Abstract Details

Title Distinguishing Quantitative EEG Correlates of Psychogenic Non-Epileptic Seizures versus Epilepsy

Topic Epilepsy/Clinical Neurophysiology (EEG)

Presentation(s) P1 - Poster Session 1 (9:00 AM-5:00 PM)

Poster/Presentation
Number 143

Objective

To investigate differences in quantitative electroencephalogram (EEG) measures of patients with psychogenic non-epileptic seizures (PNES) and epilepsy across multiple behavioral states.

Background

PNES presents without ictal epileptiform EEG activity despite clinically apparent seizure-like activity. Little is known about the pathophysiology of PNES. Capturing a clinical event while a patient is undergoing continuous EEG monitoring is the clinical standard to distinguish between PNES and epilepsy.

Design/Methods

The EEG records of 15 patients with epilepsy and 8 patients with PNES are included in this cohort study. Samples of a patient’s EEG were taken from ictal events, when the patient was awake, and when the patient was asleep. Spectral power and magnitude-squared coherence were calculated across frequency bands (delta: 0.5-4 Hz, theta: 4-8 Hz, alpha: 8-13 Hz, beta: 13-30 Hz, gamma: 30-70 Hz) in addition to approximate entropy analyses, across 19 standardized brain regions/scalp electrodes.

Results

During seizures, patients with PNES displayed lower FzCz coherence across delta (mean [SD] 0.284 [0.295] vs. 0.526 [0.314], p<0.05) and gamma (mean [SD] 0.305 [0.340] vs. 0.696 [0.197], p<0.001) bands compared to patients with epilepsy. Additionally during seizures, patients with PNES displayed lower C3 power across delta (mean [SD] 1.64 [1.34] vs. 3.30 [1.67], p<0.01), theta (mean [SD] 1.84 [1.35] vs. 3.47 [1.77], p<0.01), and alpha (mean [SD] 1.69 [1.11] vs. 3.29 [1.75], p<0.001) frequencies. Patients with PNES displayed greater O2 power across delta (mean [SD] 10.2 [1.63] vs. 6.77 [2.87], p<0.05), theta (mean [SD] 11.7 [0.542] vs. 7.68 [0.676], p<0.01), and beta (mean [SD] 8.76 [0.446] vs. 6.39 [0.443], p<0.05) frequencies while asleep.

Conclusions

Quantitative EEG methods can be used to differentiate between patients with PNES and epilepsy and suggest a novel path forward for the development of biomarkers to aid in patient diagnosis and treatment.

Authors/Disclosures
Josh Goldenberg PRESENTER	Mr. Goldenberg has nothing to disclose.
	No disclosure on file
Julie Roth, MD, FAAN	Dr. Roth has nothing to disclose.
Judy Liu, MD, PhD (Brown University)	The institution of Dr. Liu has received research support from NIH/NINDS.
W. C. LaFrance, Jr., MD, MPH, FAAN (Rhode Island Hospital)	Dr. LaFrance has received personal compensation in the range of $10,000-$49,999 for serving as an Expert Witness for medico-legal work.. The institution of Dr. LaFrance has received research support from Department of Defense. Dr. LaFrance has received publishing royalties from a publication relating to health care. Dr. LaFrance has received publishing royalties from a publication relating to health care. Dr. LaFrance has a non-compensated relationship as a Steering Committee Member with Xenon that is relevant to AAN interests or activities.
Andrew S. Blum, MD, PhD, FAAN (Department of Neurology, Rhode Island Hospital)	The institution of Dr. Blum has received research support from DOD-Ocean State Research Institute, Inc/NIH. The institution of Dr. Blum has received research support from NSF - SBIR. The institution of Dr. Blum has received research support from Alpert Medical School. The institution of Dr. Blum has received research support from Alpert Medical School. Dr. Blum has received publishing royalties from a publication relating to health care. Dr. Blum has received personal compensation in the range of $500-$4,999 for serving as a Medical Director for Ambulatory Video-EEG LTM services, on behalf of Brown Neurology with United Sleep Diagnostics.
Jason B. Richards, MD (Brown Neurology)	The institution of Dr. Richards has received research support from Brown Physicians, Inc.

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