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Paper Detail

Paper: PS-2B.45
Session: Poster Session 2B
Location: Symphony/Overture
Session Time: Friday, September 7, 19:30 - 21:30
Presentation Time:Friday, September 7, 19:30 - 21:30
Presentation: Poster
Publication: 2018 Conference on Cognitive Computational Neuroscience, 5-8 September 2018, Philadelphia, Pennsylvania
Paper Title: Learning to overexert cognitive control in the Stroop task
Manuscript:  Click here to view manuscript
Authors: Laura Bustamante, Princeton University, United States; Falk Lieder, Max Planck Institute for Intelligent Systems, Germany; Sebastian Musslick, Princeton University, United States; Amitai Shenhav, Brown University, United States; Jonathan Cohen, Princeton University, United States
Abstract: How does the cognitive system know when and how much cognitive control to allocate to which task? According to the Learned Value of Control (LVOC) model, people learn to predict the value of cognitive control based on a linear combination of stimulus features. This model predicts that what people learn about the value of control in one situation should transfer to other situations with shared features, leading to the intriguing prediction that maltransfer can cause people to over-exert control even when it harms their performance. To test this prediction, we designed a novel color word Stroop task in which we rewarded participants differentially for exerting cognitive control (i.e. color naming) or for engaging the more automatic response (i.e. word reading) based on individual stimulus features. We test how participants’ learned value of control transfers to novel stimuli that share features with previously exposed stimuli and create a situation that should lead to maltransfer according to the LVOC model. Empirical data from 30 participants confirmed this prediction and supports the conclusion that maltransfer in learning about the value of control can mislead people to overexert cognitive control even when it hurts their performance.