Study shows why even well-controlled epilepsy can disrupt thinking

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In the study, if an HFO occurred within several hundred milliseconds before a seizure-prone brain region began processing information, it lowered the accuracy of participants’ ability to perform simple cognitive tasks. It also slowed their response times, and they reported less confidence in the accuracy of their responses.

The researchers showed that this happens because HFOs within that period interfere with high-frequency broadband events, or HFBs, which are healthy. HFBs are associated with a brain circuit beginning to do something it’s supposed to, such as processing visual information or recalling a previous experience.

An HFO can knock out healthy brain activity for as long as a full second or so, the researchers showed.

“A cognitive demand on a brain circuit that’s just experienced an HFO is like the doorbell ringing when you’ve just been punched in the nose and you’re still seeing stars,” Parvizi said. “You might not even hear that doorbell, and you’re certainly not about to go answer it.”

Often likened to an electrical storm in the brain, epilepsy affects about 1% of the population. Medications benefit about two-thirds of people diagnosed with the disease. Implantable devices that deliver electrical pulses to the brain can sometimes succeed where medications fail. For patients with intractable seizures, surgery to excise the affected tissue is an option.

In the study, Parvizi and Liu worked with six adult patients with intractable seizures who were being evaluated at Stanford Health Care as a prelude to possible surgery. To help pinpoint the origin of their seizures, electrodes had been implanted in their brains.

While these six patients, who had agreed to be studied, were at rest, they experienced several HFOs per minute, although they weren’t experiencing visible seizures, the study said.

To elicit healthy HFBs in the participants’ seizure-prone tissue, the researchers gave them visual or memory tasks. Armed with data recorded by the electrodes, the experimenters used machine-learning techniques to train a computer to accurately and reliably distinguish HFOs and HFBs.



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