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.

High-Frequency Oscillations and Epileptogenic Network

2021 ◽  
Vol 19 ◽  
Author(s):  
Xiaonan Li ◽  
Herui Zhang ◽  
Huanling Lai ◽  
Jiaoyang Wang ◽  
Wei Wang ◽  
...  
Keyword(s):  
High Frequency ◽  
Large Scale ◽  
High Frequency Oscillation ◽  
Epileptogenic Zone ◽  
Network Development ◽  
High Frequency Oscillations ◽  
Frequency Coupling ◽  
Different Characteristics ◽  
The Relationship ◽  
Cross Frequency Coupling

: Epilepsy is a network disease caused by aberrant neocortical large-scale connectivity spanning regions on the scale of several centimeters. High-frequency oscillations, characterized by the 80–600 Hz signals in electroencephalography, have been proven to be a promising biomarker of epilepsy that can be used in assessing the severity and susceptibility of epilepsy as well as the location of the epileptogenic zone. However, the presence of a high-frequency oscillation network remains a topic of debate as high-frequency oscillations have been previously thought to be incapable of propagation, and the relationship between high-frequency oscillations and the epileptogenic network has rarely been discussed. Some recent studies reported that high-frequency oscillations may behave like networks that are closely relevant to the epileptogenic network. Pathological high-frequency oscillations are network-driven phenomena and elucidate epileptogenic network development; high-frequency oscillations show different characteristics coincident with the epileptogenic network dynamics, and cross-frequency coupling between high-frequency oscillations and other signals may mediate the generation and propagation of abnormal discharges across the network.

Neocortical pathological high-frequency oscillations are associated with frequency-dependent alterations in functional network topology

2013 ◽  
Vol 110 (10) ◽  
pp. 2475-2483 ◽  
Author(s):  
George M. Ibrahim ◽  
Ryan Anderson ◽  
Tomoyuki Akiyama ◽  
Ayako Ochi ◽  
Hiroshi Otsubo ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
High Frequency ◽  
Phase Locking ◽  
Critical Role ◽  
Intractable Epilepsy ◽  
Network Connectivity ◽  
Relative Increase ◽  
High Frequencies ◽  
High Frequency Oscillations ◽  
Cortical Regions

Synchronization of neural oscillations is thought to integrate distributed neural populations into functional cell assemblies. Epilepsy is widely regarded as a disorder of neural synchrony. Knowledge is scant, however, regarding whether ictal changes in synchrony involving epileptogenic cortex are expressed similarly across various frequency ranges. Cortical regions involved in epileptic networks also exhibit pathological high-frequency oscillations (pHFOs, >80 Hz), which are increasingly utilized as biomarkers of epileptogenic tissue. It is uncertain how pHFO amplitudes are related to epileptic network connectivity. By calculating phase-locking values among intracranial electrodes implanted in children with intractable epilepsy, we constructed ictal connectivity networks and performed graph theoretical analysis to characterize their network properties at distinct frequency bands. Ictal data from 17 children were analyzed with a hierarchical mixed-effects model adjusting for patient-level covariates. Epileptogenic cortex was defined in two ways: 1) a hypothesis-driven method using the visually defined seizure-onset zone and 2) a data-agnostic method using the high-frequency amplitude of each electrode. Epileptogenic cortex exhibited a logarithmic decrease in interregional functional connectivity at high frequencies (>30 Hz) during seizure initiation and propagation but not at termination. At slower frequencies, conversely, epileptogenic cortex expressed a relative increase in functional connectivity. Our findings suggest that pHFOs reflect epileptogenic network interactions, yielding theoretical support for their utility in the presurgical evaluation of intractable epilepsy. The view that abnormal network synchronization plays a critical role in ictogenesis and seizure dynamics is supported by the observation that functional isolation of epileptogenic cortex at high frequencies is absent at seizure termination.

scholarly journals Pannexin-1 Deficiency Decreases Epileptic Activity in Mice

2020 ◽  
Vol 21 (20) ◽  
pp. 7510 ◽  
Author(s):  
Mark S. Aquilino ◽  
Paige Whyte-Fagundes ◽  
Mark K. Lukewich ◽  
Liang Zhang ◽  
Berj L. Bardakjian ◽  
...  
Keyword(s):  
Neuronal Excitability ◽  
Critical Role ◽  
Epileptic Activity ◽  
Channel Blockers ◽  
Systemic Injection ◽  
Pannexin 1 ◽  
Severe Stage ◽  
Frequency Coupling ◽  
Epilepsy Models ◽  
Cross Frequency Coupling

Objective: Pannexin-1 (Panx1) is suspected of having a critical role in modulating neuronal excitability and acute neurological insults. Herein, we assess the changes in behavioral and electrophysiological markers of excitability associated with Panx1 via three distinct models of epilepsy. Methods Control and Panx1 knockout C57Bl/6 mice of both sexes were monitored for their behavioral and electrographic responses to seizure-generating stimuli in three epilepsy models—(1) systemic injection of pentylenetetrazol, (2) acute electrical kindling of the hippocampus and (3) neocortical slice exposure to 4-aminopyridine. Phase-amplitude cross-frequency coupling was used to assess changes in an epileptogenic state resulting from Panx1 deletion. Results: Seizure activity was suppressed in Panx1 knockouts and by application of Panx1 channel blockers, Brilliant Blue-FCF and probenecid, across all epilepsy models. In response to pentylenetetrazol, WT mice spent a greater proportion of time experiencing severe (stage 6) seizures as compared to Panx1-deficient mice. Following electrical stimulation of the hippocampal CA3 region, Panx1 knockouts had significantly shorter evoked afterdischarges and were resistant to kindling. In response to 4-aminopyridine, neocortical field recordings in slices of Panx1 knockout mice showed reduced instances of electrographic seizure-like events. Cross-frequency coupling analysis of these field potentials highlighted a reduced coupling of excitatory delta–gamma and delta-HF rhythms in the Panx1 knockout. Significance: These results suggest that Panx1 plays a pivotal role in maintaining neuronal hyperexcitability in epilepsy models and that genetic or pharmacological targeting of Panx1 has anti-convulsant effects.

scholarly journals Detection of cross-frequency coupling between brain areas: an extension of phase-linearity measurement

2020 ◽  
Author(s):  
Pierpaolo Sorrentino ◽  
Michele Ambrosanio ◽  
Rosaria Rucco ◽  
Joana Cabral ◽  
Leonardo L. Gollo ◽  
...  
Keyword(s):  
Large Scale ◽  
Brain Activity ◽  
A Priori ◽  
Broad Band ◽  
Main Idea ◽  
Theoretical Explanation ◽  
Frequency Synchronization ◽  
Brain Areas ◽  
Frequency Coupling ◽  
Cross Frequency Coupling

AbstractThe current paper proposes a method to estimate phase to phase cross-frequency coupling between brain areas, applied to broadband signals, without any a priori hypothesis about the frequency of the synchronized components. N:m synchronization is the only form of cross-frequency synchronization that allows the exchange of information at the time resolution of the faster signal, hence likely to play a fundamental role in large-scale coordination of brain activity. The proposed method, named cross-frequency phase linearity measurement (CF-PLM), builds and expands upon the phase linearity measurement, an iso-frequency connectivity metrics previously published by our group. The main idea lies in using the shape of the interferometric spectrum of the two analyzed signals in order to estimate the strength of cross-frequency coupling. Here, we demonstrate that the CF-PLM successfully retrieves the (different) frequencies of the original broad-band signals involved in the connectivity process. Furthermore, if the broadband signal has some frequency components that are synchronized in iso-frequency and some others that are synchronized in cross-frequency, our methodology can successfully disentangle them and describe the behaviour of each frequency component separately. We first provide a theoretical explanation of the metrics. Then, we test the proposed metric on simulated data from coupled oscillators synchronized in iso- and cross-frequency (using both Rössler and Kuramoto oscillator models), and subsequently apply it on real data from brain activity, using source-reconstructed Magnetoencephalography (MEG) data. In the synthetic data, our results show reliable estimates even in the presence of noise and limited sample sizes. In the real signals, components synchronized in cross-frequency are retrieved, together with their oscillation frequencies. All in all, our method is useful to estimate n:m synchronization, based solely on the phase of the signals (independently of the amplitude), and no a-priori hypothesis is available about the expected frequencies. Our method can be exploited to more accurately describe patterns of cross-frequency synchronization and determine the central frequencies involved in the coupling.

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.

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 Epileptogenic Zone Location of Temporal Lobe Epilepsy by Cross-Frequency Coupling Analysis

2021 ◽  
Vol 12 ◽  
Author(s):  
Xiaotong Liu ◽  
Fang Han ◽  
Rui Fu ◽  
Qingyun Wang ◽  
Guoming Luan
Keyword(s):  
Temporal Lobe Epilepsy ◽  
Temporal Lobe ◽  
Single Channel ◽  
Brain Networks ◽  
Brain Regions ◽  
Functional Network ◽  
Epileptogenic Zone ◽  
Coupling Analysis ◽  
Frequency Coupling ◽  
Cross Frequency Coupling

Epilepsy is a chronic brain disease with dysfunctional brain networks, and electroencephalography (EEG) is an important tool for epileptogenic zone (EZ) identification, with rich information about frequencies. Different frequency oscillations have different contributions to brain function, and cross-frequency coupling (CFC) has been found to exist within brain regions. Cross-channel and inter-channel analysis should be both focused because they help to analyze how epilepsy networks change and also localize the EZ. In this paper, we analyzed long-term stereo-electroencephalography (SEEG) data from 17 patients with temporal lobe epilepsy. Single-channel and cross-channel CFC features were combined to establish functional brain networks, and the network characteristics under different periods and the localization of EZ were analyzed. It was observed that theta–gamma phase amplitude coupling (PAC) within the electrodes in the seizure region increased during the ictal (p < 0.05). Theta–gamma and delta–gamma PAC of cross-channel were enhanced in the early and mid-late ictal, respectively. It was also found that there was a strong cross-frequency coupling state between channels of EZ in the functional network during the ictal, along with a more regular network than interictal. The accuracy rate of EZ localization was 82.4%. Overall, the combination of single-channel and multi-channel cross-band coupling analysis can help identify seizures and localize EZ for temporal lobe epilepsy. Rhythmic coupling reveals a relationship between the functional network and the seizure status of epilepsy.

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