OBJECTIVES: To analyze interictal High frequency oscillations (HFOs) as observed in the medial temporal lobe of epileptic patients and animals (ripples, 80-200Hz and fast ripples, 250-600Hz). To show that the identification of interictal HFOs raises some methodological issues, as the filtering of sharp transients (e.g., epileptic spikes or artefacts) or signals with harmonics can result in "false" ripples. To illustrate and quantify the occurrence of false ripples on filtered EEG traces. METHODS: We have performed high-pass filtering on both simulated and real data. We have also used two alternate methods: time-frequency analysis and matching pursuit. RESULTS: Two types of events were shown to produce oscillations after filtering that could be confounded with actual oscillatory activity: sharp transients and harmonics of non-sinusoidal signals. CONCLUSIONS: High-pass filtering of EEG traces for detection of oscillatory activity should be performed with great care. Filtered traces should be compared to original traces for verification of presence of transients. Additional techniques such as time-frequency transforms or sparse decompositions are highly beneficial. SIGNIFICANCE: Our study draws the attention on an issue of great importance in the marking of HFOs on EEG traces. We illustrate complementary methods that can help both researchers and clinicians.
OBJECTIVES: To analyze interictal High frequency oscillations (HFOs) as observed in the medial temporal lobe of epilepticpatients and animals (ripples, 80-200Hz and fast ripples, 250-600Hz). To show that the identification of interictal HFOs raises some methodological issues, as the filtering of sharp transients (e.g., epileptic spikes or artefacts) or signals with harmonics can result in "false" ripples. To illustrate and quantify the occurrence of false ripples on filtered EEG traces. METHODS: We have performed high-pass filtering on both simulated and real data. We have also used two alternate methods: time-frequency analysis and matching pursuit. RESULTS: Two types of events were shown to produce oscillations after filtering that could be confounded with actual oscillatory activity: sharp transients and harmonics of non-sinusoidal signals. CONCLUSIONS: High-pass filtering of EEG traces for detection of oscillatory activity should be performed with great care. Filtered traces should be compared to original traces for verification of presence of transients. Additional techniques such as time-frequency transforms or sparse decompositions are highly beneficial. SIGNIFICANCE: Our study draws the attention on an issue of great importance in the marking of HFOs on EEG traces. We illustrate complementary methods that can help both researchers and clinicians.
Authors: Daniel M Goldenholz; Masud Seyal; Lisa M Bateman; Jean Gotman; Luciana Andrade-Valenca; Rina Zelmann; Francois Dubeau Journal: Neurology Date: 2012-01-17 Impact factor: 9.910
Authors: Zachary J Waldman; Liliana Camarillo-Rodriguez; Inna Chervenova; Brent Berry; Shoichi Shimamoto; Bahareh Elahian; Michal Kucewicz; Chaitanya Ganne; Xiao-Song He; Leon A Davis; Joel Stein; Sandhitsu Das; Richard Gorniak; Ashwini D Sharan; Robert Gross; Cory S Inman; Bradley C Lega; Kareem Zaghloul; Barbara C Jobst; Katheryn A Davis; Paul Wanda; Mehraneh Khadjevand; Joseph Tracy; Daniel S Rizzuto; Gregory Worrell; Michael Sperling; Shennan A Weiss Journal: Epilepsy Behav Date: 2018-09-11 Impact factor: 2.937