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.

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 Interictal high frequency background activity as a biomarker of epileptogenic tissue

2021 ◽  
Author(s):  
Truman Stovall ◽  
Brian Hunt ◽  
Simon Glynn ◽  
William C Stacey ◽  
Stephen V Gliske
Keyword(s):  
Logistic Regression ◽  
Confidence Interval ◽  
High Frequency ◽  
High Frequency Oscillation ◽  
Epileptogenic Zone ◽  
Odds Ratios ◽  
Seizure Onset ◽  
High Frequency Oscillations ◽  
Seizure Onset Zone ◽  
Background Data

Abstract High Frequency Oscillations are very brief events that are a well-established biomarker of the epileptogenic zone, but are rare and comprise only a tiny fraction of the total recorded EEG. We hypothesize that the interictal high frequency “background” data, which has received little attention but represents the majority of the EEG record, also may contain additional, novel information for identifying the epileptogenic zone. We analyzed intracranial EEG (30–500 Hz frequency range) acquired from 24 patients who underwent resective surgery. We computed 38 quantitative features based on all usable, interictal data (63–307 hours per subject), excluding all detected high frequency oscillations. We assessed association between each feature and the seizure onset zone and resected volume using logistic regression. A pathology score per channel was also created via principle component analysis and logistic regression, using hold-out-one-patient cross validation to avoid in-sample training. Association of the pathology score with the seizure onset zone and resected volume was quantified using an asymmetry measure. Many features were associated with the seizure onset zone: 23/38 features had odds ratios >1.3 or < 0.7 and 17/38 had odds ratios different than zero with high significance (p < 0.001/39, logistic regression with Bonferroni Correction). The pathology score, the rate of high frequency oscillations, and their channel-wise product were each strongly associated with the seizure onset zone (median asymmetry > =0.44, good surgery outcome patients; median asymmetry > =0.40, patients with other outcomes; 95% confidence interval > 0.27 in both cases). The pathology score and the channel-wise product also had higher asymmetry with respect to the seizure onset zone than the high frequency oscillation rate alone (median difference in asymmetry > =0.18, 95% confidence interval >0.05). These results support that the high frequency background data contains useful information for determining the epileptogenic zone, distinct and complementary to information from detected high frequency oscillations. The concordance between the high frequency activity pathology score and the rate of high frequency oscillations appears to be a better biomarker of epileptic tissue than either measure alone.

High-Frequency Oscillations in Somatosensory System

2005 ◽  
Vol 36 (4) ◽  
pp. 278-284 ◽  
Author(s):  
Hitoshi Mochizuki ◽  
Yoshikazu Ugawa
Keyword(s):  
High Frequency ◽  
Neurological Diseases ◽  
Somatosensory System ◽  
Pyramidal Cells ◽  
High Frequency Oscillation ◽  
Medial Lemniscus ◽  
High Frequency Oscillations ◽  
Primary Sensory Cortex ◽  
Thalamocortical Projection ◽  
Deep Brain

The recent revival of interest in high-frequency oscillation (HFO) is triggered by getting an opportunity to noninvasively monitor the timing of highly synchronized and rapidly repeating population spikes generated in the human somatosensory system. HFOs could be recorded from brainstem, cuneothalamic relay neurons, thalamus, thalamocortical radiation, thalamocortical terminals and cortex with deep brain or surface electrodes, or with magnetoencephalography. Here we briefly review the HFOs at each level of somatosensory pathways. HFOs recorded at brainstem might be produced by volume conduction from oscillations of the medial lemniscus. Thalamic HFOs at around 1000 Hz frequency would be generated within the somatosensory thalamus. Cortical HFOs would be generated by at least a few different mechanisms, thalamocortical projection terminals, interneurons and pyramidal cells of the primary sensory cortex. HFOs have been studied in several ways: their modulation by arousal changes, movements or drugs, their recovery function, effects of transcranial magnetic stimulation on them and also their changes in patients with various neurological diseases.

scholarly journals High-frequency oscillations in human and monkey neocortex during the wake–sleep cycle

2016 ◽  
Vol 113 (33) ◽  
pp. 9363-9368 ◽  
Author(s):  
Michel Le Van Quyen ◽  
Lyle E. Muller ◽  
Bartosz Telenczuk ◽  
Eric Halgren ◽  
Sydney Cash ◽  
...  
Keyword(s):  
High Frequency ◽  
Large Scale ◽  
Microelectrode Array ◽  
Slow Wave Sleep ◽  
Inhibitory Neurons ◽  
Sleep Cycle ◽  
High Frequency Oscillations ◽  
Wake Patterns ◽  
Fast Oscillations ◽  
Array Recordings

Beta (β)- and gamma (γ)-oscillations are present in different cortical areas and are thought to be inhibition-driven, but it is not known if these properties also apply to γ-oscillations in humans. Here, we analyze such oscillations in high-density microelectrode array recordings in human and monkey during the wake–sleep cycle. In these recordings, units were classified as excitatory and inhibitory cells. We find that γ-oscillations in human and β-oscillations in monkey are characterized by a strong implication of inhibitory neurons, both in terms of their firing rate and their phasic firing with the oscillation cycle. The β- and γ-waves systematically propagate across the array, with similar velocities, during both wake and sleep. However, only in slow-wave sleep (SWS) β- and γ-oscillations are associated with highly coherent and functional interactions across several millimeters of the neocortex. This interaction is specifically pronounced between inhibitory cells. These results suggest that inhibitory cells are dominantly involved in the genesis of β- and γ-oscillations, as well as in the organization of their large-scale coherence in the awake and sleeping brain. The highest oscillation coherence found during SWS suggests that fast oscillations implement a highly coherent reactivation of wake patterns that may support memory consolidation during SWS.

scholarly journals The morphology of high frequency oscillations (HFO) does not improve delineating the epileptogenic zone

2016 ◽  
Vol 127 (4) ◽  
pp. 2140-2148 ◽  
Author(s):  
Sergey Burnos ◽  
Birgit Frauscher ◽  
Rina Zelmann ◽  
Claire Haegelen ◽  
Johannes Sarnthein ◽  
...  
Keyword(s):  
High Frequency ◽  
Epileptogenic Zone ◽  
High Frequency Oscillations

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 Localization of the Epileptogenic Zone by Multimodal Neuroimaging and High-Frequency Oscillation

2021 ◽  
Vol 15 ◽  
Author(s):  
Xiaonan Li ◽  
Tao Yu ◽  
Zhiwei Ren ◽  
Xueyuan Wang ◽  
Jiaqing Yan ◽  
...  
Keyword(s):  
Surgical Outcome ◽  
High Frequency ◽  
Refractory Epilepsy ◽  
Automated Analysis ◽  
Diagnostic Value ◽  
High Frequency Oscillation ◽  
Epileptogenic Zone ◽  
Frequency Oscillation ◽  
Traditional Methods ◽  
Intracranial Electrodes

Accurate localization of the epileptogenic zone (EZ) is a key factor to obtain good surgical outcome for refractory epilepsy patients. However, no technique, so far, can precisely locate the EZ, and there are barely any reports on the combined application of multiple technologies to improve the localization accuracy of the EZ. In this study, we aimed to explore the use of a multimodal method combining PET-MRI, fluid and white matter suppression (FLAWS)—a novel MRI sequence, and high-frequency oscillation (HFO) automated analysis to delineate EZ. We retrospectively collected 15 patients with refractory epilepsy who underwent surgery and used the above three methods to detect abnormal brain areas of all patients. We compared the PET-MRI, FLAWS, and HFO results with traditional methods to evaluate their diagnostic value. The sensitivities, specificities of locating the EZ, and marking extent removed versus not removed [RatioChann(ev)] of each method were compared with surgical outcome. We also tested the possibility of using different combinations to locate the EZ. The marked areas in every patient established using each method were also compared to determine the correlations among the three methods. The results showed that PET-MRI, FLAWS, and HFOs can provide more information about potential epileptic areas than traditional methods. When detecting the EZs, the sensitivities of PET-MRI, FLAWS, and HFOs were 68.75, 53.85, and 87.50%, and the specificities were 80.00, 33.33, and 100.00%. The RatioChann(ev) of HFO-marked contacts was significantly higher in patients with good outcome than those with poor outcome (p< 0.05). When intracranial electrodes covered all the abnormal areas indicated by neuroimaging with the overlapping EZs being completely removed referred to HFO analysis, patients could reach seizure-free (p < 0.01). The periphery of the lesion marked by neuroimaging may be epileptic, but not every lesion contributes to seizures. Therefore, approaches in multimodality can detect EZ more accurately, and HFO analysis may help in defining real epileptic areas that may be missed in the neuroimaging results. The implantation of intracranial electrodes guided by non-invasive PET-MRI and FLAWS findings as well as HFO analysis would be an optimized multimodal approach for locating EZ.

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 Long-range phase synchronization of high-frequency oscillations in human cortex

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
G. Arnulfo ◽  
S. H. Wang ◽  
V. Myrov ◽  
B. Toselli ◽  
J. Hirvonen ◽  
...  
Keyword(s):  
High Frequency ◽  
Large Scale ◽  
Phase Synchronization ◽  
Brain Activity ◽  
Brain Regions ◽  
Spike Timing ◽  
Human Cortex ◽  
Neuronal Communication ◽  
High Frequency Oscillations ◽  
Connectivity Patterns

Abstract Inter-areal synchronization of neuronal oscillations at frequencies below ~100 Hz is a pervasive feature of neuronal activity and is thought to regulate communication in neuronal circuits. In contrast, faster activities and oscillations have been considered to be largely local-circuit-level phenomena without large-scale synchronization between brain regions. We show, using human intracerebral recordings, that 100–400 Hz high-frequency oscillations (HFOs) may be synchronized between widely distributed brain regions. HFO synchronization expresses individual frequency peaks and exhibits reliable connectivity patterns that show stable community structuring. HFO synchronization is also characterized by a laminar profile opposite to that of lower frequencies. Importantly, HFO synchronization is both transiently enhanced and suppressed in separate frequency bands during a response-inhibition task. These findings show that HFO synchronization constitutes a functionally significant form of neuronal spike-timing relationships in brain activity and thus a mesoscopic indication of neuronal communication per se.

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