Electrode surface area impacts measurement of high frequency oscillations in human intracranial EEG
Abstract number :
637
Submission category :
1. Basic Mechanisms / 1C. Electrophysiology/High frequency oscillations
Year :
2020
Submission ID :
2422978
Source :
www.aesnet.org
Presentation date :
12/6/2020 5:16:48 PM
Published date :
Nov 21, 2020, 02:24 AM
Authors :
Kavyakantha Remakanthakarup Sindhu, University of California, Irvine; Hernando Ombao - King Abdullah University of Science and Technology; Aliza Riba - CHOC Children's; Donald Phillips - Children's Hospital of Orange County; Joffre Olaya - Children's Hosp
Rationale:
High frequency oscillations (HFOs) are a promising biomarker of the epileptogenic zone and tool for surgical planning. Their rates of occurrence and morphology have been studied extensively using recordings from depth and subdural electrodes of various geometries. There is conflicting evidence regarding the effect of electrode size on HFO measurement. Some reported that smaller electrodes are better for recording fast ripples (Worrell et al. 2008), while others reported no differences for fast ripples and small differences for ripples that were deemed to be not clinically relevant (Chatillon et al. 2013). Here we present a novel recording method to dynamically change the effective surface area of subdural electrodes after implantation in the human brain. We use this method to compare the characteristics of HFOs recorded using iEEG electrodes of different effective surface areas within a single brain region.
Method:
Three human subjects were each implanted with a high-density 8x8 subdural grid of intracranial EEG electrodes. Electrodes had surface area of 1.08mm2 and inter-electrode distance of 3mm. The effective electrode surface area was changed by electrically shorting adjacent electrodes in groups of 2 or 4. This shorting effectively averages the neural activity under the electrodes, thereby mimicking larger surface areas of 2.16mm2 and 4.32mm2. Twenty-minute iEEG recordings were thus obtained for three different electrode surface areas from a single grid in a static brain location while the subjects were sleeping. HFOs were detected using an automated algorithm (Staba et al. 2002). The average rate, amplitude, duration, and peak frequency of HFOs detected in iEEG recorded using electrodes of these three different surface areas were calculated and compared.
Results:
When electrode surface area was increased, the estimated HFO rate per area of tissue decreased significantly, for both ripples (p < 10-10) and fast ripples (p< 10-6, Wilcoxon rank sum test). The smallest electrode size recorded more fast ripples than ripples (p< 0.0001), contrary to what is typically reported for standard-size electrodes. The estimate of HFO amplitude was also found to decrease with electrode surface area, consistent with the hypothesis that larger electrodes average the activity of the underlying neural tissue. Duration and peak frequency were not affected by changes in electrode surface area.
Conclusion:
This study is the first to devise a method to record intracranial EEG from the same section of neural tissue using electrodes of different sizes. Previous studies compared electrodes of different sizes that were either adjacent to one another or in different regions of the brain. We find that measurements of HFO rate and morphology are dependent on the surface area of the recording electrodes, and our data suggest that fast ripples are more readily measured using smaller electrodes. These results suggest that accounting for electrode geometry when studying HFOs may improve demarcation of brain regions with pathological high frequency activity.
Funding:
:N/A
Basic Mechanisms