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Characterizing levels of granularity in the neural bases of motivated memory

Horwath, Elizabeth
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http://dx.doi.org/10.34944/dspace/10642
Abstract
Our memory system is highly complex and contains numerous features ranging from fine-grained, event-specific details through high-level conceptual knowledge. With immense amounts of constant incoming information, limitations on our memory system do not allow us to encode every detail into long-term memory. Thus, memory is prioritized for the information that is most valuable or important to our current or future goals (Adcock et al., 2006; Murty & Adcock, 2017). While this literature has shown a link between motivation and memory in general, our recent work has begun to characterize how motivation targets different aspects of memory, with evidence suggesting a focus on higher-level features (Horwath et al., 2023; Horwath & Murty, in-prep). Yet, investigating the neural bases of this process will further our understanding of the structure of memory. We tackled this question using representational similarity analysis (RSA) to first characterize the granularity at which reward is represented categorically or continuously in the brain, and then measure how those representations relate to subsequent memory. We measured pattern similarity in the medial temporal lobe (MTL) and a larger network containing anterior temporal (AT) regions, which supports conceptual information, and posterior medial (PM) regions, which support event-specific details. Results showed hippocampal (HPC) and AT involvement in representing categorical aspects of motivation, while PM tracked continuity across value. The AT and PM networks also revealed an important role in supporting successful memory for high- and low-value information, respectively. Together, this work highlights the importance of understanding the neural processes underlying the complexities of motivated memory.
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