Automated detection of high-frequency oscillations in electrophysiological signals: Methodological advances

Navarrete, Miguel; Pyrzowski, Jan; Corlier, Juliana; Valderrama, Mario; Quyen, Michel Le Van

doi:10.1016/j.jphysparis.2017.02.003

Cited by 16 publications

(20 citation statements)

References 122 publications

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“…Various groups have reviewed the technical aspects of HFO detection (see e.g., 39, 64, 65). The detection of HFOs is a challenging task, mainly due to their usual low signal-to-noise ratio, their association with other epileptic activity, and the still open questions regarding their nature and definition.…”

Section: High-frequency Oscillations In the Intracranial Eegmentioning

confidence: 99%

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Localization of the Epileptogenic Zone Using High Frequency Oscillations

2019

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For patients with drug-resistant focal epilepsy, surgery is the therapy of choice in order to achieve seizure freedom. Epilepsy surgery foremost requires the identification of the epileptogenic zone (EZ), defined as the brain area indispensable for seizure generation. The current gold standard for identification of the EZ is the seizure-onset zone (SOZ). The fact, however that surgical outcomes are unfavorable in 40–50% of well-selected patients, suggests that the SOZ is a suboptimal biomarker of the EZ, and that new biomarkers resulting in better postsurgical outcomes are needed. Research of recent years suggested that high-frequency oscillations (HFOs) are a promising biomarker of the EZ, with a potential to improve surgical success in patients with drug-resistant epilepsy without the need to record seizures. Nonetheless, in order to establish HFOs as a clinical biomarker, the following issues need to be addressed. First, evidence on HFOs as a clinically relevant biomarker stems predominantly from retrospective assessments with visual marking, leading to problems of reproducibility and reliability. Prospective assessments of the use of HFOs for surgery planning using automatic detection of HFOs are needed in order to determine their clinical value. Second, disentangling physiologic from pathologic HFOs is still an unsolved issue. Considering the appearance and the topographic location of presumed physiologic HFOs could be immanent for the interpretation of HFO findings in a clinical context. Third, recording HFOs non-invasively via scalp electroencephalography (EEG) and magnetoencephalography (MEG) is highly desirable, as it would provide us with the possibility to translate the use of HFOs to the scalp in a large number of patients. This article reviews the literature regarding these three issues. The first part of the article focuses on the clinical value of invasively recorded HFOs in localizing the EZ, the detection of HFOs, as well as their separation from physiologic HFOs. The second part of the article focuses on the current state of the literature regarding non-invasively recorded HFOs with emphasis on findings and technical considerations regarding their localization.

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Section: High-frequency Oscillations In the Intracranial Eegmentioning

confidence: 99%

“…HFO detection has greatly benefitted from the development of automated detectors (see 64, for a 2016 review) (30, 54, 73–76). It is well-known that visual HFO detection is very time-consuming, and the reliability of this procedure has been questioned on several occasions (16).…”

Section: High-frequency Oscillations In the Intracranial Eegmentioning

confidence: 99%

Localization of the Epileptogenic Zone Using High Frequency Oscillations

2019

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“…Several automatic detection algorithms have been developed to overcome these problems (25,(30)(31)(32)(33)(34), making it easier than ever to conduct HFO analyses. However, automatic detection algorithms are not without flaws in their own respect.…”

Section: Manual Vs Automatic Detection Of Hfosmentioning

confidence: 99%

“…Albeit these numerous investigations, the detection of HFOs remains a highly debatable subject, and many aspects need to be considered. Besides technical considerations regarding the signal-to-noise ratio and data sampling (24)(25)(26), choosing the actual method of detection can be difficult. Considering the mentioned criteria (1), visual inspection requires enlarging the signal both in time scale and amplitude in order to discern these discrete events from the background EEG (27).…”

Section: Introductionmentioning

confidence: 99%

Automatic vs. Manual Detection of High Frequency Oscillations in Intracranial Recordings From the Human Temporal Lobe

et al. 2020

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“…Here we acquired intracranial data to test the following hypotheses: 1. high frequency activity is spatially organized across processing networks, i.e., their timing and functional topography reflect either early visual or late perceptual decision processes 2. their temporal patterning reflects specific object properties, or instead just a general recognition mechanism occurring during perceptual decision-making. These remain controversial hypotheses for which ECoG provides a unique opportunity to test, even with the limitations of available mathematical models for the analysis of high-density recordings at high spatio-temporal resolutions[ 41 ]. We acquired invasive data in six patients with refractory epilepsy and also extended the range of visual categories used in previous studies by including new ambiguous stimulus categories (faces, objects and scrambled stimuli that may also activate similar decision regions) [ 42 ], allowing to test general processes.…”

Section: Introductionmentioning

confidence: 99%

Cortical functional topography of high-frequency gamma activity relates to perceptual decision: an Intracranial study

et al. 2017

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High-frequency activity (HFA) is believed to subserve a functional role in cognition, but these patterns are often not accessible to scalp EEG recordings. Intracranial studies provide a unique opportunity to link the all-encompassing range of high-frequency patterns with holistic perception. We tested whether the functional topography of HFAs (up to 250Hz) is related to perceptual decision-making. Human intracortical data were recorded (6 subjects; >250channels) during an ambiguous object-recognition task. We found a spatial topography of HFAs reflecting processing anterior dorsal and ventral streams, linked to decision independently of the type of processed object/stimulus category. Three distinct regional fingerprints could be identified, with lower gamma frequency patterns (<45Hz) dominating in the anterior semantic ventral object processing and dorsoventral integrating networks and evolving later, during perceptual decision phases, than early sensory posterior patterns (60-250Hz). This suggests that accurate object recognition/perceptual decision-making is related to distinct spatiotemporal signatures in the low gamma frequency range.

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Automated detection of high-frequency oscillations in electrophysiological signals: Methodological advances

Cited by 16 publications

References 122 publications

Localization of the Epileptogenic Zone Using High Frequency Oscillations

Localization of the Epileptogenic Zone Using High Frequency Oscillations

Automatic vs. Manual Detection of High Frequency Oscillations in Intracranial Recordings From the Human Temporal Lobe

Cortical functional topography of high-frequency gamma activity relates to perceptual decision: an Intracranial study

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