Davide Caputo

Objective: Lafora disease (LD) and Unverricht–Lundborg disease (EPM1A) are the most common forms of progressive myoclonic epilepsy and are frequently associated with photosensitivity and photic reflex myoclonus (PRM). This study aimed to characterize the photoparoxysmal response (PPR), evaluate the effect of blue lenses, and explore the neural networks underlying PPR and PRM in both conditions. Methods: Twenty‐six patients with LD and 51 with EPM1A were included. PPR was assessed on the first available electroencephalogram (EEG), including background activity and the presence and distribution of interictal epileptiform discharges, which were compared between groups. A subset of patients underwent back‐averaging analysis using 1‐Hz flash stimuli as triggers, allowing identification of the principal components of flash‐evoked responses. Results: PPR was detected in 85% of LD patients and 33% of EPM1A patients ( p < .001). Compared with EPM1A, LD patients more often showed focal seizures with visual symptoms, slower EEG background activity, and a higher presence of focal epileptiform abnormalities over the posterior regions. In both groups, PPR was mainly Waltz type 4 at 14–15 Hz and was associated with PRM in approximately half of the cases. However, in LD, the PPR latency from stimulus onset was shorter, and sensitivity to blue lenses was significantly lower. Compared with healthy controls, both patient groups exhibited increased amplitude and prolonged latency of the flash‐evoked responses. Significance: Photosensitivity is more frequent and severe in LD than in EPM1A and is associated with electrophysiological markers of occipital cortex hyperexcitability. The shorter PPR latency in LD suggests an intrinsic predisposition to generate PPR immediately after visual input, possibly related to a lack of inhibitory mechanisms. The frequent occurrence of PRM in both conditions reflects aberrant large‐scale network dynamics involving cortical and subcortical structures rather than pure occipital cortex dysfunction.

Periventricular nodular heterotopia (PVNH) is a genetically heterogeneous malformation of cortical development with variable neurological outcomes. Among recessive forms, ARFGEF2-related disorder is uniquely characterised by the association of diffuse PVNH and progressive microcephaly. We describe a two-year-old boy born to consanguineous parents who presented with severe developmental delay, hypotonia, progressive microcephaly, and infantile-onset epileptic spasms with developmental regression. Brain MRI showed extensive bilateral PVNH associated with callosal hypoplasia and ventriculomegaly. EEG revealed dysmature background activity with multifocal epileptiform discharges and runs of asynchronous fast activity during sleep. Genetic testing identified a novel homozygous nonsense variant in ARFGEF2. The clinical course was characterised by drug-resistant epilepsy and multisystemic involvement, including feeding difficulties and recurrent respiratory infections. To contextualise this case, we performed a comprehensive review of previously reported patients, further delineating the clinical, neuroradiological, and electroclinical spectrum of ARFGEF2-related disorder. This case highlights progressive microcephaly as a key distinguishing feature of ARFGEF2-related PVNH and underscores the importance of early genetic diagnosis to guide targeted surveillance for extra-CNS complications and multidisciplinary care.

Background: Hyperkinetic movement disorders (MDs) in children, including tremor, myoclonus, dystonia, chorea, and tics, often present with overlapping or evolving clinical features, making classification based on observation alone challenging. Neurophysiological techniques such as video-EEG polymyography (P-VEEG) and somatosensory evoked potentials (SEPs) may provide objective markers to improve diagnostic accuracy, yet their application in pediatric populations remains limited. Objective: To describe the polygraphic characteristics of hyperkinetic MDs in a large pediatric cohort and to assess whether specific EMG patterns can support movement disorder classification beyond clinical inspection. Methods: Seventy-three patients with pediatric-onset hyperkinetic MDs underwent standardized P-VEEG recordings and SEPs at Besta Neurological Institute between January and October 2024. EMG activity was recorded from antagonist muscle pairs during rest, posture maintenance, and specific tasks according to age. Polygraphic findings were compared with clinical diagnoses. Associations between EMG patterns and clinical variables were analyzed using Chi-square tests and regression analyses. Results: Mean age at MD onset was 9.4 ± 6.1 years and mean age at recording was 13.5 ± 5.1 years. Polygraphic analysis identified four distinct EMG patterns: (i) regular rhythmic oscillatory pattern (RRO), consistent with tremor, in 40 patients (56%); (ii) repetitive myoclonic pattern (RM) in 11 (15%); (iii) complex mixed repetitive pattern (CR) in 9 (12%); and (iv) complex non-rhythmic pattern (CNR), encompassing chorea, dystonia, tics and other dyskinesias, in 11 (15%). Significant differences among repetitive patterns were observed in rhythmicity ( p < 0.001), burst duration ( p < 0.001), agonist–antagonist synchrony ( p < 0.001), and SEP hyperexcitability ( p < 0.03). RM was significantly associated with enhanced amplitude SEPs ( p = 0.023), supporting a cortical origin of myoclonus in most cases. A significant association between clinical diagnosis and EMG pattern was found ( p = 0.003), yet discrepancies between clinical and polygraphic classification was found in 22 cases (30%), particularly among tremor and myoclonus presentations. RM and CR were prevalent in older patients compared with CNR. Conclusion: P-VEEG proved to be an easily applicable tool providing valuable objective markers for the characterization of pediatric hyperkinetic MDs, revealing distinct EMG patterns that complement clinical evaluation and improve diagnostic precision. Systematic integration of neurophysiological assessment may enhance classification, diagnostic accuracy and help guide management in childhood movement disorders.

Objective: To characterize the clinical, electroencephalographic, and genetic features of epilepsies featuring absence seizures within monogenic etiology, highlighting the diagnostic, treatment and prognostic implications. Methods: We conducted a retrospective, multicenter study including patients with monogenic epilepsies and electroencephalography (EEG)–documented absence seizures. We analyzed clinical data, electroclinical findings, neurodevelopmental outcomes, and treatment responses through standardized questionnaires and medical records. We classified genetic variants according to American College of Medical Genetics and Genomics (ACMG) guidelines and performed univariate and multivariate analyses to identify predictors of developmental outcomes. Results: We included 160 patients (111 female; median age at last follow‐up: 13 years) with absence seizures and confirmed pathogenic or likely pathogenic monogenic variants. The most frequently implicated genes were SLC2A1, SLC6A1, SYNGAP1 , CHD2, and SCN1A . Four genes— HESX1, NCKAP1, SON, STARD9 —had not been previously associated with absence seizures. In 35% of patients, absence seizures were the only seizure type and in 67% were the initial manifestation. Atypical features included irregular EEG discharges (56%) eyelid myoclonia (42%), and automatisms (33%). Early‐onset (before age 3) seizures occurred in 58% and was significantly associated with atypical features ( p < .03). Using existing International League Against Epilepsy (ILAE) epilepsy syndrome classification, 60% of patients could not be classified. Developmental delay occurred in 54%, intellectual disability in 65%, and other neurodevelopmental comorbidities in 49%. Predictors of poor developmental outcomes included early developmental delay, drug‐resistant epilepsy, and early absence onset. We found no difference in the prevalence of drug resistance across the various genetic etiologies. The most effective medications for absence seizures included valproate, ethosuximide, benzodiazepines, and lamotrigine. Disease‐specific therapies (e.g., ketogenic diet in SLC2A1 , stiripentol/fenfluramine in SCN1A) were effective in select cases. Significance: Absence seizures are a common manifestation of different monogenic epilepsies, often associated with early onset, atypical clinical and/or EEG features, developmental delay or drug resistance. Classification models should incorporate genetic data alongside electroclinical features, especially as next‐generation sequencing is increasingly used.

Objective: Conditions presenting with both epilepsy and movement disorders (EPIMDs) range from relatively benign cases to severe developmental encephalopathies. However, the full clinical and genetic spectrum still needs to be better defined. The aim of this study is to describe the presentation of EPIMDs in pediatric patients with known genetic etiologies, correlating these features with age at onset and underlying pathological mechanisms to identify patterns that could improve patient management. Methods: We retrospectively analyzed the clinical records of pediatric patients who underwent genetic testing for EPIMDs at our institution between 2009 and 2022. Genetic testing included single‐gene Sanger sequencing, multigene next‐generation sequencing panels targeting epilepsy and/or MDs, and array comparative genome hybridization. Demographic, clinical, and electroencephalography (EEG) data were collected. Statistical analyses were conducted using multivariate and cluster analyses. Results: A total of 97 subjects were included. The mean age ± SD at epilepsy onset was 3.6 ± 4.4 years, whereas the mean age at MD onset was 5.2 ± 4.9 years. Based on the mechanism of genetic dysfunction, we identified six groups: transportopathies ( n = 18), synaptopathies ( n = 11), channelopathies ( n = 18), metabolic disorders ( n = 15), intracellular trafficking defects ( n = 8), and unknown/complex function disorders ( n = 27). Cluster analysis identified three distinct groups: (1) early‐onset epilepsy and paroxysmal MDs with normal intelligence quotient (IQ) and mild intellectual disability, associated with transportopathies ( n = 38); (2) early‐onset epilepsy with dystonia and myoclonus, low IQ, and developmental and epileptic encephalopathy, associated with channelopathies ( n = 31); (3) epilepsy onset between 1 and 5 years of age with developmental delay, parkinsonism, and low IQ, associated with metabolic etiology ( n = 26). Significance: Our study demonstrates that, despite the phenotypic and genetic pleiotropy observed in EPIMDs, a precise characterization of semiological and cognitive features remains essential to support variant interpretation and to refine the diagnostic process and patient management in these rare conditions.

Sigma power and sleep spindles are key elements of Non‐Rapid Eye Movement (NREM) sleep. They reflect anatomical and physiological properties of brain circuits, are linked with various behavioral outcomes in typically development (TD) children, and undergo significant modifications during development. Furthermore, recent studies have highlighted the potential of NREM sigma power and sleep spindles as early neurophysiological markers for autism spectrum disability (ASD). Here, we conducted polysomnography (PSG)/EEG recordings during afternoon naps on 50 children aged between 2 and 6 years, diagnosed with ASD or TD. EEG recordings from 19 scalp leads were analyzed, focusing on sigma power and sleep spindle parameters. EEG analyses revealed significant differences in power spectral density between ASD and TD children, particularly in the sigma band and adjacent alpha and beta bands, with increased power localized to anterior EEG leads in ASD children. Higher spindle amplitude and integrated spindle activity (ISA) were found in the ASD group, especially in frontal regions. Additional frequency‐specific analyses (10–12 Hz, 12–14 Hz, 14–16 Hz) confirmed significant differences in spindle amplitude and distribution patterns, emphasizing the role of brain regions that are detectable from anterior EEG leads in ASD‐related sleep abnormalities. No significant differences were found in spindle density, duration, or frequency outside specific clusters. These findings indicate that some sleep spindle parameters, particularly in frontal areas, are altered in ASD. The study highlights the feasibility of using afternoon nap PSG as a practical and effective method to detect these abnormalities in clinical settings. Future research should investigate the developmental trajectory of spindles in ASD and their potential role as neurophysiological biomarkers, offering valuable insights for diagnosis and prognosis.