Monthly Brain Cycles Predict Epilepsy Seizures

A new study suggests it may soon be possible to know when epilepsy patients are at highest risk for seizures by identifying monthly cycles of brain activity.

Researchers at the University of California, San Francisco (UCSF; USA), the Wyss Center for Bio and Neuroengineering (Geneva, Switzerland), and other institutions conducted a study in 37 subjects previously implanted with the NeuroPace (Mountain View, CA, USA) RNS brain stimulation system in an attempt to define the relationship of seizure timing to fluctuating rates of interictal epileptiform activity (IEA), a marker of brain irritability observed between seizures by electroencephalography (EEG).

The study found that IEA oscillates with circadian and subject-specific multidien (multi-day) periods. The multidien periodicities, most commonly 20–30 days in duration, were found to be robust and relatively stable for up to 10 years in both men and women, and that the seizures occured preferentially during the rising phase of IEA rhythms. By combining the phase information from circadian and multidien IEA rhythms, a novel biomarker for determining relative seizure risk is available in most subjects. The study was published on January 8, 2017, in Nature Communications.

“One of the most disabling aspects of having epilepsy is the seeming randomness of seizures. If your neurologist can't tell you if your next seizure is a minute from now or a year from now, you live your life in a state of constant uncertainty, like walking on eggshells,” said senior author Vikram Rao, MD, PhD, of UCSF. “The exciting thing here is that we may soon be able to empower patients by letting them know when they are at high risk and when they can worry less.”

“I like to compare it to a weather forecast; in the past, the field has focused on predicting the exact moment a seizure will occur, which is like predicting when lightning will strike; that's pretty hard,” concluded Dr. Rao. “It may be more useful to be able tell people there is a five percent chance of a thunderstorm this week, but a ninety percent chance next week. That kind of information lets you prepare.”

The NeuroPace RNS system is designed to detect the brain’s electrical activity. When it identifies seizure activity, it attempts to suppress the seizure by sending electrical stimulation through implanted leads to the brain. A physician-operated programmer communicates with the RNS, allowing stored information to be reviewed. An optional data transmitter can provide the physician with the information in real-time, so that the response to the stimulation can be evaluated to decide on the best seizure detection and stimulation settings for the patient.

Related Links:
University of California, San Francisco
Wyss Center for Bio and Neuroengineering
NeuroPace