How prior knowledge impacts episodic memory deficits in aging - PROJECT SUMMARY/ABSTRACT
The decline of episodic memory is one of the most commonly reported causes of anxiety related to
aging, and an ever-growing public health burden—but when older adults’ prior knowledge (i.e., schema) is
consistent with what they are trying to remember, older adults typically exhibit no memory deficits relative to
younger adults. When their schema is conflicting with to-be-remembered information, however, older adults
exhibit marked memory deficits relative to younger adults. The mechanisms driving these schema effects on
older adults’ memory are still unclear, and there is lively debate regarding those mechanisms: One prevailing
theory of age-related memory deficits proposes that schema effects are driven by degraded episodic memory
fidelity in older adults, while the other proposes that these effects are instead driven by older adults failing to
inhibit inappropriate schema influence. Critically, no extant theory of memory decline can account for the full
pattern of schema effects on older adults’ memory; thus, the drivers of schema effects on age-related memory
deficits are unknown. Until we understand how schema-memory interactions shape older adults’ memory, we
cannot fully understand age-related memory decline. This project aims to elucidate the processes through
which schemas influence older adults’ memory deficits in two specific aims: (1) Test the predictions of a novel
theory of age differences in schema-memory interactions, and (2) Determine the cognitive mechanisms
underlying schema effects on age-related memory deficits. A converging operations approach will be taken,
using computational cognitive modeling, eyetracking, and new behavioral paradigms with parametric memory
assessments and real-world scenes. The fellow’s primary training goal is to learn to use computational
cognitive modeling, which will permit direct examination of nuanced interactions between relevant cognitive
processes—such as the role of inhibitory control in driving age differences in schema-memory interactions.
The sponsors have complementary expertise in computational cognitive modeling, schema-memory
interactions, memory aging, and inhibitory control. The applicant will benefit from the rich research and training
environment within the sponsors’ research groups as well as at the university at large, which offers resources
that are uniquely relevant to the project such as a speaker series on advanced memory analysis; a workshop
series for learning advanced programming skills; a high-performance computing center that offers hardware,
training, and consultation; and graduate seminars in computational cognitive modeling. The proposed research
stands to substantially advance our understanding of memory deficits in healthy aging by directly testing
previously theorized mechanisms for the first time, identifying new mechanisms that had not previously been
considered, and putting forward a new theory that stands to reconcile competing theories. These findings are
thus expected to provide a strong foundation for the development of interventions for memory decline in aging,
such as interventions targeting the use of schemas in memory decisions.
