scholarly journals Interictal epileptiform discharges shape large-scale intercortical communication

Brain ◽  
2019 ◽  
Vol 142 (11) ◽  
pp. 3502-3513 ◽  
Author(s):  
Prawesh Dahal ◽  
Naureen Ghani ◽  
Adeen Flinker ◽  
Patricia Dugan ◽  
Daniel Friedman ◽  
...  
Keyword(s):  
Large Scale ◽  
Focal Epilepsy ◽  
Brain Dysfunction ◽  
Normal Brain ◽  
Brain Rhythms ◽  
Epileptiform Discharges ◽  
Interictal Epileptiform Discharges

Focal epilepsy is associated with large-scale brain dysfunction. Dahal et al. reveal that interictal epileptiform discharges modulate normal brain rhythms in regions beyond the epileptic network, potentially impairing processes that rely heavily upon intercortical communication, such as cognition and memory.

scholarly journals The Oscillatory Basis of Working Memory Function and Dysfunction in Epilepsy

2021 ◽  
Vol 14 ◽  
Author(s):  
Olivia N. Arski ◽  
Julia M. Young ◽  
Mary-Lou Smith ◽  
George M. Ibrahim
Keyword(s):  
Working Memory ◽  
High Frequency ◽  
Large Scale ◽  
Memory Function ◽  
Epileptic Activity ◽  
Functional Roles ◽  
High Frequency Oscillations ◽  
Epileptiform Discharges ◽  
Interictal Epileptiform Discharges

Working memory (WM) deficits are pervasive co-morbidities of epilepsy. Although the pathophysiological mechanisms underpinning these impairments remain elusive, it is thought that WM depends on oscillatory interactions within and between nodes of large-scale functional networks. These include the hippocampus and default mode network as well as the prefrontal cortex and frontoparietal central executive network. Here, we review the functional roles of neural oscillations in subserving WM and the putative mechanisms by which epilepsy disrupts normative activity, leading to aberrant oscillatory signatures. We highlight the particular role of interictal epileptic activity, including interictal epileptiform discharges and high frequency oscillations (HFOs) in WM deficits. We also discuss the translational opportunities presented by greater understanding of the oscillatory basis of WM function and dysfunction in epilepsy, including potential targets for neuromodulation.

scholarly journals Unsupervised Learning of Spatiotemporal Interictal Discharges in Focal Epilepsy

Neurosurgery ◽  
2017 ◽  
Vol 83 (4) ◽  
pp. 683-691 ◽  
Author(s):  
Maxime O Baud ◽  
Jonathan K Kleen ◽  
Gopala K Anumanchipalli ◽  
Liberty S Hamilton ◽  
Yee-Leng Tan ◽  
...  
Keyword(s):  
Unsupervised Learning ◽  
Learning Algorithm ◽  
Focal Epilepsy ◽  
Basis Functions ◽  
Spatiotemporal Pattern ◽  
Operating Characteristics ◽  
Temporal Dimension ◽  
Epileptiform Discharges ◽  
Interictal Epileptiform Discharges ◽  
Propagation Network

Abstract BACKGROUND Interictal epileptiform discharges are an important biomarker for localization of focal epilepsy, especially in patients who undergo chronic intracranial monitoring. Manual detection of these pathophysiological events is cumbersome, but is still superior to current rule-based approaches in most automated algorithms. OBJECTIVE To develop an unsupervised machine-learning algorithm for the improved, automated detection and localization of interictal epileptiform discharges based on spatiotemporal pattern recognition. METHODS We decomposed 24 h of intracranial electroencephalography signals into basis functions and activation vectors using non-negative matrix factorization (NNMF). Thresholding the activation vector and the basis function of interest detected interictal epileptiform discharges in time and space (specific electrodes), respectively. We used convolutive NNMF, a refined algorithm, to add a temporal dimension to basis functions. RESULTS The receiver operating characteristics for NNMF-based detection are close to the gold standard of human visual-based detection and superior to currently available alternative automated approaches (93% sensitivity and 97% specificity). The algorithm successfully identified thousands of interictal epileptiform discharges across a full day of neurophysiological recording and accurately summarized their localization into a single map. Adding a temporal window allowed for visualization of the archetypal propagation network of these epileptiform discharges. CONCLUSION Unsupervised learning offers a powerful approach towards automated identification of recurrent pathological neurophysiological signals, which may have important implications for precise, quantitative, and individualized evaluation of focal epilepsy.

scholarly journals Interictal epileptiform discharges in focal epilepsy are preceded by a gradual increase in low-frequency oscillations

2020 ◽  
Author(s):  
Karin Westin ◽  
Gerald Cooray ◽  
Daniel Lundqvist
Keyword(s):  
Gradual Increase ◽  
Focal Epilepsy ◽  
Brain Activity ◽  
Low Frequency ◽  
Negative Influence ◽  
Oscillatory Activity ◽  
Brain State ◽  
Negative Effects ◽  
Epileptiform Discharges ◽  
Interictal Epileptiform Discharges

AbstractEpilepsy is characterized by recurrent seizures and may also have negative influence on cognitive function. In addition to ictal activity, the epileptic brain also gives rise to interictal epileptiform discharges (IEDs). These IEDs constitute the diagnostic hallmark of epilepsy, and have been linked to impaired memory formation and negative effects on neurodevelopment. The neurophysiological dynamics underlying IED generation seem to resemble those underlying seizure development. Understanding the neurophysiological characteristics surrounding and preceding IED development would hence provide valuable insights into the pathophysiology of the epileptic brain. In order to improve this understanding, we aimed to characterize the dynamical activity changes that occurs immediately prior to an IED onset. We used magnetoencephalography (MEG) recordings from nine focal epilepsy patients to characterize the oscillatory activity preceding IED onsets. Our results showed a systematic and gradual increase in oscillatory delta and theta band activity (1-4 Hz and 4-8 Hz, respectively) during this pre-IED interval, reaching a maximum power at IED onset. These results indicate that the pre-IED brain state is characterized by a gradual synchronization that culminates in the neuronal hypersynchronization underlying IEDs. We discuss how IED generation might resemble seizure development, where physiological brain activity similarly undergoes a gradual synchronization that terminates in seizure onset.

scholarly journals Musical components important for the Mozart K448 effect in epilepsy

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Robert J. Quon ◽  
Michael A. Casey ◽  
Edward J. Camp ◽  
Stephen Meisenhelter ◽  
Sarah A. Steimel ◽  
...  
Keyword(s):  
Refractory Epilepsy ◽  
Focal Epilepsy ◽  
Epileptiform Activity ◽  
Brain Regions ◽  
Original Version ◽  
Pharmacological Intervention ◽  
Theta Power ◽  
Epileptiform Discharges ◽  
Interictal Epileptiform Discharges ◽  
Insight Into

AbstractThere is growing evidence for the efficacy of music, specifically Mozart’s Sonata for Two Pianos in D Major (K448), at reducing ictal and interictal epileptiform activity. Nonetheless, little is known about the mechanism underlying this beneficial “Mozart K448 effect” for persons with epilepsy. Here, we measured the influence that K448 had on intracranial interictal epileptiform discharges (IEDs) in sixteen subjects undergoing intracranial monitoring for refractory focal epilepsy. We found reduced IEDs during the original version of K448 after at least 30-s of exposure. Nonsignificant IED rate reductions were witnessed in all brain regions apart from the bilateral frontal cortices, where we observed increased frontal theta power during transitions from prolonged musical segments. All other presented musical stimuli were associated with nonsignificant IED alterations. These results suggest that the “Mozart K448 effect” is dependent on the duration of exposure and may preferentially modulate activity in frontal emotional networks, providing insight into the mechanism underlying this response. Our findings encourage the continued evaluation of Mozart’s K448 as a noninvasive, non-pharmacological intervention for refractory epilepsy.

Diagnostic yield of seizure recordings and neuroimaging in patients with focal epilepsy without interictal epileptiform discharges

2020 ◽  
Vol 112 ◽  
pp. 107468
Author(s):  
Minori Suzuki ◽  
Kazutaka Jin ◽  
Yu Kitazawa ◽  
Mayu Fujikawa ◽  
Yosuke Kakisaka ◽  
...  
Keyword(s):  
Focal Epilepsy ◽  
Diagnostic Yield ◽  
Epileptiform Discharges ◽  
Interictal Epileptiform Discharges

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 Synaptic Reshaping and Neuronal Outcomes in the Temporal Lobe Epilepsy

2021 ◽  
Vol 22 (8) ◽  
pp. 3860
Author(s):  
Elisa Ren ◽  
Giulia Curia
Keyword(s):  
Animal Models ◽  
Temporal Lobe Epilepsy ◽  
Temporal Lobe ◽  
Current Knowledge ◽  
Focal Epilepsy ◽  
Ex Vivo ◽  
Hippocampal Sclerosis ◽  
Control Group ◽  
Epileptogenic Zone ◽  
Epileptiform Discharges

Temporal lobe epilepsy (TLE) is one of the most common types of focal epilepsy, characterized by recurrent spontaneous seizures originating in the temporal lobe(s), with mesial TLE (mTLE) as the worst form of TLE, often associated with hippocampal sclerosis. Abnormal epileptiform discharges are the result, among others, of altered cell-to-cell communication in both chemical and electrical transmissions. Current knowledge about the neurobiology of TLE in human patients emerges from pathological studies of biopsy specimens isolated from the epileptogenic zone or, in a few more recent investigations, from living subjects using positron emission tomography (PET). To overcome limitations related to the use of human tissue, animal models are of great help as they allow the selection of homogeneous samples still presenting a more various scenario of the epileptic syndrome, the presence of a comparable control group, and the availability of a greater amount of tissue for in vitro/ex vivo investigations. This review provides an overview of the structural and functional alterations of synaptic connections in the brain of TLE/mTLE patients and animal models.

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.

Sign in / Sign up

Export Citation Format

Share Document