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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., (© 2024. Fondazione Società Italiana di Neurologia.)

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., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Clementi et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Objective: We use co-registration of foramen-ovale and scalp-EEG to investigate network alterations in temporal-lobe epilepsy during focal seizures without (aura) or with impairment of awareness (SIA)., Methods: One aura and one SIA were selected from six patients. Temporal dynamic among 4 epochs, as well as the differences between aura and SIA, were analyzed through partial directed coherence and graph theory-based indices of centrality., Results: Regarding the auras temporal evolution, fronto-parietal (FP) regions showed decreased connectivity with respect to the interictal period, in both epileptogenic (EH) and non-epileptogenic hemisphere (nEH). During SIAs, temporal dynamic showed more changes than auras: centrality of mesial temporal (mT) regions changes during all conditions, and nEH FP centrality showed the same dynamic trend of the aura (decreased centrality), until the last epoch, close to the impaired awareness, when showed increased centrality. Comparing SIA with aura, in proximity of impaired awareness, increased centrality was found in all the regions, except in nEH mT., Conclusions: Our findings suggested that the impairment of awareness is related to network alterations occurring first in neocortical regions and when awareness is still retained., Significance: The analysis of 'hub' alteration can represent a suitable biomarker for scalp EEG-based prediction of awareness impairment., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.)

Objective: We evaluated four imaging techniques, i.e. Electroencephalography (EEG)-functional Magnetic Resonance Imaging (MRI) (EEG-fMRI), High-resolution EEG (HR-EEG), Magnetoencephalography (MEG) and 2-[18F]fluoro-2-deoxy-D-glucose positron emission tomography (PET), for the identification of the epileptogenic zone (EZ) in 41 patients with negative MRI, candidate to neurosurgery., Methods: For each technique, results were compared to the Stereo-EEG. Diagnostic measures were calculated with respect to the post-surgical outcome, either for all the patients (39/41, two patients excluded) and for the subgroup of patients with the EZ involving more than one lobe (20/41)., Results: When considered individually, each functional technique showed accuracy values ranging 54,6%-63,2%, having PET, MEG and HR-EEG higher sensitivity, and EEG-fMRI higher specificity. In patients with multilobar epileptogenic zone, functional techniques achieved the best accuracies (up to 80%) when three techniques, including EEG-fMRI, were considered together., Conclusions: The study highlights the accuracy of a combination of functional imaging techniques in the identification of EZ in MRI negative focal epilepsy. The best diagnostic yield was obtained if the combination of PET, MEG (or HR-EEG as alternative), EEG-fMRI were considered together., Significance: The functional imaging techniques may improve the presurgical workup of MRI negative focal epilepsy, if epileptogenic zone involves more than one lobe., Competing Interests: Declaration of Competing Interest None of the authors has any conflict of interest to disclose. We confirm that we have read the journal’s position on the issues involved in ethical publication, and affirm that this report is consistent with those guidelines., (Copyright © 2020 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.)

Objective: The clinical and neurophysiological characteristics of myoclonus in Angelman syndrome (AS) have been evaluated in single case or small cohorts, with contrasting results. We evaluated the features of myoclonus in a wide cohort of AS patients., Methods: We performed polygraphic EEG-EMG recording in 24 patients with genetically confirmed AS and myoclonus. Neurophysiological investigations included jerk-locked back-averaging (JLBA), cortico-muscular coherence (CMC) and generalised partial directed coherence (GPDC). CMC and GPDC analyses were compared to those obtained from 10 healthy controls (HC)., Results: Twenty-four patients (aged 3-35 years, median 20) were evaluated. Sequences of quasi-continuous rhythmic jerks mostly occurred at alpha frequency or just below (mean 8.4 ± 1.4 Hz), without EEG correlate. JLBA did not show any clear transient preceding the jerks. CMC showed bilateral over-threshold CMC in alpha band that was prominent on the contralateral hemisphere in the patient group as compared to HC group. GPDC showed a significantly higher alpha outflow from both hemispheres toward activated muscles in the patient group, and a significantly higher beta outflow from contralateral hemisphere in the HC group., Conclusions: These neurophysiological findings suggest a subcortical generator of myoclonus in AS., Significance: Myoclonus in AS has not a cortical origin as previously hypothesised., (Copyright © 2019 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.)

Purpose: Structural brain imaging has revealed that damage to different brain regions may impair theory of mind (ToM) while functional imaging has shown that distributed neural circuits are activated by ToM and empathy. However, the coherence of the electroencephalogram (EEG) frequencies in a definite time span may change during these processes, indicating different neurophysiological correlates. This study evaluated the changes of EEG coherence during ToM tasks in comparison with Empathy, Physical causality, and baseline conditions, aiming to determine the neurophysiological correlates of ToM., Methods: Sixteen healthy adults underwent a visual activation paradigm using 30 comic strips concerning ToM, Empathy, or Physical causality during EEG recording. The interhemispheric coherence was estimated using a bivariate autoregressive (AR) parametric model. The coherence spectra were analyzed in the alpha, beta, and gamma frequency EEG bands., Results: Coherence analysis taking all of the responses showed that in the gamma band, in comparison with the Empathy, Physical causality, and baseline conditions, ToM was associated with significantly higher peaks between the frontal and parietal areas in the right hemisphere and, in comparison with the Physical causality and baseline conditions, in the left hemisphere. Analysis taking the correct responses confirmed these results., Conclusions: In healthy adults, ToM processes are associated with immediate specific changes of brain connectivity, as expressed by high cortical coherence within the right frontal and parietal areas. These previously unexplored aspects indicate an online involvement of the right hemisphere networks in normal ToM. In patients with epilepsy, the study of EEG coherence during specific tasks may help determine the neural dysfunctions associated with impaired ToM. This article is part of the Special Issue "Epilepsy and social cognition across the lifespan"., (Copyright © 2019 Elsevier Inc. All rights reserved.)

Background: Magneto- and Electro-encephalography record the electromagnetic field generated by neural currents with high temporal frequency and good spatial resolution, and are therefore well suited for source localization in the time and in the frequency domain. In particular, localization of the generators of neural oscillations is very important in the study of cognitive processes in the healthy and in the pathological brain., New Method: We introduce the use of a Bayesian multi-dipole localization method in the frequency domain. Given the Fourier Transform of the data at one or multiple frequencies and/or trials, the algorithm approximates numerically the posterior distribution with Monte Carlo techniques., Results: We use synthetic data to show that the proposed method behaves well under a wide range of experimental conditions, including low signal-to-noise ratios and correlated sources. We use dipole clusters to mimic the effect of extended sources. In addition, we test the algorithm on real MEG data to confirm its feasibility., Comparison With Existing Method(s): Throughout the whole study, DICS (Dynamic Imaging of Coherent Sources) is used systematically as a benchmark. The two methods provide similar general pictures; the posterior distributions of the Bayesian approach contain much richer information at the price of a higher computational cost., Conclusions: The Bayesian method described in this paper represents a reliable approach for localization of multiple dipoles in the frequency domain., (Copyright © 2018 Elsevier B.V. All rights reserved.)

In this paper we propose a new methodology for introducing thresholds in the analysis of neuro- biological databases. Often, in Neuroscience, absolute thresholds are adopted. This is done by cutting the data below (or above) predetermined values of the involved parameters, without an analysis of the distribution of the collected data concerning the phenomenon under investigation. Despite an absolute threshold could be rigorously defined in terms of physic parameters, it can be influenced by many different subjective aspects, including cognitive processes, and individual adaptation to the external stimuli. A possible related risk is that, mainly in experiments also de-pending on personal reactions, a significant portion of meaningful data, relevant for that specific task, could be neglected. In order to reduce these deviations, we are proposing to adopt a task-dependent approach, based on the comparison between the collected data and some database concerning a different task, assumed as a baseline. After giving the necessary theoretical back-ground, we test our methodology on real EEG data involving two subjects in a musical task. In addition to some natural results, new and unexpected neurological links can be emphasized and discussed.

Electroencephalographic (EEG) photoparoxysmal response has been little investigated in very young patients. We studied 5055 patients aged less than 5 years with no acquired brain damage, who underwent EEG recording. We determined the prevalence and significance of photoparoxysmal response induced by 1 to 20 Hz photic stimulation. Fifty-three showed photoparoxysmal response and were diagnosed as having Dravet syndrome (11), epileptic encephalopathy with myoclonic seizures (8), neurodegenerative disorders (8), benign idiopathic epilepsies (9), and static disorders with a known or suspected genetic origin (17). Photoparoxysmal response occurred in response to 1 to 5 Hz trains in 41.5% subjects. In most patients with epileptic encephalopathies, photoparoxysmal response was a transient finding: in 53.2%, it failed to be replicated in the recordings performed more than 6 months after initial evaluation. Photoparoxysmal response is rare in patients aged less than 5 years and has some peculiarities such as occurrence with low-frequency stimuli. Its distribution in specific conditions indicates that photoparoxysmal response may be useful in diagnostic workup., (© The Author(s) 2015.)

Although several brain regions show significant specialization, higher functions such as cross-modal information integration, abstract reasoning and conscious awareness are viewed as emerging from interactions across distributed functional networks. Analytical approaches capable of capturing the properties of such networks can therefore enhance our ability to make inferences from functional MRI, electroencephalography and magnetoencephalography data. Graph theory is a branch of mathematics that focuses on the formal modelling of networks and offers a wide range of theoretical tools to quantify specific features of network architecture (topology) that can provide information complementing the anatomical localization of areas responding to given stimuli or tasks (topography). Explicit modelling of the architecture of axonal connections and interactions among areas can furthermore reveal peculiar topological properties that are conserved across diverse biological networks, and highly sensitive to disease states. The field is evolving rapidly, partly fuelled by computational developments that enable the study of connectivity at fine anatomical detail and the simultaneous interactions among multiple regions. Recent publications in this area have shown that graph-based modelling can enhance our ability to draw causal inferences from functional MRI experiments, and support the early detection of disconnection and the modelling of pathology spread in neurodegenerative disease, particularly Alzheimer's disease. Furthermore, neurophysiological studies have shown that network topology has a profound link to epileptogenesis and that connectivity indices derived from graph models aid in modelling the onset and spread of seizures. Graph-based analyses may therefore significantly help understand the bases of a range of neurological conditions. This review is designed to provide an overview of graph-based analyses of brain connectivity and their relevance to disease aimed principally at general neuroscientists and clinicians.

We postulate that "system epilepsies" (SystE) are due to an enduring propensity to generate seizures of functionally characterized brain systems. Data supporting this hypothesis-that some types of epilepsy depend on the dysfunction of specific neural systems-are reviewed. The SystE hypothesis may drive pathophysiologic and clinical studies that can advance our understanding of epilepsies and can open up new therapeutic perspectives., (Wiley Periodicals, Inc. © 2012 International League Against Epilepsy.)

Human emotion perception is a topic of great interest for both cognitive and clinical neuroscience, but its electrophysiological correlates are still poorly understood. The present study is aimed at evaluating if measures of synchronization and indexes based on graph-theory are a tool suitable to study and quantify electrophysiological changes due to emotional stimuli perception. In particular, our study is aimed at evaluating if different EEG connectivity patterns can be induced by pleasant (consonant) or unpleasant (dissonant) music, in a population of healthy subjects, and in patients with severe disorders of consciousness (DOCs), namely vegetative state (VS) patients. In the control group, pleasant music induced an increase in network number of connections, compared with the resting condition, while no changes were caused by the unpleasant stimuli. However, clustering coefficient and path length, two indexes derived from graph theory, able to characterise segregation and integration properties of a network, were not affected by the stimuli, neither pleasant nor unpleasant. In the VS group, changes were found only in those patients with the less severe consciousness impairment, according to the clinical assessment. In these patients a stronger synchronization was found during the unpleasant condition; moreover we observed changes in the network topology, with decreased values of clustering coefficient and path length during both musical stimuli.Our results show that measures of synchronization can provide new insights into the study of the electro physiological correlates of emotion perception, indicating that these tools can be used to study patients with DOCs, in whom the issue of objective measures and quantification of the degree of impairment is still an open and unsolved question.

We used electroencephalography (EEG)-polygraphic recordings to classify myoclonus in 109 patients with Creutzfeldt-Jakob disease (CJD) on the basis of its electromyography (EMG) pattern, time course, distribution, and EEG correlates. We recorded myoclonic jerks in 55 patients (50.4%), and we classified them as periodic myoclonus in 28, rhythmic in 13, and irregular in 20 (6 patients showed two types of myoclonus). Myoclonus occurred as a prominently negative event (interrupting the EMG discharge) in 10. Periodic sharp-wave complexes (PSWCs) were present in all but one patient with myoclonic jerks but were time-locked with EMG-bursts only in case of periodic myoclonus. Jerk-locked back averaging revealed a variable EEG-EMG transfer-time commonly exceeding that characterizing cortical myoclonus. Myoclonus was frequently associated with Met/Met polymorphism at codon 129 of the prion protein gene, but it was also observed in association with Met/Val or Val/Val polymorphisms provided that the EEG showed the presence of the PSWC pattern. The presence of enlarged somatosensory evoked potentials significantly correlated with the myoclonic presentation, as did MR signal hyperintensity involving the cortical mantle. Our observations on the basis of standard polygraphic criteria suggest that CJD associates with a remarkable variety of myoclonic jerks, and therefore different brain structures are probably involved as generators. The significant association between the presence of all myoclonus types with PSWCs suggests that hyperexcitable corticosubcortical loops are always required to generate (or allow) both myoclonus and the EEG complexes, either they are time locked or not., (© 2010 Movement Disorder Society.)

We performed simultaneous acquisition of EEG-fMRI in seven patients with Unverricht-Lundborg disease (ULD) and in six healthy controls using self-paced finger extension as a motor task. The event-related desynchronization/synchronization (ERD/ERS) analysis showed a greater and more diffuse alpha desynchronization in central regions and a strongly reduced post-movement beta-ERS in patients compared with controls, suggesting a significant dysfunction of the mechanisms regulating active movement and movement end. The event-related hemodynamic response obtained from fMRI showed delayed BOLD peak latency in the contralateral primary motor area suggesting a less efficient activity of the neuronal populations driving fine movements, which are specifically impaired in ULD.

Infantile spasms (IS) are so typically associated with West syndrome that the term IS, properly referred to as a seizure type, is currently used synonymously with this severe infantile epilepsy. This chapter reviews some clinical and experimental observations relevant to IS pathophysiology with particular regard to maturational aspects that may account for IS age-related expression. Neither the cortical nor the brain stem generator hypotheses account for all the clinical features of IS. It is suggested that IS are generated whenever a cortical discharge is able to influence some archaic circuit located putatively in the brain stem through either an excitatory or a disinhibitory mechanism. This may occur with the highest probability during a developmental window in which IS typically occur, when N-methyl-D-aspartate (NMDA) transmission is particularly facilitated due a reduced sensitivity of NMDA receptors to the Mg2+ block. Interestingly, in this age range (0-18 postnatal day in rat), flexion spasms can be elicited experimentally by NMDA administration. These data provide an important key to further investigating IS pathophysiology, thus allowing us to design more effective strategies aimed at counteracting this harmful infantile epilepsy.

Neurological derangement has been reported in haemodialysed patients receiving intravenous desferrioxamine (DFO) for aluminium-related disorders. The possible direct effects of desferrioxamine on EEG recordings were investigated in ten haemodialysed patients who underwent a DFO test 2 h after the end of dialysis. According to a commonly accepted protocol, 40 mg/kg body-weight of desferrioxamine was infused in 60 min. EEG recording was continuously performed, starting 30 min before and stopping 30 min after the desferrioxamine infusion. Besides visual inspection, EEG records were digitised, tapered, and spectrally analysed with Digital PDP 11/73 microcomputer. Basal EEG recording was normal in all patients. In three patients a progressive EEG slowing was detected by visual inspection during desferrioxamine infusion; in these cases automatic analysis revealed a 50% increase in power of slower frequencies 30 min after starting the infusion, when no changes in plasma aluminium concentrations are detected; a complete recovery was observed 30 min after desferrioxamine withdrawal. In one patient bilateral paroxysms of slow waves appeared, so we stopped desferrioxamine infusion. Two of the three patients who developed EEG abnormalities also had an increased aluminium body burden (positive DFO test). Results indicated that desferrioxamine per se can modify EEG in haemodialysis patients and that its effect is not mediated by acute increases of plasma aluminium concentrations. The finding of a positive DFO test in two of three patients with EEG changes may suggest that an aluminium-induced blood-brain barrier derangement could have played a role. However, prompt recovery after ceasing desferrioxamine infusion strongly suggests a direct role of desferrioxamine in the induction of EEG changes.(ABSTRACT TRUNCATED AT 250 WORDS)

A procedure is described which aims to classify an EEG recorded during neurosurgery, for example intracerebral aneurysm clipping. A parametric approach is used; it employs auto-regressive (AR) modelling and Kalman filtering to quantify directly the dynamics of the EEG generating mechanism, supposing it to be a linear, time-invariant system driven by white noise. The results of this EEG processing are analysed together with simultaneous values of arterial blood pressure (ABP) as surgery of this kind is carried out under conditions of controlled hypotension. The object is to compare the sensitivity of ABP data with that obtained from the EEG and so provide an early warning of a potentially dangerous non-physiological state induced by the hypotensive drug (in this case sodium nitroprusside). Some methodological comments on the correct implementation of these algorithms are given and the procedure is compared with similar approaches which have appeared in the literature during the last few years. Particular emphasis is placed on the power spectral analysis of the signal by pointing out a method for spectral decomposition, related to AR power density estimation, which permits the separation of single spectral components in terms of central frequencies and their associated power. Other potential applications of this method are in long term EEG monitoring for the detection of changes due for example to drug infusion, to fast transient events, or to changes in the stationary condition.