Virtual reality navigation assessment and 7 tesla MR imaging of the entorhinal-hippocampal circuit in asymptomatic at-risk Alzheimer's disease

Identification of the initial alterations of brain function in Alzheimer’s disease (AD) is critically important for early disease detection and future use of disease-modifying drugs to delay progression to dementia. Given that AD-related neurodegeneration is first observed in the entorhinal cortex (EC), and that EC neurons contribute to path integration-based navigation, this thesis aimed to test the hypothesis that path integration would be impaired in people at risk of AD, prior to symptom onset. In Experiment 1, path integration was assessed using an immersive virtual reality assessment in 100 cognitively asymptomatic individuals from the PREVENT Dementia Programme with pre-existing clinical and cognitive profiles. They were aged between 43-66 years and stratified by AD risk status on the basis of three risk factors (family history, APOEe4 allele, lifestyle dementia risk score). In addition, a subset of 55 individuals further underwent Experiment 2, a 7 tesla MRI scan to explore structural and functional correlates of path integration function. Results showed that path integration in individuals at higher risk of AD was impaired only when supportive environment boundary information was removed, with this effect observed to differing extents across all AD risk factors. Effects tentatively associated with altered grid cell fMRI representations and, in family history only, altered CA1 subfield volume. In cognitive data collected as part of the PREVENT Programme, a family history of dementia and higher lifestyle risk score were also associated with impaired allocentric spatial memory. Importantly, performance on non-navigation related cognitive assessments was unrelated to risk of AD. These data support the future use of navigation tests to detect the earliest stages of AD, and the basis of path integration testing on knowledge of EC single cell activity aids translational research aiming to understand how the effect of AD molecular pathology on cellular function results in clinical manifestations of disease.

Name dc:type.qualificationname

Doctor of Philosophy (PhD)

Level dc:type.qualificationlevel

Doctoral

Grantor dc:publisher.institution

University of Cambridge

Year dc:date.issued

2023

Author dc:creator

• Newton, Charlotte

Advisors dc:contributor.advisor

• Su, Li
• O'Brien, John

• Alzheimer's disease
• Spatial navigation
• Virtual reality
• Neuroimaging

Licence

• https://www.rioxx.net/licenses/all-rights-reserved/

Language dc:language

eng

DOI dc:identifier.doi

https://doi.org/10.17863/CAM.93912

OAI identifier oai:identifier

oai:www.repository.cam.ac.uk:1810/346497