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  Bayesian reinforcement learning models reveal how great-tailed grackles improve their behavioral flexibility in serial reversal learning experiments

Lukas, D., McCune, K., Blaisdell, A., Johnson-Ulrich, Z., MacPherson, M., Seitz, B., et al. (2024). Bayesian reinforcement learning models reveal how great-tailed grackles improve their behavioral flexibility in serial reversal learning experiments. Peer Community Journal, 4: e88. doi:10.24072/pcjournal.456.

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 Creators:
Lukas, Dieter1, Author                 
McCune, Kelsey, Author
Blaisdell, Aaron, Author
Johnson-Ulrich, Zoe, Author
MacPherson, Maggie, Author
Seitz, Benjamin, Author
Sevchik, August, Author
Logan, Corina J.1, Author                 
Affiliations:
1Department of Human Behavior Ecology and Culture, Max Planck Institute for Evolutionary Anthropology, Max Planck Society, ou_2173689              

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Free keywords: Behavioral flexibility, comparative cognition, grackle, innovativeness, multi-access box, problem solving, reversal learning
 Abstract: Environments can change suddenly and unpredictably and animals might benefit from being able to flexibly adapt their behavior through learning new associations. Serial (repeated) reversal learning experiments have long been used to investigate differences in behavioral flexibility among individuals and species. In these experiments, individuals initially learn that a reward is associated with a specific cue before the reward is reversed back and forth between cues, forcing individuals to reverse their learned associations. Cues are reliably associated with a reward, but the association between the reward and the cue frequently changes. Here, we apply and expand newly developed Bayesian reinforcement learning models to gain additional insights into how individuals might dynamically modulate their behavioral flexibility if they experience serial reversals. We derive mathematical predictions that, during serial reversal learning experiments, individuals will gain the most rewards if they 1) increase their *rate of updating associations* between cues and the reward to quickly change to a new option after a reversal, and 2) decrease their *sensitivity* to their learned association to explore the alternative option after a reversal. We reanalyzed reversal learning data from 19 wild-caught great-tailed grackles (Quiscalus mexicanus), eight of whom participated in serial reversal learning experiment, and found that these predictions were supported. Their estimated association-updating rate was more than twice as high at the end of the serial reversal learning experiment than at the beginning, and their estimated sensitivities to their learned associations declined by about a third. The changes in behavioral flexibility that grackles showed in their experience of the serial reversals also influenced their behavior in a subsequent experiment, where individuals with more extreme rates or sensitivities solved more options on a multi-option puzzle box. Our findings offer new insights into how individuals react to uncertainty and changes in their environment, in particular, showing how they can modulate their behavioral flexibility in response to their past experiences.

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Language(s): eng - English
 Dates: 2024-09-05
 Publication Status: Published online
 Pages: -
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 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.24072/pcjournal.456
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Title: Peer Community Journal
Source Genre: Journal
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Pages: - Volume / Issue: 4 Sequence Number: e88 Start / End Page: - Identifier: ISSN: 2804-3871