PROJECT SUMMARY
The CA1 subfield of the hippocampus is particularly susceptible to developing tau pathology in aging and
preclinical Alzheimer’s disease (AD). Tau-related dysfunction of CA1 is therefore a likely candidate to
contribute to both age- and AD-related memory decline. However, no previous study has investigated the
direct relationship between tau pathology in CA1, CA1 activation, and memory performance. Emerging
evidence suggests that CA1 supports statistical learning, a memory process in which regularities between
distinct episodes are rapidly learning and integrated. The relationship between CA1 activation during statistical
learning and behavioral performance has not yet been investigated in an older adult population. In this study,
we propose to determine whether tau pathology in CA1 is associated with dysfunctional CA1 activation during
statistical learning, and whether these factors contribute to the expression of memory impairment in cognitive
normal older adults (OA). We will use a novel high-resolution multimodal neuroimaging design, assessing tau
deposition with the positron emission tomography (PET) tracer [18F] MK-6240 and CA1 activation with task-
based fMRI while subjects perform a statistical learning paradigm. We leverage an existing cohort from an
NIH-funded PET biomarker study (PI: Yassa) to conduct this ancillary study in a subsample of OAs enriched
for amyloid-positivity (n=60, age 60-85, 60% women). In Aim 1, we will assess the relationship between
statistical learning performance and CA1 activation in OA. We hypothesize that high-performing OA will have
greater CA1 activation than low-performing OA, and that CA1 activation will increase across the task as
regularities between stimuli are learned. We will further explore the representation of statistical learning across
the anterior-posterior and distal-proximal axes of CA1. In Aim 2, we will assess the impact of tau pathology on
CA1 activation and statistical learning performance. We hypothesize that hippocampal tau pathology, reflecting
CA1 tau, will be related to decreased activation and worse behavioral performance on the statistical learning
task. We will further develop methods to quantify tau pathology specifically within CA1, leveraging the
unmatched resolution of UCI’s PET scanner. In Aim 3, we will use resting state functional connectivity to
identify how entorhinal-hippocampal microcircuits are altered with tau pathology. We hypothesize that
hippocampal tau will specifically be related to disrupted connectivity between the entorhinal cortex and CA1
(monosynaptic pathway). We will also explore functional connectivity between CA1 and entorhinal subregions,
and other neocortical and subcortical regions. In summary, the proposed project will be the first to assess
relationships between CA1 tau pathology, CA1 function, and statistical learning behavioral performance in
aging and preclinical AD. Insights from this study will contribute to our understanding of how tau pathology
leads to memory decline in aging and AD. Statistical learning performance may be a valuable behavioral
marker of underlying tau pathology in CA1, with implications for trials assessing tau-lowering therapeutics.
