Published On September 21, 2017
The brain consists of 86 million neurons. They communicate with one another through electrical impulses, and as they fire, the electricity they generate forms into distinctive waves. By measuring the waves’ frequency and shape, researchers gain a window into the kind of activity happening in the brain. For instance, some waves are more characteristic of the waking brain, and others of the sleeping brain—important information for an anesthesiologist who tries to keep patients on one side of that line.
Patrick Purdon, in the department of anesthesia, critical care and pain medicine at Massachusetts General Hospital, noticed something unique about the brainwaves of patients with Alzheimer’s disease. Under anesthesia, those waves were weaker than the typical “rhythms” induced by the drugs. Purdon’s lab, with the help of a recent grant from the National Institutes of Health, is now exploring brainwaves as a potential diagnostic tool.
Q: How did you make the jump from anesthesia to Alzheimer’s?
A: My initial research was looking at how different anesthetic drugs alter the timing and function of brain signals to produce unconsciousness. For the past several years, we’ve been trying to understand how that brain activity changes as a function of age, so we were looking specifically at the brains of elderly people.
Q: What have you discovered?
A: We noticed that in elderly patients under anesthesia, brain waves were significantly smaller and slower than they were for younger patients. As the brain ages, the activity normally induced by anesthetic drugs changes too. So then we looked at those brain circuits that were affected, and discovered that they align with brain areas that typically undergo degeneration in aging and Alzheimer’s.
Q: How can you tell?
A: Think of it this way: The brain functions on many different wavelengths, like many different keys on a piano. When you introduce the anesthetics, only certain notes on that piano are able to function. In an electroencephalogram, or EEG test, you can see these “notes” in the form of alpha oscillations that hit particular frequencies. What we are seeing in elderly patients is that those notes get softer and softer—the frequencies get lower, and sometimes go flat—presumably because the specific brain circuits that normally produce them are weaker.
Q: How does that relate to Alzheimer’s?
A: This discovery really opens up a whole new avenue of research into Alzheimer’s. What we are trying to do now is look at brain rhythms of early Alzheimer’s patients, and study those changes in brain oscillations before the disease fully develops. That could offer valuable new information.
Q: So studying brain oscillations could eventually be used to predict the onset of Alzheimer’s?
A: That’s right. One of our key collaborators, Brad Dickerson, from MGH’s department of neurology, published work a few years ago showing that if you looked at specific areas of the brain and measured the thickness of the cerebral cortex, you could more easily predict who will get Alzheimer’s. If the cortex is getting thinner, that’s a key sign that its function might be compromised. A corollary to that might be that brain oscillations coming from those areas change, so we’re looking for such changes.
Q: Has this type of research been done before?
A: The notion that you could quantify specific brain oscillations and relate that data to the disease’s underlying pathology has not really been done before. Most Alzheimer’s researchers are more focused on animal models or imaging methods. But we are using electroencephalography to monitor and record the brain’s electrical activity—and no one has yet connected the dots among EEG brain patterns and the causes and effects of this disease.
Q: Based on what you find, what would be the next step in your research?
A: We hope to get a clearer picture of a specific patient’s neurodegeneration and changes in brain function—all through electroencephalography measurements. That’s a totally new approach. If we are successful, it would be feasible for screening, longitudinal tracking, and early detection of neurodegenerative problems using EEG, which is really inexpensive compared with most medical devices like MRI or CT technology. EEG would also complement existing diagnostic tools, bringing new information about how brain circuits are (or aren’t) working. We are excited about the potential to help patients and to take better care of their brains.
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