We investigated spectral resting-state EEG in persons with chronic stroke-induced aphasia to determine its reliability, sensitivity, and relationship to functional behaviors. Resting-state EEG has not yet been characterized in this population and was selected given the demonstrated potential of resting-state investigations using other neuroimaging techniques to guide clinical decision-making. Controls and persons with chronic stroke-induced aphasia completed two EEG recording sessions, separated by approximately 1 month, as well as behavioral assessments of language, sensorimotor, and (...) cognitive domains. Power in the classic frequency bands was examined via spectral analysis of resting-state EEG data. Results suggest that power in the theta, alpha, and beta bands is reliable for use as a repeated measure. Significantly greater theta and lower beta power was observed in persons with aphasia than controls. Finally, in PWAs theta power negatively correlated with performance on a discourse informativeness measure, while alpha and beta power positively correlated with performance on the same measure. This indicates that spectral rsEEG slowing observed in PWAs in the chronic stage is pathological and suggests a possible avenue for directly altering brain activation to improve behavioral function. Taken together, these results suggest that spectral resting-state EEG holds promise for sensitive measurement of functioning and change in persons with chronic aphasia. Future studies investigating the utility of these measures as biomarkers of frank or latent aphasic deficits and treatment response in chronic stroke-induced aphasia are warranted. (shrink)

Spatial cognitive abilities, including mental rotation and visuo-spatial working memory are correlated with mathematical performance, and several studies have shown that training of these abilities can enhance mathematical performance. Here, we investigated the behavioral and neural correlates of MR and vsWM training combined with number line training. Fifty-seven children, aged 6–7, performed 25 days of NL training combined with either vsWM or MR and participated in an Electroencephalography -session in school to measure resting state activity and steady-state (...) visual evoked potentials during a vsWM task before and after training. Fifty children, aged 6–7, received usual teaching and acted as a control group. Compared to the control group, both training groups improved on a combined measure of mathematics. Cognitive improvement was specific to the training. Significant pre-post changes in resting state-EEG, common to both training groups, were found for power as well as for coherence, with no significant differences in rs-EEG-changes between the vsWM and MR groups. Two of the common rs-EEG changes were correlated with mathematical improvement: an increase in coherence between the central frontal lobe and the right parietal lobe in frequencies ranging from 16 to 25 Hz, and an increase in coherence between the left frontal lobe and the right parietal lobe ranging from 23 to 25 Hz. These results indicate that changes in fronto-parietal coherence are related to an increase in mathematical performance, which thus might be a useful measure in further investigations of mathematical interventions in children. (shrink)

Purpose: The cognitive effects of total sleep deprivation on the brain remain poorly understood. Electroencephalography is a very useful tool for detecting spontaneous brain activity in the resting state. Quasi-stable electrical distributions, known as microstates, carry useful information about the dynamics of large-scale brain networks. In this study, microstate analysis was used to study changes in brain activity after 24 h of total sleep deprivation.Participants and Methods: Twenty-seven healthy volunteers were recruited and underwent EEG scans before and after (...) 24 h of TSD. Microstate analysis was applied, and six microstate classes were identified. Topographies and temporal parameters of the microstates were compared between the rested wakefulness and TSD conditions.Results: Microstate class A showed lower global explained variance, frequency of occurrence, and time coverage in TSD than RW, whereas microstate class D displayed higher GEV, frequency of occurrence, and time coverage in TSD compared to RW. Moreover, subjective sleepiness was significantly negatively correlated with the microstate parameters of class A and positively correlated with the microstate parameters of class D. Transition analysis revealed that class B exhibited a higher probability of transition than did classes D and F in TSD compared to RW.Conclusion: The observation suggests alterations of the dynamic brain-state properties of TSD in healthy young male subjects, which may serve as system-level neural underpinnings for cognitive declines in sleep-deprived subjects. (shrink)

Background: Patients in a vegetative state pose problems in diagnosis, prognosis and treatment. Currently, no prognostic markers predict the chance of recovery, which has serious consequences, especially in end-of-life decision-making. Objective: We aimed to assess an objective measurement of prognosis using advanced electroencephalography (EEG). Methods: EEG data (19 channels) were collected in 14 patients who were diagnosed to be persistently vegetative based on repeated clinical evaluations at 3 months following brain damage. EEG structure parameters (amplitude, duration and variability within (...) quasi-stationary segments, as well as the spatial synchrony between such segments and the strength of this synchrony) were used to predict recovery of consciousness 3 months later. Results: The number and strength of cortical functional connections between EEG segments were higher in patients who recovered consciousness (P < .05 – P < .001) compared with those who did not recover. Linear regression analysis confirms that EEG structure parameters are capable of predicting (P = .0025) recovery of consciousness 6 months post-injury, whereas the same analysis failed to significantly predict patient outcome based on aspects of their clinical history alone (P = .629) or conventional EEG spectrum power (P = .473). Conclusions: The result of this preliminary study demonstrates that structural strategy of EEG analysis is better suited for providing prognosis of consciousness recovery than existing methods of clinical assessment and of conventional EEG. Our results may be a starting point for developing reliable prognosticators in patients who are in vegetative state, with the potential to improve their day-to-day management, quality of life, and access to early interventions. (shrink)

Numerous studies had found that creativity is not only associated with low effort and flexible processes, but also associated with high effort and persistent processes especially when defensive behavior being induced negative emotions. The important role of self-esteem is to buffer the negative emotions and low self-esteem are prone to instigate various forms of defensive behaviors. Thus, we thought that the relationships between trait creativity and executive control brain networks might be modulated by self-esteem. The resting-state electroencephalogram (RS-EEG) (...) microstates can divided into four classical types (MS1, MS2, MS3 and MS4) which can reflect the brain networks as well as the dynamic characteristic of them. Thus, Williams creative tendency scale (WCTS) and Rosenberg Self-Esteem Scale (RSES) were used to investigate the modulating role of self-esteem on the relationships between trait creativity and the RS-EEG microstates. As our results showed, self-esteem consistently modulated the relationships between creativity and the duration and contribution of MS2 related to visual or imagery processing, the occurrence of MS3 related to cingulo-opercular networks, as well as transitions between MS2 and MS4 which was related to frontoparietal control networks. Based on these results, we thought that Moreover, individuals with low self-esteem might be more prone to influenced by negative emotions and develop low trait creativity; bottom-up information from vision or visual imagery might be beneficial to develop trait creativity for individuals with high self-esteem to improve trait creativity, while inhibition of irrelevant information could facilitate trait creativity for individuals with low self-esteem. (shrink)

Recent fMRI studies have shown that functional networks can be extracted even from resting state data, the so called “resting state networks” (RSNs) by applying independent component analysis (ICA). However, compared to fMRI, EEG and MEG have much higher temporal resolution and provide a direct estimation of cortical activity. To date, MEG studies have applied ICA for separate frequency bands only, disregarding cross-frequency couplings. In this study, we aimed to detect EEG-RSNs and their interactions in all (...) frequency bands. We applied low resolution brain electromagnetic tomography-ICA (LORETA-ICA) to resting-state EEG data in 80 healthy subjects using five frequency bands (delta, theta, alpha, beta and gamma band) and found five RSNs in alpha, beta and gamma frequency bands. Next, taking into account these frequency properties, five RSNs were identified; 1) the visual network, 2) dual-process of visual perception network, characterized by a negative correlation between the right ventral visual pathway (VVP) and left posterior dorsal visual pathway (DVP), 3) self-referential processing network, characterized by a positive correlation between the medial PFC and right VVP, 4) dual-process of memory perception network, functionally related to a negative correlation between the left VVP and the precuneus and 5) sensorimotor network. To detect aging-related changes of these five RSNs, the subjects were divided into three age groups: younger, middle aged, and elderly group, and Student's t test with Bonferroni correction on each coefficient of five independent components were performed. We found a significant attenuation in dual-process of visual perception network in elderly relative to middle aged subjects. Overall findings indicate that LORETA-ICA with EEG data can precisely identify five RSNs in their intrinsic frequency bands, and correct correlations and aging-related changes between and within RSNs. (shrink)

In the present study we asked whether it is possible to decode personality traits from resting state EEG data. EEG was recorded from a large sample of subjects (n=289) who had answered questionnaires measuring personality trait scores of the 5 dimensions as well as the 10 subordinate aspects of the Big Five. Machine learning algorithms were used to build a classifier to predict each personality trait from power spectra of the resting state EEG data. The results (...) indicate that the five dimensions as well as their subordinate aspects could not be predicted from the resting state EEG data. Finally, to demonstrate that this result is not due to systematic algorithmic or implementation mistakes the same methods were used to successfully classify whether the subject had eyes open or closed. These results indicate that the extraction of personality traits from the power spectra of resting state EEG is extremely noisy, if possible at all. (shrink)

Recent studies have demonstrated neural overlap between resting state activity and self-referential processing. This “rest-self” overlap occurs especially in anterior cortical midline structures like the perigenual anterior cingulate cortex (PACC). However, the exact neurotemporal and biochemical mechanisms remain to be identified. Therefore, we conducted a combined electroencephalography (EEG)-magnetic resonance spectroscopy (MRS) study. EEG focused on pre-stimulus (e.g., prior to stimulus presentation or perception) power changes to assess the degree to which those changes can predict subjects’ perception (and judgment) (...) of subsequent stimuli as high or low self-related. MRS measured resting state concentration of glutamate, focusing on PACC. High pre-stimulus (e.g., prior to stimulus presentation or perception) alpha power significantly correlated with both perception of stimuli judged to be highly self-related and with resting state glutamate concentrations in the PACC. In sum, our results show (i) pre-stimulus (e.g., prior to stimulus presentation or perception) alpha power and resting state glutamate concentration to mediate rest-self overlap that (ii) dispose or incline subjects to assign high degrees of self-relatedness to perceptual stimuli. (shrink)

The prevalence of mobile phone addiction has increased rapidly in recent years, and it has had a certain negative impact on emotions and cognitive capacities. At the level of neural circuits, the continued increase in activity in the brain regions associated with addiction leads to neural adaptations and structural changes. At present, the spontaneous brain microstates that could be negatively influenced by MPA are unclear. In this study, the temporal characteristics of four resting-state electroencephalogram microstates related to mobile (...) phone addiction tendency were investigated using the Mobile Phone Addiction Tendency Scale. We attempted to analyze the correlation between MPAT and corresponding microstates and provide evidence to explain the brain and behavioral changes caused by MPA. The results showed that the total score of the MPATS was positively correlated with the duration of MS1, related to phonological processing and negatively correlated with the duration of MS2, related to visual or imagery processing, and MS4, related to the attentional network; the score of the withdrawal symptoms subscale was additionally associated with duration of MS3, related to the cingulo-opercular emotional network. Based on these results, we believe that MPAT may have some negative effects on attentional networks and sensory brain networks; moreover, withdrawal symptoms may induce some negative emotions. (shrink)

Neurofeedback has been suggested as a potential complementary therapy to different psychiatric disorders. Of interest for this approach is the prediction of individual performance and outcomes. In this study, we applied functional connectivity-based modeling using electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) modalities to (i) investigate whether resting-state connectivity predicts performance during an affective neurofeedback task and (ii) evaluate the extent to which predictive connectivity profiles are correlated across EEG and fNIRS techniques. The fNIRS oxyhemoglobin and deoxyhemoglobin concentrations (...) and the EEG beta and gamma bands modulated by the alpha frequency band (beta-m-alpha and gamma-m-alpha, respectively) recorded over the frontal cortex of healthy subjects were used to estimate functional connectivity from each neuroimaging modality. For each connectivity matrix, relevant edges were selected in a leave-one-subject-out procedure, summed into “connectivity summary scores” (CSS), and submitted as inputs to a support vector regressor (SVR). Then, the performance of the left-out-subject was predicted using the trained SVR model. Linear relationships between the CSS across both modalities were evaluated using Pearson’s correlation. The predictive model showed a mean absolute error smaller than 20%, and the fNIRS oxyhemoglobin CSS was significantly correlated with the EEG gamma-m-alpha CSS (r = −0.456, p = 0.030). These results support that pre-task electrophysiological and hemodynamic resting-state connectivity are potential predictors of neurofeedback performance and are meaningfully coupled. This investigation motivates the use of joint EEG-fNIRS connectivity as outcome predictors, as well as a tool for functional connectivity coupling investigation. (shrink)

To explore the change of brain connectivity in schizophrenics, the resting-state EEG source functional connections of SCZ and healthy control were investigated in this paper. Different band single-layer networks, multilayer networks, and improved multilayer networks were constructed and their topological attributes were extracted. The topological attributes of SCZ and HC were automatically distinguished using ensemble learning methods called Ensemble Learning based on Trees and Soft voting method, and the effectiveness of different network construction methods was compared based on (...) the classification accuracy. The results showed that the classification accuracy was 89.38% for α band network, 82.5% for multilayer network, and 86.88% for improved multilayer network. Comparing patients with SCZ to those with Alzheimer’s disease, the classification accuracy of improved multilayer network was the highest, which was 88.12%. The power spectrum in the α band of SCZ was significantly lower than HC, whereas there was no significant difference between SCZ and AD. This indicated that the improved multilayer network can effectively distinguish SCZ and other groups not only when their power spectrum was significantly different. The results also suggested that the improved multilayer topological attributes were regarded as biological markers in the clinical diagnosis of patients with schizophrenia and even other mental disorders. (shrink)

Electroencephalography provides a non-invasive means to advancing our understanding of the development and function of the brain. However, the majority of the world’s population residing in low and middle income countries has historically been limited from contributing to, and thereby benefiting from, such neurophysiological research, due to lack of scalable validated methods of EEG data collection. In this study, we establish a standard operating protocol to collect approximately 3 min each of eyes-open and eyes-closed resting-state EEG data using (...) a low-cost portable EEG device in rural households through formative work in the community. We then evaluate the acceptability of these EEG assessments to young children and feasibility of administering them through non-specialist workers. Finally, we describe properties of the EEG recordings obtained using this novel approach to EEG data collection. The formative phase was conducted with 9 families which informed protocols for consenting, child engagement strategies and data collection. The protocol was then implemented on 1265 families. 977 children and 1199 adults provided resting-state data for this study. 259 children refused to wear the EEG cap or removed it, and 58 children refused the eyes-closed recording session. Hardware or software issues were experienced during 30 and 25 recordings in eyes-open and eyes-closed conditions respectively. Disturbances during the recording sessions were rare and included participants moving their heads, touching the EEG headset with their hands, opening their eyes within the eyes-closed recording session, and presence of loud sounds in the testing environment. Similar to findings in laboratory-based studies from high-income settings, the percentage of recordings which showed an alpha peak was higher in eyes-closed than eyes-open condition, with the peak occurring most frequently in electrodes at O1 and O2 positions, and the mean frequency of the alpha peak was found to be lower in children as compared to adults. We observed a deterioration in the EEG signal with prolonged device usage. This study demonstrates the acceptability, feasibility and utility of conducting EEG research at scale in a rural low-resource community, while highlighting its potential limitations, and offers the impetus needed to further refine the methods and devices and validate such scalable methods to overcome existing research inequity. (shrink)

The value of resting electroencephalogram (EEG) in revealing neural constitutes of consciousness (NCC) was examined. We quantified the dynamic repertoire, duration and oscillatory type of EEG microstates in eyes-closed rest in relation to the degree of expression of clinical self-consciousness. For NCC a model was suggested that contrasted normal, severely disturbed state of consciousness and state without consciousness. Patients with disorders of consciousness were used. Results suggested that the repertoire, duration and oscillatory type of EEG microstates in (...) resting condition quantitatively related to the level of consciousness expression in brain-damaged patients and healthy-conscious subjects. Specifically, results demonstrated that (a) decreased number of EEG microstate types was associated with altered states of consciousness, (b) unawareness was associated with the lack of diversity in EEG alpha-rhythmic microstates, and (c) the probability for the occurrence and duration of delta-, theta- and slow-alpha-rhythmic microstates were associated with unawareness, whereas the probability for the occurrence and duration of fast-alpha-rhythmic microstates were associated with consciousness. In conclusion, resting EEG has a potential value in revealing NCC. This work may have implications for clinical care and medical–legal decisions in patients with disorders of consciousness. (shrink)

IntroductionBrain tumours frequently cause language impairments and are also likely to co-occur with localised abnormal slow-wave brain activity. However, it is unclear whether this applies specifically to low-grade brain tumours. We investigate slow-wave activity in resting-state electroencephalography in low-grade glioma and meningioma patients, and its relation to pre- and postoperative language functioning.MethodPatients with a glioma infiltrating the language-dominant hemisphere and patients with a meningioma with mass effect on this hemisphere underwent extensive language testing before and 1 year after (...) surgery. EEG was registered preoperatively, postoperatively, and once in healthy individuals. Slow-wave activity in delta- and theta- frequency bands was evaluated visually and quantitatively by spectral power at three levels over the scalp: the whole brain, the affected hemisphere, and the affected region.ResultsGlioma patients had increased delta activity and increased theta activity before and after surgery. In these patients, increased preoperative theta activity was related to the presence of language impairment, especially to poor word retrieval and grammatical performance. Preoperative slow-wave activity was also related to postoperative language outcomes. Meningioma patients showed no significant increase in EEG slow-wave activity compared to healthy individuals, but they presented with word retrieval, grammatical, and writing problems preoperatively, as well as with writing impairments postoperatively.DiscussionAlthough the brain-tumour pathology in low-grade gliomas and meningiomas has a different effect on resting-state brain activity, patients with low-grade gliomas and meningiomas both suffer from language impairments. Increased theta activity in glioma patients can be considered as a language-impairment marker, with prognostic value for language outcome after surgery. (shrink)

Using theoretical analysis of self-consciousness concept and experimental evidence on the brain default mode network (DMN) that constitutes the neural signature of self-referential processes, we hypothesized that the anterior and posterior subnets comprising the DMN should show differences in their integrity as a function of meditation training. Functional connectivity within DMN and its subnets (measured by operational synchrony) has been measured in ten novice meditators using an electroencephalogram (EEG) recording in a pre-/post-meditation intervention design. We have found that while the (...) whole DMN was clearly suppressed, different subnets of DMN responded differently after 4 months of meditation training: The strength of EEG operational synchrony in the right and left posterior modules of the DMN decreased in resting post-meditation condition compared to a pre-meditation condition, whereas the frontal DMN module on the contrary exhibited an increase in the strength of EEG operational synchrony. These findings combined with published data on functional–anatomic heterogeneity within the DMN and on trait subjective experiences commonly found following meditation allow us to propose that the first-person perspective and the sense of agency (the witnessing observer) are presented by the frontal DMN module, while the posterior modules of the DMN are generally responsible for the experience of the continuity of ‘I’ as embodied and localized within bodily space. Significance of these findings is discussed. (shrink)

This study investigated the characteristics of neural oscillation and functional connectivity in college students engaging in binge drinking using resting-state electroencephalography. Also, the associations of visual memory, evaluated by the Rey-Osterrieth Complex Figure Test, and neural oscillation with FC during the resting state were investigated. The BD and non-BD groups were selected based on scores of the Korean version of the Alcohol use disorders Identification Test and the Alcohol Use Questionnaire. EEG was performed for 6 min (...) while the participants rested with eyes closed. The theta, lower-alpha, and upper alpha powers did not differ between the BD and non-BD groups. Concerning FC, the BD group exhibited stronger theta coherence than that of the non-BD group, and in the lower and upper alpha bands, the BD group showed stronger coherence in some areas but weaker coherence in others compared with the non-BD group. However, these significant results were not observed after Bonferroni correction. The BD group showed significantly lower delayed recall scores on the RCFT than did the non-BD group. A positive correlation between the left prefrontal-parietal-occipital midline connection and performance on the delayed recall of the RCFT was observed in the BD group. The present results could suggest that binge drinkers have alterations in brain FC, which may be related to their visual memory deficits. (shrink)

Based on previous studies implicating increased functional connectivity within the self-referential brain network in major depressive disorder (MDD), and considering the functional roles of three distinct modules of such brain net (responsible for three-dimensional components of Selfhood) together with the documented abnormalities of self-related processing in MDD, we tested the hypothesis that patients with depression would exhibit increased connectivity within each module of the self-referential brain network and that the strength of these connections would correlate positively with depression severity. Applying (...) the electroencephalogram (EEG) operational synchrony analysis to extract three modules of the self-referential brain network in 12 medication-free depressive outpatients and 10 control subjects we have found an increase in the strength of EEG synchrony within all three modules in depressive patients (though non-significant for the right module). Furthermore, multiple regression analysis that used 3 factors (values of synchrony strength for all three modules) as input indicated that combined increase in the strength of synchrony in all three modules was positively associated with severity of depression. Taken together the findings of this study suggest that depression is primarily associated with hypersynchrony in all three modules of the brain self-referential network (the anterior module been responsible for “witnessing observation and first–person perspective”, the left posterior module been responsible for “reflective agency and narration” and the right posterior module been responsible for “bodily representational-emotional agency”), thus contributing to excessive self-focus, rumination, and body tension. (shrink)

Objective: The value of spontaneous EEG oscillations in distinguishing patients in vegetative and minimally conscious states was studied. Methods: We quantified dynamic repertoire of EEG oscillations in resting condition with closed eyes in patients in vegetative and minimally conscious states (VS and MCS). The exact composition of EEG oscillations was assessed by the probability-classification analysis of short-term EEG spectral patterns. Results: The probability of delta, theta and slow-alpha oscillations occurrence was smaller for patients in MCS than for VS. Additionally, (...) only patients in MCS demonstrated fast-alpha oscillation occurrence. Depending on the type and composition of EEG oscillations, the probability of their occurrence was either aetiology dependent or independent. The probability of EEG oscillations occurrence differentiated brain injuries with different aetiologies. Conclusions: Spontaneous EEG oscillations have a potential value in distinguishing patients in VS and MCS. Significance: This work may have implications for clinical care, rehabilitative programs and medical–legal decisions in patients with impaired consciousness states following coma due to acute brain injuries. (shrink)

In this single-blind within-subject study, autonomic and EEG variables were compared during 10-min, order-balanced eyes-closed rest and Transcendental Meditation (TM) sessions. TM sessions were distinguished by (1) lower breath rates, (2) lower skin conductance levels, (3) higher respiratory sinus arrhythmia levels, and (4) higher alpha anterior-posterior and frontal EEG coherence. Alpha power was not significantly different between conditions. These results were seen in the first minute and were maintained throughout the 10-min sessions. TM practice appears to (1) lead to a (...) state fundamentally different than eyes-closed rest; (2) result in a cascade of events in the central and autonomic nervous systems, leading to a rapid change in state (within a minute) that was maintained throughout the TM session; and (3) be best distinguished from other conditions through autonomic and EEG alpha coherence patterns rather than alpha power. Two neural networks that may mediate these effects are suggested. The rapid shift in physiological functioning within the first minute might be mediated by a ''neural switch'' in prefrontal areas inhibiting activity in specific and nonspecific thalamocortical circuits. The resulting ''restfully alert'' state might be sustained by a basal ganglia-corticothalamic threshold regulation mechanism automatically maintaining lower levels of cortical excitability. (shrink)

Neurovascular coupling (NVC), the transient regional hyperemia following the evoked neuronal responses, is the basis of blood oxygenation level-dependent techniques and is generally adopted across physiological conditions, including the intrinsic resting state. However, the possibility of neurovascular dissociations across physiological alterations is indicated in the literature. To examine the NVC stability across sleep–wake states, we used electroencephalography (EEG) as the index of neural activity and functional magnetic resonance imaging (fMRI) as the measure of cerebrovascular response. Eight healthy adults (...) were recruited for simultaneous EEG-fMRI recordings in nocturnal sleep. We compared the cross-modality (EEG vs. fMRI) consistency of functional indices (spectral amplitude and functional connectivity) among five states of wakefulness and sleep (state effect). We also segregated the brain into three main partitions (anterior, middle and posterior) for spatial assessments (regional effect). Significant state effects were found on δ, α and fMRI indices and regional effects on the α and fMRI indices. However, the cross-state EEG changes in spectral amplitude and functional connectivity did not consistently match the changes in the fMRI indices across sleep–wake states. In spectral amplitude, the δ band peaked at the N3 stage for all brain regions, while the fMRI fluctuation amplitude peaked at the N2 stage in the central and posterior regions. In regional connectivity, the inter-hemispheric connectivity of the δ band peaked at the N3 stage for all regions, but the bilateral fMRI connectivity showed the state changes in the anterior and central regions. The cross-modality inconsistencies across sleep–wake states provided preliminary evidence that the neurovascular relationship may not change in a linear consistency during NREM sleep. Thus, caution shall be exercised when applying the NVC presumption to investigating sleep/wake transitions, even among healthy young adults. (shrink)

Nowadays, depression is the world’s major health concern and economic burden worldwide. However, due to the limitations of current methods for depression diagnosis, a pervasive and objective approach is essential. In the present study, a psychophysiological database, containing 213 subjects, was constructed. The electroencephalogram signals of all participants under resting state and sound stimulation were collected using a pervasive prefrontal-lobe three-electrode EEG system at Fp1, Fp2, and Fpz electrode sites. After denoising using the Finite Impulse Response filter combining (...) the Kalman derivation formula, Discrete Wavelet Transformation, and an Adaptive Predictor Filter, a total of 270 linear and nonlinear features were extracted. Then, the minimal-redundancy-maximal-relevance feature selection technique reduced the dimensionality of the feature space. Four classification methods distinguished the depressed participants from normal controls. The classifiers’ performances were evaluated using 10-fold cross-validation. The results showed thatK-Nearest Neighbor had the highest accuracy of 79.27%. The result also suggested that the absolute power of the theta wave might be a valid characteristic for discriminating depression. This study proves the feasibility of a pervasive three-electrode EEG acquisition system for depression diagnosis. (shrink)

We performed an EEG graph analysis on data from 31 typical readers and 24 dyslexics, recorded while they were engaged in an audiovisual task and during resting-state. The task simulates reading acquisition as participants learned new letter-sound mappings via feedback. EEG data was filtered for the delta, theta, alpha, and beta bands. We computed the Phase Lag Index to provide an estimate of the functional connectivity between all pairs of electrodes per band. Then, networks were constructed using a (...) Minimum Spanning Tree, a unique sub-graph connecting all nodes without loops, aimed at minimizing bias in between groups and conditions comparisons. Both groups showed a comparable accuracy increase during task blocks, indicating that they correctly learned the new associations. The EEG results revealed lower task-specific theta connectivity, and lower theta degree correlation over both rest and task recordings, indicating less network integration in dyslexics compared to typical readers. This pattern suggests a role of theta oscillations in dyslexia and may reflect differences in task engagement between the groups, although robust correlations between MST metrics and performance indices were lacking. (shrink)

It is not only difficult to be a sports expert but also difficult to grow from a sports expert to a sports elite. Professional athletes are often concerned about the differences between an expert and an elite and how to eventually become an elite athlete. To explore the differences in brain neural mechanism between experts and elites in the process of motor behavior and reveal the internal connection between motor performance and brain activity, we collected and analyzed the electroencephalography findings (...) of 14 national archers and 14 provincial archers during aiming and resting states and constructed the EEG brain network of the two archer groups based on weighted phase lag index; the graph theory was used to analyze and compare the network characteristics via local network and global network topologies. The results showed that compared with the expert archers, the elite archers had stronger functional coupling in beta1 and beta2 bands, and the difference was evident in the frontal and central regions; in terms of global characteristics of brain network topology, the average clustering coefficient and global efficiency of elite archers were significantly higher than that of expert archers, and the eigenvector centrality of expert archers was higher; for local characteristics, elite archers had higher local efficient; and the brain network characteristics of expert archers showed a strong correlation with archery performance. This suggests that compared with expert archers, elite archers showed stronger functional coupling, higher integration efficiency of global and local information, and more independent performance in the archery process. These findings reveal the differences in brain electrical network topologies between elite and expert archers in the archery preparation stage, which is expected to provide theoretical reference for further training and promotion of professional athletes. (shrink)

In this exploratory, correlational study, several psychophysiological measures were assessed and the relation between these measures and an experimental self-report questionnaire to measure the seven implicit beliefs of sexual offenders ) was established in a sample of Dutch participants recruited from the healthy population using correlational analyses. After analyzing task performance, electroencephalogram data and electrocardiogram data, the psychophysiological variables were correlated with the experimental QITSO subscales. The subscale “children as sexual beings” correlated positively with the P300 amplitude at electrode Pz. (...) The subscale “women are unknowable” correlated positively with resting-state beta activity during eyes closed and eyes open, and with alpha activity during eyes open. Additionally, the subscale “entitlement’ correlated positively with low frequency heart rate variability power during eyes closed and eyes open, and with high frequency power during eyes closed. This study is a first exploratory step towards establishing a psychophysiological profile underlying the self-report questionnaire QITSO. (shrink)

Joint Analysis of EEG and fMRI datasets can bring new insight into brain mechanisms. In this paper, we employed the recently introduced Correlated Coupled Tensor Matrix Factorization (CCMTF) method for analysis of the emotion regulation paradigm based on EEG frontal asymmetry neurofeedback in the alpha frequency band with simultaneous fMRI. CCMTF method assumes that the co-variations of the common dimension (temporal dimension) between EEG and fMRI are correlated and not necessarily identical. The results of the CCMTF method suggested that EEG (...) and fMRI had similar covariations during the transition of brain activities from resting states to task (view and upregulation) states and these covariations followed an increasing trend. The fMRI shared spatial component showed activations in the limbic system, DLPFC, OFC, and VLPC regions, which were consistent with the previous studies and were linked to EEG frequency patterns in the range of 1–15 Hz with a correlation value close to 0.75. The estimated regions from the CCMTF method were then used as the candidate nodes for dynamic functional connectivity (dFC) analysis, in which the changes in connectivity from view to upregulation states were examined. The results of the dFC analysis were compared with a Normalized Mutual information (NMI) based approach in two different frequency ranges (1–15 and 15–40 Hz) as the NMI method was applied to the vectors of dFC nodes of EEG and fMRI data. The results of the two methods illustrated that the relation between EEG and fMRI datasets was mostly in the frequency range of 1–15 Hz. These relations were both in the brain activations and the dFCs between the two modalities. This paper suggests that the CCMTF method is a capable approach for extracting the shared information between EEG and fMRI data and can reveal new information about brain functions and their connectivity without solving the EEG inverse problem or analyzing different frequency bands. (shrink)

Recent advances in neuroscience indicate that analysis of bio-signals such as rest state electroencephalogram and eye-tracking data can provide more reliable evaluation of children autism spectrum disorder than traditional methods of behavior measurement relying on scales do. However, the effectiveness of the new approaches still lags behind the increasing requirement in clinical or educational practices as the “bio-marker” information carried by the bio-signal of a single-modality is likely insufficient or distorted. This study proposes an approach to joint analysis of (...) EEG and eye-tracking for children ASD evaluation. The approach focuses on deep fusion of the features in two modalities as no explicit correlations between the original bio-signals are available, which also limits the performance of existing methods along this direction. First, the synchronization measures, information entropy, and time-frequency features of the multi-channel EEG are derived. Then a random forest applies to the eye-tracking recordings of the same subjects to single out the most significant features. A graph convolutional network model then naturally fuses the two group of features to differentiate the children with ASD from the typically developed subjects. Experiments have been carried out on the two types of the bio-signals collected from 42 children. The results indicate that the proposed approach can achieve an accuracy of 95% in ASD detection, and strong correlations exist between the two bio-signals collected even asynchronously, in particular the EEG synchronization against the face related/joint attentions in terms of covariance. (shrink)

ObjectiveSchizophrenia is a mental disorder that is characterized by progressive cognitive impairment. Objective measures of cognitive function may provide reliable neurobiomarkers for patients with schizophrenia. The goal of the current work is to explore the correlation between resting theta power and cognitive performance in patients with schizophrenia.MethodsTwenty-two patients with schizophrenia and 23 age-, sex-, and education-matched healthy controls were included in this study. The MATRICS Consensus Cognitive Battery was used for cognitive evaluation and the Positive and Negative Syndrome Scale (...) for evaluation of clinical symptoms. EEGs were acquired in the resting state with closed and opened eyes. Between the two groups, we compared the relative theta power and examined their relationship with cognitive performance.ResultsCompared to healthy controls, patients with schizophrenia showed significantly higher theta power, both with eyes closed and open. When the eyes were open, negative correlations were found in patients with schizophrenia between theta power in the central and parietal regions with processing speed scores, and between the theta power of the Pz electrode and verbal learning and reasoning and problem-solving scores. In the control group, theta power over the Fz electrode was negatively correlated with processing speed.ConclusionsOur findings showed that theta activity increased in certain brain regions during resting state in schizophrenia. Negative associations between resting theta power over the parietal-occipital regions with MCCB domains scores suggest that altered theta activity can be used as a neurobiological indicator to predict cognitive performance. (shrink)

Transcranial Photobiomodulation has demonstrated its ability to alter electrophysiological activity in the human brain. However, it is unclear how tPBM modulates brain electroencephalogram networks and is related to human cognition. In this study, we recorded 64-channel EEG from 44 healthy humans before, during, and after 8-min, right-forehead, 1,064-nm tPBM or sham stimulation with an irradiance of 257 mW/cm2. In data processing, a novel methodology by combining group singular value decomposition with the exact low-resolution brain electromagnetic tomography was implemented and performed (...) on the 64-channel noise-free EEG time series. The gSVD+eLORETA algorithm produced 11 gSVD-derived principal components projected in the 2D sensor and 3D source domain/space. These 11 PCs took more than 70% weight of the entire EEG signals and were justified as 11 EEG brain networks. Finally, baseline-normalized power changes of each EEG brain network in each EEG frequency band were quantified during the first 4-min, second 4-min, and post tPBM/sham periods, followed by comparisons of frequency-specific power changes between tPBM and sham conditions. Our results showed that tPBM-induced increases in alpha powers occurred at default mode network, executive control network, frontal parietal network and lateral visual network. Moreover, the ability to decompose EEG signals into individual, independent brain networks facilitated to better visualize significant decreases in gamma power by tPBM. Many similarities were found between the cortical locations of SVD-revealed EEG networks and fMRI-identified resting-state networks. This consistency may shed light on mechanistic associations between tPBM-modulated brain networks and improved cognition outcomes. (shrink)

ObjectiveWhen regaining consciousness, patients who emerge from a minimally conscious state (EMCS) present with different levels of functional disability, which pose great challenges for treatment. This study investigated the frontoparietal activity in EMCS patients and its effects on functional disability.Materials and methodsIn this preliminary study, 12 EMCS patients and 12 healthy controls were recruited. We recorded a resting-state scalp electroencephalogram (EEG) for at least 5 min for each participant. Each patient was assessed using the disability rating scale (...) (DRS) to determine the level of functional disability. We analyzed the EEG power spectral density and sensor-level functional connectivity in relation to the patient’s functional disability.ResultsIn the frontoparietal region, EMCS patients demonstrated lower relative beta power (P < 0.01) and higher weighted phase lag index (wPLI) values in the theta (P < 0.01) and gamma (P < 0.01) bands than healthy controls. The frontoparietal theta wPLI values of EMCS patients were positively correlated with the DRS scores (rs = 0.629, P = 0.029). At the whole-brain level, EMCS patients only had higher wPLI values in the theta band (P < 0.01) than healthy controls. The whole-brain theta wPLI values of EMCS patients were also positively correlated with the DRS scores (rs = 0.650, P = 0.022). No significant difference in the power and connectivity between the frontoparietal region and the whole brain in EMCS patients was observed.ConclusionEMCS patients still experience neural dysfunction, especially in the frontoparietal region. However, the theta connectivity in the frontoparietal region did not increase specifically. At the level of the whole brain, the same shift could also be seen. Theta functional connectivity in the whole brain may underlie different levels of functional disability. (shrink)

Recent EEG studies on the early postmortem interval that suggest the persistence of electrophysiological coherence and connectivity in the brain of animals and humans reinforce the need for further investigation of the relationship between the brain’s activity and the dying process. Neuroscience is now in a position to empirically evaluate the extended process of dying and, more specifically, to investigate the possibility of brain activity following the cessation of cardiac and respiratory function. Under the direction of the Center for Healthy (...) Minds at the University of Wisconsin-Madison, research was conducted in India on a postmortem meditative state cultivated by some Tibetan Buddhist practitioners in which decomposition is putatively delayed. For all healthy baseline and postmortem subjects presented here, we collected resting state electroencephalographic data, mismatch negativity, and auditory brainstem response. In this study, we present HB data to demonstrate the feasibility of a sparse electrode EEG configuration to capture well-defined ERP waveforms from living subjects under very challenging field conditions. While living subjects displayed well-defined MMN and ABR responses, no recognizable EEG waveforms were discernable in any of the tukdam cases. (shrink)

Background and Objective: Understanding how trauma impacts the self-structure of individuals suffering from the Post-Traumatic Stress Disorder (PTSD) symptoms is a complex matter and despite several attempts to explain the relationship between trauma and the “Self”, this issue still lacks clarity. Therefore, adopting a new theoretical perspective may help understand PTSD deeper and to shed light on the underlying psychophysiological mechanisms. Methods: In this study, we employed the “three-dimensional construct model of the experiential selfhood” where three major components of selfhood (...) (phenomenal first-person agency, embodiment, and reflection/narration) are related to three Operational Modules (OMs) of the self-referential brain network. These modules can be reliably estimated through operational synchrony analysis of the Electroencephalogram (EEG). Six individuals with PTSD symptoms and twenty-nine sex-, age- and demographic- (race, education, marital status) matched healthy controls underwent resting state EEG signal acquisition with the following estimation of the synchrony strength within every OM. Results: Our results indicate that subjects with PTSD symptoms had significantly stronger EEG operational synchrony within anterior and right posterior OMs as well as significantly weaker EEG operational synchrony within left posterior OM compared to healthy controls. Moreover, increased the functional integrity of the anterior OM was positively associated with hyperactivity symptoms, reduced synchrony of the left posterior OM was associated with greater avoidance, and increased right posterior OM integrity was positively correlated with intrusion and mood symptoms. Conclusion: The results are interpreted in light of the triad model of selfhood and its theoretical and clinical implications (including a new treatment approach) are discussed. (shrink)

The resting-state human electroencephalogram power spectrum is dominated by alpha and theta oscillations, and also includes non-oscillatory broadband activity inversely related to frequency. Gratton proposed that alpha and theta oscillations are both related to cognitive control function, though in a complementary manner. Alpha activity is hypothesized to facilitate the maintenance of representations, such as task sets in preparation for expected task conditions. In contrast, theta activity would facilitate changes in representations, such as the updating of task sets in (...) response to unpredicted task demands. Therefore, theta should be related to reactive control, while alpha may be more relevant to proactive control. Less is known about the possible relationship between 1/f activity and cognitive control, which was analyzed here in an exploratory fashion. To investigate these hypothesized relationships, we recorded eyes-open and eyes-closed resting-state EEG from younger and older adults and subsequently tested their performance on a cued flanker task, expected to elicit both proactive and reactive control processes. Results showed that alpha power and 1/f offset were smaller in older than younger adults, whereas theta power did not show age-related reductions. Resting alpha power and 1/f offset were associated with proactive control processes, whereas theta power was related to reactive control as measured by the cued flanker task. All associations were present over and above the effect of age, suggesting that these resting-state EEG correlates could be indicative of trait-like individual differences in cognitive control performance, which may be already evident in younger adults, and are still similarly present in healthy older adults. (shrink)

Psychedelics have been recognized as model interventions for studying altered states of consciousness. However, few empirical studies of the shamanic state of consciousness, which is anecdotally similar to the psychedelic state, exist. We investigated the neural correlates of shamanic trance using high-density electroencephalography (EEG) in 24 shamanic practitioners and 24 healthy controls during rest, shamanic drumming, and classical music listening, followed by an assessment of altered states of consciousness. EEG data were used to assess changes in absolute power, (...) connectivity, signal diversity, and criticality, which were correlated with assessment measures. We also compared assessment scores to those of individuals in a previous study under the influence of psychedelics. Shamanic practitioners were significantly different from controls in several domains of altered states of consciousness, with scores comparable to or exceeding that of healthy volunteers under the influence of psychedelics. Practitioners also displayed increased gamma power during drumming that positively correlated with elementary visual alterations. Furthermore, shamanic practitioners had decreased low alpha and increased low beta connectivity during drumming and classical music and decreased neural signal diversity in the gamma band during drumming that inversely correlated with insightfulness. Finally, criticality in practitioners was increased during drumming in the low and high beta and gamma bands, with increases in the low beta band correlating with complex imagery and elementary visual alterations. These findings suggest that psychedelic drug-induced and non-pharmacologic alterations in consciousness have overlapping phenomenal traits but are distinct states of consciousness, as reflected by the unique brain-related changes during shamanic trance compared to previous literature investigating the psychedelic state. (shrink)

The heterogeneity of transcranial direct current stimulation protocols and clinical profiles may explain variable results in modulating excitability in the motor cortex after stroke. However, the cortical electrical effects induced by different tDCS protocols remain unclear. Here, we aimed to compare rhythm changes in electroencephalography induced by three tDCS position protocols and the association between tDCS effects and clinical factors in stroke. Nineteen patients with chronic ischemic stroke underwent four experimental sessions with three tDCS protocols [anodal, cathodal, and bilateral ] (...) and a sham protocol, according to a single-blind randomized crossover design. Resting-state EEG was acquired before and after each protocol. First, a paired-sample t-test was used to examine the difference in spectral power between pre- and post-stimulation. Then, linear and quadratic regression models were used separately to describe the association between the clinical factors of stroke and changes in spectral power which was significantly different between pre- and post-tDCS. Finally, repeated measures analysis of variance with lesion hemisphere, stimulation protocol, and the location was performed to investigate the effects of tDCS over time. The induced effect of tDCS was mainly reflected in the alpha rhythms. The alpha power was increased by atDCS, especially low-alpha, in localized areas of the central and distant areas of the frontal and parietal lobes. Bi-tDCS also affected alpha power but in a smaller area that mainly focused on high-alpha rhythms. However, ctDCS and sham had no significant effects on any EEG rhythm. The clinical factors of time since stroke and motor impairment level were related to the change in high-alpha induced by atDCS and bi-tDCS following quadratic regression models. The above-mentioned modulation effect lasted for 20 min without attenuation. In conclusion, our findings provide evidence that the alpha rhythm of EEG is modulated differently by different tDCS protocols and that high alpha is affected by clinical characteristics such as post-stroke time and motor deficits, which is of great significance for understanding the modulation effect of different tDCS protocols on stroke and the guidance of protocols to promote motor recovery following stroke. (shrink)

BackgroundFunctional changes after spinal cord injury are related to changes in cortical plasticity. These changes can be measured with electroencephalography and has potential to be used as a clinical biomarker.MethodIn this longitudinal study participants underwent a total of 30 sessions of robotic-assisted gait training over a course of 6 weeks. The duration of each session was 30 min. Resting state EEG was recorded before and after 30-session rehabilitation therapy. To measure gait, we used the Walking Index for Spinal (...) Cord Injury Scale, 10-Meter- Walking Test, Timed-Up-and-Go, and 6-Min-Walking Test. Balance was measured using Berg Balance Scale.ResultsFifteen participants with incomplete SCI who had AIS C or D injuries based on American Spinal Cord Injury Association Impairment Scale classification were included in this study. Mean age was 35.7 years and the mean time since injury was 17.08 months. All participants showed clinical improvement with the rehabilitation program. EEG data revealed that high beta EEG activity in the central area had a negative correlation with gait and balance measured at baseline, in a way that greater high beta EEG power was related to worse clinical function at baseline. Moreover, improvement in gait and balance had negative correlations with the change in alpha/theta ratio in the parietal area.ConclusionIn SCI, functional impairment and subsequent improvement following rehabilitation therapy with RAGT correlated with the change in cortical activity measured by EEG. Our results suggest that EEG alpha/theta ratio may be a potential surrogate marker of functional improvement during rehabilitation. Future studies are necessary to improve and validate these findings as a neurophysiological biomarker for SCI rehabilitation. (shrink)

Virtual reality is a rapidly developing technology that simulates the real world. However, for some cybersickness-susceptible people, VR still has an unanswered problem—cybersickness—which becomes the main obstacle for users and content makers. Sensory conflict theory is a widely accepted theory for cybersickness. It proposes that conflict between afferent signals and internal models can cause cybersickness. This study analyzes the brain states that determine cybersickness occurrence and related uncomfortable feelings. Furthermore, we use the electroencephalogram microstates and functional connectivity approach based on (...) the sensory conflict theory. The microstate approach is a time–space analysis method that allows signals to be divided into several temporarily stable states, simultaneously allowing for the exploration of short- and long-range signals. These temporal dynamics can show the disturbances in mental processes associated with neurological and psychiatric conditions of cybersickness. Furthermore, the functional connectivity approach gives us in-depth insight and relationships between the sources related to cybersickness. We recruited 40 males, and they watched a VR video on a curved computer monitor for 10 min to experience cybersickness. We recorded the 5-min resting state EEG and 10-min EEG while watching the VR video. Then, we performed a microstate analysis, focusing on two temporal parameters: mean duration and global explained variance. Finally, we obtained the functional connectivity data using eLoreta and lagged phase synchronization. We discovered five sets of microstates, including four widely reported canonical microstates, during baseline and task conditions. The average duration increased in microstates A and B, which is related to the visual and auditory networks. The GEV and duration decreased in microstate C, whereas those in microstate D increased. Microstate C is related to the default mode network and D to the attention network. The temporal dynamics of the microstate parameters are from cybersickness disturbing the sensory, DMN, and attention networks. In the functional connectivity part, the LPS between the left and right parietal operculum significantly decreased compared with the baseline condition. Furthermore, the connectivity between the right OP and V5 significantly decreased. These results also support the disturbance of the sensory network because a conflict between the visual and vestibular system causes cybersickness. Changes in the microstates and functional connectivity support the sensory conflict theory. These results may provide additional information in understanding brain dynamics during cybersickness. (shrink)