The cost-based balancing of sampling versus remembering in a naturalistic task
Poster Presentation: Sunday, May 18, 2025, 2:45 – 6:45 pm, Pavilion
Session: Visual Memory: Capacity and encoding of working memory
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Candice Koolhaas1 (), Jade Zack1, Zsuzsa Kaldy1, Erik Blaser1; 1UMass Boston
Naturalistic tasks, like a successful grocery run, allow individuals to modulate their use of external resources (a shopping list) versus internal resources (memory); a sampling-remembering trade-off (Ballard et al., 1995; Van der Stigchel, 2020; Liang et al., 2025). In our view, we exploit this trade-off to maintain a preferred balance: as the cost to use internal resources would increase (a longer to-be-remembered shopping list), we compensate by sampling more; as the cost to use external resources would increase (the list is in your partner’s pocket), we compensate by remembering more. In our tablet-based ‘Shopping Game’, participants (N=27) chose items in a store from a 10-item shopping list. The list and the store were not visible simultaneously. In the low-cost baseline condition, participants could toggle freely between them. In the sampling-delay condition, sampling cost was increased by introducing an annoying 5s lag before list exposure. In the maintenance-delay condition, sampling cost was similarly increased, but now the 5s delay occurred before store exposure, meaning, critically, that remembering cost was also increased (since list items had to be maintained in working memory during the lag); i.e., opposing effects. We measured participants' study time of the list and memory usage (number of correct selections, per store visit). As expected, there was a shift toward remembering - greater study time and memory usage - in both delay conditions. Our results also reflected the opposing effects present in the maintenance-delay condition, with study time and memory usage midway between the baseline and sampling-delay conditions (a post-hoc test for linear trend (baseline, maintenance-delay, sampling-delay) was significant for both measures, F(1, 50)=19.8, p<.001 and F(1, 50)=4.95, p=.031, respectively). An ongoing analysis of concurrent task-evoked pupillometry (Tobii Nano) will be used to corroborate this cost-based rebalancing of sampling versus remembering.
Acknowledgements: The project was supported by NIH R15HD115244 and NDSEG 12084CNBS grants