Comparison of EEG Signal Characteristics Between Subdural and Depth Intracranial EEG Electrodes
Cigdem Isitan-Alkawadri1, Ayse Kocoglu kinal2, Qi Yan3, Anto Bagic4, Dennis Spencer3, Rafeed Alkawadri5
1Neurology, University of Pittsburgh Medical Center, 2İstanbul Dr. Siyami Ersek Hastanesi, 3Yale University, 4UPMC/Univesrity of Pittsburgh, 5Human Brain Mapping Program, Univreisty of Pittsburgh
Objective:
This study compares the EEG signal characteristics of subdural electrodes (SDE) and stereo-depth EEG (sEEG) electrodes placed within close proximity in patients undergoing monitoring for drug-resistant epilepsy (DRE).
Background:
DRE affects roughly one-third of epilepsy patients. Both SDE and sEEG electrodes are commonly used in invasive monitoring, yet limited research directly compares their signal profiles.
Design/Methods:
From 2012 to 2018, we evaluated intracranial EEG (icEEG) data from patients at a surgical epilepsy center. We identified electrode pairs (SDE and sEEG) within 5 mm of each other, with 24 contacts (12 pairs) meeting our criteria for signal-to-noise ratio and data completeness. Power spectral densities were analyzed using Welch's method, and coherence across standard frequency bands was calculated using fast-Fourier transform.
Results:
We observed a median distance of 3.7 mm between the electrode contact pairs. Time-aware analysis highlighted the coherence's strength primarily in the high- gamma (HG) band, where the median (r) was 0.889. Additionally, the median power ratios between the SDE and sEEG signal was 1.99. This ratio decreased from high- gamma to infra-low frequencies, with medians of 2.07 and 0.97, respectively. The power spectral densities (PSDs) for the sEEG and SDE electrodes demonstrated a strong correlation, with a median correlation coefficient (r) of 0.99 and an interquartile range (IQR) from 0.915 to 0.996.
Conclusions:
We found a frequency-dependent relationship between SDE and sEEG signals, with the strongest coherence in the HG band. Variations are likely due to differences in electrode design and placement. These findings have implications for surgical epilepsy care and Brain-Computer Interface (BCI) design.
Keywords: Subdural EEG, stereo EEG, intracranial EEG, spectral analysis, signal characteristics high-frequency oscillations (HFOs).
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