Effects of Aging on Successful Object Encoding: Enhanced Semantic Representations Compensate for Impaired Visual Representations.

Although episodic memory and visual processing decline substantially with healthy aging, semantic knowledge is generally spared. There is evidence that older adults' spared semantic knowledge can support episodic memory. Here, we used functional magnetic resonance imaging (fMRI) combined with representational similarity analyses (RSAs) to examine how novel visual and preexisting semantic representations at encoding predict subjective memory vividness at retrieval. Eighteen young and seventeen older adults (female and male participants) encoded images of objects during fMRI scanning and recalled these images while rating the vividness of their memories. After scanning, participants discriminated between studied images and similar lures. RSA based on a deep convolutional neural network and normative concept feature data were used to link patterns of neural activity during encoding to visual and semantic representations. Relative to young adults, the specificity of activation patterns for visual features was reduced in older adults, consistent with dedifferentiation. However, the specificity of activation patterns for semantic features was enhanced in older adults, consistent with hyperdifferentiation. Despite dedifferentiation, visual representations in early visual cortex (EVC) predicted high memory vividness in both age groups. In contrast, semantic representations in lingual gyrus (LG) and fusiform gyrus (FG) were associated with high memory vividness only in the older adults. Intriguingly, data suggests that older adults with lower specificity of visual representations in combination with higher specificity of semantic representations tended to rate their memories as more vivid. Our findings suggest that memory vividness in aging relies more on semantic representations over anterior regions, potentially compensating for age-related dedifferentiation of visual information in posterior regions.