TY - JOUR
T1 - Learning expectations shape cognitive control allocation
AU - Obando, Javier Alejandro Masís
AU - Musslick, Sebastian
AU - Cohen, Jonathan D.
N1 - Publisher Copyright:
Copyright © 2025 the Author(s).
PY - 2025/11/4
Y1 - 2025/11/4
N2 - Current models frame the allocation of cognitive control as a process of expected utility maximization. The benefits of a candidate control signal are weighed against its costs (e.g., opportunity costs). Recent theorizing has found that, despite promoting the counterintuitive behavior of longer deliberation, which is less rewarding in the short term, it is nevertheless normative to account for the value of learning when determining control allocation. Here, we sought to test this proposal by examining whether people were willing to allocate greater control and thereby expend greater effort (e.g., deliberate for longer) when they perceived a task to be learnable compared to when they did not. We found that participants’ proficiency and learning rate in the first block of a simple perceptual dot-motion task were able to predict their willingness to deliberate in a second block. These findings support the hypothesis that agents consider learnability when allocating cognitive control, and comply with a formal model of control allocation that considers the future discounted value of learning on reward.
AB - Current models frame the allocation of cognitive control as a process of expected utility maximization. The benefits of a candidate control signal are weighed against its costs (e.g., opportunity costs). Recent theorizing has found that, despite promoting the counterintuitive behavior of longer deliberation, which is less rewarding in the short term, it is nevertheless normative to account for the value of learning when determining control allocation. Here, we sought to test this proposal by examining whether people were willing to allocate greater control and thereby expend greater effort (e.g., deliberate for longer) when they perceived a task to be learnable compared to when they did not. We found that participants’ proficiency and learning rate in the first block of a simple perceptual dot-motion task were able to predict their willingness to deliberate in a second block. These findings support the hypothesis that agents consider learnability when allocating cognitive control, and comply with a formal model of control allocation that considers the future discounted value of learning on reward.
KW - cognitive control
KW - decision making
KW - drift diffusion model
KW - expected value of control
KW - learning
UR - https://www.scopus.com/pages/publications/105020246231
UR - https://www.scopus.com/pages/publications/105020246231#tab=citedBy
U2 - 10.1073/pnas.2416720122
DO - 10.1073/pnas.2416720122
M3 - Article
C2 - 41144677
AN - SCOPUS:105020246231
SN - 0027-8424
VL - 122
JO - Proceedings of the National Academy of Sciences of the United States of America
JF - Proceedings of the National Academy of Sciences of the United States of America
IS - 44
M1 - e2416720122
ER -