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.

Sleep pressure reflects the brain's homeostatic need to sleep, but the mechanisms underlying its regulation remain poorly understood. In mice, a subset of cortical inhibitory neuronal nitric oxide synthase (nNOS) positive interneurons tunes the electroencephalographic slow wave activity in the delta band (<4 Hz), marker of sleep pressure. Here, we demonstrate that in mice the natural killer (NK) cells and innate lymphoid cells (ILC)1 depletion inhibits nNOS+ interneurons and EEG delta activity reducing the time spent in the non-rapid eye movement (NREM) sleep. The optogenetic re-activation of nNOS+ interneurons in the cingulate cortex of NK cell/ILC1-depleted mice rescues the EEG delta activity, confirming the link between innate immune cells-nNOS+ interneurons-sleep pressure. Finally, we demonstrated that meningeal NK/ILC1 cells produce IFN-γ in a circadian independent manner and that IFN-γ blockade in vivo mimics the effect of NK cell depletion in mice. These findings provide insights into the complex network involved in sleep regulation and further support the contribution of the innate immune system on sleep pressure.

Patients with mild cognitive impairment (MCI) typically show abnormal high delta (<4 Hz) and low alpha (8–12 Hz) rhythms measured from resting-state eyes-closed electroencephalographic (rsEEG) source activities as well as white matter lesions (WMLs) measured from magnetic resonance imaging (MRI). Here we tested the hypothesis that rsEEG rhythms may not deteriorate with the increase of WLMs in patients with MCI due and not due to Alzheimer's disease (ADMCI and noADMCI). An international database provided demographic, clinical, and rsEEG datasets for cognitively unimpaired older (Healthy; N = 30), ADMCI ( N  = 64), and noADMCI ( N  = 36) participants. The rsEEG rhythms spanned individual delta, theta, and alpha frequency bands. The eLORETA freeware estimated cortical rsEEG sources. The international database also provided MRI datasets for the ADMCI and noADMCI participants. T2 and Fluid Attenuated Inversion Recovery (FLAIR) images estimated the WMLs. The posterior rsEEG alpha source activities were lower in the groups of the ADMCI with a less increase of WMLs (ADMCI-WML-), ADMCI with a high increase of WMLs (ADMCI-WML+), and noADMCI with a very high increase of WMLs (noADMCI-WL++) compared to the Healthy group ( p  < 0.001; Figure 1 ). This effect was dramatic in the ADMCI-WML- group, marked in the ADMCI-WML+ group, and moderate in the noADMCI-WML++. Furthermore, a positive association between the increase of WMLs and the worsening of executive function test scores (i.e., Trail making test part B-A) was observed in the noADMCI group (t = 3.25, p  < 0.005; Figure 2 ). These results suggest that neurophysiological brain neural oscillatory synchronization mechanisms regulating cortical arousal and vigilance through alpha rsEEG rhythms are not affected by white matter tissue damage in MCI patients.

The periodic (e.g., EEG alpha power density) and aperiodic (offset and slope of EEG power density) components of resting-state EEG rhythms reflect different aspects of global neural dynamics and have been linked to excitatory/inhibitory balance. This study investigates these components across vigilance stages (wakefulness, flattening, ripples) in patients with mild cognitive impairment due to Alzheimer's disease (ADMCI) compared to healthy elderly (NOLD). Spectral analysis was performed on EEG data recorded from 19 scalp electrodes during a ∼30-minute session in age-, sex-, and education-matched ADMCI and NOLD participants ( n  = 17 vs. n  = 11) showing transitions from quiet wakefulness (wakefulness stage, characterized by dominant posterior alpha activity at 8–12 Hz) to light sleep (flattening stage, marked by reduced EEG amplitude, and ripples stage, with diffuse theta activity at 4–7 Hz) based on a modified version of Hori's sleep onset classification. Periodic (spectral power in the 8–12 Hz alpha band for posterior electrodes) and aperiodic (offset and slope in the 3–40 Hz range) parameters were analyzed across vigilance stages. ANOVA was performed with Group, Stage, and Region of Interest (Frontal, Central, Temporal, Posterior) as factors. For the periodic EEG component, posterior alpha power density showed a significant Group effect, indicating reduced posterior alpha activity from quiet wakefulness to light sleep in ADMCI compared to NOLD ( p  < 0.01). In contrast, offset and exponent exhibited significant Condition effects, reflecting increased cortical inhibition (higher offset and exponent) across vigilance stages ( p  < 0.001) with no significant Group differences. Region of Interest effects showed greater inhibition across stages in parietal-occipital regions compared to anterior regions ( p  < 0.001). In this study, periodic EEG alpha power was the most sensitive marker of vigilance dysfunctions in ADMCI, while aperiodic EEG parameters primarily captured a general increase in inhibition during transitions from wakefulness to light sleep, independent of disease. Vigilance-related changes in cortical inhibition do not appear to be a hallmark of prodromal Alzheimer's disease, which is instead characterized by altered oscillatory, frequency-specific activity. Future research should integrate both periodic and aperiodic EEG features to enhance the understanding of neurophysiological dynamics in Alzheimer's disease.

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

It is well-known that in patients with Alzheimer's disease (AD) and high education attainment, cognitive performance is typically better than expected based on the burden of brain neuropathology and neurodegeneration (Stern et al., 2018; doi: 10.1016/j.neuroimage.2018.05.033). This resilience of the cognitive status was attributed to a sort of cognitive reserve (CR) accumulated by persons with high education attainment, which predicts a life with engaging job, intellectual, and social demands (Arenaza-Urquijo et al. 2015; doi: 10.3389/fnagi.2015.00134; Stern et al. 2018). Previous resting-state eyes-closed electroencephalographic (rsEEG) studies showed that alpha rhythms in posterior visual and visuospatial areas are related to CR in healthy adults, subjective memory complaints (SMC) seniors, and patients with mild cognitive impairment due to AD (ADMCI). In the present exploratory study, we used the database of the INSIGHT cohort (Dubois et al., 2018; doi: 10.1016/S1474-4422(18)30029-2), we investigated whether older adults with subjective memory complaints (SMC) and brain amyloid-β accumulation may exhibit clinical progression over 2 years as a function of educational attainment (a proxy of cognitive reserve). SMCneg with high educational attainment (Edu+) participants showed greater posterior rsEEG alpha rhythms compared to SMCneg with low educational attainment (Edu-) participants. In contrast, SMCpos Edu+ participants exhibited reduced posterior rsEEG alpha rhythms and parietal cortical thickness compared to SMCpos Edu- participants. No EEG (Figure 1) or MRI (Figure 2) marker significantly changed over the 2-year follow-up period These findings suggest that a substantially longer time interval than 2 years should be assessed to evaluate the Alzheimer's disease progression and biomarker-guided targeted therapies in presymptomatic SMCpos adults.

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.

Huntington’s disease (HD) is a progressive neurodegenerative disorder phenotypically manifested by motor, cognitive and psychiatric symptoms (Novak and Tabrizi, 2011). These patients are also characterized by vigilance abnormalities. This has been demonstrated by electrophysiological measures (Wiegand et al., 1991). In particular, previous studies have shown that HD patients have reduced alpha amplitude (de Tommaso et al., 2003; Bellotti et al., 2004) and increased resting delta activity (Bylsma et al., 1994). These electroencephalographic changes resemble those observed in patients with Alzheimer’s dementia (Babiloni et al., 2020). To date, there have been only a few studies on the specific pathophysiological changes that are the cause of the above changes in brain rhythms. In our opinion, the comparison of these two populations could be an enrichment of the physiological model that explains the electroencephalographic changes that have been observed in HD patients. Clinical and EEG datasets in 21 ADD (Dementia due to Alzheimer Disease), 16 S-HD (Symptomatic Huntington Disease) and 39 Healthy (Nold) individuals matched for demography, education, and gender were taken from an Eurasian database. The rsEEG frequency bands were individual delta, theta, alpha as well as fixed beta (14-30 Hz) and gamma (30-40 Hz). The eLORETA freeware was used to estimate cortical rsEEG sources at delta, theta, alpha, beta, and gamma frequency bands during eyes-closed and-open conditions. As core findings, we have showed that global delta source activities (and central, parietal, and occipital delta source activity) are significantly greater in S-HD than in ADD (p<0.05 Bonferroni corrected) and that frontal and temporal alpha 2 source activities are significantly lower in S-HD than in ADD (p<0.05 Bonferroni corrected) Showed in Figure 1. The present findings showed more abnormalities in delta source activities in HD patients if compared to the ADD patients, possibly related to an abnormal functioning of dopaminergic ascending neuromodulation of basal ganglia in HD subjects. Moreover, the HD peculiar alterations in alpha source activities could be related to more alterations in the cholinergic system impinging upon basal ganglia if compared with ADD patients.

Alzheimer’s Disease (AD) and Sleep disturbances are closely linked in a bidirectional relationship. Indeed, sleep alterations represent a precipitating factor in early pathogenesis of neurodegeneration. Conversely, the accumulation of Aβ and tau proteins directly disrupts sleep-wake cycles. Sleep disturbances are extremely prevalent in AD and the relationship between these disorders has been thoroughly investigated. Our study is the first to investigate the electroencephalographic cortical sources during the transitional stages between quiet wakefulness and light sleep in AD patients with MCI. We analysed data from an international database ( www.pdwaves.org ) comprising clinical, neuropsychological, EEG morning recordings (45 minutes), cerebrospinal fluid (CSF), structural and functional MRI data in n=36 ADMCI, n=20 showing transition to light sleep (t-ADMCI) and n=16 without transition to sleep (nt-ADMCI)(Table 1). The database also included clinical, neuropsychological, and EEG data of n=11 matched healthy elderly (Nold) persons transitioning to light sleep. The EEG traces were reviewed by researchers blinded to the diagnosis, divided in 4” epochs and categorised in four different vigilance conditions: Eyes Open, Wakefulness, Flattening of alpha (drowinsess), Ripples (light sleep), according to the sleep classification by Hori et al (1994). Individual alpha frequency (IAF) was used to determine the EEG delta, theta, and alpha bands. Regional EEG cortical sources were estimated using the eLORETA freeware. Compared to Nold subjects, the ADMCI subjects showed greater Frontal Delta Cortical source activity in all vigilance conditions (p<0,001) (Figure 1). Furthermore, when compared to nt-ADMCI, t-ADMCI showed an increased diffuse delta cortical source activity (p<0.0001) during the wakefulness period (Figure 2). No differences between these two last groups emerged in CSF neurodegeneration biomarkers, neuropsychological testing nor structural or functional MRI measures. The higher Frontal Delta Cortical Source activity across all vigilance conditions in t-ADMCI subjects as compared to Nold, and the persistence of this result when compared to matched nt-ADMCI patients, likely reflects the presence of dominant local delta rhythms, normally found during N3 and REM sleep, due to a low dopaminergic and cholinergic tone. Our findings might reflect a “disconnection” of frontal regions due to the loss of projections from monoaminergic subcortical nuclei, affected by early neuronal loss from AD neuropathology.

Huntington's disease (HD) differs from Alzheimer's disease (AD) in its clinical presentation, particularly regarding vigilance, with notable motor, functional, and cognitive impairments that may be mirrored in resting-state electroencephalographic (rsEEG) rhythms. To evaluate this hypothesis, clinical and rsEEG data were gathered from age-, sex-, and education-matched groups, including HD patients ( N  = 29), AD patients ( N  = 24), and healthy older participants (Nold, N = 29). EEG sources were computed using eLORETA software. The findings are as follows: (1) Compared to the Nold participants, both AD and HD patients exhibited higher widespread delta source activities (with HD > AD); (2) HD patients with the most pronounced motor deficits showed very high delta and theta source activities across widespread cortical regions; (3) HD patients with the most severe cognitive deficits exhibited lower alpha and higher delta source activities in widespread cortical regions; and (4) HD patients with the most significant functional deficits displayed very high delta source activities in widespread cortical regions. These findings indicate that in HD patients during quiet wakefulness, disruptions in cortical neural synchronization at delta and alpha frequencies are distinctly linked to cognitive, motor, and functional impairments. This underscores a unique interaction between the cholinergic and dopaminergic systems, which likely modulates the generation of alpha and delta source activities.

Vigilance and sleep disturbances in Alzheimer’s and related diseases, even at the stage of mild cognitive impairment (MCI), have been extensively documented, showing abnormal daytime naps and alterations in the sleep-wake cycle. However, the EEG correlates of the transition from wakefulness to light sleep have not yet been compared between MCI patients due to Alzheimer’s vs. other neurodegenerative diseases. Therefore, it is unclear whether there are specific features of these correlates in Alzheimer’s disease (AD) patients. This issue was investigated in the present study for the first time. Data were analyzed from an international database ( https://www.pdwaves.eu/ ) comprising neuropsychological tests, long resting-state EEG recordings, cerebrospinal fluid biomarkers, and MRI. For this study, 18 ADMCI patients, 9 NOADMCI patients, and 11 age- and sex-matched healthy (Nold) participants showing transitions from wakefulness to light sleep during the EEG recording were selected based on the evaluation of two researchers blinded to the diagnoses. EEG periods were classified into four classes according to Hori et al.’s criteria: eyes open, eyes closed, EEG flattening, and EEG ripples (the last two representing drowsiness/light sleep stages). Individual alpha frequency peak (IAF) was obtained and used to determine EEG delta, theta, and alpha (1, 2, and 3) bands. Regional EEG cortical sources (Frontal, Parietal, and Occipital) were estimated using eLORETA freeware and the ratio of the source current density for the eyes closed and ripples conditions (EC/R) was considered as the EEG correlate of sleep-wake transitions. Participants’ characteristics are reported in Table 1. The ANOVA showed a 2-way interaction between Group and Band (p<.001), unveiling reduced EC/R source activity in the alpha 2 (p-values<.001) and alpha 3 (p-values<.001) bands in the ADMCI and NOADMCI groups (Figure 1). No differences in EEG source activity were found between the ADMCI and NOADMCI groups (p>.05). The preliminary results of the present study showed widespread abnormalities in the cortical neurophysiological mechanisms oscillating at alpha frequencies in patients with Alzheimer’s and related diseases at the stage of MCI, but no differences between Alzheimer’s and non-Alzheimer’s diseases. Future studies should cross-validate these findings with larger clinical populations and test their relationship with night sleep disorders.

In this "centenary" paper, an expert panel revisited Hans Berger's groundbreaking discovery of human restingstate electroencephalographic (rsEEG) alpha rhythms (8-12 Hz) in 1924, his foresight of substantial clinical applications in patients with "senile dementia," and new developments in the field, focusing on Alzheimer's disease (AD), the most prevalent cause of dementia in pathological aging. Clinical guidelines issued in 2024 by the US National Institute on Aging-Alzheimer's Association (NIA-AA) and the European Neuroscience Societies did not endorse routine use of rsEEG biomarkers in the clinical workup of older adults with cognitive impairment. Nevertheless, the expert panel highlighted decades of research from independent workgroups and different techniques showing consistent evidence that abnormalities in rsEEG delta, theta, and alpha rhythms (< 30 Hz) observed in AD patients correlate with wellestablished AD biomarkers of neuropathology, neurodegeneration, and cognitive decline. We posit that these abnormalities may reflect alterations in oscillatory synchronization within subcortical and cortical circuits, inducing cortical inhibitory-excitatory imbalance (in some cases leading to epileptiform activity) and vigilance dysfunctions (e.g., mental fatigue and drowsiness), which may impact AD patients' quality of life. Berger's vision of using EEG to understand and manage dementia in pathological aging is still actual.

Parkinson’s disease and Huntington’s disease are both neurodegenerative conditions involving the basal ganglia area of the brain. Both conditions can cause symptoms that affect movement. Cognitive decline or dementia can also occur in both. Resting state EEG (rsEEG) rhythms reflect neurophysiological mechanisms and operational functions related to the fluctuation of brain arousal and quiet vigilance in humans. The hypothesis was that rsEEG sources may be more abnormal in Huntington’s disease patients in symptomatic stage (S-HD) than patients with dementia due to Parkinson’s disease. Clinical and rsEEG datasets in 16 PDD, 18 S-HD, and 25 matched cognitively unimpaired (Nold) participants - matched as demography, education, and gender - were taken from an international archive. The eLORETA freeware was used to estimate cortical rsEEG sources at delta, theta, alpha1, alpha2, alpha3, beta1, beta2, and gamma frequency bands. Results showed lower amplitude of the posterior alpha activities and higher amplitude of widespread low frequencies bands (i.e., delta and theta) in the PDD and S-HD groups than in the Healthy group. As compared to the PDD group, the S-HD showed greater reductions in the rsEEG alpha 2 rhythms in the frontal and temporal regions (see Figure 1). These results suggest that cortical sources of rsEEG rhythms might reflect different abnormalities of the core neurophysiological mechanisms underlying brain arousal in quiet wakefulness and low vigilance in PDD, and S-HD patients. The mentioned rsEEG markers might be clinically useful in the disease staging, monitoring over time, and drug discovery.