Clues to Controlling Seizures

New approaches to modeling the brain could improve electrical-stimulation therapies.

The same type of modeling used by meteorologists to forecast the weather could help scientists design better electrical-stimulation therapies for the brain. These therapies, which involve sending small jolts of electricity to specific neural targets, are currently in use for both Parkinson's and epilepsy, two neurological diseases in which drugs have had limited success.

Modeling seizures: By building models that mimic the neural activity characteristic of seizures, scientists hope to improve electrical-stimulation therapies for epilepsy patients. Neural activity recorded from a slice of rat cortex is shown in the top box. (Neurons in a dissected piece of brain can stay active for hours if treated properly.) Results of three versions of a computational model calculated from real neural activity are shown below, each capturing a different aspect of the actual neural activity. The colors represent changes in voltage in the real or simulated neural tissue. Credit: Steven Schiff (Pennsylvania State University), Xiaoying Huang and Jian-Young Wu (Georgetown University Medical Center)

Multimedia   See neural activity recorded from a slice of rat cortex and simulated neural activity from three versions of a model calculated from that activity.

As neurosurgical technologies improve and medical devices become smaller and more precise, interest in stimulation therapies has blossomed: different therapies are now being tested in a range of disorders, including brain injury, obsessive-compulsive disorder, and depression. Scientists theorize that electrical stimulation blocks abnormal electrical patterns that arise with different diseases, but little is known about how these devices actually work. As use of this technology grows, it is becoming increasingly important for scientists to develop more precise ways to target aberrant brain activity while leaving normal neural communication intact.

"In some sense, we have no idea what electrical stimulation is doing to the brain," says Robert Duckrow, a neurologist at Yale University, in New Haven, CT, who tests electrical therapies. "It's almost as if we need to take a step back and say, What is the right way to stimulate the brain to achieve a specific end?"

Steven Schiff, a neurosurgeon and engineer at Pennsylvania State University, is trying to do just that. Schiff and his collaborators are borrowing an engineering technique, known as control theory, to model the networks of neurons that produce the abnormal electrical activity that is characteristic of both seizures and movement disorders such as Parkinson's. The results should allow scientists to more precisely design stimulation therapies, improving their effectiveness. "We would like to get to the point where we can minimize the energy used and minimize the effect on normal [cognitive] processes," says Schiff.

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With epilepsy, 30 to 40 percent of patients fail to find relief from anticonvulsant medications, and not all patients are eligible for surgery to remove the part of the brain that generates seizures. The vagus nerve stimulator, which stimulates a nerve leading to the brain, was approved for epilepsy treatment more than a decade ago. But it has limited success: only about a third of patients who undergo the procedure report a reduction in seizure rates by 50 percent or more.

Deep brain stimulation, which involves surgically implanting electrodes directly into the brain, has become routine for treating Parkinson's disease: nearly 40,000 Parkinson's patients have undergone the procedure to date. While for many patients it's a welcome alternative to drugs, the treatment needs to be effective for many symptoms, not just the tremors which are the most obvious visible signs of the disease. "It's the inability to start a movement which is the most disabling to many patients. The harder thing to do is to be more sophisticated in how you maximize patients' ability to move, and by using models, we hope to create more effective algorithms to interact with the brain's activity in such patients," says Schiff