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.

Isolated/idiopathic rapid-eye-movement (REM)-Sleep Behavior Disorder (iRBD) is characterized by dream enactment behaviors associated with loss of REM atonia. iRBD is in most cases a prodromal synucleinopathy, and emerging evidence suggests associations between RBD and other neurological and psychiatric conditions. In this study, we performed pathway-based polygenic risk score (PRS) and rare variant burden analyses to examine these potential associations. Pathway-specific PRS were constructed from genome-wide association study summary statistics of five neurodegenerative and seven psychiatric traits across 10 biologically relevant pathway categories, including a total of 279 pathways, in 1,573 iRBD cases and 16,022 controls from the International RBD Study Group and UK Biobank. Rare variant burden tests were performed in 1,264 iRBD cases and 2,581 controls. We identified multiple potential pathways indicating shared polygenic risk between RBD and both neurodegenerative and psychiatric disorders. Lewy body diseases and post-traumatic stress disorder had the most shared polygenic risk pathways in neurological and psychiatric disorders, respectively. Two pathways, the serotonin transport pathway and the chaperone-mediated autophagy pathway, showed the strongest association with iRBD, and gene-based rare variants analyses revealed five genes associated with iRBD: GBA1, PLEKHM1, LRP2, P2RX1, and HAP1. Subsequent analysis of these genes in Parkinson's disease and dementia with Lewy bodies replicated several associations. Together, these findings provide novel insights into the shared genetic architecture underlying iRBD, neurodegenerative disorders, and psychiatric traits, with implications for early identification and mechanistic understanding.

Dementia with Lewy Bodies (DLB) is a heterogeneous disease characterized by four core clinical features: visual hallucinations, REM sleep behaviour disorder (RBD), cognitive fluctuations and Parkinsonism. We study the relationship between these features and functional connectivity from high-density electroencephalographic data of 33 subjects with early-stage DLB and 21 healthy controls. We used two connectivity metrics averaged on the individual theta and alpha bands, defined by determining the individual theta-to-alpha transition frequency through the package transfreq. After showing that DLB determines a shift toward lower frequencies of posterior dominant rhythm and theta-alpha transition, we used Network Based Statistics to explore differential connectivity networks between subgroups of DLB patients with different features. We found that both visual hallucinations and RBD are associated with increased connectivity in early DLB patients mostly in the left hemisphere, while cognitive fluctuations and Parkinsonism appear to have a non-significant impact on functional connectivity metrics in our population.

Abstract INTRODUCTION Regional patterns of amyloid beta (Aβ) deposition in Alzheimer's disease (AD) may be influenced by cerebrovascular architecture. We examined the relationship between normative arterial and venous density maps and cortical Aβ burden. METHODS Seventy‐four amyloid‐positive AD patients underwent amyloid positron emission tomography (PET) and magnetic resonance imaging. Regional Aβ uptake was quantified; spatial associations with normative arterial (time‐of‐flight magnetic resonance angiography) and venous (susceptibility‐weighted imaging) density maps were assessed using correlation analyses and partial least squares (PLS) regression, controlling for early‐frame PET as a proxy for perfusion. RESULTS Higher arterial density was associated with lower Aβ uptake (r = −0.68, p < 0.001), independent of venous density and perfusion. PLS explained 71% of regional variance, highlighting temporo‐limbic regions. Subject‐level analyses showed heterogeneous vascular–amyloid coupling, related to education and global Aβ burden. DISCUSSION Arterial architecture may contribute to regional amyloid vulnerability through vascular clearance mechanisms.

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.

Alterations of neurotransmitter systems in Alzheimer's Disease (AD) remain partially understood, mainly due to the complexity of simultaneously and directly assessing these systems in vivo. To address this knowledge gap, recent approaches have been proposed correlating normative multi-tracer neurotransmitter data with established disease biomarkers, including [18F]FDG-PET. We retrospectively enrolled 90 AD patients (72.8 ± 7 years, Mini Mental State Examination - MMSE 24 ± 4.1) and 42 Healthy Controls (HC, 70 ± 8.5 years, MMSE 29 ± 0.8), all with a brain [18F]FDG-PET scan and MMSE collected at baseline. All AD diagnoses were confirmed by a positive amyloid marker (CSF or Amyloid PET). We performed a voxel-based analysis between AD and HC to explore brain relative hypometabolism and then, using the established JuSpace toolbox, we explored the spatial correlation between brain hypometabolism and PET-maps targeting glutamate (mGluR5), GABA (GABA-a), dopamine (D1, D2, FDOPA), serotonin (SERT, 5HT1a, 5HT1b, 5HT2a, 5HT4), noradrenaline (NAT) and choline (VAChT) systems. The significant results obtained were then correlated with MMSE and cortical amyloid burden, measured with Amyloid PET. The distribution of brain relative hypometabolism of AD patients was spatially associated with maps of 5HT2a and mGluR5 distribution (both p = 0.02, r = -0.11). Both 5HT2a and mGluR5 regional relative distribution correlated with a lower MMSE, 5HT2a was also associated with a greater cerebral amyloid burden. These findings are consistent with recent multimodal imaging studies and suggest that serotonergic and glutamatergic receptor-dense regions may show preferential metabolic vulnerability in AD, with relevance for cognitive impairment.

Clinical progression from prodromal to overt stages of alpha-synucleinopathies is highly heterogeneous, and there is an urgent need for reliable clinical progression markers. Exploiting the Disease Course Map (DCM) model, we investigated how clinical signs evolve in patients with idiopathic/isolated rapid-eye-movement sleep behavior disorder (iRBD), extracting clinical progression measures for use at the single-subject level. Furthermore, we correlated them with both established and innovative neurodegeneration biomarkers. We trained a DCM model using cognitive and motor scores of a longitudinal cohort of 766 iRBD patients (166 female, 67.9 ± 7.4 years). We personalized the model by extracting three parameters to describe the single subject in comparison to the averaged population data. We tested the model on a blind set of 49 iRBD patients (7 female, 68.5 ± 7.1 years) who underwent both longitudinal clinical evaluations and instrumental evaluation at the first observation. In the blind set, we correlated the individual model parameters with presynaptic dopaminergic impairment, an established biomarker of substantia nigra neurodegeneration, and cortical electrophysiological dysfunction-measured by high-density electroencephalography (HD-EEG)-an innovative neurodegeneration biomarker. We identified three individual clinical markers reflecting early/late (time shift, τ) and fast/slow (acceleration factor, α) disease progression, as well as the individual clinical trajectory (i.e., earlier motor or cognitive impairment, intermarker spacing, ω). The individual model parameters are significantly associated with phenoconversion, with a 73% chance of distinguishing between clinically stable patients (non-converters) and those converting during the longitudinal observation to an overt alpha-synucleinopathy (converters). Motor scores progress 35% faster than cognitive scores in our iRBD cohort. Converter iRBD patients exhibited a faster and earlier disease progression than non-converters, and, on average, they showed an earlier worsening of motor scores than cognitive scores, regardless of the clinical diagnosis of overt parkinsonism. Patients with iRBD who developed parkinsonism worsened earlier than those who develop dementia. At baseline, an earlier progression was related to presynaptic dopaminergic impairment and higher phase synchronization in the theta band (4-8 Hz). Higher synchronization in the theta band was also associated with an earlier worsening of motor scores than cognitive scores. In this study, we investigated a large longitudinal iRBD cohort, applying an advanced disease progression model. We found three individual clinical markers that were able to monitor disease progression and showed significant association with both established and innovative neurodegeneration biomarkers. We suggest that these clinical markers could be used as efficacy endpoints in disease-modifying clinical trials.

In Alzheimer’s disease(AD), core CSF biomarkers incompletely predict clinical progression. Synaptic biomarkers may add prognostic information by capturing distinct biological dimensions, from synaptic injury to adaptive network function. Although correlated, neurogranin (Ng) is interpreted as a marker of post-synaptic injury, whereas neuronal pentraxin-2(NPTX2) is more closely related to circuit homeostasis. We tested whether CSF NPTX2 contains a specific component statistically associated with a putative adaptive network signal, interpreted within a hypothesized compensatory framework, using clinical progression and brain metabolism as convergent readouts. We retrospectively studied 104 patients with typical MCI-AD. CSF core AD biomarkers, NPTX2 and Ng were measured with commercial immunoassays. Early and late MCI stages were defined by proximity to dementia conversion (LMCI ≤ 2 years; EMCI > 2 years or stable). A residual NPTX2 measure(Res_NPTX2) was derived by regressing z-transformed NPTX2 on Ng, an index of AD burden based on tau/amyloid ratio, and age. Associations with MMSE and time-to-conversion were tested using linear and survival models. In all patients, brain [18F]FDG PET was analyzed with voxel-based methods to identify metabolic correlates of NPTX2 and Res_NPTX2 relative to AD-related hypometabolic regions. Ng correlated strongly with NPTX2 (ρ = 0.67,p < 0.001). Res_NPTX2 was higher in EMCI than LMCI (p = 0.0006), associated with better baseline MMSE (p = 0.008), and predicted less MMSE decline over time (p = 0.002). During follow-up, 55/104 patients(52.9

INTRODUCTION:Tau positron emission tomography (PET) probes Alzheimer's disease (AD) severity via regional tau spread but is not widely available. We tested whether multiregion structural magnetic resonance imaging (MRI) could approximate individual tau burden. METHODS:We studied 378 Alzheimer's Disease Neuroimaging Initiative (ADNI) participants with mild cognitive impairment (MCI)-AD or AD dementia with paired T1-MRI and [18F]flortaucipir tau-PET (≤6 months apart). Regional cortical thickness and volume were extracted with FreeSurfer. Principal component analysis and multivariable linear regression yielded MRI signatures of tau-PET standardized uptake value ratio (SUVR) in Braak composite regions (I, III-IV, V-VI), a meta-temporal region of interest (ROI), and a global neocortical meta-ROI. Performance and high/low tau classification were evaluated by leave-one-out cross-validation against published cut-offs. RESULTS:MRI signatures were significantly associated with tau-PET burden across all regions (p < 0.001). High-versus-low tau discrimination varied: AUC ≈ 0.70 in Braak I, ≈0.89 in Braak V-VI, and ≈0.90 globally. Discussion:Here we provide proof-of-concept evidence that multiregion T1-MRI patterns can inform on tau-PET burden in AD and may support approximate tau staging when tau-PET is unavailable, especially in subjects with more advanced tau burden.

The “Neuroimaging and Pathology Biomarkers in Parkinson’s Disease” course held on 12–13 September 2025 in Milan, Italy, convened an international faculty to review state-of-the-art biomarkers spanning neurotransmitter dysfunction, protein pathology and clinical translation. Here, we synthesize the four themed sessions and highlights convergent messages for diagnosis, stratification and trial design. The first session focused on neuroimaging markers of neurotransmitter dysfunction, highlighting how positron emission tomography (PET), single photon emission computed tomography (SPECT), and magnetic resonance imaging (MRI) provided complementary insights into dopaminergic, noradrenergic, cholinergic and serotonergic dysfunction. The second session addressed in vivo imaging of protein pathology, presenting recent advances in PET ligands targeting α-synuclein, progress in four-repeat tau imaging for progressive supranuclear palsy and corticobasal syndromes, and the prognostic relevance of amyloid imaging in the context of mixed pathologies. Imaging of neuroinflammation captures inflammatory processes in vivo and helps study pathophysiological effects. The third session bridged pathology and disease mechanisms, covering the biology of α-synuclein and emerging therapeutic strategies, the clinical potential of seed amplification assays and skin biopsy, the impact of co-pathologies on disease expression, and the “brain-first” versus “body-first” model of pathological spread. Finally, the fourth session addressed disease progression and clinical translation, focusing on imaging predictors of phenoconversion from prodromal to clinically overt stages of synucleinopathies, concepts of neural reserve and compensation, imaging correlates of cognitive impairment, and MRI approaches for atypical parkinsonism. Biomarker-informed pharmacological, infusion-based, and surgical strategies, including network-guided and adaptive deep brain stimulation, were discussed as examples of how multimodal biomarkers may inform personalized management. Across all sessions, the need for harmonization, longitudinal validation, and pathology-confirmed outcome measures was consistently emphasized as essential for advancing biomarker qualification in multicentre research and clinical practice.

Evidence linking sleep and circadian disruptions to the course of dementias, particularly Alzheimer's disease, has expanded. Such alterations are detectable from preclinical stages and parallel the disease progression. Assessing and managing sleep and circadian disturbances in patients with dementia remains challenging. New technologies are emerging, but their validation is still pending. We prepared a clinical review outlining a stepped-care, gradual, and sustainable approach aimed at achieving the most accurate possible diagnosis of different sleep disturbances. This review encompasses diagnostic methods ranging from questionnaires to instrumental assessments, progressing from simpler to more complex techniques including biological evaluations of circadian rhythm alterations. This work reflects a scientific consensus within the "Sleep" study group of the Italian Association for Dementia (SINdem), supported by certified sleep specialists. The document aims to support clinicians in adopting a tailored approach to the evaluation of sleep disturbances in dementia offering a dynamic framework balancing complexity and feasibility.

Abstract Isolated/idiopathic rapid-eye movement (REM) sleep behavior disorder (iRBD) is, in most cases, an early form of α -synuclein-related neurodegenerative diseases, including Parkinson’s disease and dementia with Lewy bodies. Clinical reports suggest that iRBD is more common in individuals with Post-Traumatic Stress Disorder (PTSD) compared to those without PTSD. We conducted polygenic risk score (PRS), genetic correlation, and Mendelian randomization analyses to explore potential genetic and/or causal associations between PTSD and iRBD. Dopamine transporter imaging binding status was also examined in iRBD patients with ( N = 6) and without PTSD ( N = 32). While not supporting a causal relationship, genetic analyses revealed a significant association between PTSD and iRBD, consistent with the exploratory imaging substudy. These findings suggest that individuals genetically at risk for PTSD may also be at higher risk for iRBD. Further investigation of iRBD in individuals with PTSD may help inform potential neurodegenerative risk.

INTRODUCTION:Daridorexant is a dual orexin receptor antagonist with optimized pharmacokinetics to improve sleep and daytime functioning, without residual effects. This review summarizes the evidence for daridorexant in the management of insomnia disorder. AREAS COVERED:This article gives a brief overview of insomnia disorder and the mechanism of action for dual orexin receptor antagonists; it also gives coverage to the distinct pharmacokinetics of daridorexant. Evidence evaluating daridorexant in the management of insomnia disorder is summarized, based on a narrative literature search of PubMed and Embase. All full-length publications reporting original research of Phase 1-4 clinical trials and observational studies of daridorexant were considered. EXPERT OPINION:Consistent nightly treatment with daridorexant showed significant and clinically meaningful improvements in both sleep and daytime functioning at the 50 mg dose. In clinical trials, daridorexant demonstrated efficacy across objective and patient-reported sleep measures in a broad adult population, including older adults, and efficacy was maintained for up to 1 year. Reduced wakefulness throughout the entire night with daridorexant was associated with improvement in daytime functioning. Head-to-head comparisons with standard insomnia hypnotics are limited to a Phase 2 dose-finding study. Its favorable safety profile makes daridorexant appropriate for many patients, including older adults.

Introduction Chronic insomnia disorder significantly affects cognitive, emotional, and physical health. Recently, the dual orexin receptor antagonist (DORA) daridorexant was approved for treating chronic insomnia in several countries. Given the limited evidence available, expert consensus was sought to clarify key clinical issues, inform practice, and guide future research. Methods Thirteen Italian sleep experts employed the Nominal Group Technique (NGT) to identify and rank important clinical questions. The process involved independent thought generation, group discussion, and online voting using a 5-point Likert scale. Results The NGT process resulted in 55 statements across five key clinical questions, with relevance scores guiding their categorization into three tiers. Key findings highlight daridorexant's mechanism of action, safety profile, efficacy on night and day parameters, and suitability for long-term use. The experts emphasized cross-tapering strategies for switching from other hypnotics, the importance of sleep psychoeducation, and using the Insomnia Severity Index and sleep diaries for treatment evaluation. Discussion Daridorexant may address insomnia without increasing sedation via its dual orexin receptor antagonism. Daridorexant seems to be effective and safe even in special patient populations, such as the elderly and those with comorbid conditions (neurodegenerative disorders and cognitive impairment, comorbid insomnia and sleep apnea, psychiatric conditions and mood disorders, epilepsy, and restless leg syndrome), thus representing a new, promising option for insomnia treatment. Conclusion The expert consensus provides a comprehensive framework for daridorexant clinical application, advocating for further research to expand the evidence base and refine best practices, as well as underscoring the importance of a multidisciplinary approach that combines both pharmacological and psychosocial interventions to optimize outcomes.

BACKGROUND:Insomnia is common in restless legs syndrome (RLS), significantly impairing quality of life. Dual orexin receptor antagonists (DORAs) have demonstrated efficacy in managing insomnia and RLS symptoms. Daridorexant is a recently approved DORA for insomnia disorder. OBJECTIVES:Evaluate the effectiveness of daridorexant 50 mg/night in treating insomnia in patients with RLS. METHODS:This multicenter prospective observational study included 21 patients with RLS and insomnia, evaluated at baseline and after 3 months of treatment with daridorexant 50 mg/night using Insomnia Severity Index (ISI), International Restless Legs Syndrome Study Group Rating Scale (IRLS), Beck Depression Inventory-II (BDI-II), and a visual analogue scale for sleep quality. RESULTS:Sixteen patients completed follow-up. Significant improvements were observed at follow-up in ISI (P = 0.001), IRLS (P = 0.001) and BDI-II scores (P = 0.001), and sleep quality (P < 0.001). CONCLUSIONS:Daridorexant 50 mg/night improved insomnia, RLS, depressive symptoms, and sleep quality in RLS patients, supporting its potential use in this population.

Arterial Spin Labelling MRI is a neuroimaging technique able to evaluate brain perfusion, an indirect measure of brain metabolism and function. Arterial Spin Labelling MRI showed to have performances comparable to [18F]fluorodeoxyglucose-PET in in epilepsy, yet literature data is still lacking about its use in children and the value of voxel-based asymmetry index analysis. Purpose of the project is to compare the Arterial Spin Labelling MRI and [18F]fluorodeoxyglucose-PET ability to identify the epileptogenic zone before and after asymmetry index analysis in children. In this observational study, paediatric patients with focal onset drug-resistant epilepsy that underwent presurgical evaluation, including Arterial Spin Labelling MRI and [18F]fluorodeoxyglucose-PET, were enrolled. The epileptogenic zone was defined by anatomo-electroclinical correlation and post-surgical outcome, when feasible. The rates of concordance with the epileptogenic zone of Arterial Spin Labelling MRI and [18F]fluorodeoxyglucose-PET before (visual analysis) and after asymmetry index analysis, were calculated. Statistically significant differences between were determined using Mc Nemar’s test (p < 0.05). 28 paediatric patients (mean age 10.07 years, 15 females) with focal epilepsy were enrolled; 22 underwent epilepsy surgery (mean age 9.86 years, 12 females). When comparing the techniques, visual analysis of Arterial Spin Labelling MRI had a significantly lower rate of concordance with the epileptogenic zone (p < 0.05). Voxel-based asymmetry index analysis increased significantly the rate of concordance of Arterial Spin Labelling MRI with the epileptogenic zone, achieving results comparable with [18F]fluorodeoxyglucose-PET in a cohort of paediatric patients.

Rapid eye movement (REM) sleep behavior disorder (RBD) is a parasomnia, and its isolated form is of particular interest, as it is an early phase alpha-synucleinopathy. Machine learning (ML) and deep learning (DL) models offer potential for automated detection, prediction of phenoconversion, and phenotyping. This scoping review identified 75 studies applying ML/DL in RBD and evaluated their methodological and reporting quality using the APPRAISE-AI tool. Most studies (73.3%) focused on RBD detection and mainly used polysomnographic data for this, while 16% addressed prediction of phenoconversion, with imaging data being the most employed modality. Sample sizes were generally small (most studies including only 20-100 individuals). According to APPRAISE-AI scores, 80% of studies had moderate overall methodological and reporting quality. Common deficiencies included lack of transparency in data and code sharing (23.3%), and poor reporting of hyperparameter tuning (17.1%), bias assessment (26.9%), and error analysis (0.66%). Data leakage was observed in 32% of studies. These issues hinder clinical translation and prevent incremental progress between research groups. Without transparent reporting and shared resources, replication and model comparisons become nearly impossible. Future work should adopt open science principles and rigorous validation to advance AI-based tools in sleep medicine.

To define how dopamine transporter (DaT) SPECT can be used to stage neurodegeneration in neuronal alpha-synucleinopathy patients at the individual level. This is an international multicenter study involving 1067 subjects (mean age 69.8 ± 8.7 years; 63.2