Features of intracranial interictal epileptiform discharges associated with memory encoding

Epilepsia ◽  
2021 ◽  
Author(s):  
Robert J. Quon ◽  
Edward J. Camp ◽  
Stephen Meisenhelter ◽  
Yinchen Song ◽  
Sarah A. Steimel ◽  
...  
Keyword(s):  
Memory Encoding ◽  
Epileptiform Discharges ◽  
Interictal Epileptiform Discharges ◽  
With Memory

Prevalence of Interictal Epileptiform Discharges in Children Less Than One Year of Age Referred for Polysomnography

2015 ◽  
Vol 55 (2) ◽  
pp. 122-132
Author(s):  
Adetayo Adeleye ◽  
Alice W. Ho ◽  
Alberto Nettel-Aguirre ◽  
Valerie Kirk ◽  
Jeffrey Buchhalter
Keyword(s):  
Epileptiform Discharges ◽  
Interictal Epileptiform Discharges ◽  
One Year

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.

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.

Deep learning for robust detection of interictal epileptiform discharges

2021 ◽  
Author(s):  
David Geng ◽  
Ayham Alkhachroum ◽  
Manuel Melo Bicchi ◽  
Jonathan Jagid ◽  
Iahn Cajigas ◽  
...  
Keyword(s):  
Deep Learning ◽  
Robust Detection ◽  
Epileptiform Discharges ◽  
Interictal Epileptiform Discharges

scholarly journals The first-hour-of-the-day sleep EEG reliably identifies interictal epileptiform discharges during long-term video-EEG monitoring

Seizure ◽  
2018 ◽  
Vol 63 ◽  
pp. 48-51 ◽  
Author(s):  
Xi Liu ◽  
Naoum P. Issa ◽  
Sandra Rose ◽  
Shasha Wu ◽  
Taixin Sun ◽  
...  
Keyword(s):  
Sleep Eeg ◽  
Eeg Monitoring ◽  
Epileptiform Discharges ◽  
Interictal Epileptiform Discharges ◽  
Video Eeg
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