-DD) groups. Voxelwise regression analyses were also performed to examine linear relationship between DD and emotion processing. FMRI signal was extracted from clusters showing group differences and Spearman's correlations assessed relationships with symptom scores.

RESULTS

Groups did not differ in FS age of onset, sex distribution, years of education, TBI characteristics, EFT in-scanner or post-test performance, or scores on the GAF, BDI-II, BAI, and PCL-S measures. The s-DD group was younger than l-DD (mean age 32.6 vs. 40.1; p = 0.022) at the time of study participation. After correcting for age, compared to s-DD, the l-DD group showed greater fMRI activation to sad faces in the bilateral posterior cingulate cortex (PCC) and to neutral faces in the right anterior insula. Within-group linear regression revealed that with increasing DD, there was increased fMRI activation to sad faces in the PCC and to happy faces in the right anterior insula/inferior frontal gyrus (AI/IFG). There were positive correlations between PCC response to sad faces and BDI-II scores in the l-DD group (rho = 0.48, p = 0.012) and the combined sample (rho = 0.30, p = 0.029). Increased PCC activation to sad faces in those in the l-DD group was associated with worse symptoms of depression (i.e. higher BDI-II score).

CONCLUSIONS

Delay in FS diagnosis is associated with fMRI changes in PCC and AI/IFG. As part of the default mode network, PCC is implicated in mood control, self-referencing, and other emotion-relevant processes. In our study, PCC changes are linked to depression. Future studies should assess the effects of interventions on these abnormalities.

Angular gyrus connectivity at alpha and beta oscillations is reduced during tonic pain - Differential effect of eye state

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Tonic pain differentially altered AG connectivity during eyes closed and eyes open.

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Negative mood and/or sleep quality can influence pain-related connectivity.

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Eyes closed baseline may allow for a reliable detection of pain-related changes.

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Eyes-closed-eyes-open sequence is crucial for assessing pain-related connectivity.

The angular gyrus (AG) is a common hub in the pain networks. The role of the AG during pain perception, however, is still unclear. This crossover study examined the effect of tonic pain on resting state functional connectivity (rsFC) of the AG under eyes closed (EC) and eyes open (EO). It included two sessions (placebo/pain) separated by 24 hours. Pain was induced using topical capsaicin (or placebo as control) on the right forearm. Electroencephalographic rsFC assessed by Granger causality was acquired from 28 healthy participants (14 women) before (baseline) and 1-hour following the application of placebo/capsaicin. Subjects were randomly assigned and balanced to groups of recording sequence (EC-EO, EO-EC). Decreased rsFC at alpha-1 and beta, but not alpha-2, oscillations was found during pain compared to baseline during EC only. For alpha-1, EC-EO group showed a pain-induced decrease only among connections between the right AG and each of the posterior cingulate cortex (PCC, P = 0.002), medial prefrontal cortex (mPFC, P = 0.005), and the left AG (P = 0.023). For beta rsFC, the EC-EO group showed a bilateral decrease in rsFC spanning the connections between the right AG and mPFC (P = 0.015) and between the left AG and each of PCC (P = 0.004) and mPFC (P = 0.026). In contrast, the EO-EC group showed an increase in beta rsFC only among connections between the left AG and each of PCC (P = 0.012) and mPFC (P = 0.036). No significant change in the AG rsFC was found during EO. These results provide insight into the involvement of the AG in pain perception and reveal methodological considerations when assessing rsFC during EO and EC.

Preferred music listening is associated with perceptual learning enhancement at the expense of self-focused attention

Can preferred music listening improve following attentional and learning performances? Here we suggest that this may be the case. In Experiment 1, following preferred and non-preferred musical-piece listening, we recorded electrophysiological responses to an auditory roving-paradigm. We computed the mismatch negativity (MMN - the difference between responses to novel and repeated stimulation), as an index of perceptual learning, and we measured the correlation between trial-by-trial EEG responses and the fluctuations in Bayesian Surprise, as a quantification of the neural attunement with stimulus informational value. Furthermore, during music listening, we recorded oscillatory cortical activity. MMN and trial-by-trial correlation with Bayesian surprise were significantly larger after subjectively preferred versus non-preferred music, indicating the enhancement of perceptual learning. The analysis on oscillatory activity during music listening showed a selective alpha power increased in response to preferred music, an effect often related to cognitive enhancements. In Experiment 2, we explored whether this learning improvement was realized at the expense of self-focused attention. Therefore, after preferred versus non-preferred music listening, we collected Heart-Beat Detection (HBD) accuracy, as a measure of the attentional focus toward the self. HBD was significantly lowered following preferred music listening. Overall, our results suggest the presence of a specific neural mechanism that, in response to aesthetically pleasing stimuli, and through the modulation of alpha oscillatory activity, redirects neural resources away from the self and toward the environment. This attentional up-weighting of external stimuli might be fruitfully exploited in a wide area of human learning activities, including education, neurorehabilitation and therapy.

Aperiodic measures of neural excitability are associated with anticorrelated hemodynamic networks at rest: A combined EEG-fMRI study

The hallmark of resting EEG spectra are distinct rhythms emerging from a broadband, aperiodic background. This aperiodic neural signature accounts for most of total EEG power, although its significance and relation to functional neuroanatomy remains obscure. We hypothesized that aperiodic EEG reflects a significant metabolic expenditure and therefore might be associated with the default mode network while at rest. During eyes-open, resting-state recordings of simultaneous EEG-fMRI, we find that aperiodic and periodic components of EEG power are only minimally associated with activity in the default mode network. However, a whole-brain analysis identifies increases in aperiodic power correlated with hemodynamic activity in an auditory-salience-cerebellar network, and decreases in aperiodic power are correlated with hemodynamic activity in prefrontal regions. Desynchronization in residual alpha and beta power is associated with visual and sensorimotor hemodynamic activity, respectively. These findings suggest that resting-state EEG signals acquired in an fMRI scanner reflect a balance of top-down and bottom-up stimulus processing, even in the absence of an explicit task.

A method to assess the default EEG macrostate and its reactivity to stimulation

OBJECTIVE

The default mode network (DMN) is deactivated by stimulation. We aimed to assess the DMN reactivity impairment by routine EEG recordings in stroke patients with impaired consciousness.

METHODS

Binocular light flashes were delivered at 1 Hz in 1-minute epochs, following a 1-minute baseline (PRE). The EEG was decomposed in a series of binary oscillatory macrostates by topographic spectral clustering. The most deactivated macrostate was labeled the default EEG macrostate (DEM). Its reactivity (DER) was quantified as the decrease in DEM occurrence probability during stimulation. A normalized DER index (DERI) was calculated as DER/PRE. The measures were compared between 14 healthy controls and 32 comatose patients under EEG monitoring following an acute stroke.

RESULTS

The DEM was mapped to the posterior DMN hubs. In the patients, these DEM source dipoles were 3-4 times less frequent and were associated with an increased theta activity. Even in a reduced 6-channel montage, a DER below 6.26% corresponding to a DERI below 0.25 could discriminate the patients with sensitivity and specificity well above 80%.

CONCLUSION

The method detected the DMN impairment in post-stroke coma patients.

SIGNIFICANCE

The DEM and its reactivity to stimulation could be useful to monitor the DMN function at bedside.

Relationship between Resting-State Alpha Coherence and Cognitive Control in Individuals with Internet Gaming Disorder: A Multimodal Approach Based on Resting-State Electroencephalography and Event-Related Potentials

The human brain is constantly active, even at rest. Alpha coherence is an electroencephalography (EEG) rhythm that regulates functional connectivity between different brain regions. However, the relationships between resting-state alpha coherence and N2/P3 components associated with response inhibition and cognitive processes have not been investigated in addictive disorders. The present study investigated the relationships between alpha coherence during the resting state and N2/P3 components of event-related potentials during the Go/Nogo task in healthy controls (HCs) and patients with Internet gaming disorder (IGD). A total of 64 young adults (HC: n = 31; IGD: n = 33) participated in this study. Alpha coherence values at left fronto-central and bilateral centro-temporal electrode sites were significantly correlated with P3 latency in HCs, whereas inverse correlations were observed in patients with IGD. Furthermore, significant differences were observed in the correlation values between the groups. Our results suggest that patients with IGD lack dynamic interactions of functional connectivity between the fronto-centro-temporal regions during the resting state and the event-related potential (ERP) index during cognitive tasks. The findings of this study may have important implications for understanding the neurophysiological mechanisms linking resting-state EEG and task-related ERPs underlying IGD.

Cross-Task Consistency of Electroencephalography-Based Mental Workload Indicators: Comparisons Between Power Spectral Density and Task-Irrelevant Auditory Event-Related Potentials

Mental workload (MWL) estimators based on ongoing electroencephalography (EEG) and event-related potentials (ERPs) have shown great potentials to build adaptive aiding systems for human-machine systems by estimating MWL in real time. However, extracting EEG features which are consistent in indicating MWL across different tasks is still one of the critical challenges. This study attempts to compare the cross-task consistency in indexing MWL variations between two commonly used EEG-based MWL indicators, power spectral density (PSD) of ongoing EEG and task-irrelevant auditory ERPs (tir-aERPs). The verbal N-back and the multi-attribute task battery (MATB), both with two difficulty levels, were employed in the experiment, along with task-irrelevant auditory probes. EEG was recorded from 17 subjects when they were performing the tasks. The tir-aERPs elicited by the auditory probes and the relative PSDs of ongoing EEG between two consecutive auditory probes were extracted and statistically analyzed to reveal the effects of MWL and task type. Discriminant analysis and support vector machine were employed to examine the generalization of tir-aERP and PSD features in indexing MWL variations across different tasks. The results showed that the amplitudes of tir-aERP components, N1, early P3a, late P3a, and the reorienting negativity, significantly decreased with the increasing MWL in both N-back and MATB. Task type had no obvious influence on the amplitudes and topological layout of the MWL-sensitive tir-aERP features. The relative PSDs in θ, α, and low β bands were also sensitive to MWL variations. However, the MWL-sensitive PSD features and their topological patterns were significantly affected by task type. The cross-task classification results based on tir-aERP features also significantly outperformed the PSD features. These results suggest that the tir-aERPs should be potentially more consistent MWL indicators across very different task types when compared to PSD. The current study may provide new insights to our understanding of the common and distinctive neuropsychological essences of MWL across different tasks.

Local Oscillatory Brain Dynamics of Mind Wandering in Schizophrenia

A number of studies have focused on brain dynamics underlying mind wandering (MW) states in healthy people. However, there is limited understanding of how the oscillatory dynamics accompanying MW states and task-focused states are characterized in clinical populations. In this study, we explored EEG local synchrony of MW associated with schizophrenia, under the premise that changes in attention that arise during MW are associated with a different pattern of brain activity. To this end, we measured the power of EEG oscillations in different frequency bands, recorded while participants watched short video clips. In the group of participants diagnosed with schizophrenia, the power in MW states was significantly lower than during task-focused states, mainly in the frontal and posterior regions. However, in the group of healthy controls, the differences in power between the task-focused and MW states occurred exclusively in the posterior region. Furthermore, the power of the frequency bands during MW and during episodes of task-focused attention correlated with cognitive variables such as processing speed and working memory. These findings on dynamic changes of local synchronization in different frequency bands and areas of the cortex can improve our understanding of mental disorders, such as schizophrenia.

Neuronal activation and performance changes in working memory induced by chronic sleep restriction in adolescents

Most adolescents get less than the recommended 8-10 hr of sleep per night. Functional deficits from lack of sleep include disruption of working memory. Adult neuroimaging studies of sleep deprivation suggest diminished responses in task-related brain networks if performance degrades, but compensatory increased responses with maintained performance. This study utilized functional magnetic resonance imaging to examine compensatory and diminished brain responses in adolescents during working memory performance, comparing chronic sleep restriction and healthy sleep duration. Thirty-six healthy adolescents, 14-17 years old, experienced a 3-week protocol: (a) sleep phase stabilization; (b) sleep restriction (~6.5 hr nightly); and (c) healthy sleep duration (~9 hr nightly). After each sleep manipulation, we acquired functional magnetic resonance imaging with an NBack working memory task with four difficulty levels (0 to 3-back). NBack performance degraded with higher task difficulty, but without a detectable effect of sleep duration. ANOVA revealed main effects of both NBack difficulty and sleep in widespread brain networks. Planned contrasts showed that, compared with healthy sleep, sleep restriction resulted in greater medial prefrontal activation and weaker activation in the precuneus for the most difficult task condition. During sleep restriction, we found compensatory functional responses in brain regions that process sensory input and vigilance. However, adolescents also showed impaired performance and diminished brain responses during the hardest task level under a week of chronic sleep restriction. Chronic sleep restriction during adolescence is common. Understanding the impact of ongoing functional compensation and performance breakdown during this developmental period can have important implications for learning and educational strategies.

Event-Related Alpha-Band Power Changes During Self-reflection and Working Memory Tasks in Healthy Individuals

Dysfunctional attentional control is observed in patients with mental disorders. However, there is no established neurophysiological method to assess attention in such patients. We showed a discrepancy in alpha-band power in the tasks that evoked internal and external attention event-related alpha-band power changes in healthy subjects during self-reflection (SR) and working memory (WM) tasks in a preliminary study. In this study, we aimed at elucidating event-related alpha-band power changes in healthy subjects during the tasks, addressing the shortcomings of the previous study. Sixteen healthy volunteers were examined for the event-related power (ERpow) change during the tasks. The results demonstrated the discrepancy of alpha-band ERpow at 8, 10, and 12 Hz in the parieto-occipital area between the WM and SR tasks for a period between a target stimulus and a command stimulus, where a participant switched to internal attention from external attention according to the SR task and remained at external attention according to the WM task. The results suggest that alpha-band ERpow in this area is associated with the direction of attention in response to cognitive stimuli, indicating that the findings of ERpow during the two tasks would potentially aid in the clarification of the pathophysiology of the dysfunctional change in attention in patients with psychiatric disorders.

Correlation between executive function and quantitative EEG in patients with anxiety by the Research Domain Criteria (RDoC) framework

The Research Domain Criteria (RDoC) project was proposed by the National Institute of Mental Health in 2010 to create a new diagnostic system including symptoms and data from genetics, neuroscience, physiology, and self-reports. The purpose of this study was to determine the link between anxiety and executive functions through quantitative electroencephalography (qEEG) based on the RDoC system. Nineteen-channel EEGs were recorded at the psychiatric clinic from 41 patients with symptoms of anxiety. The EEG power spectra were analysed. The Executive Intelligence Test (EXIT) including the K-WAIS-IV, Stroop, controlled oral word association, and the design fluency tests were performed. A partial, inversed, and significant association was observed between executive intelligence quotient (EIQ) and the absolute delta power in the central region. Similarly, a partial, inversed, and significant association was observed between design fluency and the absolute delta power in the left parietal area. Our findings suggest that the increase in delta power in the central region and left P3 was negatively correlated with the decrease in executive function. It is expected that the absolute delta power plays a specific role in the task-negative default mode network in the relationship between anxiety and executive function.

Resting-state posterior alpha power changes with prolonged exposure in a natural environment

Exposure to environments that contain natural features can benefit mood, cognition, and physiological responses. Previous research proposed exposure to nature restores voluntary attention - attention that is directed towards a task through top down control. Voluntary attention is limited in capacity and depletes with use. Nature provides unique stimuli that do not require voluntary attention; therefore, the neural resources needed for attention to operate efficiently are theorized to restore when spending time in nature. Electroencephalography reflects changes in attention through fluctuations in power within specific frequencies. The current study (N = 29) measured changes in averaged resting state posterior alpha power before, during, and after a multiday nature exposure. Linear mixed-effects models revealed posterior alpha power was significantly lower during the nature exposure compared to pre-trip and post-trip testing, suggesting posterior alpha power may be a potential biomarker for differences related to exposure to natural and urban environments.

Probing the neural signature of mind wandering with simultaneous fMRI-EEG and pupillometry

Mind wandering reflects the shift in attentional focus from task-related cognition driven by external stimuli toward self-generated and internally-oriented thought processes. Although such task-unrelated thoughts (TUTs) are pervasive and detrimental to task performance, their underlying neural mechanisms are only modestly understood. To investigate TUTs with high spatial and temporal precision, we simultaneously measured fMRI, EEG, and pupillometry in healthy adults while they performed a sustained attention task with experience sampling probes. Features of interest were extracted from each modality at the single-trial level and fed to a support vector machine that was trained on the probe responses. Compared to task-focused attention, the neural signature of TUTs was characterized by weaker activity in the default mode network but elevated activity in its anticorrelated network, stronger functional coupling between these networks, widespread increase in alpha, theta, delta, but not beta, frequency power, predominantly reduced amplitudes of late, but not early, event-related potentials, and larger baseline pupil size. Particularly, information contained in dynamic interactions between large-scale cortical networks was predictive of transient changes in attentional focus above other modalities. Together, our results provide insight into the spatiotemporal dynamics of TUTs and the neural markers that may facilitate their detection.

EEG Alpha-Rhythm-Related Changes in BOLD fMRI Signal in Neurofeedback Training

Interaction of EEG and BOLD brain activity was studied in subjects during EEG-biofeedback training course (20 sessions). Healthy male subjects aged 20-35 underwent a training course of sound-reinforced upregulation of alpha- (20 participants) or beta-activity (9 participants). Pretraining, intermediate (after 10 sessions), and post-training fMRI-EEG recordings were conducted in resting state and during the participants' attempts to upregulate the power of target EEG activity. Regression analysis was carried out on three sessions in total; the main changes in BOLD signal connected with alpha rhythm power were related to the subjects who performed alpha training "good enough" (were able to increase alpha power at least at one stage). Maximum changes in BOLD response connected with alpha rhythm power were observed in the form of deactivation at T8 lead in the right hemisphere, and at F7 in the left hemisphere, and involved middle frontal gyrus, triangular part of inferior frontal gyrus, superior temporal gyrus, parietal lobule, and insula. The identified areas correspond to the executive control network (ECN) and anterior salience network (ASN).

Neuroimaging Study of Alpha and Beta EEG Biofeedback Effects on Neural Networks

Neural networks interaction was studied in healthy men (20-35 years old) who underwent 20 sessions of EEG biofeedback training outside the MRI scanner, with concurrent fMRI-EEG scans at the beginning, middle, and end of the course. The study recruited 35 subjects for EEG biofeedback, but only 18 of them were considered as "successful" in self-regulation of target EEG bands during the whole course of training. Results of fMRI analysis during EEG biofeedback are reported only for these "successful" trainees. The experimental group (N = 23 total, N = 13 "successful") upregulated the power of alpha rhythm, while the control group (N = 12 total, N = 5 "successful") beta rhythm, with the protocol instructions being as for alpha training in both. The acquisition of the stable skills of alpha self-regulation was followed by the weakening of the irrelevant links between the cerebellum and visuospatial network (VSN), as well as between the VSN, the right executive control network (RECN), and the cuneus. It was also found formation of a stable complex based on the interaction of the precuneus, the cuneus, the VSN, and the high level visuospatial network (HVN), along with the strengthening of the interaction of the anterior salience network (ASN) with the precuneus. In the control group, beta enhancement training was accompanied by weakening of interaction between the precuneus and the default mode network, and a decrease in connectivity between the cuneus and the primary visual network (PVN). The differences between the alpha training group and the control group increased successively during training. Alpha training was characterized by a less pronounced interaction of the network formed by the PVN and the HVN, as well as by an increased interaction of the cerebellum with the precuneus and the RECN. The study demonstrated the differences in the structure and interaction of neural networks involved into alpha and beta generating systems forming and functioning, which should be taken into account during planning neurofeedback interventions. Possibility of using fMRI-guided biofeedback organized according to the described neural networks interaction may advance more accurate targeting specific symptoms during neurotherapy.

Pulsed Near Infrared Transcranial and Intranasal Photobiomodulation Significantly Modulates Neural Oscillations: a pilot exploratory study

Transcranial photobiomodulation (tPBM) is the application of low levels of red or near-infrared (NIR) light to stimulate neural tissues. Here, we administer tPBM in the form of NIR light (810 nm wavelength) pulsed at 40 Hz to the default mode network (DMN), and examine its effects on human neural oscillations, in a randomized, sham-controlled, double-blinded trial. Using electroencephalography (EEG), we found that a single session of tPBM significantly increases the power of the higher oscillatory frequencies of alpha, beta and gamma and reduces the power of the slower frequencies of delta and theta in subjects in resting state. Furthermore, the analysis of network properties using inter-regional synchrony via weighted phase lag index (wPLI) and graph theory measures, indicate the effect of tPBM on the integration and segregation of brain networks. These changes were significantly different when compared to sham stimulation. Our preliminary findings demonstrate for the first time that tPBM can be used to non-invasively modulate neural oscillations, and encourage further confirmatory clinical investigations.

Decreased occipital alpha oscillation in children who stutter during a visual Go/Nogo task

OBJECTIVE

Our goal was to discover attention- and inhibitory control-related differences in the main oscillations of the brain of children who stutter (CWS) compared to typically developed children (TDC).

METHODS

We performed a time-frequency analysis using wavelets, fast Fourier transformation (FFT) and the Alpha/Theta power ratio of EEG data collected during a visual Go/Nogo task in 7-9 year old CWS and TDC, including also the time window between consecutive tasks.

RESULTS

CWS showed significantly reduced occipital alpha power and Alpha/Theta ratio in the "resting" or preparatory period between visual stimuli especially in the Nogo condition.

CONCLUSIONS

The CWS demonstrate reduced inhibition of the visual cortex and information processing in the absence of visual stimuli, which may be related to problems in attentional gating.

SIGNIFICANCE

Occipital alpha oscillation is elementary in the control and inhibition of visual attention and the lack of occipital alpha modulation indicate fundamental differences in the regulation of visual information processing in CWS. Our findings support the view of stuttering as part of a wide-ranging brain dysfunction most likely involving also attentional and inhibitory networks.