Scalp EEG recordings and the classification of interictal epileptiform discharges (IED) in patients with epilepsy provide valuable information about the epileptogenic network, particularly by ...defining the boundaries of the “irritative zone” (IZ), and hence are helpful during pre-surgical evaluation of patients with severe refractory epilepsies. The current detection and classification of epileptiform signals essentially rely on expert observers. This is a very time-consuming procedure, which also leads to inter-observer variability. Here, we propose a novel approach to automatically classify epileptic activity and show how this method provides critical and reliable information related to the IZ localization beyond the one provided by previous approaches. We applied Wave_clus, an automatic spike sorting algorithm, for the classification of IED visually identified from pre-surgical simultaneous Electroencephalogram–functional Magnetic Resonance Imagining (EEG–fMRI) recordings in 8 patients affected by refractory partial epilepsy candidate for surgery. For each patient, two fMRI analyses were performed: one based on the visual classification and one based on the algorithmic sorting. This novel approach successfully identified a total of 29 IED classes (compared to 26 for visual identification). The general concordance between methods was good, providing a full match of EEG patterns in 2 cases, additional EEG information in 2 other cases and, in general, covering EEG patterns of the same areas as expert classification in 7 of the 8 cases. Most notably, evaluation of the method with EEG–fMRI data analysis showed hemodynamic maps related to the majority of IED classes representing improved performance than the visual IED classification-based analysis (72% versus 50%). Furthermore, the IED-related BOLD changes revealed by using the algorithm were localized within the presumed IZ for a larger number of IED classes (9) in a greater number of patients than the expert classification (7 and 5, respectively). In contrast, in only one case presented the new algorithm resulted in fewer classes and activation areas. We propose that the use of automated spike sorting algorithms to classify IED provides an efficient tool for mapping IED-related fMRI changes and increases the EEG–fMRI clinical value for the pre-surgical assessment of patients with severe epilepsy.
•We used a new approach for classifying epileptic spikes in 8 patients.•We compared the results with visual classification using EEG–fMRI maps.•The performance for EEG–fMRI analysis improved from 46 to 72%.•IED-cluster localization matched presumed IZ in additional 4 classes and 1 patient.
•VoA – DBS is effective on both dystonia and tremor.•VoA – DBS benefits are not impaired by tolerance or side effects.•The variable VoA-DBS outcome previously reported were not proven by VTA ...simulation.•Application of new consensus on tremor classification may improve patient selection.
•Status epilepticus and encephalopathy can complicate Influenza infection.•New onset status can be the first manifestation of a genetic generalized epilepsy (GGE).•New onset status during influenza ...infection can be the presenting manifestation of GGE.
We hereby present a case of a young woman with no history of seizures or epilepsy who experienced a de novo generalized Non Convulsive Status Epilepticus (NCSE) followed by encephalopathy lasting for several days during influenza B infection. Influenza can have a broad spectrum of presentation ranging from an uncomplicated illness to many serious conditions as is the case of influenza associated encephalitis/encephalopathy (IAE). In this context however, it is possible to observe seizures and/or status epilepticus as the presenting manifestation of a genetic generalized epilepsy.
Simultaneous EEG-fMRI can contribute to identify the epileptogenic zone (EZ) in focal epilepsies. However, fMRI maps related to Interictal Epileptiform Discharges (IED) commonly show multiple regions ...of signal change rather than focal ones. Dynamic causal modeling (DCM) can estimate effective connectivity, i.e. the causal effects exerted by one brain region over another, based on fMRI data. Here, we employed DCM on fMRI data in 10 focal epilepsy patients with multiple IED-related regions of BOLD signal change, to test whether this approach can help the localization process of EZ. For each subject, a family of competing deterministic, plausible DCM models were constructed using IED as autonomous input at each node, one at time. The DCM findings were compared to the presurgical evaluation results and classified as: “Concordant” if the node identified by DCM matches the presumed focus, “Discordant” if the node is distant from the presumed focus, or “Inconclusive” (no statistically significant result). Furthermore, patients who subsequently underwent intracranial EEG recordings or surgery were considered as having an independent validation of DCM results. The effective connectivity focus identified using DCM was Concordant in 7 patients, Discordant in two cases and Inconclusive in one. In four of the 6 patients operated, the DCM findings were validated. Notably, the two Discordant and Invalidated results were found in patients with poor surgical outcome. Our findings provide preliminary evidence to support the applicability of DCM on fMRI data to investigate the epileptic networks in focal epilepsy and, particularly, to identify the EZ in complex cases.
In this note, we assess the predictive validity of stochastic dynamic causal modeling (sDCM) of functional magnetic resonance imaging (fMRI) data, in terms of its ability to explain changes in the ...frequency spectrum of concurrently acquired electroencephalography (EEG) signal. We first revisit the heuristic model proposed in Kilner et al. (2005), which suggests that fMRI activation is associated with a frequency modulation of the EEG signal (rather than an amplitude modulation within frequency bands). We propose a quantitative derivation of the underlying idea, based upon a neural field formulation of cortical activity. In brief, dense lateral connections induce a separation of time scales, whereby fast (and high spatial frequency) modes are enslaved by slow (low spatial frequency) modes. This slaving effect is such that the frequency spectrum of fast modes (which dominate EEG signals) is controlled by the amplitude of slow modes (which dominate fMRI signals). We then use conjoint empirical EEG-fMRI data-acquired in epilepsy patients-to demonstrate the electrophysiological underpinning of neural fluctuations inferred from sDCM for fMRI.
Generalised spike wave (GSW) discharges are the electroencephalographic (EEG) hallmark of absence seizures, clinically characterised by a transitory interruption of ongoing activities and impaired ...consciousness, occurring during states of reduced awareness. Several theories have been proposed to explain the pathophysiology of GSW discharges and the role of thalamus and cortex as generators. In this work we extend the existing theories by hypothesizing a role for the precuneus, a brain region neglected in previous works on GSW generation but already known to be linked to consciousness and awareness. We analysed fMRI data using dynamic causal modelling (DCM) to investigate the effective connectivity between precuneus, thalamus and prefrontal cortex in patients with GSW discharges.
We analysed fMRI data from seven patients affected by Idiopathic Generalized Epilepsy (IGE) with frequent GSW discharges and significant GSW-correlated haemodynamic signal changes in the thalamus, the prefrontal cortex and the precuneus. Using DCM we assessed their effective connectivity, i.e. which region drives another region. Three dynamic causal models were constructed: GSW was modelled as autonomous input to the thalamus (model A), ventromedial prefrontal cortex (model B), and precuneus (model C). Bayesian model comparison revealed Model C (GSW as autonomous input to precuneus), to be the best in 5 patients while model A prevailed in two cases. At the group level model C dominated and at the population-level the p value of model C was approximately 1.
Our results provide strong evidence that activity in the precuneus gates GSW discharges in the thalamo-(fronto) cortical network. This study is the first demonstration of a causal link between haemodynamic changes in the precuneus -- an index of awareness -- and the occurrence of pathological discharges in epilepsy.
Summary
The study aims at assessing the changes in electroencephalography (as measured by the A‐phases of cyclic alternating pattern) and autonomic activity (based on pulse wave amplitude) at the ...recovery of airway patency in patients with obstructive sleep apnea syndrome. Analysis of polysomnographic recordings from 20 male individuals with obstructive sleep apnea syndrome was carried out in total sleep time, non‐rapid eye movement and rapid eye movement sleep. Scoring quantified the combined occurrence (time range of 4 s before and 4 s after respiratory recovery) or separate occurrence of A‐phases (cortical activation), and pulse wave amplitude drops (below 30%) to apneas, hypopneas or flow limitation events. A dual response (A‐phase associated with a pulse wave amplitude drop) was the most frequent response (71.8% in total sleep time) for all types of respiratory events, with a progressive reduction from apneas to hypopneas and flow limitation events. The highly significant correlation in total sleep time (r = 0.9351; P < 0.0001) between respiratory events combined with A‐phases and respiratory events combined with pulse wave amplitude drops was confirmed both in non‐rapid eye movement (r = 0.9622; P < 0.0001) and rapid eye movement sleep (r = 0.7162; P < 0.0006). In conclusion, a dual cortical and autonomic activation is the most common manifestation at the recovery of airway patency. The significant correlation between A‐phases and relevant pulse wave amplitude drops suggests a possible role of pulse wave amplitude as a marker of cerebral response to respiratory events.
We propose a rapid method for
Saccharomyces cerevisiae strain identification based on multiplex PCR analysis of polymorphic microsatellite loci. Simple DNA extraction without the use of phenol, ...followed by a rapid PCR procedure optimised for multiplex amplification of loci SC8132X, YOR267C and SCPTSY7 and band pattern analysis of the fragments generated by agarose and polyacrylamide gel electrophoresis, has allowed us to distinguish among a panel of 30 tested commercial wine strains. This method was successfully performed in an ecological study where dominance between two strains was checked at two fermentation temperatures: 15 and 20
°C.
The method should be useful for routine and low-budget discrimination of yeast strains, both in the wine and yeast production industries.
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