Seizure onset predicts its type

Donos, Cristian; Mălîia, Mihai Dragoş; Dümpelmann, Matthias; Schulze‐Bonhage, Andreas

doi:10.1111/epi.13997

Cited by 17 publications

(16 citation statements)

References 35 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This study also provides evidence that clinical seizure subtypes can be predicted at seizure onset by studying the neural activity within and outside the SOZ . This evidence is in contrast to conventional teaching that seizure propagation and not onset determines seizure subtypes.…”

Section: Discussionmentioning

confidence: 68%

Spectral organization of focal seizures within the thalamotemporal network

Pizarro

Ilyas

Chaitanya

et al. 2019

Ann Clin Transl Neurol

View full text Add to dashboard Cite

Objective To investigate dynamic changes in neural activity between the anterior nucleus of the thalamus (ANT) and the seizure onset zone (SOZ) in patients with drug‐resistant temporal lobe epilepsy (TLE) based on anatomic location, seizure subtype, and state of vigilance (SOV). Methods Eleven patients undergoing stereoelectroencephalography for seizure localization were recruited prospectively for local field potential (LFP) recording directly from the ANT. The SOZ was identified using line length and epileptogenicity index. Changes in power spectral density (PSD) were compared between the two anatomic sites as seizures (N = 53) transitioned from interictal baseline to the posttermination stage. Results At baseline, the thalamic LFPs were significantly lower and distinct from the SOZ with the presence of higher power in the fast ripple band (P < 0.001). Temporal changes in ictal power of neural activity within ANT mimic those of the SOZ, are increased significantly at seizure onset (P < 0.05), and are distinct for seizures that impaired awareness or that secondarily generalized (P < 0.05). The onset of seizure was preceded by a decrease in the mean power spectral density (PSD) in ANT and SOZ (P < 0.05). Neural activity correlated with different states of vigilance at seizure onset within the ANT but not in the SOZ (P = 0.005). Interpretation The ANT can be recruited at the onset of mesial temporal lobe seizures, and the recruitment pattern differs with seizure subtypes. Furthermore, changes in neural dynamics precede seizure onset and are widespread to involve temporo‐thalamic regions, thereby providing an opportunity to intervene early with closed‐loop DBS.

show abstract

Section: Discussionmentioning

confidence: 68%

Spectral organization of focal seizures within the thalamotemporal network

Pizarro

Ilyas

Chaitanya

et al. 2019

Ann Clin Transl Neurol

View full text Add to dashboard Cite

show abstract

“…Knowledge of parameter transitions within neural models can increase the information extracted from EEG, informing new hypotheses of seizure mechanisms and guiding clinical practice. There is some evidence to suggest that the clinical classification of a seizure is predictable soon after its onset [ 51 ], in other words, the evolution of a seizure may be somewhat predetermined. Our results support the existence of predictable seizure types, and provide additional metrics (based on the parameters of a neural model) that may extend our understanding of traditional seizure types.…”

Section: Discussionmentioning

confidence: 99%

Seizure pathways: A model-based investigation

et al. 2018

View full text Add to dashboard Cite

We present the results of a model inversion algorithm for electrocorticography (ECoG) data recorded during epileptic seizures. The states and parameters of neural mass models were tracked during a total of over 3000 seizures from twelve patients with focal epilepsy. These models provide an estimate of the effective connectivity within intracortical circuits over the time course of seizures. Observing the dynamics of effective connectivity provides insight into mechanisms of seizures. Estimation of patients seizure dynamics revealed: 1) a highly stereotyped pattern of evolution for each patient, 2) distinct sub-groups of onset mechanisms amongst patients, and 3) different offset mechanisms for long and short seizures. Stereotypical dynamics suggest that, once initiated, seizures follow a deterministic path through the parameter space of a neural model. Furthermore, distinct sub-populations of patients were identified based on characteristic motifs in the dynamics at seizure onset. There were also distinct patterns between long and short duration seizures that were related to seizure offset. Understanding how these different patterns of seizure evolution arise may provide new insights into brain function and guide treatment for epilepsy, since specific therapies may have preferential effects on the various parameters that could potentially be individualized. Methods that unite computational models with data provide a powerful means to generate testable hypotheses for further experimental research. This work provides a demonstration that the hidden connectivity parameters of a neural mass model can be dynamically inferred from data. Our results underscore the power of theoretical models to inform epilepsy management. It is our hope that this work guides further efforts to apply computational models to clinical data.

show abstract

“…For example, a single prolonged convulsive seizure may cause greater morbidity than a cluster of brief focal aware seizures. Although methods to predict seizure timing are emerging, 5 methods to anticipate seizure severity are still lacking 6,7 …”

Section: Introductionmentioning

confidence: 99%

“…Although methods to predict seizure timing are emerging, 5 methods to anticipate seizure severity are still lacking. 6,7 A common clinical observation made by patients is that longer periods of seizure freedom appear to give rise to more severe seizures. 6 If time since last seizure indeed informs the severity of future seizures, seizure forecasting models could potentially provide information about the likely morbidity of future seizures.…”

Section: Introductionmentioning

confidence: 99%

Evidence for long memory in focal seizure duration

2021

View full text Add to dashboard Cite

Objective A major source of disability for people with epilepsy involves uncertainty surrounding seizure timing and severity. Although patients often report that long seizure‐free intervals are followed by more severe seizures, there is little experimental evidence supporting this observation. Optimal characterization of seizure severity is debated; however, seizure duration is associated with seizure type and can be quantified in electrographic recordings as a limited proxy of clinical seizure severity. Here, using chronic intracranial electroencephalography (cEEG), we investigate the relationship between interseizure interval (ISI) and duration of the subsequent seizure. Methods We performed a retrospective analysis of 14 subjects implanted with a responsive neurostimulation device (RNS System) that provides cEEG, including timestamps of electrographic seizures. We determined seizure durations for isolated seizures and for representative seizures from clusters determined through unsupervised methods. For each subject, the median ISI preceding long‐duration seizures, defined as the top quintile of seizure durations, was compared with the median ISI preceding seizures with durations in the residual quintiles. In a group analysis, the mean seizure duration and the proportion of long‐duration seizures were compared across ISI categories representing different lengths. Results For 5 out of 14 subjects (36%), the median ISI preceding long‐duration seizures was significantly greater than the median ISI preceding shorter‐duration seizures. In the group analysis, when ISI was categorized by length, the proportion of long‐duration seizures within the high ISI category was significantly higher than that of the low ISI category (P < 0.001). Significance By leveraging cEEG and accounting for seizure clusters, we found that the likelihood of long‐duration seizures positively correlates with ISI length, in a subset of individuals. These findings corroborate anecdotal clinical observations and support the existence of capacitor‐like long memory processes governing the dynamics of focal seizures.

show abstract

Seizure onset predicts its type

Abstract: These findings provide the basis for developing systems for specific early warning of patients and health care providers, and for targeting EEG-based closed-loop intervention approaches to electrographic patterns with a high inherent risk to become clinically manifest.

Cited by 17 publications

References 35 publications

Spectral organization of focal seizures within the thalamotemporal network

Spectral organization of focal seizures within the thalamotemporal network

Seizure pathways: A model-based investigation

Evidence for long memory in focal seizure duration

Contact Info

Product

Resources

About