Lewy body disease (LBD) and Alzheimer’s disease (AD) are the most common causes of cognitive decline and dementia and are associated with characteristic alterations in resting-state electroencephalographic (rsEEG) activity. This multicenter exploratory study investigated periodic and aperiodic rsEEG features in patients with cognitive decline due to Lewy body disease (LBCD) and Alzheimer’s disease (ADCD), compared with cognitively unimpaired older adults (Nold), and examined the clinical relevance of these markers in LBCD. A total of 140 LBCD, 135 ADCD, and 118 Nold datasets from the PDWAVES archive underwent spectral parameterization to decompose rsEEG power spectra (1–30 Hz) into periodic peaks and aperiodic background activity. Both clinical groups showed a significant slowing of the individual alpha frequency (IAF), more pronounced in LBCD, along with reduced periodic alpha and beta power reflected in a lower vigilance index. The aperiodic exponent was elevated in both groups, and the aperiodic offset was also higher in LBCD, suggesting steeper spectral profiles consistent with increased inhibitory cortical tone. Within the LBCD group, poorer cognition was associated with higher low-frequency alpha power, whereas better cognition was predicted by higher high-frequency alpha power. A reduced vigilance index was associated with the presence of visual hallucinations, while no associations emerged for other symptoms. These findings suggest that combined periodic and aperiodic rsEEG features may provide relevant markers of altered vigilance regulation in LBCD. Future studies should evaluate whether these EEG markers can inform targeted interventions, such as neuromodulatory or audiovisual stimulation, to stabilize quiet-vigilance states and improve clinical outcomes. Panel A shows the spectral parameterization of rsEEG activity into periodic and aperiodic components. Panel B summarizes the main group differences in key rsEEG markers across LBCD, ADCD, and Nold participants. Panel C shows the topographical associations between the vigilance index and cognition and visual hallucinations in LBCD; colors reflect the direction and strength of the associations. For the visual hallucinations map, negative log-odds indicate lower odds of hallucinations for higher vigilance index values, whereas positive log-odds indicate higher odds; values around ± 1.5 correspond approximately to odds ratios of 0.22 and 4.5, respectively. Abbreviations: rsEEG, resting-state electroencephalography; LBCD, cognitive decline due to Lewy body disease; ADCD, cognitive decline due to Alzheimer’s disease; Nold, cognitively unimpaired older adults; IAF, individual alpha frequency; MMSE, Mini-Mental State Examination; p, standardized regression coefficient; log-odds, logistic regression coefficient.

OBJECTIVE:We evaluated the accuracy of standard machine learning (ML) algorithms in predicting 1-year cognitive decline in Alzheimer's disease patients with mild cognitive impairment (ADMCI) using resting-state electroencephalographic (rsEEG) biomarkers enriched with APOE genotype, sex, age, and educational attainment data. METHODS:The study analyzed datasets from 63 ADMCI patients obtained from an international archive. The ML algorithms included Simple Logistic Regression, Model Trees, Logistic Regression, K-nearest neighbor, and Support Vector Machine. Input features comprised lobar rsEEG source activities across delta (<4 Hz) to alpha (≈10-12 Hz) bands, cerebrospinal fluid (CSF Aβ1-42/p-tau), and structural magnetic resonance imaging (sMRI) biomarkers. Cognitive decline was assessed over a 1-year follow-up ("stable" vs. "decliner") based on Mini-Mental State Examination (MMSE) scores. RESULTS:The four independent ML algorithms accurately predicted changes in the MMSE score over a 1-year follow-up, with accuracies of 77-78% in ADMCI participants aged ≥ 70 years and 74-77% in those aged < 70 years. CONCLUSIONS AND SIGNIFICANCE:These findings suggest that rsEEG biomarkers in ADMCI patients may not only reveal underlying pathophysiological mechanisms affecting cortical arousal and vigilance but also hold predictive value for cognitive outcomes.

INTRODUCTION:We evaluated whether the brain glymphatic drainage function estimated by the diffusion tensor imaging along the perivascular space (DTI-ALPS) index relates to white matter (WM) integrity, Alzheimer's disease (AD) neuropathology, resting-state electroencephalogram (rsEEG) alpha rhythms underpinning quiet vigilance, and cognitive decline in mild cognitive impairment (MCI). METHODS:Clinical, neuroimaging, and rsEEG data were analyzed in matched mild cognitive impairment due to AD (ADMCI) and MCI not due to AD (noADMCI) participants. DTI-ALPS index and aperiodic and periodic components of the rsEEG power spectra were calculated following standard pipelines. RESULTS:Lower DTI-ALPS index was associated with higher AD neuropathology and WM lesions, lower periodic rsEEG alpha rhythms, and worse cognition in patients with ADMCI and noADMCI as a whole population, with the ADMCI (over noADMCI) group showing lower DTI-ALPS index, greater AD neuropathology, and lower periodic rsEEG alpha rhythms. CONCLUSIONS:The DTI-ALPS index may capture glymphatic system impairment linked to AD neuropathology, vigilance dysfunction, and cognitive decline in MCI.

ContextMild autonomous cortisol secretion (MACS) is increasingly recognized as a condition associated with subtle cognitive, functional, and clinical alterations, despite the absence of overt hypercortisolism. Its impact on brain function, sleep quality, and mood, however, remains incompletely understood.ObjectiveThe aim of this observational, cross-sectional study was to investigate cognitive performance, sleep quality, mood, and structural and functional brain alterations in patients with MACS compared with those with non-functioning adrenal tumors (NFAT).ParticipantsForty-eight patients with adrenal incidentalomas were enrolled, including 28 patients with MACS and 20 with NFAT, all without clinical signs of overt hypercortisolism at study entry.MethodsParticipants had a confirmed failure to suppress cortisol on 1 mg of dexamethasone and underwent comprehensive neuropsychological testing, sleep quality assessment (PSQI), mood evaluation (BDI-II), and brain magnetic resonance imaging (MRI) including structural imaging, voxel-based morphometry, and resting-state functional MRI (fMRI).ResultsCompared with patients with NFAT, those with MACS exhibited slightly lower Mini-Mental State Examination (MMSE) scores and poorer delayed verbal recall, both negatively correlated with serum cortisol levels. Patients with MACS also showed significantly poorer sleep quality, with MACS status and female sex emerging as independent predictors. No group differences were observed in depressive symptoms. Resting-state fMRI revealed altered hippocampal connectivity in MACS, with reduced connectivity with the caudate nucleus and increased connectivity with mesial occipital regions. Voxel-based morphometry showed no structural differences between groups.ConclusionsEven mild, clinically silent cortisol excess can be associated with subtle cognitive alterations, impaired sleep, and early functional connectivity changes, despite preserved brain morphology. Longitudinal studies are needed to determine whether these alterations progress over time and whether they improve with targeted treatment.

The prevalence of Mild Cognitive Impairment (MCI) is increasing worldwide, while the scarce evidence regarding clinical practice requires real-life research and consensus. This study examined real-life practices regarding the diagnosis and management of subjects with MCI in Italy. Data were collected from a modified Delphi study conducted in April-December 2023. The study involved 12 advisors and 16 specialists working in Italian Memory Clinics. The 50 statements proposed by the 12 advisors were rated on a 1–6 Likert scale in a two-round survey. Consensus was a priori defined when the rates of each statement in each round reached a mean value ≥ 5. The ratings of each statement were collected using an Excel spreadsheet. The data were analysed using Microsoft Excel and expressed as mean, median, and standard deviation (SD). The response rate was 100

Unsupervised serious video games on the SmartMe You home telemonitoring platform may enable the assessment of cognitive fluctuations in older individuals, with or without cognitive deficits. Here, we tested their validity in cognitively unimpaired older adults (Healthy) and patients with mild cognitive impairment and mild to moderate dementia due to Parkinson’s disease (PDCD). Such validity was assessed using Mini-Mental State Examination (MMSE) scores and resting-state eyes-closed electroencephalography (rsEEG) activity. Clinical, demographic, and rsEEG datasets were collected from 34 healthy and 68 PDCD participants. The SmartMe You video games included 7 unsupervised cognitive tasks implemented on a commercial tablet. The rsEEG source activities in the individual delta, theta, and alpha frequency bands were estimated using the eLORETA freeware. As novel findings, we showed that game performance: (1) discriminated between healthy participants and PDCD patients, with overall accuracy exceeding 90

OBJECTIVES:This exploratory study tested the hypothesis that Huntington's disease (HD) is characterized by distinct abnormalities in resting-state electroencephalographic (rsEEG) rhythms compared to Alzheimer's disease (AD). METHODS:Clinical and rsEEG data were collected from 35 patients with HD, 81 patients with AD, and 102 healthy controls (HC). The rsEEG cortical source activations from 30 electrodes were estimated using eLORETA and were harmonized across clinical sites. RESULTS:Compared to the HC group, both the HD and AD groups showed widespread increases in rsEEG delta source activation and decreases in alpha source activation, with the HD patients exhibiting the most pronounced frontal effects. In patients with HD, those abnormal rsEEG source activations were associated with cognitive, motor, and functional deficits. CONCLUSIONS:Patients with HD were characterized by a particular slowing of frontal rsEEG rhythms associated with clinically relevant variables. SIGNIFICANCE:A topographically widespread slowing of cortical oscillatory activity was observed in both HD and AD groups, with a particularly pronounced frontal effect in HD, which may predict a greater impact on the sleep-wake cycle. These observations should be considered exploratory and need validation in future studies with enhanced vigilance monitoring during longer rsEEG recordings.

Sedentary behavior is a recognized and modifiable risk factor for cognitive decline and dementia across neurodegenerative conditions. This study used a smartwatch-based telemonitoring procedure combined with ecological cognitive assessment to examine whether step counts can capture sedentary behavior and its association with cognitive functioning in patients with mild cognitive impairment (ADMCI) and dementia (ADD) due to Alzheimer’s disease. Then, 19 ADD, 28 ADMCI, and 23 cognitively unimpaired older adults (Nold) were consecutively recruited. Participants underwent clinical assessment, resting-state electroencephalography (rsEEG), and neuropsychological testing. They were then monitored at home for approximately one week using Samsung Galaxy Watch 4–6 devices recording step counts (total, purposeful, and incidental) and activity intensity (peak 30-min cadence), together with the unsupervised SmartMe You-TELEMAIA serious videogame battery administered on a commercial tablet for cognitive assessment. The ADD group showed reduced step counts and lower peak cadence than both ADMCI and Nold participants, whereas rsEEG markers and cognitive measures discriminated the three groups with a graded pattern. Within the AD sample, smartwatch-derived activity metrics were associated with cognitive functioning as assessed by conventional neuropsychological testing and ecological serious videogame performance, but showed limited associations with rsEEG rhythms. EEG delta and alpha rhythms were also more abnormal in the ADD group than in the ADMCI group. Home-based daytime activity monitoring with commercial smartwatches indicated that step volume and intensity are associated with cognitive status in patients with ADMCI and ADD. These findings suggest that smartwatch-derived activity metrics may provide feasible and cost-effective markers of everyday functioning in Alzheimer’s disease. a Schematic overview of the study design, including resting-state EEG, one-week smartwatch-based activity monitoring, and unsupervised ecological cognitive assessment with the SmartMe You-TELEMAIA Platform. b Group differences in daily activity metrics across participants with Alzheimer’s disease with dementia (ADD; N = 19), Alzheimer’s disease with mild cognitive impairment (ADMCI; N = 28), and cognitively unimpaired older adults (Nold; N = 23), indicating reduced daily step volume and peak cadence mainly in ADD. c Representative significant associations within the AD clinical sample (ADD + ADMCI; up to N = 47), showing that step metrics were more closely related to cognition (MMSE) and depressive symptom severity (BDI-II) than to resting-state EEG activity, for which only limited associations emerged.

Alzheimer's disease (AD) dementia is associated with marked disruptions in resting-state eyes-closed electroencephalographic (rsEEG) rhythms, particularly in the periodic alpha band (8-12 Hz), suggesting impaired vigilance regulation. In contrast, the aperiodic rsEEG component, reflecting global cortical arousal, has been reported to remain unchanged. This exploratory study examined periodic and aperiodic EEG activity in patients with mild cognitive impairment due to AD (ADMCI) during transitions from quiet wakefulness to light sleep. EEG datasets (∼30 min) from 19 ADMCI patients and 18 matched cognitively unimpaired older adults (control) were analyzed. Vigilance stages were scored using a reduced version of Hori's system, distinguishing the alpha-dominant wakefulness stage and the theta-dominant light sleep (ripples) stage. EEG spectra were parameterized using the specparam algorithm. ADMCI participants showed reduced reactivity of individual alpha power between the wakefulness and ripples stages compared to the control group. Conversely, both groups exhibited comparable increases in fronto-central theta power and steepening of the aperiodic slope and offset. No group differences emerged in aperiodic exponent and offset, although statistical power was limited by modest sample size. Overall, EEG alpha rhythms reflecting vigilance regulation are disrupted in prodromal AD, while periodic and aperiodic signatures of sleep onset are relatively preserved, suggesting selective vulnerability of attentional thalamocortical systems.

Patients with mild cognitive impairment due to Alzheimer’s disease (ADMCI) typically show abnormally high delta (<4 Hz) and low alpha (8–12 Hz) rhythms measured from resting-state eyes-closed electroencephalographic (rsEEG) activity. Here, we hypothesized that the abnormalities in rsEEG activity may be greater in ADMCI patients than in those with MCI not due to AD (noADMCI). Furthermore, they may be associated with the diagnostic cerebrospinal fluid (CSF) amyloid–tau biomarkers in ADMCI patients. An international database provided clinical–demographic–rsEEG datasets for cognitively unimpaired older (Healthy; N = 45), ADMCI (N = 70), and noADMCI (N = 45) participants. The rsEEG rhythms spanned individual delta, theta, and alpha frequency bands. The eLORETA freeware estimated cortical rsEEG sources. Posterior rsEEG alpha source activities were reduced in the ADMCI group compared not only to the Healthy group but also to the noADMCI group (p < 0.001). Negative associations between the CSF phospho-tau and total tau levels and posterior rsEEG alpha source activities were observed in the ADMCI group (p < 0.001), whereas those with CSF amyloid beta 42 levels were marginal. These results suggest that neurophysiological brain neural oscillatory synchronization mechanisms regulating cortical arousal and vigilance through rsEEG alpha rhythms are mainly affected by brain tauopathy in ADMCI patients.

Here, we investigated whether educational attainment influences the neurophysiological mechanisms underlying vigilance regulation, as reflected in resting-state eyes-closed electroencephalographic (rsEEG) rhythms, in patients with dementia due to Parkinson's (PDD) and Lewy body disease (DLB). Clinical, demographic, and rsEEG data were obtained from an international database, including PDD patients (N = 75), DLB patients (N = 50), and cognitively unimpaired older controls (Healthy; N = 54). Each group was partitioned into low (Edu-) and high (Edu+) educational attainment subgroups, matched for age, sex, and cognitive-motor status. We analyzed rsEEG rhythms across the individual delta, theta, and alpha frequency bands. Cortical rsEEG source topography was estimated using eLORETA freeware. In the Healthy group, Edu+ participants exhibited significantly greater widespread rsEEG alpha source activities compared to Edu- participants, possibly reflecting neuroprotective neurophysiological mechanisms. Conversely, in the PDD group, Edu+ patients showed lower widespread rsEEG alpha source activities than Edu- patients, possibly indicating compensatory mechanisms. No significant differences in rsEEG source activities were observed between DLB-Edu+ and DLB-Edu- patients. Educational attainment may be associated with compensatory mechanisms that counteract the abnormal neurophysiological processes underlying rsEEG alpha rhythms and vigilance regulation in PDD patients, but not in DLB patients. Future studies combining rsEEG and neuroimaging techniques should investigate the metabolic and functional connectivity correlates of these putative compensatory mechanisms in the PDD brain. Early education may be a key investment for national governments, especially in low-income countries, to prevent the cognitive deficits of Parkinson's disease along aging, thereby reducing the unbearable social and economic burden.

Parkinson's disease with dementia (PDD) and dementia with Lewy bodies (DLB) are more prevalent in males than females. Furthermore, they typically showed abnormally high delta (< 4 Hz) and low alpha (8-10 Hz) rhythms from resting-state electroencephalographic (rsEEG) activity. Here, we hypothesized that those abnormalities may depend on the patient's sex. An international database provided clinical-demographic-rsEEG datasets for cognitively unimpaired older (Healthy; N = 49; 24 females), PDD (N = 39; 13 females), and DLB (N = 38; 15 females) participants. Each group was stratified into matched female and male subgroups. The rsEEG rhythms were investigated across the individual rsEEG delta, theta, and alpha frequency bands based on the individual alpha frequency peak. The eLORETA freeware was used to estimate cortical rsEEG sources. In the Healthy group, widespread rsEEG alpha source activities were greater in the females than in the males. In the PDD group, widespread rsEEG delta source activities were lower and widespread rsEEG alpha source activities were greater in the females than in the males. In the DLB group, central-parietal rsEEG delta source activities were lower, and posterior rsEEG alpha source activities were greater in the females than in the males. These results suggest sex-dependent hormonal modulation of neuroprotective-compensatory neurophysiological mechanisms in PDD and DLB patients underlying the generation of rsEEG delta and alpha rhythms, which should be considered in the treatment of vigilance dysregulation in those patients.

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The Italian telephone-based Mini-Mental State Examination (Itel-MMSE) is considered a very easy tool for screening individuals with dementia, gained importance during COVID-19, but lacks validation and faces a ceiling effect. In the present study, we conducted a study standardizing and validating it, establishing cut-off values for two versions. Across 24 Italian sites, 707 healthy individuals (50–89 years, men: 268, women: 439) with diverse educational levels (3–24 years) were recruited. Subjects met criteria for normal conditions investigated through a semi-structured interview covering neurological, psychiatric, general medical, and psychopharmacological history. Two test versions were created to assess test–retest reliability at 45-day intervals. We also enrolled 187 subjects with Mild Cognitive Impairment (MCI) and 181 with Alzheimer's Disease (AD) for validation. The raw scores obtained on both versions of Itel-MMSE were set as dependent variables in linear regression models that included age, education, and gender as independent variables. Mean raw Itel-MMSE1 score was 20.82 (range: 13–22). Multiple linear regression demonstrated significant effects of sociodemographic variables for age and education, establishing a new cut-off ≥ 18.49. Mean raw Itel-MMSE2 score was 20.97 (range: 10–22), with a new cut-off ≥ 18.45. Validation showed high informative values, with areas under the curve (AUCs) for MCI and AD conditions and both versions (Itel-MMSE1: MCI AUC = 0.801, AD AUC = 0.907; Itel-MMSE2: MCI AUC = 0.827, AD AUC = 0.977). The Itel-MMSE proves valuable as a screening method for detecting and monitoring dementia in remote phone screenings, with different cut-offs aiding MCI patient identification in clinical settings.

The present study was developed based on the data of The PDWAVES Consortium (www.pdwaves.eu) and the PharmaCog project. The Partners and institutional affiliations are reported on the cover page of this manuscript. In this study, the clinical, neuropsychological, and magnetic resonance imaging data collection and analysis in patients with ADMCI and healthy control participants were partially supported by the funds of “Ricerca Corrente 2022-2023” (Italian Ministry of Health) to the IRCCS Synlab SDN of Naples (Italy), IRCCS Ospedale San Martino of Genoa (Italy), Oasi Research Institute-IRCCS, Troina (Italy), IRCCS Fatebenefratelli of Brescia (Italy), and IRCCS San Raffaele Pisana of Rome (Italy). Prof. Claudio Del Percio’s and Dr. Roberta Biundo’s work for this study was supported by funds of the “PRIN-2022” project entitled "AmyEEG” (Italian Ministry of University and Research, Prot. 2022FJAXY8). At the same time, Prof. Claudio Babiloni’s work was supported by funds of the “Horizon Marie S. Curie Doctoral Network ” project entitled "CombiDiag” (European Committee, Proposal: 101071485).

Here, we hypothesized that the reactivity of posterior resting-state electroencephalographic (rsEEG) alpha rhythms during the transition from eyes-closed to -open condition might be lower in patients with Parkinson's disease dementia (PDD) than in patients with Alzheimer's disease dementia (ADD). A Eurasian database provided clinical-demographic-rsEEG datasets in 73 PDD patients, 35 ADD patients, and 25 matched cognitively unimpaired (Healthy) persons. The eLORETA freeware was used to estimate cortical rsEEG sources. Results showed substantial (greater than -10%) reduction (reactivity) in the posterior alpha source activities from the eyes-closed to the eyes-open condition in 88% of the Healthy seniors, 57% of the ADD patients, and only 35% of the PDD patients. In these alpha-reactive participants, there was lower reactivity in the parietal alpha source activities in the PDD group than in the healthy control seniors and the ADD patients. These results suggest that PDD patients show poor reactivity of mechanisms desynchronizing posterior rsEEG alpha rhythms in response to visual inputs. That neurophysiological biomarker may provide an endpoint for (non) pharmacological interventions for improving vigilance regulation in those patients.

Here we tested the exploratory hypothesis that resting-state eyes-closed electroencephalographic (rsEEG) alpha rhythms may predict and be sensitive to the Alzheimer’s disease mild cognitive impairment (ADMCI) progression at a 6-month follow-up (a relevant feature for intervention clinical trials).Clinical, neuroimaging, and rsEEG datasets in 52 ADMCI and 60 matched healthy elderly (Healthy) seniors were available from an international archive (www.pdwaves.eu). The rsEEG frequency bands were individual delta, theta, and alpha (defined based on its posterior topography and “reactivity” to the eyes-open condition) or background frequency (BGF), as well as fixed beta (14-30 Hz) and gamma (30-40 Hz). Cortical source estimation was performed by eLORETA freeware.Results showed a substantial (> -10%) reduction in the posterior alpha source activities during the eyes-open condition in about 90% and 70% of the Healthy and ADMCI participants, respectively. In the younger ADMCI participants (mean age of 64.3±1.1) with “reactive” rsEEG alpha source activities, posterior alpha source activities during the eyes-closed condition predicted the global cognitive status at 6-month follow-up. In all younger ADMCI participants with “reactive” rsEEG alpha source activities, posterior alpha source activities during the eyes-closed condition reduced in magnitude at that follow-up. These effects could not be explained by neuroimaging and neuropsychological biomarkers of AD.These results suggest that in ADMCI patients, the true (“reactive”) posterior rsEEG alpha rhythms, when present, predict (in relation to younger age) and are quite sensitive to the effects of the disease progression on neurophysiological mechanisms underpinning vigilance regulation.

Here we tested the hypothesis of a relationship between the cortical default mode network (DMN) structural integrity and the resting state electroencephalographic (rsEEG) rhythms in patients with Alzheimer's disease with dementia (ADD). Clinical and instrumental datasets in 45 ADD patients and 40 normal elderly (Nold) persons originated from the PDWAVES Consortium (www.pdwaves.eu). Individual rsEEG delta, theta, alpha, and fixed beta and gamma bands were considered. Freeware platforms served to derive (1) the (gray matter) volume of the DMN, dorsal attention (DAN), and sensorimotor (SMN) cortical networks and (2) the rsEEG cortical eLORETA source activities. We found a significant positive association between the DMN gray matter volume, the rsEEG alpha source activity estimated in the posterior DMN nodes (parietal and posterior cingulate cortex), and the global cognitive status in the Nold and ADD participants. Compared with the Nold, the ADD group showed lower DMN gray matter, lower rsEEG alpha source activity in those nodes, and lower global cognitive status. This effect was not observed in the DAN and SMN. These results suggest that the DMN structural integrity and the rsEEG alpha source activities in the DMN posterior hubs may be related and predict the global cognitive status in ADD and Nold persons.

Graph theory models a network by its nodes and connections. “Degree” hubs reflect node centrality, while “connector” hubs are those linked to several clusters of nodes. Here we compared hubs modelled from measures of interdependencies of between-electrode resting-state eyes-closed electroencephalography (rsEEG) rhythms in normal old (Nold) and Alzheimer’s disease dementia (ADD) participants. As ADD is considered as a “network disease” and is typically associated with abnormal rsEEG delta (< 4 Hz) and alpha rhythms (8-12 Hz) over associative posterior areas, we predicted abnormal posterior hubs from measures of interdependencies of those rhythms in ADD as compared to Nold participants. To report robust results, we measured interdependencies of rsEEG rhythms from delta to gamma bands (2-40 Hz) by both bivariate linear lagged connectivity and multivariate (directional) isolated lagged effective coherence. Furthermore, we used three different definitions of “connector” hub. Convergent results showed that in both Nold and ADD groups, there were significant parietal “degree” and “connector” hubs derived from alpha rhythms. These hubs had a prominent outward “directionality” in the two groups, but that “directionality” was lower in ADD than Nold participants (Figure 1). Independent methodologies and hub definitions suggest that ADD patients may be characterized by low outward “directionality” of topologically partially resilient parietal “degree” and “connector” hubs derived from rsEEG alpha rhythms. Combined use of independent methodologies in rsEEG studies may produce robust results in clinical applications in ADD patients.