The University of Cambridge has discovered that virtual reality (VR) could help identify early symptoms of Alzheimer’s disease more accurately than existing cognitive tests. The research highlights the potential of assistive technologies to help diagnose and monitor dementia.

In 2014, UCL’s Professor John O’Keefe was jointly awarded the Nobel Prize in Physiology or Medicine for ‘discoveries of cells that constitute a positioning system in the brain’. The prize was awarded for Professor O’Keefe’s discovery that the brain contains a mental ‘satnav’ of where people are, where they have been, and how to navigate different spaces.

A key component of this internal satnav is a region of the brain known as the entorhinal cortex. This is one of the first regions to be damaged in Alzheimer’s disease, which could explain why people with the disease get lost, notes the University.

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However, current clinical cognitive tests are unable to test for navigation difficulties and instead spot memory loss symptoms, a later development in Alzheimer’s disease.

In collaboration with Professor Neil Burgess at UCL, a team of scientists at the University of Cambridge, led by Dr Dennis Chan, previously Professor O’Keefe’s PhD student, developed and trialled a VR navigation test in patients at risk of developing dementia. The results are published in the journal Brain.

The test saw a patient wearing a VR headset undertake a navigational task while walking in a simulated environment. Successful completion of the task required intact functioning of the entorhinal cortex, so Dr Chan’s team believed that patients with early Alzheimer’s disease would perform worse on the test.

The team recruited 45 patients with mild cognitive impairment (MCI) from the Cambridge University Hospitals NHS Trust Mild Cognitive Impairment and Memory Clinics.

Patients with MCI typically exhibit memory impairment, but while MCI can indicate early Alzheimer’s, it can also be caused by other conditions such as anxiety and normal ageing, according to the University. It was therefore important to establish the cause of MCI to determine whether affected individuals were at risk of developing dementia in the future.

The researchers took samples of cerebrospinal fluid (CSF) to look for biomarkers of underlying Alzheimer’s disease in their MCI patients, with 12 testing positive. The researchers also recruited 41 age-matched healthy controls for comparison.

All of the patients with MCI performed worse on the navigation task than their healthy counterparts. However, the study revealed two crucial additional observations.

First, MCI patients with positive CSF markers performed worse than those with negative CSF markers at low risk of future dementia.

Secondly, the VR navigation task was better at differentiating between these low- and high-risk MCI patients than current, leading tests for the diagnosis of Alzheimer’s.

Dr Chan believes technology could play a crucial role in diagnosing and monitoring Alzheimer’s disease. He is working with Professor Cecilia Mascolo at Cambridge’s Centre for Mobile, Wearable Systems and Augmented Intelligence to develop apps for detecting the disease and monitoring its progression.

These would also look for changes in how individuals navigate and changes in other everyday activities such as sleep and communication.

“We know that Alzheimer’s affects the brain long before symptoms become apparent,” said Dr Chan. “We’re getting to the point where everyday tech can be used to spot the warning signs of the disease well before we become aware of them.

“We live in a world where mobile devices are almost ubiquitous, and so app-based approaches have the potential to diagnose Alzheimer’s disease at minimal extra cost and at a scale way beyond that of brain scanning and other current diagnostic approaches.”

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