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Updated: Feb 7, 2026

Automatic Detection of Highly Organized Theta Oscillations in the Murine EEG
Published on: March 10, 2017
Visually validated semi-automatic high-frequency oscillation detection aides the delineation of epileptogenic regions
Shennan Aibel Weiss1, Brent Berry2, Inna Chervoneva3
1Dept. of Neurology and Neuroscience, Thomas Jefferson University, Philadelphia, PA 19107, USA.
Objective:
To test the utility of a novel semi-automated method for detecting, validating, and quantifying high-frequency oscillations (HFOs): ripples (80-200 Hz) and fast ripples (200-600 Hz) in intra-operative electrocorticography (ECoG) recordings.
Methods:
Sixteen adult patients with temporal lobe epilepsy (TLE) had intra-operative ECoG recordings at the time of resection. The computer-annotated ECoG recordings were visually inspected and false positive detections were removed. We retrospectively determined the sensitivity, specificity, positive and negative predictive value (PPV/NPV) of HFO detections in unresected regions for determining post-operative seizure outcome.
Results:
Visual validation revealed that 2.81% of ripple and 43.68% of fast ripple detections were false positive. Inter-reader agreement for false positive fast ripple on spike classification was good (ICC = 0.713, 95% CI: 0.632-0.779). After removing false positive detections, the PPV of a single fast ripple on spike in an unresected electrode site for post-operative non-seizure free outcome was 85.7 [50-100%]. Including false positive detections reduced the PPV to 64.2 [57.8-69.83%].
Conclusions:
Applying automated HFO methods to intraoperative electrocorticography recordings results in false positive fast ripple detections. True fast ripples on spikes are rare, but predict non-seizure free post-operative outcome if found in an unresected site.
Significance:
Semi-automated HFO detection methods are required to accurately identify fast ripple events in intra-operative ECoG recordings.
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