Simple test to detect Alzheimer's risk

A new affordable, non-invasive test that detects electrical activity in the brain may predict the risk of Alzheimer's disease, scientists say.
Researchers from the University of Texas identified a specific variation in brain waves of people with amnestic mild cognitive impairment (aMCI), who are at twice the risk in their age group of developing Alzheimer's disease.
The findings depict a pattern of delayed neural activity that is directly related to the severity of impairment in cognitive performance on a word finding task and may indicate an early dysfunction of progression to Alzheimer's disease.
Impaired episodic memory, the ability to retain new memories such as recent conversations, events, or upcoming appointments, is a hallmark symptom of Alzheimer's disease.

The potential diagnostic approach utilises electroencephalogram (EEG) technology, a more affordable and non-invasive alternative, to measure neural responses while participants access semantic memory or long-term memory.
"This is a promising start at looking at a group of MCI patients. The long-term goal is whether this can be applied to individual patients one day," said principal investigator John Hart, Medical Science Director at the Centre for BrainHealth.

The study showed that individuals with aMCI performed less accurately and more slowly on the semantic memory task than the healthy control group.
When researchers took into account performance on an episodic memory evaluation, they found that the worse the episodic memory performance, the greater the delayed activity that appeared in the EEG.

For the study, 16 individuals with aMCI and 17 age matched healthy controls were monitored by EEG and presented with pairs of words that either described features of an object or were randomly paired.
For example, 'humps' and 'desert' would evoke the memory of the word 'camel', but 'humps' and 'monitor' would be considered a random pair.
Participants were then asked to indicate by button press whether the pair conjured any particular object memory or not.
"The majority of EEG research in aMCI has focused on looking at the mind 'at rest', but we are looking at the brain while it is engaged in the object memory retrieval process," said lead author Hsueh-Sheng Chiang, previously a student at Centre for BrainHealth and now a post-doctoral fellow at UT Southwestern Medical Centre.

"We think this might be more sensitive and more specific in pointing out certain cognitive deficits, in this case semantic memory, than other non-EEG methods available, because EEG reflects direct neural activity," Chiang said.
"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," Chiang added.
The study was published in the Journal of Alzheimer's Disease.