Correlation between autistic traits and brain functional connectivity in preschoolers with autism spectrum disorder: a resting state MEG study.

BACKGROUND: Neurophysiological studies recognized that Autism Spectrum Disorder (ASD) is associated with altered patterns of over- and under-connectivity. However, little is known about network organization in children with ASD in the early phases of development and its correlation with the severity of core autistic features. METHODS: The present study aimed at investigating the association between brain connectivity derived from MEG signals and severity of ASD traits measured with different diagnostic clinical scales, in a sample of 16 children with ASD aged 2 to 6 years. RESULTS: A significant correlation emerged between connectivity strength in cortical brain areas implicated in several resting state networks (Default mode, Central executive, Salience, Visual and Sensorimotor) and the severity of communication anomalies, social interaction problems, social affect problems, and repetitive behaviors. Seed analysis revealed that this pattern of correlation was mainly caused by global rather than local effects. CONCLUSIONS: The present evidence suggests that altered connectivity strength in several resting state networks is related to clinical features and may contribute to neurofunctional correlates of ASD. Future studies implementing the same method on a wider and stratified sample may further support functional connectivity as a possible biomarker of the condition.

Early cortico-muscular coherence and cortical network changes in Parkinson's patients treated with MRgFUS.

Introduction: To investigate cortical network changes using Magnetoencephalography (MEG) signals in Parkinson's disease (PD) patients undergoing Magnetic Resonance-guided Focused Ultrasound (MRgFUS) thalamotomy. Methods: We evaluated the MEG signals in 16 PD patients with drug-refractory tremor before and after 12-month from MRgFUS unilateral lesion of the ventralis intermediate nucleus (Vim) of the thalamus contralateral to the most affected body side. We recorded patients 24 h before (T0) and 24 h after MRgFUS (T1). We analyzed signal epochs recorded at rest and during the isometric extension of the hand contralateral to thalamotomy. We evaluated cortico-muscular coherence (CMC), the out-strength index from non-primary motor areas to the pre-central area and connectivity indexes, using generalized partial directed coherence. Statistical analysis was performed using RMANOVA and post hoct-tests. Results: Most changes found at T1 compared to T0 occurred in the beta band and included: (1) a re-adjustment of CMC distribution; (2) a reduced out-strength from non-primary motor areas toward the precentral area; (3) strongly reduced clustering coefficient values. These differences mainly occurred during motor activation and with few statistically significant changes at rest. Correlation analysis showed significant relationships between changes of out-strength and clustering coefficient in non-primary motor areas and the changes in clinical scores. Discussion: One day after MRgFUS thalamotomy, PD patients showed a topographically reordered CMC and decreased cortico-cortical flow, together with a reduced local connection between different nodes. These findings suggest that the reordered cortico-muscular and cortical-networks in the beta band may represent an early physiological readjustment related to MRgFUS Vim lesion.

Myoclonus: Differential diagnosis and current management.

Myoclonus classically presents as a brief (10-50 ms duration), non-rhythmic jerk movement. The etiology could vary considerably ranging from self-limited to chronic or even progressive disorders, the latter falling into encephalopathic pictures that need a prompt diagnosis. Beyond the etiological classification, others evaluate myoclonus' body distribution (i.e., clinical classification) or the location of the generator (i.e., neurophysiological classification); particularly, knowing the anatomical source of myoclonus gives inputs on the observable clinical patterns, such as EMG bursts duration or EEG correlate, and guides the therapeutic choices. Among all the chronic disorders, myoclonus often presents itself as a manifestation of epilepsy. In this context, myoclonus has many facets. Myoclonus occurs as one, or the only, seizure manifestation while it can also present as a peculiar type of movement disorder; moreover, its electroclinical features within specific genetically determined epileptic syndromes have seldom been investigated. In this review, following a meeting of recognized experts, we provide an up-to-date overview of the neurophysiology and nosology surrounding myoclonus. Through the dedicated exploration of epileptic syndromes, coupled with pragmatic guidance, we aim to furnish clinicians and researchers alike with practical advice for heightened diagnostic management and refined treatment strategies. PLAIN LANGUAGE SUMMARY: In this work, we described myoclonus, a movement characterized by brief, shock-like jerks. Myoclonus could be present in different diseases and its correct diagnosis helps treatment.

Novel lissencephaly-associated NDEL1 variant reveals distinct roles of NDE1 and NDEL1 in nucleokinesis and human cortical malformations.

The development of the cerebral cortex involves a series of dynamic events, including cell proliferation and migration, which rely on the motor protein dynein and its regulators NDE1 and NDEL1. While the loss of function in NDE1 leads to microcephaly-related malformations of cortical development (MCDs), NDEL1 variants have not been detected in MCD patients. Here, we identified two patients with pachygyria, with or without subcortical band heterotopia (SBH), carrying the same de novo somatic mosaic NDEL1 variant, p.Arg105Pro (p.R105P). Through single-cell RNA sequencing and spatial transcriptomic analysis, we observed complementary expression of Nde1/NDE1 and Ndel1/NDEL1 in neural progenitors and post-mitotic neurons, respectively. Ndel1 knockdown by in utero electroporation resulted in impaired neuronal migration, a phenotype that could not be rescued by p.R105P. Remarkably, p.R105P expression alone strongly disrupted neuronal migration, increased the length of the leading process, and impaired nucleus-centrosome coupling, suggesting a failure in nucleokinesis. Mechanistically, p.R105P disrupted NDEL1 binding to the dynein regulator LIS1. This study identifies the first lissencephaly-associated NDEL1 variant and sheds light on the distinct roles of NDE1 and NDEL1 in nucleokinesis and MCD pathogenesis.

Anatomically compliant modes of variations: New tools for brain connectivity.

Anatomical complexity and data dimensionality present major issues when analysing brain connectivity data. The functional and anatomical aspects of the connections taking place in the brain are in fact equally relevant and strongly intertwined. However, due to theoretical challenges and computational issues, their relationship is often overlooked in neuroscience and clinical research. In this work, we propose to tackle this problem through Smooth Functional Principal Component Analysis, which enables to perform dimensional reduction and exploration of the variability in functional connectivity maps, complying with the formidably complicated anatomy of the grey matter volume. In particular, we analyse a population that includes controls and subjects affected by schizophrenia, starting from fMRI data acquired at rest and during a task-switching paradigm. For both sessions, we first identify the common modes of variation in the entire population. We hence explore whether the subjects' expressions along these common modes of variation differ between controls and pathological subjects. In each session, we find principal components that are significantly differently expressed in the healthy vs pathological subjects (with p-values < 0.001), highlighting clearly interpretable differences in the connectivity in the two subpopulations. For instance, the second and third principal components for the rest session capture the imbalance between the Default Mode and Executive Networks characterizing schizophrenia patients.

Case report: SLC6A1 mutations presenting with isolated absence seizures: description of 2 novel cases.

We report the clinical and EEG data of two patients harboring heterozygous SLC6A1 mutations, who presented with typical absence seizures at 3 Hz spike and wave as well as with mild cognitive disability. Neuroradiological and other laboratory investigations were normal. Our observations suggest that SLC6A1 mutations can be suspected in children with typical absences as the only seizure type, especially if associated with, even mild, cognitive deficits.

Cortico-muscular coherence and brain networks in familial adult myoclonic epilepsy and progressive myoclonic epilepsy.

OBJECTIVE: Familial Adult Myoclonic Epilepsy (FAME) presents with action-activated myoclonus, often associated with epilepsy, sharing various features with Progressive Myoclonic Epilepsy (PMEs), but with slower course and limited motor disability. We aimed our study to identify measures suitable to explain the different severity of FAME2 compared to EPM1, the most common PME, and to detect the signature of the distinctive brain networks. METHODS: We analyzed the EEG-EMG coherence (CMC) during segmental motor activity and indexes of connectivity in the two patient groups, and in healthy subjects (HS). We also investigated the regional and global properties of the network. RESULTS: In FAME2, differently from EPM1, we found a well-localized distribution of beta-CMC and increased betweenness-centrality (BC) on the sensorimotor region contralateral to the activated hand. In both patient groups, compared to HS, there was a decline in the network connectivity indexes in the beta and gamma band, which was more obvious in FAME2. CONCLUSIONS: In FAME2, better localized CMC and increased BC in comparison with EPM1 patients could counteract the severity and the spreading of the myoclonus. Decreased indexes of cortical integration were more severe in FAME2. SIGNIFICANCE: Our measures correlated with different motor disabilities and identified distinctive brain network impairments.

Rhythmic cortical myoclonus in patients with 6Q22.1 deletion.

DNA deletions involving 6q22.1 region result in developmental encephalopathy (DE), often associated with movement disorders and epilepsy. The phenotype is attributed to the loss of the NUS1 gene included in the deleted region. Here we report three patients with 6q22.1 deletions of variable length all showing developmental delay, and rhythmic cortical myoclonus. Two patients had generalized seizures beginning in infancy. Myoclonic jerks had polygraphic features consistent with a cortical origin, also supported by cortico-muscular coherence analysis displaying a significant peak around 20 Hz contralateral to activated segment. Deletions in 6q22.1 region, similarly to NUS1 loss-of-function mutations, give rise to DE and cortical myoclonus via a haploinsufficiency mechanism. A phenotype of progressive myoclonic epilepsy (PME) may also occur.

IRF2BPL: A new genotype for progressive myoclonus epilepsies.

The progressive myoclonus epilepsies (PMEs) are a heterogeneous group of neurodegenerative disorders, typically presenting in late childhood. An etiologic diagnosis is achieved in about 80% of patients with PME, and genome-wide molecular studies on remaining, well-selected, undiagnosed cases can further dissect the underlying genetic heterogeneity. Through whole-exome sequencing (WES), we identified pathogenic truncating variants in the IRF2BPL gene in two, unrelated patients presenting with PME. IRF2BPL belongs to the transcriptional regulators family and it is expressed in multiple human tissues, including the brain. Recently missense and nonsense mutations in IRF2BPL were found in patients presenting with developmental delay and epileptic encephalopathy, ataxia, and movement disorders, but none with clear PME. We identified 13 other patients in the literature with myoclonic seizures and IRF2BPL variants. There was no clear genotype-phenotype correlation. With the description of these cases, the IRF2BPL gene should be considered in the list of genes to be tested in the presence of PME, in addition to patients with neurodevelopmental or movement disorders.

Differential diagnosis of familial adult myoclonic epilepsy.

OBJECTIVE: Familial adult myoclonic epilepsy (FAME) is an under-recognized disorder characterized by cortical myoclonus, generalized tonic-clonic seizures, and additional clinical symptoms, which vary depending on the FAME subtype. FAME is caused by pentanucleotide repeat expansions of intronic TTTCA/TTTTA in different genes. FAME should be distinguished from a range of differential diagnoses. METHODS: The differential diagnoses and frequent presentations leading to misdiagnosis of FAME were investigated from the available literature and reported based on an expert opinion survey. RESULTS: The phenotypic features of FAME, including generalized tonic-clonic and myoclonic seizures, are also seen in other epilepsy syndromes, such as juvenile myoclonic epilepsy, with a resultant risk of misdiagnosis and lack of identification of the underlying cause. Cortical myoclonus may mimic essential tremor or drug-induced tremor. In younger individuals, the differential diagnosis includes progressive myoclonus epilepsies (PMEs), such as Unverricht-Lundborg disease, whereas, in adulthood, late-onset variants of PMEs, such as sialidoses, myoclonus epilepsy, and ataxia due to potassium channel pathogenic variants should be considered. PMEs may also be suggested by cognitive impairment, cerebellar signs, or psychiatric disorders. Electroencephalography (EEG) may show similarities to other idiopathic generalized epilepsies or PMEs, with generalized spike-wave activity. Signs of cortical hyperexcitability may be seen, such as an increased amplitude of somatosensory evoked potentials or enhanced cortical reflex to sensory stimuli, together with the neurophysiological pattern of the movement disorder. SIGNIFICANCE: Recognition of FAME will inform prognostic and genetic counseling and diagnosis of the insidious progression, which may occur in older individuals who show mild cognitive deterioration. Distinguishing FAME from other disorders in individuals or families with this constellation of symptoms is essential to allow the identification of underlying etiology.

Progressive myoclonus epilepsies due to SEMA6B mutations. New variants and appraisal of published phenotypes.

Variants of SEMA6B have been identified in an increasing number of patients, often presenting with progressive myoclonus epilepsy (PME), and to lesser extent developmental encephalopathy, with or without epilepsy. The exon 17 is mainly involved, with truncating mutations causing the production of aberrant proteins with toxic gain of function. Herein, we describe three adjunctive patients carrying de novo truncating SEMA6B variants in this exon (c.1976delC and c.2086C > T novel; c.1978delC previously reported). These subjects presented with PME preceded by developmental delay, motor and cognitive impairment, worsening myoclonus, and epilepsy with polymorphic features, including focal to bilateral seizures in two, and non-convulsive status epilepticus in one. The evidence of developmental delay in these cases suggests their inclusion in the "PME plus developmental delay" nosological group. This work further expands our knowledge of SEMA6B variants causing PMEs. However, the data to date available confirms that phenotypic features do not correlate with the type or location of variants, aspects that need to be further clarified by future studies.

MRI-guided focused-ultrasound thalamotomy in essential tremor: Immediate and delayed changes in cortico-muscular coherence and cortico-cortical out-strength.

OBJECTIVE: Drug-resistant essential tremor (ET) can be treated by Magnetic-Resonance-guided Focused-Ultrasound (MRgFUS) targeted to thalamic ventralis-intermediate nucleus (ViM). We are presenting the results obtained in ET patients by evaluating the cortico-muscular coherence (CMC) and the out-strength among cortical areas. METHODS: We recorded MEG-EMG signals in 16 patients with predominant tremor on the right upper limb. The examination was performed the day before MRgFUS (T0) treatment, 24 hours (T1), and 3-months (T2) after lesioning the left ViM. Normalized CMC (nCMC) and cortico-cortical out-strength among cortical areas were assessed during isometric extension of the right hand. RESULTS: According to the Essential Tremor Rating Assessment Scale, 13 of 16 patients were considered responders. At T1, in the beta-band, nCMC increased in the left hemisphere, namely in the areas directly involved in motor functions. At T2, the nCMC in non-motor areas decreased and the out-strength from other examined cortical areas toward the left motor-area decreased. CONCLUSIONS: In patients positively responding to MRgFUS, the CMC increased in the motor-area of the treated hemisphere immediately after the treatment, while the reorganization of CMC and cortico-cortical out-strength toward the cortical motor area occurred with a delay. SIGNIFICANCE: The effective treatment with MRgFUS corresponds with a readjustment of the CMC and of the communication between cortical areas.

Entropy Metrics Correlating with Higher Residual Functioning in Patients with Chronic Disorders of Consciousness.

To test the ability of different entropy measures to classify patients with different conditions of chronic disorder of consciousness, we applied the Lempel-Ziv complexity, the amplitude coalition entropy (ACE), and the synchrony coalition entropy (SCE) to the EEG signals recorded in 32 patients, clinically evaluated using the coma recovery scale revised (CRS-R). All the entropy measures indicated that differences found in the theta and alpha bands can distinguish patients in a minimal consciousness state (MCS) with respect to those in a vegetative state/unresponsive wakefulness state (VS/UWS). These differences were significant comparing the entropy measure performed on the anterior region of the left hemisphere and midline region. The values of theta-alpha entropy positively correlated with those of the CRS-R scores. Among the entropy measures, ACE most often highlighted significant differences. The higher values found in MCS were for the less impaired patients, according to their CRS-R, suggest that the preservation of signal entropy on the anterior region of the dominant hemisphere correlates with better preservation of consciousness, even in chronic conditions.

EEG Power spectra and subcortical pathology in chronic disorders of consciousness.

BACKGROUND: Despite a growing understanding of disorders of consciousness following severe brain injury, the association between long-term impairment of consciousness, spontaneous brain oscillations, and underlying subcortical damage, and the ability of such information to aid patient diagnosis, remains incomplete. METHODS: Cross-sectional observational sample of 116 patients with a disorder of consciousness secondary to brain injury, collected prospectively at a tertiary center between 2011 and 2013. Multimodal analyses relating clinical measures of impairment, electroencephalographic measures of spontaneous brain activity, and magnetic resonance imaging data of subcortical atrophy were conducted in 2018. RESULTS: In the final analyzed sample of 61 patients, systematic associations were found between electroencephalographic power spectra and subcortical damage. Specifically, the ratio of beta-to-delta relative power was negatively associated with greater atrophy in regions of the bilateral thalamus and globus pallidus (both left > right) previously shown to be preferentially atrophied in chronic disorders of consciousness. Power spectrum total density was also negatively associated with widespread atrophy in regions of the left globus pallidus, right caudate, and in the brainstem. Furthermore, we showed that the combination of demographics, encephalographic, and imaging data in an analytic framework can be employed to aid behavioral diagnosis. CONCLUSIONS: These results ground, for the first time, electroencephalographic presentation detected with routine clinical techniques in the underlying brain pathology of disorders of consciousness and demonstrate how multimodal combination of clinical, electroencephalographic, and imaging data can be employed in potentially mitigating the high rates of misdiagnosis typical of this patient cohort.

Genotype-phenotype correlations in SCN8A-related disorders reveal prognostic and therapeutic implications.

We report detailed functional analyses and genotype-phenotype correlations in 392 individuals carrying disease-causing variants in SCN8A, encoding the voltage-gated Na+ channel Nav1.6, with the aim of describing clinical phenotypes related to functional effects. Six different clinical subgroups were identified: Group 1, benign familial infantile epilepsy (n = 15, normal cognition, treatable seizures); Group 2, intermediate epilepsy (n = 33, mild intellectual disability, partially pharmaco-responsive); Group 3, developmental and epileptic encephalopathy (n = 177, severe intellectual disability, majority pharmaco-resistant); Group 4, generalized epilepsy (n = 20, mild to moderate intellectual disability, frequently with absence seizures); Group 5, unclassifiable epilepsy (n = 127); and Group 6, neurodevelopmental disorder without epilepsy (n = 20, mild to moderate intellectual disability). Those in Groups 1-3 presented with focal or multifocal seizures (median age of onset: 4 months) and focal epileptiform discharges, whereas the onset of seizures in patients with generalized epilepsy was later (median: 42 months) with generalized epileptiform discharges. We performed functional studies expressing missense variants in ND7/23 neuroblastoma cells and primary neuronal cultures using recombinant tetrodotoxin-insensitive human Nav1.6 channels and whole-cell patch-clamping. Two variants causing developmental and epileptic encephalopathy showed a strong gain-of-function (hyperpolarizing shift of steady-state activation, strongly increased neuronal firing rate) and one variant causing benign familial infantile epilepsy or intermediate epilepsy showed a mild gain-of-function (defective fast inactivation, less increased firing). In contrast, all three variants causing generalized epilepsy induced a loss-of-function (reduced current amplitudes, depolarizing shift of steady-state activation, reduced neuronal firing). Functional effects were known for 170 individuals. All 136 individuals carrying a functionally tested gain-of-function variant had either focal (n = 97, Groups 1-3) or unclassifiable (n = 39) epilepsy, whereas 34 individuals with a loss-of-function variant had either generalized (n = 14), no (n = 11) or unclassifiable (n = 6) epilepsy; only three had developmental and epileptic encephalopathy. Computational modelling in the gain-of-function group revealed a significant correlation between the severity of the electrophysiological and clinical phenotypes. Gain-of-function variant carriers responded significantly better to sodium channel blockers than to other anti-seizure medications, and the same applied for all individuals in Groups 1-3. In conclusion, our data reveal clear genotype-phenotype correlations between age at seizure onset, type of epilepsy and gain- or loss-of-function effects of SCN8A variants. Generalized epilepsy with absence seizures is the main epilepsy phenotype of loss-of-function variant carriers and the extent of the electrophysiological dysfunction of the gain-of-function variants is a main determinant of the severity of the clinical phenotype in focal epilepsies. Our pharmacological data indicate that sodium channel blockers present a treatment option in SCN8A-related focal epilepsy with onset in the first year of life.

Comparison of Resampling Techniques for Imbalanced Datasets in Machine Learning: Application to Epileptogenic Zone Localization From Interictal Intracranial EEG Recordings in Patients With Focal Epilepsy.

Aim: In neuroscience research, data are quite often characterized by an imbalanced distribution between the majority and minority classes, an issue that can limit or even worsen the prediction performance of machine learning methods. Different resampling procedures have been developed to face this problem and a lot of work has been done in comparing their effectiveness in different scenarios. Notably, the robustness of such techniques has been tested among a wide variety of different datasets, without considering the performance of each specific dataset. In this study, we compare the performances of different resampling procedures for the imbalanced domain in stereo-electroencephalography (SEEG) recordings of the patients with focal epilepsies who underwent surgery. Methods: We considered data obtained by network analysis of interictal SEEG recorded from 10 patients with drug-resistant focal epilepsies, for a supervised classification problem aimed at distinguishing between the epileptogenic and non-epileptogenic brain regions in interictal conditions. We investigated the effectiveness of five oversampling and five undersampling procedures, using 10 different machine learning classifiers. Moreover, six specific ensemble methods for the imbalanced domain were also tested. To compare the performances, Area under the ROC curve (AUC), F-measure, Geometric Mean, and Balanced Accuracy were considered. Results: Both the resampling procedures showed improved performances with respect to the original dataset. The oversampling procedure was found to be more sensitive to the type of classification method employed, with Adaptive Synthetic Sampling (ADASYN) exhibiting the best performances. All the undersampling approaches were more robust than the oversampling among the different classifiers, with Random Undersampling (RUS) exhibiting the best performance despite being the simplest and most basic classification method. Conclusions: The application of machine learning techniques that take into consideration the balance of features by resampling is beneficial and leads to more accurate localization of the epileptogenic zone from interictal periods. In addition, our results highlight the importance of the type of classification method that must be used together with the resampling to maximize the benefit to the outcome.