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Poster F54

Behavioral and neural correlates of visual statistical learning during n-back working memory in cognitively healthy young and older adults

Poster Session F - Tuesday, April 16, 2024, 8:00 – 10:00 am EDT, Sheraton Hall ABC

Hwamee Oh1, Shanti Mechery1; 1Brown University

Visual statistical learning involves the implicit association of temporally linked visual stimuli, which was often studied in the context of long term memory. Using fMRI, we examined behavioral and neural correlates of visual statistical learning during working memory and their age-related differences. Twenty-eight young (mean age=20.1(SD=3.0)) and nineteen cognitively normal older adults (mean age=67.1(SD=8.0)) performed 2-back working memory tasks with grey-scaled face and scene images. Each visual category was presented in block where face or scene images were either repeatedly followed by a predetermined face or scene image (STRONG-PAIR) or by different images in rotation (WEAK-PAIR). Additionally, other images were randomly selected with no pre-specified temporal association (RANDOM). Across the age groups, response time (RT) was faster for faces than scenes (p<0.001), with significant differences across pairs (p<0.001), having faster RT for WEAK-PAIR items than STRONG-PAIR and RANDOM items. Accuracy was higher for face than scene 2-back task performance (p<0.01), with higher accuracy with WEAK-PAIR than STRONG-PAIR or RANDOM (p<0.05). Overall, young subjects responded faster with higher accuracy than older adults (p<0.01). Across the age groups, greater hippocampal activations were associated with STRONG-PAIR compared with WEAK-PAIR items for both face and scene conditions, with greater activations in the left middle frontal cortex and left parietal cortex found in the face 2-back task. The present results suggest that visual statistical learning may interfere with working memory performance in both young and older adults by hampering the control of items in working memory with the learned associations between the items.

Topic Area: LONG-TERM MEMORY: Development & aging


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April 13–16  |  2024