A team of scientists from the University of Cambridge have discovered a VR test that could help detect navigation problems - often one of the first parts of the brain affected by Alzheimer’s disease. The entorhinal cortex is both used to help navigation and often one of the first brain regions to show neurodegeneration in the disease. The scientists published their findings in Brain, an open access journal, which can be read in full, online.
45 patients who had been diagnosed with mild cognitive impairment (MCI), were recruited from the Cambridge University Hospitals MHS Trust. Using a different method to score, the scientists evaluated objective cognitive decline. The patients also had blood taken to exclude other possible causes of MCI, which could include a major psychiatric or medical disorder, history of alcoholism, visual or mobility impairment, severe enough to compromise the patient’s ability to take the VR test, epilepsy or a high stroke risk score.
26 of the participants were given biomarker studies as part of their clinical diagnostics, while the other 19 were not. 41 healthy control patients were also recruited from Join Dementia Research, which is an online group of volunteers and patients who want to participate in dementia research.
The study asked participants to map out a 3.5 x 3.5m space, which they walked while in the VR task. Participants who walked beyond the boundary by 30cm were warned by a sign and the scientists stayed nearby to keep participants inside the test space. They created three unique environments which included surface details, lighting and boundary cues. They aimed for the participants to use EC-grid cell dependent strategies and they programmed the VR equipment to use 1-1 correspondence between the real and virtual worlds. The participants were asked to follow an ‘L’ shaped path, marked by cones which were seen one at a time. When the participants had reached the third cone, they were asked to find their way back to the location of cone 1, using memory. Once they had reached where they had started from, they pressed a hand-held controller, which showed their end position and finished the trial. They were given time to get used to the environment and take part in practice trials before taking part in the actual trials.
The participants were also given traditional tests which were considered to be sensitive to early Alzheimer’s disease. The group with MCI showed larger absolute distance errors when compared to the healthy control group. The scientists could not use gender, years in education or age as predictions of absolute distance error, but found that those with MCI-biomarker positive patients could be differentiated from those patients who were biomarker-negative, both specifically and with higher sensitivity than when using the normal gold standard cognitive tests. The results agreed with previous navigational research studies, but showed that people who were already showing physical signs of Alzheimer’s disease found it difficult to perform navigation tasks. The scientists suggested that the navigational problems may be specific to the disease - the impairment seemed to be distance estimation and could relate to a build-up of tau.
The limitations of the study was the small sample size and the fact that the test space size was not that big, but all that was available with the current VR. Future VR will enable larger spaces to be used, which could prove more definitive in proving that spatial awareness is related to development of Alzheimer’s disease. However the study showed that VR has potential to diagnose potential cases of Alzheimer’s more accurately than the paper and pen tests currently used. One of the lead scientists sees technology as important to help diagnose and monitor the disease. He is working with a team to develop future technology to enable AI and wearable technology to help monitor progression of Alzheimer’s disease.
Chan, D., et al., Differentiation of mild cognitive impairment using an entorhinal cortex-based test of virtual reality navigation. Brain, Vol: 142, Issue 6, June 2019, pp 1751-1766