Functional Connectivity and Quantitative EEG in Women with Alcohol Use Disorders: A Resting-State Study

Effects of Alcohol on EEG Activity: A Systematic Review Focused on Sex-Related Differences in Youth

BACKGROUND

Most electroencephalographic (EEG) investigations on alcohol have focused on adults, and scarce data is available about the potential of EEG measurements to detect young people at high-risk, as well as, to understand possible sex differences in alcohol impact on the brain.

OBJECTIVE

This systematic review aimed to explore sex-related differences in EEG among young people with alcohol misuse, alcohol use disorder (AUD), and offspring of families with AUD.

METHODS

A systematic review of the literature was conducted following PRISMA guidelines. Review protocol was registered in Prospero (ID: CRD42024511471). After article selection process and quality assessment, 25 studies were included in our review. The search included participants between 12 and 30 years old with problematic alcohol consumption, as defined by DSM, AUDIT, or specific alcohol misuse questionnaires.

RESULTS

It seems that beta was generally higher in young males with AUD, and they usually exhibited greater interhemispheric connectivity (interHC), whereas young females with AUD tended towards enhanced intraHC. P3 appears to be particularly sensitive to alcohol misuse, with males typically exhibiting a lower amplitude than young females. Other event related potentials (ERPs) such as N415, P640, and the error-related negativity (ERN) lacked sufficient methodological support to draw conclusions regarding sex differences, N340 and P540 suggested avenues for expanding research on memory processing, indicating differences in amplitude between males and females.

CONCLUSION

Considering sex variables in clinical research will enhance our understanding of alterations in brain function and structure with the goal of tailoring treatment strategies for AUD.

Dynamic functional connectivity correlates of mental workload

Tasks with high mental workload often involve higher cognitive functions of the human brain and complex information flow involving multiple brain regions. However, the dynamics of functional connectivity between brain regions during high mental workload have not been well-studied. We use an analysis approach designed to find repeating network states from gamma-band phase locking value networks built from electroencephalograph data collected while participants engaged in tasks with different levels of mental workload. First, we define network states as results of clustering based on the closeness centrality node-level network metric. Second, we found that the transition between network states is not completely random. And, we found significant differences in network state statistics between low and high mental workload. Third, we found significant correlation between features calculated from the network state sequence and behavioral performance. Finally, we use dynamic network features as input to a support vector machine classifier and obtain cross-participant average decoding accuracy of 69.6%. Our methods provide a new perspective for analyzing the dynamics of electroencephalograph signals and have potential application to the decoding of mental workload level.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11571-024-10101-4.

Neural signatures of imaginary motivational states: desire for music, movement and social play

The literature has demonstrated the potential for detecting accurate electrical signals that correspond to the will or intention to move, as well as decoding the thoughts of individuals who imagine houses, faces or objects. This investigation examines the presence of precise neural markers of imagined motivational states through the combining of electrophysiological and neuroimaging methods. 20 participants were instructed to vividly imagine the desire to move, listen to music or engage in social activities. Their EEG was recorded from 128 scalp sites and analysed using individual standardized Low-Resolution Brain Electromagnetic Tomographies (LORETAs) in the N400 time window (400-600 ms). The activation of 1056 voxels was examined in relation to the 3 motivational states. The most active dipoles were grouped in eight regions of interest (ROI), including Occipital, Temporal, Fusiform, Premotor, Frontal, OBF/IF, Parietal, and Limbic areas. The statistical analysis revealed that all motivational imaginary states engaged the right hemisphere more than the left hemisphere. Distinct markers were identified for the three motivational states. Specifically, the right temporal area was more relevant for "Social Play", the orbitofrontal/inferior frontal cortex for listening to music, and the left premotor cortex for the "Movement" desire. This outcome is encouraging in terms of the potential use of neural indicators in the realm of brain-computer interface, for interpreting the thoughts and desires of individuals with locked-in syndrome.

Risky alcohol use during youth: Impact on emotion, cognitive networks, and resting-state EEG activity

The identification of the risk factors of alcohol consumption in youths is crucial for early interventions focused on reducing harmful alcohol use. In our study, 82 college students (40 healthy control (CO group) and 42 with risky alcohol use (RAU group) determined by AUDIT questionnaire) between the ages of 18 and 25 years underwent a comprehensive neuropsychological assessment covering emotional and cognitive functioning. Their resting-state activity was also recorded with an EEG for 10 min with their eyes open (EO) and 10 min with their eyes closed (EC) and analyzed using the Fitting Oscillations & One-Over-F (FOOOF) paradigm. After adjusting for sex, those in the RAU group had higher emotional dysregulation and impulsivity traits. The RAU girls presented more emotional regulation problems, such as dysregulation and negative urgency compared with the RAU boys. The RAU youths had significantly worse functioning in several cognitive domains, such as sustained attention, verbal memory, and executive functions. Cognitive network analysis revealed a different pattern of connections in each group showing that in the RAU group, the verbal memory domain had the highest connection with other cognitive functions. The EEG analyses did not reveal any significant differences between the CO and the RAU groups. However, we observed only in the EO condition that boys the from the RAU group displayed a higher theta/beta ratio than the RAU girls, whereas these differences were not observed within the CO group. Our findings highlight the need to explore more deeply the emotional, cognitive and brain changes underlying the RAU in young people.

Vulnerable at rest? A resting-state EEG study and psychosocial factors of young adult offspring of alcohol-dependent parents

BACKGROUND

Offspring of parents with alcohol use disorder (AUD) are more susceptible to developing AUD, with an estimated heritability of around 50%. Vulnerability to AUD in first-degree relatives is influenced by biological factors, such as spontaneous brain activity, and high-risk psychosocial characteristics. However, existing resting-state EEG studies in AUD offspring have shown inconsistent findings regarding theta, alpha, and beta band frequencies. Additionally, research consistently demonstrates an increased risk of internalizing and externalizing disorders, self-regulation difficulties, and interpersonal issues among AUD offspring.

METHODS

This study aimed to investigate the absolute power of theta, alpha, and beta frequencies in young adult offspring with a family history of AUD compared to individuals without family history. The psychosocial profiles of the offspring were also examined in relation to individuals without a family history of AUD. Furthermore, the study sought to explore the potential association between differences in frequency bands and psychosocial variables. Resting-state EEG recordings were obtained from 31 young adult healthy offspring of alcohol-dependent individuals and 43 participants with no family history of AUD (age range: 16-25 years). Participants also completed self-report questionnaires assessing anxiety and depressive symptoms, impulsivity, emotion regulation, and social involvement.

RESULTS

The results revealed no significant differences in spontaneous brain activity between the offspring and participants without a family history of AUD. However, in terms of psychosocial factors, the offspring exhibited significantly lower social involvement than the control group.

CONCLUSIONS

This study does not provide evidence suggesting vulnerability in offspring based on differences in spontaneous brain activity. Moreover, this investigation highlights the importance of interventions aimed at enhancing social connections in offspring. Such interventions can not only reduce the risk of developing AUD, given its strong association with increased feelings of loneliness but also improve the overall well-being of the offspring.

Multimodal Assessment of Smoking cue Reactivity During a Smoking Cue Exposure Task

Background. Cue-reactivity as a characteristic symptom of substance use disorders (SUD) is highly context dependent. Paradigms with high context validity need to be established for the investigation of underlying neurobiological mechanisms. While craving can be assessed by self-report as one aspect of cue-reactivity (CR), the assessment of biological measures such as the autonomous response and EEG promises a holistic perspective including CR at an automatized level. In a multimodal approach, smoking cue exposure (CE) effects on heart rate variability (HRV), EEG frequency power, and craving as well as their interrelation were assessed. This pilot study focused on the validity of CR measurements in a naturalistic CE paradigm. Methods. EEG frequency power, HRV, and craving were assessed during resting state (RS) and smoking CE in smokers (n = 14) and nonsmoking controls (n = 10) to investigate the psychophysiological and subjective reactions to CE. Results. Increased beta power was found only in smokers during CE compared to the control condition. There was an inverse correlation of beta power and maximum craving. Likewise, HRV correlated negatively with maximum smoking urges in smokers immediately after the measurements, without differentiation between CE and control condition. Conclusion. The increased beta power in smokers during CE is discussed as increased inhibitory control related to reduced craving in smokers. Furthermore, increased craving during CE seems to be associated to decreased vagal activity. The multimodal measurements during the CE showed ecological validity to be fundamental for CE assessment in clinical populations to evaluate its predictive value.

Frontal EEG response to alcohol craving elicited by individually tailored video cues

BACKGROUND

Most findings on the pathophysiology of alcoholism are based on studies using resting-state electroencephalography (EEG). There are few studies on cue-induced craving and on its utility as an electrophysiological index. We examined quantitative EEG (qEEG) activities in alcoholics and social drinkers exposed to video cues and compared their association with subjective alcohol craving and other related psychiatric symptoms, including anxiety and depression.

METHODS

This is a between-subjects design. Adult male alcoholics (n = 34) and healthy social drinkers (n = 33) participated. In a laboratory, EEGs were recorded while the participants were presented with craving-inducing video stimuli. Measures used were the Visual Analog Scale (VAS) for subjective alcohol craving, Alcohol Urge Questionnaire (AUQ), Michigan Alcoholism Screening Test (MAST), Beck Anxiety Inventory (BAI), and Beck Depression Inventory (BDI) scores.

RESULTS

One-way analysis of covariance with age showed that alcoholics had significantly increased beta activity in the right DLPFC region (F4) (F = 4.029, p = 0.049), compared to social drinkers when craving-inducing stimuli were presented. Beta activity at the F4 electrode was positively correlated with AUQ (r = .284, p = 0.021), BAI (r = .398, p = 0.001), BDI (r = .291, p = 0.018), and changes in VAS (r = .292, p = 0.017) scores in both alcoholics and social drinkers. In alcoholics, beta activity was significantly correlated with BAI (r = .392, p = 0.024).

CONCLUSIONS

These findings imply functional importance of hyperarousal and negative emotions upon exposure to craving-inducing cues. Frontal EEG indices with beta power could serve as an objective electrophysiological index of craving induced by individually tailored video cues in alcohol consumption behavior.

Alterations in the topological organization of the default-mode network in Tourette syndrome

BACKGROUND

The exact pathophysiology of TS is still elusive. Previous studies have identified default mode networks (DMN) abnormalities in patients with TS. However, these literatures investigated the neural activity during the tic suppression, not a true resting-state. Therefore, this study aimed to reveal the neural mechanism of Tourette's syndrome (TS) from the perspective of topological organization and functional connectivity within the DMN by electroencephalography (EEG) in resting-state.

METHODS

The study was conducted by analyzing the EEG data of TS patients with graph theory approaches. Thirty children with TS and thirty healthy controls (HCs) were recruited, and all subjects underwent resting-state EEG data acquisition. Functional connectivity within the DMN was calculated, and network properties were measured.

RESULTS

A significantly lower connectivity in the neural activity of the TS patients in the β band was found between the bilateral posterior cingulate cortex/retrosplenial cortex (t = -3.02, p < 0.05). Compared to HCs, the TS patients' local topological properties (degree centrality) in the left temporal lobe in the γ band were changed, while the global topological properties (global efficiency and local efficiency) in DMN exhibited no significant differences. It was also demonstrated that the degree centrality of the left temporal lobe in the γ band was positively related to the Yale Global Tic Severity Scale scores (r = 0.369, p = 0.045).

CONCLUSIONS

The functional connectivity and topological properties of the DMN of TS patients were disrupted, and abnormal DMN topological property alterations might affect the severity of tic in TS patients. The abnormal topological properties of the DMN in TS patients may be due to abnormal functional connectivity alterations. The findings provide novel insight into the neural mechanism of TS patients.

Brain optimization with additional study time: potential brain differences between high- and low-performance college students

This study investigates potential differences in brain function among high-, average-, and low-performance college students using electroencephalography (EEG). We hypothesize that the increased academic engagement of high-performance students will lead to discernible EEG variations due to the brain's structural plasticity. 61 third-year college students from identical majors were divided into high-performance (n = 20), average-performance (n = 21), and low-performance (n = 20) groups based on their academic achievements. We conducted three EEG experiments: resting state, Sternberg working memory task, and Raven progressive matrix task. Comprehensive analyses of the EEG data from the three experiments focused on power spectral density (PSD) and functional connectivity, with coherence (COH) employed as our primary metric for the latter. The results showed that in all experiments, there were no differences in working memory ability and IQ scores among the groups, and there were no significant differences in the power spectral densities of the delta, theta, alpha1, alpha2, beta, and gamma bands among the groups. Notably, on the Raven test, compared to their high-performing peers, low-performing students showed enhanced functional connectivity in the alpha 1 (8-9 Hz) band that connects the frontal and occipital lobes. We explored three potential explanations for this phenomenon: fatigue, anxiety, and greater cognitive effort required for problem-solving due to inefficient self-regulation and increased susceptibility to distraction. In essence, these insights not only deepen our understanding of the neural basis that anchors academic ability, but also hold promise in guiding interventions that address students' diverse academic needs.

The Moderating Role of Sex in the Relation between Cue-Induced Craving and Resting-State Functional Connectivity in the Salience Network of Non-Clinically Diagnosed Drinkers

INTRODUCTION

Previous research indicates a relation between craving and increased connectivity in the resting-state salience network. However, the link between cue-induced craving and connectivity in the salience network remains unclear. Further investigation is needed to understand the effect of sex on the relationship between cue-induced craving and the salience network. We investigated the role of sex in the association between the resting-state functional connectivity (RSFC) salience network and subjective cue-induced craving.

METHODS

Twenty-six males (mean age = 25.3) and 23 females (mean age = 26.0), with a score of 12 or higher on the alcohol use disorder identification test, were included in the current study. No significant difference in age was observed between males and females. Participants underwent a resting-state MRI scan for 6 min. Following the MRI scan, participants completed an alcohol cue-exposure task for 5.5 min to assess cue-induced craving using the desire to drink alcohol questionnaire. We applied independent component analysis methods to determine functional connectivity within the salience network. Subsequently, we investigated how cue-induced craving is related to the salience network's RSFC and if this relationship is moderated by sex.

RESULTS

The association between the salience network and cue-induced craving was not statistically significant nor did we find a moderating effect for sex.

CONCLUSION

The null findings in the study may be explained by a lack of power. Alternatively, alcohol use sex disparities may be more prevalent in the recreational/impulsive stage, whereas participants in our study were in the later stage of addiction.

WOMEN'S USE OF ALCOHOL: NEUROBIOBEHAVIORAL CONCOMITANTS AND CONSEQUENCES

In this narrative review, we draw from historical and contemporary literature to explore the impact of alcohol consumption on brain and behavior among women. We examine three domains: 1) the impact of alcohol use disorder (AUD) on neurobiobehavioral outcomes, 2) its impact on social cognition/emotion processing, and 3) alcohol's acute effects in older women. There is compelling evidence of alcohol-related compromise in neuropsychological function, neural activation, and brain structure. Investigations of social cognition and alcohol effects in older women represent emerging areas of study. Initial analyses suggest that women with AUD show significant deficits in emotion processing, a finding also observed in older women who have consumed a moderate dose of alcohol. Critically, despite the long-recognized need for programmatic interrogation of alcohol's effect in women, studies with sufficient numbers of women for meaningful analysis represent a small proportion of the literature, constraining interpretation and generalization.

Impulsivity Classification Using EEG Power and Explainable Machine Learning

Impulsivity is a multidimensional construct often associated with unfavorable outcomes. Previous studies have implicated several electroencephalography (EEG) indices to impulsiveness, but results are heterogeneous and inconsistent. Using a data-driven approach, we identified EEG power features for the prediction of self-reported impulsiveness. To this end, EEG signals of 56 individuals (18 low impulsive, 20 intermediate impulsive, 18 high impulsive) were recorded during a risk-taking task. Extracted EEG power features from 62 electrodes were fed into various machine learning classifiers to identify the most relevant band. Robustness of the classifier was varied by stratified [Formula: see text]-fold cross validation. Alpha and beta band power showed best performance in the classification of impulsiveness (accuracy = 95.18% and 95.11%, respectively) using a random forest classifier. Subsequently, a sequential bidirectional feature selection algorithm was used to estimate the most relevant electrode sites. Results show that as little as 10 electrodes are sufficient to reliably classify impulsiveness using alpha band power ([Formula: see text]-measure = 94.50%). Finally, the Shapley Additive exPlanations (SHAP) analysis approach was employed to reveal the individual EEG features that contributed most to the model's output. Results indicate that frontal as well as posterior midline alpha power seems to be of most importance for the classification of impulsiveness.

Brain oscillatory functioning after long-term alcohol abstinence

The heterogeneity of the population with alcohol use disorder (AUD) sometimes makes the knowledge generated in areas such as neuroscience appear to be contradictory. One aspect that may help elucidate this apparent contradiction is controlling for certain variables that are not usually controlled, such as the abstinence time in people with AUD. This research aims to study the neuroelectrical oscillations in people with AUD with longer and shorter abstinence time in comparison with healthy individuals. We recruited twenty-nine individuals with AUD with abstinence time longer than fifteen days and shorter than six months (STA), twenty-six individuals with AUD with abstinence time longer than six months and shorter than thirteen months (LTA), and sixteen healthy individuals (HC). All participants underwent electroencephalographic recording in resting-state with eyes closed. The oscillatory activity obtained was analyzed to obtain the spectral power and phase synchronization level. Regarding the obtained spectral power results, these revealed that the STA group showed higher theta band power and lower alpha band power than the LTA and HC groups. The obtained results at the phase synchronization level also show two main results. On the one hand, the STA group showed lower alpha band phase synchronization than the LTA and HC groups. On the other hand, the HC group showed higher beta band phase synchronization than the STA and LTA groups. In conclusion, the obtained results reflect that abstinence maintenance for six or more months appears to produce an important oscillatory brain functioning normalization in people with AUD.

Association between resting-state EEG oscillation and psychometric properties in perimenopausal women

Background

The perimenopausal period is associated with a higher risk of various mood disorders. Similarly, although resting-state electroencephalogram (rsEEG) brain oscillatory activity has been associated with various neuropsychological disorders and behaviours, these issues have not been assessed in perimenopausal women. This study aimed to evaluate quantitative relationships between psychometric properties and rsEEG rhythms (delta, theta, alpha, beta and gamma powers) in perimenopausal women.

Methods

A cross-sectional correlational descriptive study was conducted to quantitatively analyze the correlations between rsEEG low-to-high band activities (delta, theta, alpha, beta, and gamma powers) and psychometric properties in 14 perimenopausal women. Participants completed a psychological inventory comprising the State Anxiety Inventory (SAI), Depression Inventory (DI), Behavioural Inhibition Scale (BIS) and short-form UPPS Impulsive Behaviour Scale (IS) before EEG recording.

Results

Results showed that impulsivity was positively related to the beta power, symmetrical at most channels (frontal, temporal, central, parietal and occipital regions; p < .05); but did not related to the delta, theta, alpha and gamma powers. The brainwave low-to-high bands, delta, theta, alpha, beta and gamma power were not associated with DI, SAI or BIS scores.

Conclusions

This study’s findings propose that significantly enhanced resting-state beta activity is a trait of impulsivity in perimenopausal women. Therefore, results have potential implications for the preclinical or clinical evaluation of these issues in perimenopausal women.

Differentiating Individuals with and without Alcohol Use Disorder Using Resting-State fMRI Functional Connectivity of Reward Network, Neuropsychological Performance, and Impulsivity Measures

Individuals with alcohol use disorder (AUD) may manifest an array of neural and behavioral abnormalities, including altered brain networks, impaired neurocognitive functioning, and heightened impulsivity. Using multidomain measures, the current study aimed to identify specific features that can differentiate individuals with AUD from healthy controls (CTL), utilizing a random forests (RF) classification model. Features included fMRI-based resting-state functional connectivity (rsFC) across the reward network, neuropsychological task performance, and behavioral impulsivity scores, collected from thirty abstinent adult males with prior history of AUD and thirty CTL individuals without a history of AUD. It was found that the RF model achieved a classification accuracy of 86.67% (AUC = 93%) and identified key features of FC and impulsivity that significantly contributed to classifying AUD from CTL individuals. Impulsivity scores were the topmost predictors, followed by twelve rsFC features involving seventeen key reward regions in the brain, such as the ventral tegmental area, nucleus accumbens, anterior insula, anterior cingulate cortex, and other cortical and subcortical structures. Individuals with AUD manifested significant differences in impulsivity and alterations in functional connectivity relative to controls. Specifically, AUD showed heightened impulsivity and hypoconnectivity in nine connections across 13 regions and hyperconnectivity in three connections involving six regions. Relative to controls, visuo-spatial short-term working memory was also found to be impaired in AUD. In conclusion, specific multidomain features of brain connectivity, impulsivity, and neuropsychological performance can be used in a machine learning framework to effectively classify AUD individuals from healthy controls.

Effective Connectivity in Default Mode Network for Alcoholism Diagnosis

Alcohol Use Disorder (AUD) is a chronic relapsing brain disease characterized by excessive alcohol use, loss of control over alcohol intake, and negative emotional states under no alcohol consumption. The key factor in successful treatment of AUD is the accurate diagnosis for better medical and therapy management. Conventionally, for individuals to be diagnosed with AUD, certain criteria as outlined in the Diagnostic and Statistical Manual of Mental Disorders (DSM) should be met. However, this process is subjective in nature and could be misleading due to memory problems and dishonesty of some AUD patients. In this paper, an assessment scheme for objective diagnosis of AUD is proposed. For this purpose, EEG recording of 31 healthy controls and 31 AUD patients are used for the calculation of effective connectivity (EC) between the various regions of the brain Default Mode Network (DMN). The EC is estimated using partial directed coherence (PDC) which are then used as input to a 3D Convolutional Neural Network (CNN) for binary classification of AUD cases. Using 5-fold cross validation, the classification of AUD vs. HC effective connectivity matrices using the proposed 3D-CNN gives an accuracy of 87.85 ± 4.64 %. For further validation, 32 and 30 subjects are randomly selected for training and testing, respectively, giving 100% correct classification of all the testing subjects.

Cerebral microstructural abnormalities in impulsivity: a magnetic resonance study

Studies that investigated neurobiological parameters subtended to impulsivity trait found their relationship with structural and functional brain alterations. No studies investigated the white matter microstructural attributes of impulsivity in a large sample of healthy subjects. In the present study 1007 subjects from Human Connectome Project public dataset were divided in two groups, impulsive and not impulsive, basing on Delay Discounting task score. For both groups brain morphometric and microstructural characteristics were investigated. A t-test (correct for multiple comparisons) was performed for each brain parcel and impulsivity measure. Magnetic resonance diffusion images were pre-processed and selected to perform a voxelwise analysis on the fractional anisotropy (FA) maps between impulsive and not impulsive groups. Group analysis showed significant differences in morphometric brain data mainly for temporal and frontal lobes. The impulsive group presented higher FA values in four regions: bilateral medial lemniscus and midbrain reticular formation, right superior longitudinal fasciculus, left forceps major, right corticospinal tract. Not impulsive group showed higher FA values in two significant regions: right and left anterior thalamus radiation. Concluding, macroscopic and microstructural brain alterations were assessed, identifying new neuroanatomical substrates for multidimensional impulsivity construct in a large sample of healthy subjects.

TMS-EEG: An emerging tool to study the neurophysiologic biomarkers of psychiatric disorders

The etiology of psychiatric disorders remains largely unknown. The exploration of the neurobiological mechanisms of mental illness helps improve diagnostic efficacy and develop new therapies. This review focuses on the application of concurrent transcranial magnetic stimulation and electroencephalography (TMS-EEG) in various mental diseases, including major depressive disorder, bipolar disorder, schizophrenia, autism spectrum disorder, attention-deficit/hyperactivity disorder, substance use disorder, and insomnia. First, we summarize the commonly used protocols and output measures of TMS-EEG; then, we review the literature exploring the alterations in neural patterns, particularly cortical excitability, plasticity, and connectivity alterations, and studies that predict treatment responses and clinical states in mental disorders using TMS-EEG. Finally, we discuss the potential mechanisms underlying TMS-EEG in establishing biomarkers for psychiatric disorders and future research directions.

EEG-Derived Functional Connectivity Patterns Associated with Mild Cognitive Impairment in Parkinson's Disease

OBJECTIVE

To evaluate EEG-derived functional connectivity (FC) patterns associated with mild cognitive impairment (MCI) in Parkinson's disease (PD).

METHODS

A sample of 15 patients without cognitive impairment (PD-WCI), 15 with MCI (PD-MCI), and 26 healthy subjects were studied. The EEG was performed in the waking functional state with eyes closed, for the functional analysis it was used the synchronization likelihood (SL) and graph theory (GT).

RESULTS

PD-MCI patients showed decreased FC in frequencies alpha, in posterior regions, and delta with a generalized distribution. Patients, compared to the healthy people, presented a decrease in segregation (lower clustering coefficient in alpha p = 0.003 in PD-MCI patients) and increased integration (shorter mean path length in delta (p = 0.004) and theta (p = 0.002) in PD-MCI patients). There were no significant differences in the network topology between the parkinsonian groups. In PD-MCI patients, executive dysfunction correlated positively with global connectivity in beta (r = 0.47) and negatively with the mean path length at beta (r = -0.45); alterations in working memory were negatively correlated with the mean path length at beta r = -0.45.

CONCLUSIONS

PD patients present alterations in the FC in all frequencies, those with MCI show less connectivity in the alpha and delta frequencies. The neural networks of the patients show a random topology, with a similar organization between patients with and without MCI. In PD-MCI patients, alterations in executive function and working memory are related to beta integration.

Addiction history moderates the effect of prefrontal 10-Hz transcranial alternating current stimulation on habitual action selection

Individuals with substance use disorders (SUDs) transition more quickly from goal-directed to habitual action-selection, but the neural mechanisms underlying this phenomenon remain unclear. Data from animal models suggest that drugs of abuse can modify the neurocircuits that regulate action-selection, enhancing circuits that drive inflexible, habit-based stimulus-response (S-R) action-selection and weakening circuits that drive flexible, goal-directed actions. Here, we tested the effect of bilateral 10-Hz transcranial alternating current stimulation (10Ηz-tACs) of the dorsolateral prefrontal cortex on action-selection in men and women with a SUD history and an age- and sex-matched control group. We tested the hypothesis that true 10Ηz-tACS versus active sham stimulation would reduce perseverative errors after changed response contingencies for well-learned S-R associations, reflecting reduced habit-based action-selection, specifically in the SUD group. We found that 10 Hz-tACS increased perseverative errors in the control group, but in the SUD group, 10 Hz-tACS effects on perseverative errors depended on substance abuse duration: a longer addiction history was associated with a greater reduction of perseverative errors. These results suggest that 10Ηz-tACs altered circuit level dynamics regulating behavioral flexibility, and provide a foundation for future studies to test stimulation site, frequency, and timing specificity. Moreover, these data suggest that chronic substance abuse is associated with altered circuit dynamics that are ameliorated by 10Ηz-tACs. Determining the generalizability of these effects and their duration merits investigation as a direction for novel therapeutic interventions. These findings are timely based on growing interest in transcranial stimulation methods for treating SUDs.NEW & NOTEWORTHY Treating the executive dysfunction associated with addiction is hampered by redundancies in pharmacological regulation of different behavioral control circuits. Thus, nonpharmacological interventions hold promise for addiction treatment. Here, we show that, among people with an addiction history, 10-Hz transcranial alternating current stimulation (10Hz-tACS) of the dorsolateral prefrontal cortex can reduce habitual actions. The fact that 10Hz-tACS can regulate behavioral flexibility suggests its possible utility in reducing harmful habitual actions.

Functional Connectivity Derived From Electroencephalogram in Pharmacoresistant Epileptic Encephalopathy Using Cannabidiol as Adjunctive Antiepileptic Therapy

To explore brain function using functional connectivity and network topology derived from electroencephalogram (EEG) in patients with pharmacoresistant epileptic encephalopathy with cannabidiol as adjunctive antiepileptic treatment. Sixteen epileptic patients participated in the study, six of whom had epileptic encephalopathy with a stable dose of cannabidiol Epidiolex (CBD) as adjunctive therapy. Functional connectivity derived from EEG was analyzed based on the synchronization likelihood (SL). The analysis also included reconstructing graph-theoretic measures from the synchronization matrix. Comparison of functional connectivity data between each pathological group with the control group was carried out using a nonparametric permutation test applied to SL values between pairs of electrodes for each frequency band. To compare the association patterns between graph-theoretical properties of each pathological group with the control group, Z Crawford was calculated as a measure of distance. There were differences between pairs of electrodes in all frequency bands evaluated in encephalopathy epileptic patients with CBD adjunctive therapy compared with the control (p < 0.05, permutation test). In the epileptic encephalopathy group without CBD therapy, the SL values were higher than in the control group for the beta, theta, and delta EEG frequency bands, and lower for the alpha frequency band. Interestingly, patients who had CBD as adjunctive therapy demonstrated greater synchronization for all frequency bands, showing less spatial distribution for alpha frequency compared with the control. When comparing both epileptic groups, those patients who had adjunctive CBD treatment also showed increased synchronization for all frequency bands. In epileptic encephalopathy with adjunctive CBD therapy, the pattern of differences for graph-theoretical measures according to Z Crawford indicated less segregation and greater integration suggesting a trend towards the random organization of the network principally for alpha and beta EEG bands. This exploratory study revealed a tendency to an overconnectivity with a random network topology mainly for fast EEG bands in epileptic encephalopathy patients using CBD adjunctive therapy. It can therefore be assumed that the CBD treatment could be related to inhibition of the transition of the interictal to ictal state and/or to the improvement of EEG organization and brain function.

Alterations of Functional Connectivity During the Resting State and Their Associations With Visual Memory in College Students Who Binge Drink

This study investigated the characteristics of neural oscillation and functional connectivity (FC) in college students engaging in binge drinking (BD) using resting-state electroencephalography (EEG). Also, the associations of visual memory, evaluated by the Rey-Osterrieth Complex Figure Test (RCFT), and neural oscillation with FC during the resting state were investigated. The BD (n = 35) and non-BD (n = 35) groups were selected based on scores of the Korean version of the Alcohol use disorders (AUDs) 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.

Investigation of Brain Functional Networks in Children Suffering from Attention Deficit Hyperactivity Disorder

ADHD defects the recognition of facial emotions. This study assesses the neurophysiological differences between children with ADHD and matched healthy controls during a face emotional recognition task. The study also explores how brain connectivity is affected by ADHD. Electroencephalogram (EEG) signals were recorded from 64 scalp electrodes. Event-related phase coherence (ERPCOH) method was applied to pre-processed signals, and functional connectivity between any pair of electrodes was computed in different frequency bands. A logistic regression (LR) classifier with elastic net regularization (ENR) was trained to classify ADHD and HC participants using the functional connectivity of frequency bands as a potential biomarker. Subsequently, the brain network is constructed using graph-theoretic techniques, and graph indices such as clustering coefficient (C) and shortest path length (L) were calculated. Significant intra-hemispheric and the inter-hemispheric discrepancy between ADHD and healthy control (HC) groups in the beta band was observed. The graph features indicate that the clustering coefficient is significantly higher in the ADHD group than that in the HC group. At the same time, the shortest path length is significantly lower in the beta band. ADHD's brain networks have a problem in transferring information among various neural regions, which can cause a deficiency in the processing of facial emotions. The beta band seems better to reflect the differences between ADHD and HC. The observed functional connectivity and graph differences could also be helpful in ADHD investigations.

Random Forest Classification of Alcohol Use Disorder Using EEG Source Functional Connectivity, Neuropsychological Functioning, and Impulsivity Measures

: Individuals with alcohol use disorder (AUD) manifest a variety of impairments that can be attributed to alterations in specific brain networks. The current study aims to identify features of EEG-based functional connectivity, neuropsychological performance, and impulsivity that can classify individuals with AUD (N = 30) from unaffected controls (CTL, N = 30) using random forest classification. The features included were: (i) EEG source functional connectivity (FC) of the default mode network (DMN) derived using eLORETA algorithm, (ii) neuropsychological scores from the Tower of London test (TOLT) and the visual span test (VST), and (iii) impulsivity factors from the Barratt impulsiveness scale (BIS). The random forest model achieved a classification accuracy of 80% and identified 29 FC connections (among 66 connections per frequency band), 3 neuropsychological variables from VST (total number of correctly performed trials in forward and backward sequences and average time for correct trials in forward sequence) and all four impulsivity scores (motor, non-planning, attentional, and total) as significantly contributing to classifying individuals as either AUD or CTL. Although there was a significant age difference between the groups, most of the top variables that contributed to the classification were not significantly correlated with age. The AUD group showed a predominant pattern of hyperconnectivity among 25 of 29 significant connections, indicating aberrant network functioning during resting state suggestive of neural hyperexcitability and impulsivity. Further, parahippocampal hyperconnectivity with other DMN regions was identified as a major hub region dysregulated in AUD (13 connections overall), possibly due to neural damage from chronic drinking, which may give rise to cognitive impairments, including memory deficits and blackouts. Furthermore, hypoconnectivity observed in four connections (prefrontal nodes connecting posterior right-hemispheric regions) may indicate a weaker or fractured prefrontal connectivity with other regions, which may be related to impaired higher cognitive functions. The AUD group also showed poorer memory performance on the VST task and increased impulsivity in all factors compared to controls. Features from all three domains had significant associations with one another. These results indicate that dysregulated neural connectivity across the DMN regions, especially relating to hyperconnected parahippocampal hub as well as hypoconnected prefrontal hub, may potentially represent neurophysiological biomarkers of AUD, while poor visual memory performance and heightened impulsivity may serve as cognitive-behavioral indices of AUD.

Random Forest Classification of Alcohol Use Disorder Using fMRI Functional Connectivity, Neuropsychological Functioning, and Impulsivity Measures

Individuals with alcohol use disorder (AUD) are known to manifest a variety of neurocognitive impairments that can be attributed to alterations in specific brain networks. The current study aims to identify specific features of brain connectivity, neuropsychological performance, and impulsivity traits that can classify adult males with AUD (n = 30) from healthy controls (CTL, n = 30) using the Random Forest (RF) classification method. The predictor variables were: (i) fMRI-based within-network functional connectivity (FC) of the Default Mode Network (DMN), (ii) neuropsychological scores from the Tower of London Test (TOLT), and the Visual Span Test (VST), and (iii) impulsivity factors from the Barratt Impulsiveness Scale (BIS). The RF model, with a classification accuracy of 76.67%, identified fourteen DMN connections, two neuropsychological variables (memory span and total correct scores of the forward condition of the VST), and all impulsivity factors as significantly important for classifying participants into either the AUD or CTL group. Specifically, the AUD group manifested hyperconnectivity across the bilateral anterior cingulate cortex and the prefrontal cortex as well as between the bilateral posterior cingulate cortex and the left inferior parietal lobule, while showing hypoconnectivity in long-range anterior-posterior and interhemispheric long-range connections. Individuals with AUD also showed poorer memory performance and increased impulsivity compared to CTL individuals. Furthermore, there were significant associations among FC, impulsivity, neuropsychological performance, and AUD status. These results confirm the previous findings that alterations in specific brain networks coupled with poor neuropsychological functioning and heightened impulsivity may characterize individuals with AUD, who can be efficiently identified using classification algorithms such as Random Forest.

Neuropsychophysiological Measures of Alcohol Dependence: Can We Use EEG in the Clinical Assessment?

Addiction management is complex, and it requires a bio-psycho-social perspective, that ought to consider the multiple etiological and developmental factors. Because of this, a large amount of resources has been allocated to assess the vulnerability to dependence, i.e., to identify the processes underlying the transition from substance use to dependence, as well as its course, in order to determine the key points in its prevention, treatment, and recovery. Consequently, knowledge \from neuroscience must be taken into account, which is why different initiatives have emerged with this objective, such as the "Research Domain Criteria" (RDoC), and the "Addiction Neuroclinical Assessment" (ANA). Particularly, neuropsychophysiological measures could be used as markers of cognitive and behavioral attributes or traits in alcohol dependence, and even trace clinical change. In this way, the aim of this narrative review is to provide an overview following ANA clinical framework, to the most robust findings in neuropsychophysiological changes in alcohol dependence, that underlie the main cognitive domains implicated in addiction: incentive salience, negative emotionality, and executive functioning. The most consistent results have been found in event-related potential (ERP) analysis, especially in the P3 component, that could show a wide clinical utility, mainly for the executive functions. The review also shows the usefulness of other components, implicated in affective and substance-related processing (P1, N1, or the late positive potential LPP), as well as event-related oscillations, such as theta power, with a possible use as vulnerability or clinical marker in alcohol dependence. Finally, new tools emerging from psychophysiology research, based on functional connectivity or brain graph analysis could help toward a better understanding of altered circuits in alcohol dependence, as well as communication efficiency and effort during mental operations. This review concludes with an examination of these tools as possible markers in the clinical field and discusses methodological differences, the need for more replicability studies and incipient lines of work. It also uses consistent findings in psychophysiology to draw possible treatment targets and cognitive profiles in alcohol dependence.

Computer-aided classifying and characterizing of methamphetamine use disorder using resting-state EEG

Methamphetamine (meth) is potently addictive and is closely linked to high crime rates in the world. Since meth withdrawal is very painful and difficult, most abusers relapse to abuse in traditional treatments. Therefore, developing accurate data-driven methods based on brain functional connectivity could be helpful in classifying and characterizing the neural features of meth dependence to optimize the treatments. Accordingly, in this study, computation of functional connectivity using resting-state EEG was used to classify meth dependence. Firstly, brain functional connectivity networks (FCNs) of 36 meth dependent individuals and 24 normal controls were constructed by weighted phase lag index, in six frequency bands: delta (1-4 Hz), theta (4-8 Hz), alpha (8-15 Hz), beta (15-30 Hz), gamma (30-45 Hz) and wideband (1-45 Hz).Then, significant differences in graph metrics and connectivity values of the FCNs were used to distinguish the two groups. Support vector machine classifier had the best performance with 93% accuracy, 100% sensitivity, 83% specificity and 0.94 F-score for differentiating between MDIs and NCs. The best performance yielded when selected features were the combination of connectivity values and graph metrics in the beta frequency band.

Brain functional connectivity after cognitive-bias modification and behavioral changes in abstinent alcohol-use disorder patients

The use of the cognitive-bias modification (CBM) method has emerged as a therapeutic complement in the treatment of alcoholism, producing changes at behavioral and brain level. Nevertheless, the impact of the CBM procedure could be improved by the memory retrieval-extinction process (REP). Different studies have demonstrated that the retrieval of drug memories before extinction training later reduced the reinstatement of drug-seeking behavior. The main aim of this work was to study the effect of the CBM procedure itself, as well as in combination with the activation of alcohol-related memories, on the brain oscillatory activity of abstinent patients with alcohol-use disorder. The study sample comprised 33 patients divided into three groups: A-CBM (alcohol-related memory activation + CBM), N-CBM (neutral memory activation + CBM) and N-INT (no-intervention) groups. A resting-state EEG was obtained before and after each protocol, along with the assessment of the automatic action tendencies. A-CBM group showed a general alpha synchronization increase after the protocol, while the other groups did not show any significant change. Besides, A-CBM group showed significant intra and inter-group differences in the automatic action tendencies after the protocol, reflected in higher avoidance bias toward appetitive, aversive and without context alcohol-related stimuli. The alpha phase synchronization increase could be the neural manifestation of the conditioning produced between the alcohol-related stimuli and the automatic avoidance response. Moreover, the activation of the alcohol-related memories favors this conditioning with those alcohol-related stimuli associated with the activated memories, because it increases their threat level for the abstinence maintenance.

EEG Frequency Bands in Psychiatric Disorders: A Review of Resting State Studies

A significant proportion of the electroencephalography (EEG) literature focuses on differences in historically pre-defined frequency bands in the power spectrum that are typically referred to as alpha, beta, gamma, theta and delta waves. Here, we review 184 EEG studies that report differences in frequency bands in the resting state condition (eyes open and closed) across a spectrum of psychiatric disorders including depression, attention deficit-hyperactivity disorder (ADHD), autism, addiction, bipolar disorder, anxiety, panic disorder, post-traumatic stress disorder (PTSD), obsessive compulsive disorder (OCD) and schizophrenia to determine patterns across disorders. Aggregating across all reported results we demonstrate that characteristic patterns of power change within specific frequency bands are not necessarily unique to any one disorder but show substantial overlap across disorders as well as variability within disorders. In particular, we show that the most dominant pattern of change, across several disorder types including ADHD, schizophrenia and OCD, is power increases across lower frequencies (delta and theta) and decreases across higher frequencies (alpha, beta and gamma). However, a considerable number of disorders, such as PTSD, addiction and autism show no dominant trend for spectral change in any direction. We report consistency and validation scores across the disorders and conditions showing that the dominant result across all disorders is typically only 2.2 times as likely to occur in the literature as alternate results, and typically with less than 250 study participants when summed across all studies reporting this result. Furthermore, the magnitudes of the results were infrequently reported and were typically small at between 20% and 30% and correlated weakly with symptom severity scores. Finally, we discuss the many methodological challenges and limitations relating to such frequency band analysis across the literature. These results caution any interpretation of results from studies that consider only one disorder in isolation, and for the overall potential of this approach for delivering valuable insights in the field of mental health.

EEG correlates associated with the severity of gambling disorder and serum BDNF levels in patients with gambling disorder

Background and aims This study aimed to evaluate the association between the severity of pathological gambling, serum brain-derived neurotrophic factor (BDNF) level, and the characteristics of quantitative electroencephalography (EEG) in patients with gambling disorder. Methods A total of 55 male patients aged 18-65 with gambling disorder participated. The severity of pathological gambling was assessed with the nine-item Problem Gambling Severity Index from the Canadian Problem Gambling Index (CPGI-PGSI). The Beck Depression Inventory and Lubben Social Network Scale were also assessed. Serum BDNF levels were assessed from blood samples. The resting-state EEG was recorded while the eyes were closed, and the absolute power of five frequency bands was analyzed: delta (1-4 Hz), theta (4-8 Hz), alpha (8-12 Hz), beta (12-30 Hz), and gamma (30-50 Hz). Results Serum BDNF level was positively correlated with theta power in the right parietal region (P4, r = .403, p = .011), beta power in the right parietal region (P4, r = .456, p = .010), and beta power in the right temporal region (T8, r = .421, p = .008). Gambling severity (CPGI-PGSI) was positively correlated with absolute beta power in the left frontal region (F7, r = .284, p = .043) and central region [(C3, r = .292, p = .038), (C4, r = .304, p = .030)]. Conclusions These findings support the hypothesis that right-dominant lateralized correlations between BDNF and beta and theta power reflect right-dominant brain activation in addiction. The positive correlations between beta power and the severity of gambling disorder may be associated with hyperexcitability and increased cravings. These findings contribute to a better understanding of brain-based electrophysiological changes and BDNF levels in patients with pathological gambling.

The neural correlates of the unified percept of alcohol-related craving: a fMRI and EEG study

Alcohol addiction is accompanied by aberrant neural activity. Previously, task-based fMRI and resting-state EEG studies have revealed that craving, a critical component of addiction, is linked to abnormal activity in cortical regions including the dorsal anterior cingulate cortex (dACC), nucleus accumbens (NAcc), posterior cingulate cortex (PCC) and pregenual anterior cingulate cortex (pgACC), etc. In this study, we combine these two imaging techniques to investigate a group of alcohol-addicted patients and provide convergent evidence for the neural correlates of craving not only in alcohol but substance abuse in general. We observe abnormal BOLD signal levels in the dACC, NAcc, pgACC, PCC, amygdala, and parahippocampus (PHC) in a cue-reactivity fMRI experiment. These findings are consistent with increased beta-band activity in the dACC and pgACC in resting-state EEG. We further observe desynchronization characterized by decreased functional connectivity in cue-based fMRI and hypersynchronization characterized by increased functional connectivity between these regions in the theta frequency band. The results of our study show a consistent pattern of alcohol craving elicited by external cues and internal desires. Given the advantage of superior spatial and temporal resolution, we hypothesize a "central craving network" that integrates the different aspects of alcohol addiction into a unified percept.

Heavy alcohol use in adolescence is associated with altered cortical activity: a combined TMS-EEG study

Long-term alcohol use affects cognitive and neurophysiological functioning as well as structural brain development. Combining simultaneous electroencephalogram (EEG) recording with transcranial magnetic stimulation (TMS) enables direct, in vivo exploration of cortical excitability and assessment of effective and functional connectivity. In the central nervous system, the effects of alcohol are particularly mediated by alterations in gamma-aminobutyric acid (GABA)ergic neurotransmission, and TMS-evoked potentials (TEPs) N45 and N100 in EEG are known to reflect GABAergic function. However, no previous studies have examined the effects of long-term alcohol use in adolescence on TEPs. In this study, a total of 27 young adults with heavy alcohol use in adolescence and 25 age-matched, gender-matched and education-matched controls with little or no alcohol use participated in TMS-EEG measurements. The motor cortex (M1) was stimulated with an intensity of 90 percent of the resting motor threshold of the abductor pollicis brevis muscle. No significant differences were found in the resting motor threshold, TEP latencies or neuropsychological functioning between the groups. We observed an increase in the global mean field power in the time window of 54- to 75-millisecond post-TMS, as well as significant topographical differences in the P60 and N100 in those with a history of heavy drinking. Furthermore, there was a marked increase in the GABAergic N45 amplitude in alcohol users. These findings suggest that long-term alcohol use in adolescence, even when not meeting the diagnostic criteria for a disorder, is associated with changes in connectivity and cortical excitability.

Age-Related Differences in Reorganization of Functional Connectivity for a Dual Task with Increasing Postural Destabilization

The aged brain may not make good use of central resources, so dual task performance may be degraded. From the brain connectome perspective, this study investigated dual task deficits of older adults that lead to task failure of a suprapostural motor task with increasing postural destabilization. Twelve younger (mean age: 25.3 years) and 12 older (mean age: 65.8 years) adults executed a designated force-matching task from a level-surface or a stabilometer board. Force-matching error, stance sway, and event-related potential (ERP) in the preparatory period were measured. The force-matching accuracy and the size of postural sway of the older adults tended to be more vulnerable to stance configuration than that of the young adults, although both groups consistently showed greater attentional investment on the postural task as sway regularity increased in the stabilometer condition. In terms of the synchronization likelihood (SL) of the ERP, both younger and older adults had net increases in the strengths of the functional connectivity in the whole brain and in the fronto-sensorimotor network in the stabilometer condition. Also, the SL in the fronto-sensorimotor network of the older adults was greater than that of the young adults for both stance conditions. However, unlike the young adults, the older adults did not exhibit concurrent deactivation of the functional connectivity of the left temporal-parietal-occipital network for postural-suprapostural task with increasing postural load. In addition, the older adults potentiated functional connectivity of the right prefrontal area to cope with concurrent force-matching with increasing postural load. In conclusion, despite a universal negative effect on brain volume conduction, our preliminary results showed that the older adults were still capable of increasing allocation of neural sources, particularly via compensatory recruitment of the right prefrontal loop, for concurrent force-matching under the challenging postural condition. Nevertheless, dual-task performance of the older adults tended to be more vulnerable to postural load than that of the younger adults, in relation to inferior neural economy or a slow adaptation process to stance destabilization for scant dissociation of control hubs in the temporal-parietal-occipital cortex.

An Increase in Postural Load Facilitates an Anterior Shift of Processing Resources to Frontal Executive Function in a Postural-Suprapostural Task

Increase in postural-demand resources does not necessarily degrade a concurrent motor task, according to the adaptive resource-sharing hypothesis of postural-suprapostural dual-tasking. This study investigated how brain networks are organized to optimize a suprapostural motor task when the postural load increases and shifts postural control into a less automatic process. Fourteen volunteers executed a designated force-matching task from a level surface (a relative automatic process in posture) and from a stabilometer board while maintaining balance at a target angle (a relatively controlled process in posture). Task performance of the postural and suprapostural tasks, synchronization likelihood (SL) of scalp EEG, and graph-theoretical metrics were assessed. Behavioral results showed that the accuracy and reaction time of force-matching from a stabilometer board were not affected, despite a significant increase in postural sway. However, force-matching in the stabilometer condition showed greater local and global efficiencies of the brain networks than force-matching in the level-surface condition. Force-matching from a stabilometer board was also associated with greater frontal cluster coefficients, greater mean SL of the frontal and sensorimotor areas, and smaller mean SL of the parietal-occipital cortex than force-matching from a level surface. The contrast of supra-threshold links in the upper alpha and beta bands between the two stance conditions validated load-induced facilitation of inter-regional connections between the frontal and sensorimotor areas, but that contrast also indicated connection suppression between the right frontal-temporal and the parietal-occipital areas for the stabilometer stance condition. In conclusion, an increase in stance difficulty alters the neurocognitive processes in executing a postural-suprapostural task. Suprapostural performance is not degraded by increase in postural load, due to (1) increased effectiveness of information transfer, (2) an anterior shift of processing resources toward frontal executive function, and (3) cortical dissociation of control hubs in the parietal-occipital cortex for neural economy.

Impact of the reference choice on scalp EEG connectivity estimation

OBJECTIVE

Several scalp EEG functional connectivity studies, mostly clinical, seem to overlook the reference electrode impact. The subsequent interpretation of brain connectivity is thus often biased by the choice of a non-neutral reference. This study aims at systematically investigating these effects.

APPROACH

As EEG reference, we examined the vertex electrode (Cz), the digitally linked mastoids (DLM), the average reference (AVE), and the reference electrode standardization technique (REST). As a connectivity metric, we used the imaginary part of the coherency. We tested simulated and real data (eyes-open resting state) by evaluating the influence of electrode density, the effect of head model accuracy in the REST transformation, and the impact on the characterization of the topology of functional networks from graph analysis.

MAIN RESULTS

Simulations demonstrated that REST significantly reduced the distortion of connectivity patterns when compared to AVE, Cz, and DLM references. Moreover, the availability of high-density EEG systems and an accurate knowledge of the head model are crucial elements to improve REST performance, with the individual realistic head model being preferable to the standard realistic head model. For real data, a systematic change of the spatial pattern of functional connectivity depending on the chosen reference was also observed. The distortion of connectivity patterns was larger for the Cz reference, and progressively decreased when using the DLM, the AVE, and the REST. Strikingly, we also showed that network attributes derived from graph analysis, i.e. node degree and local efficiency, are significantly influenced by the EEG reference choice.

SIGNIFICANCE

Overall, this study highlights that significant differences arise in scalp EEG functional connectivity and graph network properties, in dependence on the chosen reference. We hope that our study will convey the message that caution should be used when interpreting and comparing results obtained from different laboratories using different reference schemes.