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An affordable and noninvasive test might predict those at risk for Alzheimer’s

by Lauren Dubinsky, Senior Reporter | July 16, 2015
Alzheimers/Neurology Medical Devices
There is no conclusive test to predict who will develop Alzheimer’s disease, but researchers from the University of Texas have developed a diagnostic test using electroencephalogram (EEG) technology that may determine who is at most risk.

People with amnestic mild cognitive impairment (aMCI) have a two times higher chance of developing Alzheimer’s than others in their age group. The majority of EEG research on aMCI patients has focused on looking at the mind at rest, but the researchers decided to take a different approach.

For the study, 16 patients with aMCI and 17 healthy controls in the same age group were monitored with EEG as they were presented with pairs of words that either described features of an object or were randomly paired. They were instructed to press buttons based on whether the pair of words conjured a particular memory of an object or not.

The researchers found that individuals with aMCI performed less accurately and more slowly on the semantic memory task than the healthy controls. The EEG results revealed that they experienced delayed brain activity while performing the task.

Using EEG to assess brain activity is more affordable and noninvasive compared to other available methods including MRI and spinal tap. In addition, the researchers noted that it is more sensitive and more specific at pointing out certain cognitive deficits compared to performing EEG while the patient’s mind is at rest.

"This protocol could potentially provide complementary information for diagnosis of pre-dementia stages including MCI and identify neural changes that can occur in cases of Alzheimer's disease,” Dr. Hsueh-Sheng Chiang, the study’s lead author, said in a statement.

The researchers will continue to assess whether this test has the potential to help predict which patients may progress to Alzheimer’s. They are planning on recruiting more participants in order to follow them longitudinally.

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