scholarly journals Spatiotemporal Patterns of High-Frequency Activity (80-170 Hz) in Long-term Intracranial EEG

Neurology ◽  
2020 ◽  
pp. 10.1212/WNL.0000000000011408
Author(s):  
Zhuying Chen ◽  
David B. Grayden ◽  
Anthony N. Burkitt ◽  
Udaya Seneviratne ◽  
Wendyl J. D'Souza ◽  
...  
Keyword(s):  
Circadian Rhythms ◽  
High Frequency ◽  
Focal Epilepsy ◽  
High Amplitude ◽  
Oscillatory Behavior ◽  
Patient Specific ◽  
Intracranial Eeg ◽  
Large Variability ◽  
High Frequency Activity

Objective:To determine the utility of high-frequency activity (HFA) and epileptiform spikes as biomarkers for epilepsy, we examined the variability in their rates and locations using long-term ambulatory intracranial EEG (iEEG) recordings.Methods:This study used continuous iEEG recordings obtained over an average of 1.4 years from 15 patients with drug-resistant focal epilepsy. HFA was defined as 80-170 Hz events with amplitudes clearly larger than the background, which was automatically detected using a custom algorithm. The automatically detected HFA was compared with visually annotated high-frequency oscillations (HFOs). The variations of HFA rates were compared with spikes and seizures on patient-specific and electrode-specific bases.Results:HFA included manually annotated HFOs and high-amplitude events occurring in the 80-170 Hz range without observable oscillatory behavior. HFA and spike rates had high amounts of intra- and inter-patient variability. Rates of HFA and spikes had large variability after electrode implantation in most of the patients. Locations of HFA and/or spikes varied up to weeks in more than one-third of the patients. Both HFA and spike rates showed strong circadian rhythms in all patients and some also showed multiday cycles. Furthermore, the circadian patterns of HFA and spike rates had patient-specific correlations with seizures, which tended to vary across electrodes.Conclusions:Analysis of HFA and epileptiform spikes should consider post-implantation variability. HFA and epileptiform spikes, like seizures, show circadian rhythms. However, the circadian profiles can vary spatially within patients and their correlations to seizures are patient-specific.

scholarly journals Spatiotemporal patterns of high-frequency activity (80-170 Hz) in long-term intracranial EEG

2020 ◽  
Author(s):  
Zhuying Chen ◽  
David B. Grayden ◽  
Anthony N. Burkitt ◽  
Udaya Seneviratne ◽  
Wendyl J. D’Souza ◽  
...  
Keyword(s):  
Circadian Rhythms ◽  
High Frequency ◽  
Focal Epilepsy ◽  
Patient Specific ◽  
Intracranial Eeg ◽  
Electrode Implantation ◽  
High Frequency Oscillations ◽  
Total Data ◽  
High Frequency Activity

AbstractObjectiveTo assess the variability in the rates and locations of high-frequency activity (HFA) and epileptiform spikes after electrode implantation, and to examine the long-term patterns of HFA using ambulatory intracranial EEG (iEEG) recordings.MethodsContinuous iEEG recordings obtained over an average of 1.4 years from 15 patients with drug-resistant focal epilepsy were used in this study. HFA was defined as high-frequency events with amplitudes clearly larger than the background, which was automatically detected using a custom algorithm. High-frequency oscillations (HFOs) were also visually annotated by three neurologists in randomly sampled segments of the total data. The automatically detected HFA was compared with the visually marked HFOs. The variations of HFA rates were compared with spikes and seizures on patient-specific and electrode-specific bases.ResultsHFA was a more general event that encompassed HFOs manually annotated by different reviewers. HFA and spike rates had high amounts of intra- and inter-patient variability. The rates and locations of HFA and spikes took up to weeks to stabilize after electrode implantation in some patients. Both HFA and spike rates showed strong circadian rhythms in all patients and some also showed multiday cycles. Furthermore, the circadian patterns of HFA and spike rates had patient-specific correlations with seizures, which tended to vary across electrodes.ConclusionsAnalysis of HFA and epileptiform spikes should account for post-implantation variability. Like seizures, HFA and epileptiform spikes show circadian rhythms. However, the circadian profiles can vary spatially within patients and their correlations to seizures are patient-specific.

Dynamic Spectral Imaging: Online and Offline Functional Brain Mapping Using High-Frequency Activity [50–150 Hz] in SEEG

2018 ◽  
pp. 453-464
Author(s):  
Jean-Philippe Lachaux
Keyword(s):  
High Frequency ◽  
Large Scale ◽  
Human Cognition ◽  
Gamma Activity ◽  
Intracranial Eeg ◽  
Cortical Dynamics ◽  
Functional Brain Mapping ◽  
High Gamma ◽  
High Frequency Activity ◽  
Eeg Recordings

At the end of the twentieth century, a handful of research groups discovered that neural processing leaves a characteristic signature in intracranial EEG recordings: an increase of power in a broad frequency range above 50 Hz, dubbed ‘high-gamma’ of high-frequency activity ([50–150 Hz]). Since then, intracranial EEG research on human cognition has focused primarily on high-gamma activity to reveal the large-scale cortical dynamics of most major cognitive functions, not only offline in well-controlled paradigms, but also online, while patients freely interact with their environment. This chapter introduces that approach, including its recent extension to task-induced neural activity suppressions and functional connectivity mapping, and its clinical application to minimize cognitive deficits induced by epilepsy surgery.

scholarly journals Slow modulations of high-frequency activity (40–140 Hz) discriminate preictal changes in human focal epilepsy

2014 ◽  
Vol 4 (1) ◽  
Author(s):  
C. Alvarado-Rojas ◽  
M. Valderrama ◽  
A. Fouad-Ahmed ◽  
H. Feldwisch-Drentrup ◽  
M. Ihle ◽  
...  
Keyword(s):  
High Frequency ◽  
Focal Epilepsy ◽  
High Frequency Activity

scholarly journals Thalamocortical dysrhythmia in intraoperative recordings of focal epilepsy

2019 ◽  
Vol 121 (6) ◽  
pp. 2020-2027 ◽  
Author(s):  
Daniel J. Martire ◽  
Simeon Wong ◽  
Mirriam Mikhail ◽  
Ayako Ochi ◽  
Hiroshi Otsubo ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
High Frequency ◽  
Large Scale ◽  
Focal Epilepsy ◽  
Critical Role ◽  
Epileptogenic Zone ◽  
Thalamocortical Dysrhythmia ◽  
High Frequency Activity ◽  
Frequency Coupling ◽  
Cross Frequency Coupling

Resonant interactions between the thalamus and cortex subserve a critical role for maintenance of consciousness as well as cognitive functions. In states of abnormal thalamic inhibition, thalamocortical dysrhythmia (TCD) has been described. The characteristics of TCD include a slowing of resting oscillations, ectopic high-frequency activity, and increased cross-frequency coupling. Here, we demonstrate the presence of TCD in four patients who underwent resective epilepsy surgery with chronically implanted electrodes under anesthesia, continuously recording activity from brain regions at the periphery of the epileptogenic zone before and after resection. Following resection, we report an acceleration of the large-scale network resting frequency coincident with decreases in cross-frequency phase-amplitude coupling. Interregional functional connectivity in the surrounding cortex was also increased following resection of the epileptogenic focus. These findings provide evidence for the presence of TCD in focal epilepsy and highlight the importance of reciprocal thalamocortical oscillatory interactions in defining novel biomarkers for resective surgeries. NEW & NOTEWORTHY Thalamocortical dysrhythmia (TCD) occurs in the context of thalamic dysfacilitation and is characterized by slowing of resting oscillations, ectopic high-frequency activity, and cross-frequency coupling. We provide evidence for TCD in focal epilepsy by studying electrophysiological changes occurring at the periphery of the resection margin. We report acceleration of resting activity coincident with decreased cross-frequency coupling and increased functional connectivity. The study of TCD in epilepsy has implications as a biomarker and therapeutic target.

scholarly journals Characterizing the role of the structural connectome in seizure dynamics

Brain ◽  
2019 ◽  
Vol 142 (7) ◽  
pp. 1955-1972 ◽  
Author(s):  
Preya Shah ◽  
Arian Ashourvan ◽  
Fadi Mikhail ◽  
Adam Pines ◽  
Lohith Kini ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Structure Function ◽  
Focal Epilepsy ◽  
Diffusion Imaging ◽  
Structural Connectivity ◽  
Patient Specific ◽  
High Angular Resolution ◽  
Intracranial Eeg ◽  
Structural Connectome ◽  
The Relationship

Abstract How does the human brain’s structural scaffold give rise to its intricate functional dynamics? This is a central question in translational neuroscience that is particularly relevant to epilepsy, a disorder affecting over 50 million subjects worldwide. Treatment for medication-resistant focal epilepsy is often structural—through surgery or laser ablation—but structural targets, particularly in patients without clear lesions, are largely based on functional mapping via intracranial EEG. Unfortunately, the relationship between structural and functional connectivity in the seizing brain is poorly understood. In this study, we quantify structure-function coupling, specifically between white matter connections and intracranial EEG, across pre-ictal and ictal periods in 45 seizures from nine patients with unilateral drug-resistant focal epilepsy. We use high angular resolution diffusion imaging (HARDI) tractography to construct structural connectivity networks and correlate these networks with time-varying broadband and frequency-specific functional networks derived from coregistered intracranial EEG. Across all frequency bands, we find significant increases in structure-function coupling from pre-ictal to ictal periods. We demonstrate that short-range structural connections are primarily responsible for this increase in coupling. Finally, we find that spatiotemporal patterns of structure-function coupling are highly stereotyped for each patient. These results suggest that seizures harness the underlying structural connectome as they propagate. Mapping the relationship between structural and functional connectivity in epilepsy may inform new therapies to halt seizure spread, and pave the way for targeted patient-specific interventions.

scholarly journals Visualization of Phase-Amplitude Coupling Using Rhythmic High-Frequency Activity

2020 ◽  
Author(s):  
Hiroaki Hashimoto ◽  
Hui Ming Khoo ◽  
Takufumi Yanagisawa ◽  
Naoki Tani ◽  
Satoru Oshino ◽  
...  
Keyword(s):  
High Frequency ◽  
Focal Epilepsy ◽  
Low Frequency ◽  
Θ Rhythm ◽  
Human Epilepsy ◽  
High Frequency Activity ◽  
Phase Amplitude ◽  
Intracranial Electrode ◽  
Intracranial Electrodes ◽  
Frequency Phase

AbstractObjectiveHigh-frequency activities (HFAs) and phase-amplitude coupling (PAC) are gaining attention as key neurophysiological biomarkers for studying human epilepsy. We aimed to clarify and visualize how HFAs are modulated by the phase of low-frequency bands during seizures.MethodsWe used intracranial electrodes to record seizures of symptomatic focal epilepsy (15 seizures in seven patients). Ripples (80–250 Hz), as representative of HFAs, were evaluated along with PAC. The synchronization index (SI), representing PAC, was used to analyze the coupling between the amplitude of ripples and the phase of lower frequencies. We created a video in which the intracranial electrode contacts were represented by circles that were scaled linearly to the power changes of ripple.ResultsThe main low frequency band modulating ictal-ripple activities was the θ band (4–8 Hz), and after completion of ictal-ripple burst, δ (1–4 Hz)-ripple PAC occurred. The video showed that fluctuation of the diameter of these circles indicated the rhythmic changes during significant high values of θ-ripple PAC.ConclusionsWe inferred that ripple activities occurring during seizure evolution were modulated by θ rhythm. In addition, we concluded that rhythmic circles’ fluctuation presented in the video represents the PAC phenomenon. Our video is thus a useful tool for understanding how ripple activity is modulated by the low-frequency phase in relation with PAC.

scholarly journals How sensitive is functional connectivity to electrode resampling on intracranial EEG? Implications for personalized network models in drug-resistant epilepsy

2019 ◽  
Author(s):  
Erin C. Conrad ◽  
John M. Bernabei ◽  
Lohith G. Kini ◽  
Preya Shah ◽  
Fadi Mikhail ◽  
...  
Keyword(s):  
Focal Epilepsy ◽  
Network Models ◽  
Local Network ◽  
Patient Specific ◽  
Intracranial Eeg ◽  
Targeted Interventions ◽  
Depth Electrodes ◽  
Intracranial Electrode ◽  
Network Metrics ◽  
Incomplete Sampling

AbstractFocal epilepsy is a clinical condition arising from disordered brain networks. Network models hold promise to map these networks, localize seizure generators, and inform targeted interventions to control seizures. However, incomplete sampling of epileptic brain due to sparse placement of intracranial electrodes may profoundly affect model results. In this study, we evaluate the robustness of several published network measures applied to intracranial electrode recordings and propose an algorithm, using network resampling, to determine confidence in model results. We retrospectively subsampled intracranial EEG data from 28 patients who were implanted with grid, strip, and depth electrodes during evaluation for epilepsy surgery. We recalculated global and local network metrics after both randomly and systematically resampling subsets of intracranial EEG electrode contacts. We found that sensitivity to incomplete sampling varied significantly across network metrics, and that this sensitivity was independent of the distance of removed contacts from the seizure onset zone. We present an algorithm, using random resampling, to compute patient-specific confidence intervals for network localizations on both global and nodal network statistics. Our findings highlight the difference in robustness between commonly used network metrics and provide tools to assess confidence in intracranial network localization. We present these techniques as an important step toward assessing the accuracy of intracranial electrode implants and translating personalized network models of seizures into rigorous, quantitative approaches to invasive therapy.

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