Distinguishing epileptic seizures from parasomnias is challenging due to overlapping motor features. This study evaluated a SlowFast deep learning model using video recordings of 167 individuals to classify Sleep-Related Hypermotor Epilepsy, Disorders of Arousal, and REM Sleep Behavior Disorder. The model achieved a mean accuracy of 83.3% across three data splits. This work represents an initial step toward developing automated tools to support clinicians in assessing sleep-related motor events.

STUDY OBJECTIVES:We aim to analyze the microbiota composition in Restless Legs Syndrome (RLS) patients and its relationship with the different RLS phenotypes. METHODS:We recruited idiopathic RLS (RLS) and insomnia (INS) patients and healthy subjects (CTRL). Validated questionnaires (Pittsburg Sleep Quality Index, International Restless Legs Syndrome Study Group Rating Scale, Insomnia Severity Index, Beck Depression Inventory-II) were administered in the RLS and INS. Fecal microbiota was analyzed by 16S rRNA gene sequencing according to Illumina metagenomics standard procedure on MiSeq Platform. Dada2 pipeline was used to process sequencing data, while DESeq2 and Aldex2 tools were used to calculate differential abundance taxa, correcting for age, sex, body mass index, sequencing run, and presence of mood disorders. RESULTS:The sample included 37 RLS (28 females, mean age 64.78 years), 31 INS (22 females, mean age 60.64 years), and 33 CTRL (24 females, mean age 62.54 years). Differential abundance analysis revealed a statistically significant decrease in the abundance of Lachnoclostridium and Flavonifractor genera in RLS compared to CTRL and INS, but not in the INS compared to CTRL. Lachnoclostridium abundance tended to decrease with long disease duration and a predominant motor phenotype. In the RLS group, several genera were identified as significantly associated with International Restless Legs Syndrome Study Group Rating Scale and Pittsburg Sleep Quality Index scores. CONCLUSIONS:Although only a few previous studies have reported the presence of small intestinal bacterial overgrowth in RLS, to the best of our knowledge this is the first study to highlight significant differences in the gut microbiota composition of RLS compared to both CTRL and INS, identifying a specific RLS metagenomic signature. Statement of Significance This is the first study to comprehensively characterize the gut microbiota in patients with Restless Legs Syndrome (RLS), identifying a distinct microbial signature compared to insomnia patients and healthy controls. We observed alterations alpha and beta diversity and specific changes in bacterial families and genera, some of which significantly correlated with RLS clinical features. In particular, Lachnoclostridium genus was significantly reduced in RLS and tended to be less abundant in patients with longer disease duration and without sensory symptoms. This genus is known to modulate systemic inflammation through the production of short-chain fatty acids, suggesting a potential link between gut dysbiosis, inflammation, and dopaminergic dysfunction. These findings support a role for gut microbiota alterations in RLS pathogenesis and open new avenues for microbiota-based diagnostic and therapeutic strategies.

STUDY OBJECTIVES:For most sleep disorders, in-laboratory video-polysomnography (VPSG) is currently considered the gold diagnostic standard. However, a growing need for more accessible diagnostic tools has been highlighted. This study aims to describe the experience of the Bologna Sleep Center in evaluating sleep-related motor behaviors using home VPSG. METHODS:Consecutive patients referred to the Bologna Sleep Center between April 2016 and May 2024 for suspected sleep-related motor behaviors were recorded. Based on clinical suspicion, patients underwent either a 48-h monitoring with a full electroencephalogram montage (for non-rapid eye movement parasomnias or epilepsy) or a 24-h monitoring with a sleep montage (for patients with rapid eye movement [REM] sleep behavior disorder). Patients were equipped in the sleep lab by expert sleep technicians, who also provided instructions for continuing the recording in the home setting. A technical evaluation of recording quality was conducted on the first 50 recordings. RESULTS:We included 305 patients, resulting in a total of 489 home VPSGs. Overall, 82% of the recordings were diagnostic (either confirming or excluding the clinical suspicion), while 18% were nondiagnostic due to insufficient evidence to confirm a diagnosis or technical issues. A detailed technical evaluation of the quality of the tracings in the first 50 recordings revealed a mean artifact percentage of 8% on polygraphic channels. CONCLUSIONS:Home VPSG demonstrated good diagnostic accuracy and exhibited limited technical issues that do not significantly interfere with its diagnostic capability. Recording in the patient's natural environment may increase the likelihood of capturing habitual episodes. Statement of Significance The present study demonstrates that diagnosing sleep-related motor behaviors using home video-polysomnography is feasible. In particular, one recording night is often sufficient for a diagnosis of REM sleep behavior disorder, while two consecutive nights provide good diagnostic efficacy for disorders of arousal, for which the home environment may increase the likelihood of capturing habitual episodes. Careful work by the sleep lab staff is essential for the success of the recordings, ensuring tracings with minimal artifacts. Future studies may further minimize technical issues by incorporating video tutorials or telemonitoring to address critical technical challenges. In conclusion, home video-polysomnography may serve as a valuable implement at the sleep expert's disposal, providing lower costs and shorter waiting lists than in-lab video-polysomnography.

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.

Isolated REM sleep behavior disorder (iRBD) is among the most reliable prodromal markers of α-synucleinopathies, yet accessible biomarkers of phenoconversion risk are lacking and the fecal metabolome remains poorly investigated in this population. In this exploratory, cross-sectional study of 21 iRBD patients and 15 healthy controls, we characterized fecal samples through an integrated multi-omics framework. The fecal metabolome was profiled on two complementary mass spectrometry platforms: HS-SPME GC-EI-high-resolution MS, used for both untargeted volatilomics and targeted quantification of linear and branched short-chain fatty acids, and untargeted LC-MS/MS for the non-volatile fraction. Gut microbial community composition was characterized on the same material by 16S rRNA gene sequencing, and the metabolomic and microbial layers were combined by DIABLO multi-omics integration. Linear short-chain fatty acids were preserved, whereas branched-chain fatty acids were selectively increased in iRBD, indicating a shift toward proteolytic fermentation. Volatile indole was reduced, while p-cresol and 2-octanone were increased, paralleled at the LC-MS/MS level by attenuation of the tryptophan-indole axis, class-level bile acid depletion, and increased acylcarnitines. The microbiome was depleted of Blautia and Faecalibacterium and enriched in Oscillospirales. Integration resolved a coherent host-microbe signature discriminating groups with 84.8% cross-validated accuracy, positioning fecal metabolomics as a sensitive window into prodromal gut-brain interactions.

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 Extracellular vesicles (EVs) hold promise as minimally invasive biomarkers for neurodegenerative proteinopathies, but disease- and stage-specific profiles remain unclear. For this study, we enrolled 378 participants across five centers and the MJFF-BioFIND cohort: 100 healthy controls [HC], 64 isolated REM sleep behavior disorder [iRBD], 41 DeNovo Parkinson’s Disease [PD], 89 Late PD, 32 other Synucleinopathies, and 52 Tauopathies. All participants underwent clinical evaluation and blood collection. The 77 subjects from the BioFIND cohort also provided CSF samples. EV concentration and size were assessed by nanoparticle tracking analysis; flow cytometry quantified tetraspanins (CD9/CD63/CD81) and 37 surface markers. Multivariable logistic regression, receiver operating characteristic analyses (ROC), and repeated random forest (rRF) classifiers evaluated diagnostic utility. Late PD showed the highest EV concentrations compared to HC and other disease groups. Participants exhibited distinct EV surface immunophenotypes, with the iRBD group displaying the most extensive immune activation signature vs HC, followed by PD patients. Multivariate logistic regression analysis identified diagnostic marker panels: CD3/CD9/CD25/CD56 for iRBD, SSEA4 for Late PD, CD146/CD209 for Synucleinopathies, and CD8/CD45/CD62P for Tauopathies. ROC confirmed good discriminatory performance, with CD56 emerging as the strongest single predictor for iRBD vs HC, SSEA4 showing high sensitivity for Late PD, and marker combinations providing optimal balance for Synucleinopathy/Tauopathy classification vs HC. In the CSF BioFIND subset, Late PD EVs exhibited increased myeloid (CD1c), adhesion (CD29), activation (CD69), and epithelial (CD326) markers compared to HC. Among these, CD326 was independently associated with Late PD diagnosis. Machine learning classifiers using all 37 surface antigens achieved excellent training performance (91.7-94.3% accuracy for iRBD/Synucleinopathies vs HC) and maintained robust validation accuracy, particularly for iRBD (77.8%) and DeNovo PD (76.6%) vs HC. EV immuno-phenotyping reveals distinct signatures across the neurodegenerative proteinopathies spectrum, with the highest diagnostic utility for prodromal iRBD detection. Longitudinal validation and cell-of-origin refinement represent key next steps toward clinical translation.

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.

Deep brain stimulation (DBS) of the subthalamic nucleus (STN) influences the sleep-wake cycle, yet in vivo evidence remains limited. We conducted a longitudinal, multimodal study in 38 patients with Parkinson's disease undergoing STN-DBS, integrating full-night video-polysomnography with synchronized subthalamic local field potentials (LFPs) 6 months post-surgery. Twenty patients completed pre/post video-polysomnography (19 with LFPs data). Slow-wave sleep increased after DBS, with no change of efficiency and fragmentation indices. Mean heart rate decreased in wake and sleep. REM-related motor events within REM sleep Behavior Disorder (RBD) declined, no change was seen in REM sleep without atonia (RSWA). LFPs showed delta/theta-band increase from wake to NREM and marked beta suppression in N2-N3. Arousals exhibited alpha/beta-band elevation. During REM, RSWA featured higher alpha/beta/gamma with lower delta versus atonic REM; RBD episodes further increased theta/beta/gamma and total power. These measures identify promising subcortical signatures of sleep and REM motor phenomena, informing sleep-aware adaptive DBS.

BACKGROUND:Sleep-related hypermotor epilepsy (SHE) and disorders of arousal (DoA) are two conditions that, despite originating from distinct etiological mechanisms, share the manifestation of complex motor behaviours emerging from sleep. Their overlapping clinical features have long posed challenges for differential diagnosis, particularly in adults. SUMMARY:Both SHE and DoA exhibit a close relationship with sleep physiology; consequently, increasing attention has recently been devoted to the neurophysiological mechanisms underlying these motor phenomena, with a specific focus on sleep microstructure and arousal system dynamics. K-complexes may play a key role in the onset of SHE seizures, as evidenced by the tendency of seizures to occur in quasi-periodic clusters at frequencies consistent with K-complexes and other physiological oscillations during light sleep. Analyses of the cyclic alternating pattern (CAP), an EEG marker of sleep instability, have shown that epileptic activity is not uniformly distributed across non-rapid eye movement sleep but is instead enhanced during specific CAP subtypes. A similar pattern has been observed in DoA, with episodes frequently arising during CAP phase A. The sleep instability observed in both SHE and DoA suggests that transient cortical activations may act as triggers for motor events, facilitating the expression of innate motor patterns through subcortical circuit activation. Although distinct in origin, physiological in DoA, and epileptic in SHE, both disorders reflect altered arousal regulation and disrupted cortical-subcortical interactions. KEY MESSAGES:This review aimed to provide an integrated neurophysiological perspective on SHE and DoA, emphasizing their distinctive mechanisms and the broader implications for understanding sleep-related motor behaviours.

Isolated REM Sleep Behavior Disorder (iRBD) is a well-recognized prodromal state of an underlying α-synucleinopathy, occurring several years before an overt neurodegenerative disorder becomes fully manifest. iRBD has been related to poorer cognitive performance and higher frequency of mild cognitive impairment (MCI). The aim of this study was to explore in detail, with structural and functional MRI, frontal-executive dysfunction in iRBD patients and to evaluate its association with cognitive performance. Thirty-two iRBD patients (24 males; age, mean±SD = 67.9±7.1 years) and thirty age-matched healthy controls were recruited and underwent an extensive neuropsychological assessment and multiparametric MR acquisition. The MR protocol (3T) included T1-w volumetric (isotropic 1mm 3 ), diffusion weighted imaging (b = 2000 s/mm 2 , 64 directions) and resting-state (TR = 0.735s, 10 minutes) acquisitions. Brain volumetry analysis was conducted using FreeSurfer. TBSS was applied to evaluate white matter microstructural alterations. Resting state networks were investigated with ICA. Correlations between MR parameters and neuropsychological variables were explored with Spearman’s test. iRBD patients, when compared with healthy controls, showed worse performance on tests related to attentive-executive, memory, and visuospatial functions (i.e., cancellation test p = 0.041, similarities p = 0.015, 15-words recall p = 0.004, and simple drawing copy p = 0.007); they also showed volume reduction in left rostral anterior cingulate (p = 0.005). TBSS highlighted increased anterior corpus callosum and forceps minor Radial Diffusivity in iRBD patients (p <0.05). Significant correlations were found between this alteration and executive dysfunctions (i.e. Stroop test, r = 0.46, p = 0.009). Moreover, fMRI data showed ‘Executive control’ network alteration in iRBD patients within cortical (i.e. superior and middle frontal gyrus, opercular cortex, paracingulate and precentral gyrus) and subcortical structures (i.e. putamen and caudate); these data correlated with worse performance in executive-attentive tests (i.e., cancellation time, r = -0.45, p = 0.018 and frontal assessment battery, r = 0.44, p = 0.023). This study showed that structural and functional frontal-executive alterations in iRBD patients are associated with attentive-executive functioning, findings that are similar to those observed in some synucleinopathies. Further studies with bigger samples and follow-ups are needed to confirm these results, and to monitor the trajectory of these alterations longitudinally. Acknowledgement : This study was supported by the Italian Ministry of Health (#GR-2019-12369242).

BACKGROUND:The sleep-wake cycle and the autonomic nervous system (ANS) can be impaired in neurodegenerative diseases. OBJECTIVES:To describe sleep-wake cycle and circadian rhythms of body core temperature (BcT) and cardiovascular parameters in Progressive Supranuclear Palsy (PSP). METHODS:We prospectively recorded 48 hour video-polysomnography, BcT and blood pressure (BP) in 14 PSP patients (disease duration 5.9 ± 2.6 years) under controlled environmental conditions. We analyzed wake-sleep parameters and state-dependent modulation for BcT, BP and heart rate from the last 24 h of recording. Twelve healthy younger controls were used for comparison. RESULTS:Patients slept less than 5 hours/night with frequent awakenings, daytime naps were shorter than 60 minutes and mainly represented by light sleep resulting in a 24 h sleep deprivation. Patients with PSP slept less compared to younger controls and normative values for age. Only two patients reported excessive daytime sleepiness. There were no significant differences in sleep parameters according to the presence of sleep disorders. Compared to controls, patients showed significantly higher BcT values during wake and sleep. Twelve patients presented an abnormal BP pattern at nighttime. CONCLUSION:PSP patients experienced profound sleep deprivation across the 24 h study period. An imbalance between sympathetic and parasympathetic function with sympathetic predominance may be associated with this alteration. Whether this autonomic dysfunction is the primary drive for the sleep-wake cycle disruption or the consequence of sleep loss needs to be elucidated.

BACKGROUND AND OBJECTIVES:Isolated REM sleep behavior disorder (iRBD) is a prodromal state of α-synucleinopathies, presenting years before overt neurodegenerative disorders. Autonomic nervous system (ANS) involvement, particularly cardiovascular autonomic failure, may indicate progression. However, its role as a (multidimensional) marker for disease progression and phenoconversion remains unclear. This study aimed to investigate whether cardiovascular autonomic failure and symptoms of autonomic dysfunction serve as multidimensional markers in patients with iRBD. METHODS:We conducted a prospective cohort study of patients with iRBD (iRBDs) and controls. Participants underwent cardiovascular reflex tests (CRTs) with beat-to-beat monitoring of blood pressure (BP) and ANS symptom assessments at baseline and annually. Primary outcomes were prevalence and progression of cardiovascular autonomic failure and the risk factors of phenoconversion. Longitudinal changes were evaluated through mixed-effects regression, predictors associated with conversion with Cox regression analysis. RESULTS:Sixty-four iRBDs (mean age 68.89 ± 6.75 years, 75% male) and 67 controls (66.57 ± 7.91 years, 68% male) were recruited. At baseline, iRBDs exhibited a prevalent sympathetic cardiovascular dysfunction, with more frequent neurogenic orthostatic hypotension (nOH in 9 iRBDs) and abnormal BP responses to CRTs (pathologic Valsalva maneuver [VM] overshoot in 27 iRBDs). Longitudinal data demonstrated progressive deterioration of sympathetic baroreflex function, with increased prevalence of nOH (7 iRBDs with incident nOH; yearly odds ratio [OR] = 2.44) and deterioration of parasympathetic cardiovagal function. Thirteen patients (20.3%) phenoconverted to α-synucleinopathies. Neurogenic OH (hazard ratio [HR] = 5.05), altered sympathetic baroreflex function (pathologic VM HR = 3.49), and blunted parasympathetic cardiovagal responses (pathologic deep breathing heart rate ratio HR = 3.27) were significant risk factors for phenoconversion; their early appearance 5 years from iRBD onset increased the conversion risk, up to 4-fold. Symptoms of autonomic failure were more prevalent in iRBD and deteriorated over time but failed to predict conversion. DISCUSSION:Progressive deterioration of cardiovascular autonomic function is a feature of iRBDs and affects the risk of phenoconversion. Limitations include the relatively short follow-up period and small number of converters. This study highlights the importance of objective cardiovascular autonomic testing as a multidimensional marker for risk stratification in iRBD.

Diagnosis of Parkinson’s disease (PD) remains challenging due to the lack of reliable biomarkers. To address this need, we quantified plasma levels of brain-specific c-Jun N-terminal kinase 3 (JNK3), a protein involved in neurodegeneration. A total of 108 participants were enrolled, including 25 individuals with isolated REM sleep behavior disorder (iRBD), 26 patients with De Novo PD, 29 with Late PD, and 28 age-matched healthy controls (HC). All subjects underwent clinical assessment, blood sampling, and skin biopsy. Plasma JNK3 levels were significantly elevated in PD and iRBD compared to HC, a finding that remained robust after adjustment for age and sex in multivariate logistic regression. ROC analysis demonstrated that JNK3 levels distinguished PD from HC with 100% specificity and 65% sensitivity in Late PD. In contrast, Neurofilament Light Chain showed non-significant group differences and weak discriminative performance. Notably, while JNK3 declined with age in HC, it increased with age in Late PD (P = 0.048, B = 0.105) and negatively correlated with motor impairment. Elevated JNK3 was also associated with pathological α-Synuclein in skin biopsy. These findings highlight JNK3 as a promising blood biomarker for PD, with meaningful diagnostic and prognostic value, suggesting that its implementation could refine patient stratification and improve clinical trial efficiency.

Restless legs syndrome (RLS) is a common sensorimotor disorder, and the most common sleep-related movement disorder with a prevalence of up to 15% in the European and US population. This review addresses key aspects of RLS, focusing on novel data that have or will likely have an impact on clinical practice. These include novel insights into pathophysiology and motor activity during sleep, with a key focus on implications for RLS treatment. Along this line, we discuss the problem of augmentation before introducing new treatment paradigms and insights into new drug targets from genetics. Besides RLS, restless sleep disorder, neck myoclonus, fragmentary myoclonus, propriospinal myoclonus at the wake-sleep transition, and facio-mandibular myoclonus are discussed. This review provides an overview of the most recent insights into sleep-related movement disorders, and of how they are changing clinical practice.

Patients with isolated rapid eye movement (REM) sleep behavior disorder (iRBD) are considered to be in the prodromal stage of alpha-synucleinopathy. They exhibit abnormal muscle activity during REM sleep and dream enactment. Currently, diagnosing iRBD requires an in-lab video-polysomnography (v-PSG), which involves manual and time-consuming analyses. In this study, we explore the feasibility of using a small and portable depth sensor to identify patients with iRBD, potentially enabling home-based assessments. Our study included 10 patients with iRBD, 10 patients with differential diagnoses of RBD, and 5 control subjects. Depth data were recorded simultaneously with v-PSG. After preprocessing to remove noise, we tested various temporal, spatiotemporal convolutional kernels, and dense optical flow to generate motion maps from depth data. Movements were then automatically detected during REM and non-REM sleep, and relevant features were extracted. Logistic regression models with leave-one-subject-out cross-validation were used to discriminate patients with iRBD, with performance evaluated based on the area under the curve (AUC). The highest AUC (0.900) was achieved when analyzing REM and non-REM sleep movements, using a convolutional kernel to detect fast movements. High performance (AUC = 0.893) was also observed when using features from movements in REM sleep identified with a spatiotemporal kernel. Although not achieving as high performance as when using movements annotated by experts (AUC of 0.993), our findings support the feasibility of using a small, portable depth sensor for the automatic detection of patient movements and the reliable identification of patients with iRBD.Clinical relevance— The proposed approach has the potential to be implemented in home environments to detect patients with iRBD, enabling faster and more objective identification.

The evolution from nocturnal paroxysmal dystonia (NPD) to sleep-related hypermotor epilepsy (SHE) is a complex and fascinating journey, marked by numerous twists and discoveries.1 This topic was recently reviewed by Fotedar and Luders,2 who erroneously concluded that SHE is not an identifiable focal epilepsy syndrome as they believed that it is based on weak evidence. We wish to address errors in their analysis and offer a more balanced understanding of this important form of epilepsy. The authors2review more than 40 years of history largely through a lens based on electrophysiology and pre-surgical evaluation. They challenge the epileptic origin of SHE, previously termed nocturnal frontal lobe epilepsy (NFLE), now recognized as a well-characterized entity 3. Their chronological reconstruction, more comprehensively addressed in previous works,1, 4 seems arbitrary and incomplete, omitting key studies that have contributed significantly to the understanding of the epileptic origin of the syndrome. In particular, even before the debates on the true nature of NPD began, others had observed episodes similar to NPD in patients with confirmed epilepsy. From the 1970s, authorities in North America began to define frontal lobe epilepsy (nocturnal and diurnal), often misdiagnosed as psychiatric in origin (Figure 1).3, 5-18 The historical reconstruction presented in the review2 is also incomplete in its identification of three eras marked by landmark studies (1972–1993, 1994–1998, 1999 to present), paying cursory attention to a crucial event: the Consensus Conference in Bologna,17 which established diagnostic criteria for the syndrome (Table 1). The syndrome was subsequently accepted by the International League Against Epilepsy (ILAE) Commission on Terminology.3 The consensus conference method is recommended for addressing important clinical questions in the face of limited high-quality evidence. The main outcome, a consensus statement, represents the collective opinions of an expert panel, derived from systematic review and discussion of available evidence.19 The Bologna Consensus Conference was planned and completed between November 2013 and September 2014, using rigorous methods addressing conditions with limited evidence, such as rare diseases (see online appendix in Tinuper et al.17 for details). The final definition of the condition was reached through a transparent process that included predefined research questions, a systematic review for each question, an independent systematic mapping of the evidence,20 an assessment of the literature's quality with reliable tools,21, 22 and an open, structured debate of 2 days involving a workgroup of experts for each the three main topics (clinical history; electro-clinical features; etiologic and pathogenic background) and a multidisciplinary international panel jury including specialists in child and adult epilepsy, sleep medicine, neurosurgery, genetics, epidemiology, and research methodology. The analysis explicitly covered all controversies and gray areas highlighted by Fotedar and Luders2 (e.g., absence of a clear ictal rhythm does not exclude an epileptic origin, not all seizures in SHE are frontal in origin, and so on). Fotedar and Luders correctly delineate the change in terminology over decades but failed to note that terms such as paroxysmal arousal (PA),23 epileptic nocturnal wandering (ENW),24 and minor motor episodes or events (MMEs)25, 26 – have been long since abandoned.3, 17 We agree that not all episodes previously reported under the term "NPD" are unequivocally epileptic. However, there is robust evidence for an epileptic basis in many cases, based on consistent hypermotor seizure semiology observed in the same patient, both within the same night and over the years, supported by anatomo-electro-clinical data in some. The evolution of seizures with the same semiological onset but varying duration has led to seemingly distinct descriptors, ranging from very brief motor attacks (brief) to hypermotor seizures sometimes followed by prolonged complex ambulatory behavior (long). These have been subsequently recognized as part of the clinical spectrum of seizures in SHE, both within and between patients.1 Fotedar and Luders express frustration that influential neurologists in the mid-1990s led the community to believe that epilepsy was the basis for most sleep-related paroxysmal motor episodes.14-16 They argued that all of these episodes were automatically assumed to be seizures and alternative diagnoses were often dismissed. This was never the case. Indeed, it is essential to recognize the extensive work that was done to clarify the differential diagnosis between sleep-related seizures and other sleep disorders (e.g., parasomnias), which remains a challenging but critical distinction. In that period, in addition to further electroclinical studies, diagnostic tools such as questionnaires and algorithms were developed, to aid clinicians in minimizing diagnostic errors in either direction, assessing the diagnostic accuracy of semiological patterns observed on video27 or reported on clinical history.28-33 Fotedar and Luders emphasize that the frequency of definitive interictal epileptiform changes on the electroencephalography (EEG) recordings of pre-surgical SHE cases is considerably higher than that seen in familial cases of SHE and even in a series of sporadic cases. We agree with this observation, which is likely an artifact of ascertainment bias, EEG recording time, and etiology. Pre-surgical cases are studied because they are drug resistant and typically have days or weeks of day and night video-EEG monitoring, and may have lesions. Milder cases, especially those in families, may have a single routine EEG and may be in remission at the time they are evaluated and are typically non-lesional.15 The absence of ictal and interictal epileptiform abnormalities does not exclude a diagnosis of SHE, in severe cases (concentrated in surgical series) or milder ones. In surgical series, it is widely recognized that co-registration of the scalp and stereo EEG (SEEG) can show surprisingly little abnormality on scalp EEG even when SEEG is very active (Figure 2). The authors cite (Figure 2 in ref.2) a case with PAs16 to support their criticism that many of the published NPD cases lacked definitive ictal/interictal epileptiform changes. PAs, frequently occurring in patients with SHE, are characterized by abrupt trunk and limb movements that can resemble simple motor sleep phenomena and exhibit a pseudoperiodic pattern linked to K-complex bursts or Cyclic Alternating Pattern (CAP) recurrence.1 However, the Consensus Conference deemed PAs insufficient for diagnosing SHE due to their controversial nature, inconsistent nomenclature across SHE study groups, and the risk of unreliable clinical diagnosis when only minor motor events or few episodes are captured.1, 17 We also note the attempts by Fotedar and Luders to reinterpret EEG tracings from older publications, especially given the challenges of analyzing published figures, rather than the whole recording. We do not wish to address every critique related to interpretations of EEG records from the 1990s, but we want to highlight one specific case—figure 42 – which the authors cited as a paradigmatic example of "overreading." Although we will not delve into the objections about this EEG tracing (whose quality understandably falls short of 2024 standards), we would like to point out that the patient in question carried a pathogenic KCNT1 variant (Figure 2, Family B, subject III.2 in Heron et al.34). This patient subsequently underwent epilepsy surgery involving resection of the right mesiolateral frontal region, with histopathology confirming the presence of focal cortical dysplasia (Figure 1, Family B, subject III.2).35 Furthermore, the authors propose that epileptic sleep-related paroxysmal motor events require the presence of a magnetic resonance imaging (MRI) lesion (table 1 in ref.2). However, even with advances in MRI techniques, 40%–50% of patients with SHE have negative MRIs in surgical series of drug-resistant patients.18, 36 Fotedar and Luders point out that many of the cases of SHE may have originated outside the frontal lobe. This has been well recognized by many groups and emphasized at the Consensus Conference and, precisely for this reason, led to the change of name from NFLE to SHE.17 It is well established that up to 30% of patients with hypermotor seizures, once categorized as the hallmark of NFLE, actually have seizures originating from extrafrontal regions.17 Seizures may arise in areas including the insula,37 midline parietal cortex,38 and other regions.18, 39 Therefore, revisiting this well-established point adds little value to their article. In the initial part of their "critical review," Fotedar and Luders disingenuously imply that the finding of CHRNA4 pathogenic variants was not replicated. Their review of molecular genetics is outdated, incomplete, and inaccurate. For CHRNA4, its pathogenic role in SHE is cemented by identification in both families and de novo cases, in individuals of European, Lebanese, and Japanese ethnicities.40-42 Multiple groups over the last three decades have confirmed the presence of autosomal dominant pathogenic variants in a range of genes including those encoding nicotinic subunits (CHRNA4, CHRNB2, and CHRNA2), mechanistic target of rapamycin (mTOR) pathway proteins (DEPDC5, NPRL2, and NPRL3) and potassium sodium-activated channel subunit (KCNT1) (Table 2).34, 43-47 In a series of 103 SHE cases, 19% of familial and 7% of sporadic cases had a pathogenic variant in an established SHE gene.48 The mTOR pathway genes are sometimes associated with structural malformations visible on MRI and may be included in surgical series.49, 50 nAChRs genes43 CHRNA4 CHRNB2 CHRNA2 Cholinergic Receptor Nicotinic Alpha 4 Subunit Cholinergic Receptor Nicotinic Beta 2 Subunit Cholinergic Receptor Nicotinic Alpha 2 Subunit 20q13.33 1q21.3 8p21.2 AD AD AD MIM*118504 MIM*118507 MIM*118502 GATOR-1 genes DEPDC5 44, 45 NPRL2 46 NPRL3 47 DEP Domain Containing 5 NPR2- like Protein Nitrogen Permease Regulator-like 3 22q12.2-q12.3 3p21.31 16p13.3 AD AD AD MIM*614191 MIM*607072 MIM*600928 The authors later try to disconnect the molecular findings from the epileptology, implying that these validated genetic variants are associated with non-specific sleep-related paroxysmal motor episodes, rather than with SHE. The clinical relationship of SHE to parasomnias remains poorly understood but, at this time, there is no evidence associating these genes with other familial sleep disorders.51 There are several reports of patients with pathogenic variants in CHRNA4, clinical features of SHE, and ictal epileptiform changes48 including one case with SEEG documenting a widespread epileptogenic network (case 352). The same findings have been reported for a few patients with germ-line pathogenic variants in the mTOR pathway genes.53 Overlooking this well-supported evidence disregards significant advancements in understanding the genetic underpinnings of epilepsy. The authors proposed a four-dimensional classification system for paroxysmal motor sleep episodes based on semiology, naming the new entity "sleep-related paroxysmal motor episodes" (SPME). We believe that this definition lacks both clarity and utility in the terms required by current scientific standards for defining new diagnostic criteria (e.g., prognostic ability, reproducibility, accuracy, and favorable balance between benefits and harms in applying the new definition).54 The implications of not differentiating epileptic seizures from other sleep-related motor phenomena, resulting in incorrect diagnosis and management, are potentially dangerous in terms of morbidity, mortality risk, and impact on quality of life. In conclusion, although we certainly welcome continued discourse on SHE, it is important that these discussions be grounded in comprehensive, up-to-date evidence and not a rehash of debates that have long been resolved. We thank Dr. Lorenzo Ferri and Giulia Bruschi for their assistance in preparing the figures and Dr. Anna Scarabello and Dr. Lorenzo Muccioli for their contributions to the editing of the manuscript and the bibliographic review. Open access publishing facilitated by The University of Melbourne, as part of the Wiley - The University of Melbourne agreement via the Council of Australian University Librarians. We confirm that we have read the Journal's position on issues involved in ethical publication and affirm that this report is consistent with those guidelines. Francesca Bisulli has served on scientific advisory boards for Jazz, Takeda Pharmaceuticals, Ethypharm, and UCB; has received speaker honoraria from Angelini, UCB, Jazz, and Eisai; has received funding for travel from Jazz, Eisai, Angelini, and UCB; has served as an investigator for UCB, Ultragenyx, Xenon Pharmaceuticals, Zogenix, and Zynerba; and has consulted for Xenon Pharmaceuticals and Takeda Pharmaceuticals. Samuel F. Berkovic has received unrestricted educational grants to his institution from UCB Pharma, Eisai, SEER, Chiesi, and LivaNova. He has served as a consultant for Praxis Precision Medicines and has received personal honoraria for lectures and presentations from Eisai and DeltaMed. He holds a patent on methods of treatment and diagnosis of epilepsy by detecting mutations in the SCN1A gene, which is held by Bionomics Inc. and licensed to Athena Diagnostics and Genetics Technologies Ltd., with institutional royalties. He serves as Chief Medical Officer for the Epilepsy Foundation (Victoria). Ingrid Scheffer has served on scientific advisory boards for BioMarin, Chiesi, Eisai, Encoded Therapeutics, GlaxoSmithKline, Knopp Biosciences, Nutricia, Takeda Pharmaceuticals, UCB, Xenon Pharmaceuticals, and Longboard Pharmaceuticals; has received speaker honoraria from GlaxoSmithKline, UCB, BioMarin, Biocodex, Chiesi, LivaNova, Nutricia, Zuellig Pharma, Stoke Therapeutics, Eisai, Akumentis, and Praxis; has received funding for travel from UCB, Biocodex, GlaxoSmithKline, Biomarin, Encoded Therapeutics, Stoke Therapeutics, Eisai, and Longboard Pharmaceuticals; has served as an investigator for Anavex Life Sciences, Cerevel Therapeutics, Eisai, Encoded Therapeutics, EpiMinder Inc., Epygenyx, ES-Therapeutics, GW Pharma, Longboard Pharmaceuticals, Marinus, Neurocrine BioSciences, Ovid Therapeutics, SK Life Science, Takeda Pharmaceuticals, UCB, Ultragenyx, Xenon Pharmaceuticals, Zogenix, and Zynerba; has consulted for Care Beyond Diagnosis, Epilepsy Consortium, Atheneum Partners, Ovid Therapeutics, UCB, Zynerba Pharmaceuticals, BioMarin, Encoded Therapeutics, Biohaven Pharmaceuticals, Stoke Therapeutics, Praxis; and is a Non-Executive Director of Bellberry Ltd. and a Director of the Australian Academy of Health and Medical Sciences. She may accrue future revenue on a pending patent WO61/010176 (filed: 2008): Therapeutic Compound; has a patent for SCN1A testing held by Bionomics Inc. and licensed to various diagnostic companies; and has a patent molecular diagnostic/theranostic target for benign familial infantile epilepsy (BFIE) [PRRT2] 2011904493 & 2 012 900 190 and PCT/AU2012/001321 (TECH ID:2012–009). Eduard Hirsch, Lino Nobili, Federica Provini, Paolo Tinuper, and Luca Vignatelli declare no disclosures related to this paper. Data sharing is not applicable to this article as no datasets were generated or analyzed.