Direct current shifts, high frequency oscillations and the epileptogenic zone

2015 ◽  
Vol 126 (1) ◽  
pp. 2-4 ◽  
Author(s):  
Stefan Rampp
Author(s):  
Truman Stovall ◽  
Brian Hunt ◽  
Simon Glynn ◽  
William C Stacey ◽  
Stephen V Gliske

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.


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

2019 ◽  
Vol 10 ◽  
Author(s):  
Aljoscha Thomschewski ◽  
Ana-Sofía Hincapié ◽  
Birgit Frauscher

2021 ◽  
Vol 19 ◽  
Author(s):  
Xiaonan Li ◽  
Herui Zhang ◽  
Huanling Lai ◽  
Jiaoyang Wang ◽  
Wei Wang ◽  
...  

: 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.


2015 ◽  
Vol 126 (1) ◽  
pp. 47-59 ◽  
Author(s):  
Kyoko Kanazawa ◽  
Riki Matsumoto ◽  
Hisaji Imamura ◽  
Masao Matsuhashi ◽  
Takayuki Kikuchi ◽  
...  

Author(s):  
Shasha Wu ◽  
Vernon L. Towle ◽  
Jonathan P. Miller ◽  
Hans O. Lüders

Direct current (DC) shift, also called infraslow activity (IFA), refers to brain activity slower than 0.5 Hz. DC shifts have been shown to have a close temporal and spatial relationship with the conventional seizure onset zone and a smaller field than the conventional ictal electroencephalogram (EEG); therefore, they may have potential value in identifying the epileptogenic zone. Studies have shown that DC shifts can be reliably recorded intracranially from chronic subdural grids or depth electrodes using AC amplifiers with a long time constant (e.g. 10 s) in a compressed viewing window. Although the mechanism remains under debate, most investigators agree that DC shifts are generated by neuroglial cells or neuroglial cells together with pyramidal neurons. With the widespread use of digital EEG recording, DC shifts, together with high-frequency oscillations should be routinely analysed in invasive EEG recordings to provide complementary information in presurgical evaluation of epilepsy.


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