Detection of Intracranial Signatures of Interictal Epileptiform Discharges from Concurrent Scalp EEG

2016 ◽  
Vol 26 (04) ◽  
pp. 1650016 ◽  
Author(s):  
Loukianos Spyrou ◽  
David Martín-Lopez ◽  
Antonio Valentín ◽  
Gonzalo Alarcón ◽  
Saeid Sanei
Keyword(s):  
Detection Algorithm ◽  
The Other ◽  
Intracranial Eeg ◽  
Scalp Eeg ◽  
Epileptiform Discharges ◽  
Interictal Epileptiform Discharges ◽  
Scalp Electroencephalogram ◽  
Patients With Epilepsy ◽  
Electrical Activities ◽  
The Brain

Interictal epileptiform discharges (IEDs) are transient neural electrical activities that occur in the brain of patients with epilepsy. A problem with the inspection of IEDs from the scalp electroencephalogram (sEEG) is that for a subset of epileptic patients, there are no visually discernible IEDs on the scalp, rendering the above procedures ineffective, both for detection purposes and algorithm evaluation. On the other hand, intracranially placed electrodes yield a much higher incidence of visible IEDs as compared to concurrent scalp electrodes. In this work, we utilize concurrent scalp and intracranial EEG (iEEG) from a group of temporal lobe epilepsy (TLE) patients with low number of scalp-visible IEDs. The aim is to determine whether by considering the timing information of the IEDs from iEEG, the resulting concurrent sEEG contains enough information for the IEDs to be reliably distinguished from non-IED segments. We develop an automatic detection algorithm which is tested in a leave-subject-out fashion, where each test subject’s detection algorithm is based on the other patients’ data. The algorithm obtained a [Formula: see text] accuracy in recognizing scalp IED from non-IED segments with [Formula: see text] accuracy when trained and tested on the same subject. Also, it was able to identify nonscalp-visible IED events for most patients with a low number of false positive detections. Our results represent a proof of concept that IED information for TLE patients is contained in scalp EEG even if they are not visually identifiable and also that between subject differences in the IED topology and shape are small enough such that a generic algorithm can be used.

scholarly journals Zero-crossing patterns reveal subtle epileptiform discharges in the scalp EEG

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jan Pyrzowski ◽  
Jean- Eudes Le Douget ◽  
Amal Fouad ◽  
Mariusz Siemiński ◽  
Joanna Jędrzejczak ◽  
...  
Keyword(s):  
Normal Subjects ◽  
Intracranial Eeg ◽  
Zero Crossing ◽  
Temporal Precision ◽  
Scalp Eeg ◽  
Epileptiform Discharges ◽  
Interictal Epileptiform Discharges ◽  
Eeg Recordings ◽  
Patients With Epilepsy ◽  
Low Amplitude

AbstractClinical diagnosis of epilepsy depends heavily on the detection of interictal epileptiform discharges (IEDs) from scalp electroencephalographic (EEG) signals, which by purely visual means is far from straightforward. Here, we introduce a simple signal analysis procedure based on scalp EEG zero-crossing patterns which can extract the spatiotemporal structure of scalp voltage fluctuations. We analyzed simultaneous scalp and intracranial EEG recordings from patients with pharmacoresistant temporal lobe epilepsy. Our data show that a large proportion of intracranial IEDs manifest only as subtle, low-amplitude waveforms below scalp EEG background and could, therefore, not be detected visually. We found that scalp zero-crossing patterns allow detection of these intracranial IEDs on a single-trial level with millisecond temporal precision and including some mesial temporal discharges that do not propagate to the neocortex. Applied to an independent dataset, our method discriminated accurately between patients with epilepsy and normal subjects, confirming its practical applicability.

scholarly journals Interictal Epileptiform Discharge Dynamics in Peri-sylvian Polymicrogyria Using EEG-fMRI

2021 ◽  
Vol 12 ◽  
Author(s):  
Noa Cohen ◽  
Yoram Ebrahimi ◽  
Mordekhay Medvedovsky ◽  
Guy Gurevitch ◽  
Orna Aizenstein ◽  
...  
Keyword(s):  
Case Series ◽  
Epileptic Seizures ◽  
Epileptic Activity ◽  
Scalp Eeg ◽  
Epileptiform Discharges ◽  
Interictal Epileptiform Discharges ◽  
Malformation Of Cortical Development ◽  
Interictal Epileptiform Discharge ◽  
Drug Resistant Epilepsy ◽  
Patients With Epilepsy

Polymicrogyria (PMG) is a common malformation of cortical development associated with a higher susceptibility to epileptic seizures. Seizures secondary to PMG are characterized by difficult-to-localize cerebral sources due to the complex and widespread lesion structure. Tracing the dynamics of interictal epileptiform discharges (IEDs) in patients with epilepsy has been shown to reveal the location of epileptic activity sources, crucial for successful treatment in cases of focal drug-resistant epilepsy. In this case series IED dynamics were evaluated with simultaneous EEG-fMRI recordings in four patients with unilateral peri-sylvian polymicrogyria (PSPMG) by tracking BOLD activations over time: before, during and following IED appearance on scalp EEG. In all cases, focal BOLD activations within the lesion itself preceded the activity associated with the time of IED appearance on EEG, which showed stronger and more widespread activations. We therefore propose that early hemodynamic activity corresponding to IEDs may hold important localizing information potentially leading to the cerebral sources of epileptic activity. IEDs are suggested to develop within a small area in the PSPMG lesion with structural properties obscuring the appearance of their electric field on the scalp and only later engage widespread structures which allow the production of large currents which are recognized as IEDs on EEG.

scholarly journals Automatic Identification of Interictal Epileptiform Discharges in Secondary Generalized Epilepsy

2016 ◽  
Vol 2016 ◽  
pp. 1-10 ◽  
Author(s):  
Won-Du Chang ◽  
Ho-Seung Cha ◽  
Chany Lee ◽  
Hoon-Chul Kang ◽  
Chang-Hwan Im
Keyword(s):  
Automatic Identification ◽  
Sharp Waves ◽  
Epileptiform Discharges ◽  
Interictal Epileptiform Discharges ◽  
Detection And Identification ◽  
Characteristic Signal ◽  
Generalized Epilepsy ◽  
Scalp Electroencephalogram ◽  
Patients With Epilepsy ◽  
Epileptogenic Foci

Ictal epileptiform discharges (EDs) are characteristic signal patterns of scalp electroencephalogram (EEG) or intracranial EEG (iEEG) recorded from patients with epilepsy, which assist with the diagnosis and characterization of various types of epilepsy. The EEG signal, however, is often recorded from patients with epilepsy for a long period of time, and thus detection and identification of EDs have been a burden on medical doctors. This paper proposes a new method for automatic identification of two types of EDs, repeated sharp-waves (sharps), and runs of sharp-and-slow-waves (SSWs), which helps to pinpoint epileptogenic foci in secondary generalized epilepsy such as Lennox-Gastaut syndrome (LGS). In the experiments with iEEG data acquired from a patient with LGS, our proposed method detected EDs with an accuracy of 93.76% and classified three different signal patterns with a mean classification accuracy of 87.69%, which was significantly higher than that of a conventional wavelet-based method. Our study shows that it is possible to successfully detect and discriminate sharps and SSWs from background EEG activity using our proposed method.

scholarly journals Human interictal epileptiform discharges are traveling waves reflecting ictal self-organization

2021 ◽  
Author(s):  
Elliot H Smith ◽  
Jyun-You Liou ◽  
Edward M. Merricks ◽  
Tyler S Davis ◽  
Kyle Thomson ◽  
...  
Keyword(s):  
Traveling Waves ◽  
Microelectrode Arrays ◽  
Interictal Spikes ◽  
Spatial Properties ◽  
Human Epilepsy ◽  
Spatial Features ◽  
Epileptiform Discharges ◽  
Interictal Epileptiform Discharges ◽  
Patients With Epilepsy ◽  
The Brain

AbstractInterictal epileptiform discharges (IEDs), also known as interictal spikes, are large intermittent electrophysiological events observed between seizures in patients with epilepsy. While seizures are infrequent and unpredictable, IEDs are far more common, often occurring several times per minute. Yet despite the abundance of IEDs, it remains unknown how they relate to seizures. To better understand this relationship, we examined multi-day recordings of 96-channel microelectrode arrays implanted in human epilepsy patients. These recordings—spanning single cell action potentials to population field potentials—allowed us to study the microscale spatiotemporal organization of over 45,000 IEDs across 10 participants from 2 surgical centers. These recordings showed that the majority of IEDs propagate across neocortex as traveling waves. While all of these traveling wave distributions exhibited a predominant, consistent direction, the majority also exhibited a second, auxiliary, direction. Clustering the IED distributions revealed that their predominant and auxiliary distributions were antipodal, mimicking the spatial microstructure of seizure discharges (SDs) that we have previously reported. We thus compared spatial features of IED sub-distributions to those for SDs, showing a correspondence between ictal and interictal spatial properties in participants whose microelectrode arrays were recruited into the seizure from adjacent cortical tissue. These results reveal fundamental relationships between IEDs and seizures and suggest how IEDs could be used to infer spatial features of seizures.One Sentence SummaryEpileptiform electrical events occurring between human seizures propagate across the brain in directions that reflect the self-organizing structure of seizures.

The Application of EEG to Epilepsy in Adults and the Elderly

2017 ◽  
Author(s):  
Vaishnav Krishnan ◽  
Bernard S. Chang ◽  
Donald L. Schomer
Keyword(s):  
The Elderly ◽  
Autism Spectrum ◽  
Focal Region ◽  
Scalp Eeg ◽  
Epileptiform Discharges ◽  
Interictal Epileptiform Discharges ◽  
Generalized Seizures ◽  
Indispensable Tool ◽  
Cortical Regions ◽  
Patients With Epilepsy

Surface or scalp electroencephalography (EEG) has become an indispensable tool for the diagnosis, classification, and care of patients with epilepsy across the age spectrum. This chapter provides an overview of interictal and corresponding ictal scalp EEG patterns observed in adults with certain classical epilepsy syndromes. In patients with one or more new-onset seizures, the value of EEG testing begins with a close examination of the interictal record. The morphology, frequency, and topography of interictal epileptiform discharges (when present) are typically sufficient to broadly distinguish between the propensity to develop “generalized seizures” (those that rapidly engage a distributed epileptogenic network) or “focal seizures” (which have a stereotyped onset within a clearly lateralized focal region or network). Epileptiform discharges may also be seen in patients without epilepsy who are affected by certain acute (e.g., severe metabolic encephalopathies) or chronic neuropsychiatric syndromes (e.g., autism spectrum disorder). An examination of the ictal recording is of crucial importance in patients with medication-refractory focal onset seizures as it serves to guide patient selection and ancillary testing for the possibility of resective surgery for epilepsy. This chapter also highlights the limited anatomical sensitivity of EEG for seizures that lack an associated impairment in consciousness (“simple partial seizures”) or those that remain confined to mesial, deep or inferior cortical regions.

scholarly journals Incorporating Uncertainty in Data Labeling into Automatic Detection of Interictal Epileptiform Discharges from Concurrent Scalp-EEG via Multi-way Analysis

2021 ◽  
pp. 2150019
Author(s):  
Bahman Abdi-Sargezeh ◽  
Antonio Valentin ◽  
Gonzalo Alarcon ◽  
Saeid Sanei
Keyword(s):  
State Of The Art ◽  
Detection System ◽  
Superior Performance ◽  
Tensor Factorization ◽  
Time Frequency ◽  
Scalp Eeg ◽  
Epileptiform Discharges ◽  
Interictal Epileptiform Discharges ◽  
The Brain ◽  
Frequency Features

Interictal epileptiform discharges (IEDs) are elicited from an epileptic brain, whereas they can also be due to other neurological abnormalities. The diversity in their morphologies, their strengths, and their sources within the brain cause a great deal of uncertainty in their labeling by clinicians. The aim of this study is therefore to exploit and incorporate this uncertainty (the probability of the waveform being an IED) in the IED detection system which combines spatial component analysis (SCA) with the IED probabilities referred to as SCA-IEDP-based method. For comparison, we also propose and study SCA-based method in which probability of the waveform being an IED is ignored. The proposed models are employed to detect IEDs in two different classification approaches: (1) subject-dependent and (2) subject-independent classification approaches. The proposed methods are compared with two other state-of-the-art methods namely, time–frequency features and tensor factorization methods. The proposed SCA-IEDP model has achieved superior performance in comparison with the traditional SCA and other competing methods. It achieved 79.9% and 63.4% accuracy values in subject-dependent and subject-independent classification approaches, respectively. This shows that considering the IED probabilities in designing an IED detection system can boost its performance.

scholarly journals Sleep spindles, ripples, and interictal epileptiform discharges in the human anterior and mediodorsal thalamus

2021 ◽  
Author(s):  
Orsolya Szalardy ◽  
Peter Simor ◽  
Peter Przemyslaw Ujma ◽  
Zsofia Jordan ◽  
Laszlo Halasz ◽  
...  
Keyword(s):  
Neural Plasticity ◽  
Nrem Sleep ◽  
Cortical Activity ◽  
Sleep Spindles ◽  
Time Frequency ◽  
Scalp Eeg ◽  
Epileptiform Discharges ◽  
Interictal Epileptiform Discharges ◽  
Human Thalamus ◽  
Result Show

Sleep spindles are major oscillatory components of Non-Rapid Eye Movement (NREM) sleep, reflecting hyperpolarization-rebound sequences of thalamocortical neurons, the inhibition of which is caused by the NREM-dependent activation of GABAergic neurons in the reticular thalamic nucleus. Reports suggest a link between sleep spindles and several forms of interictal epileptic discharges (IEDs) which are considered as expressions of pathological off-line neural plasticity in the central nervous system. Here we investigated the relationship between thalamic sleep spindles, IEDs and ripples in the anterior and mediodorsal nuclei (ANT and MD) of epilepsy patients. Whole-night LFP from the ANT and MD were co-registered with scalp EEG/polysomnography by using externalized leads in 15 epilepsy patients undergoing Deep Brain Stimulation protocol. Slow (~12 Hz) and fast (~14 Hz) sleep spindles were present in the human ANT and MD. Roughly, one third of thalamic sleep spindles were associated with IEDs or ripples. Both IED- and ripple-associated spindles were longer than pure spindles. IED-associated thalamic sleep spindles were characterized by broadband increase in thalamic and cortical activity, both below and above the spindle frequency range, whereas ripple-associated thalamic spindles exceeded pure spindles in terms of 80-200 Hz thalamic, but not cortical activity as indicated by time-frequency analysis. These result show that thalamic spindles coupled with IEDs are reflected at the scalp slow and beta-gamma oscillation as well. IED density during sleep spindles in the MD, but not in the ANT was identified as correlates of years spent with epilepsy, whereas no signs of pathological processes were correlated with measures of ripple and spindle association. Furthermore, the density of ripple-associated sleep spindles in the ANT showed a positive correlation with general intelligence. Our findings indicate the complex and multifaceted role of the human thalamus in sleep spindle-related physiological and pathological neural plasticity.

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