Congruence of Inherent and Acquired Values Facilitates Reward-Based Decision-Making

TY - JOUR

T1 - Congruence of Inherent and Acquired Values Facilitates Reward-Based Decision-Making

AU - Chien, Samson

AU - Wiehler, Antonius

AU - Spezio, Michael

AU - Gläscher, Jan

N1 - Copyright © 2016 the authors 0270-6474/16/365003-10$15.00/0.

PY - 2016/5/4

Y1 - 2016/5/4

N2 - UNLABELLED: Most real-life cues exhibit certain inherent values that may interfere with or facilitate the acquisition of new expected values during associative learning. In particular, when inherent and acquired values are congruent, learning may progress more rapidly. Here we investigated such an influence through a 2 × 2 factorial design, using attractiveness (high/low) of the facial picture as a proxy for the inherent value of the cue and its reward probability (high/low) as a surrogate for the acquired value. Each picture was paired with a monetary win or loss either congruently or incongruently. Behavioral results from 32 human participants indicated both faster response time and faster learning rate for value-congruent cue-outcome pairings. Model-based fMRI analysis revealed a fractionation of reinforcement learning (RL) signals in the ventral striatum, including a strong and novel correlation between the cue-specific decaying learning rate and BOLD activity in the ventral caudate. Additionally, we detected a functional link between neural signals of both learning rate and reward prediction error in the ventral striatum, and the signal of expected value in the ventromedial prefrontal cortex, showing a novel confirmation of the mathematical RL model via functional connectivity.SIGNIFICANCE STATEMENT: Most real-world decisions require the integration of inherent value and sensitivity to outcomes to facilitate adaptive learning. Inherent value is drawing increasing interest from decision scientists because it influences decisions in contexts ranging from advertising to investing. This study provides novel insight into how inherent value influences the acquisition of new expected value during associative learning. Specifically, we find that the congruence between the inherent value and the acquired reward influences the neural coding of learning rate. We also show for the first time that neuroimaging signals coding the learning rate, prediction error, and acquired value follow the multiplicative Rescorla-Wagner learning rule, a finding predicted by reinforcement learning theory.

AB - UNLABELLED: Most real-life cues exhibit certain inherent values that may interfere with or facilitate the acquisition of new expected values during associative learning. In particular, when inherent and acquired values are congruent, learning may progress more rapidly. Here we investigated such an influence through a 2 × 2 factorial design, using attractiveness (high/low) of the facial picture as a proxy for the inherent value of the cue and its reward probability (high/low) as a surrogate for the acquired value. Each picture was paired with a monetary win or loss either congruently or incongruently. Behavioral results from 32 human participants indicated both faster response time and faster learning rate for value-congruent cue-outcome pairings. Model-based fMRI analysis revealed a fractionation of reinforcement learning (RL) signals in the ventral striatum, including a strong and novel correlation between the cue-specific decaying learning rate and BOLD activity in the ventral caudate. Additionally, we detected a functional link between neural signals of both learning rate and reward prediction error in the ventral striatum, and the signal of expected value in the ventromedial prefrontal cortex, showing a novel confirmation of the mathematical RL model via functional connectivity.SIGNIFICANCE STATEMENT: Most real-world decisions require the integration of inherent value and sensitivity to outcomes to facilitate adaptive learning. Inherent value is drawing increasing interest from decision scientists because it influences decisions in contexts ranging from advertising to investing. This study provides novel insight into how inherent value influences the acquisition of new expected value during associative learning. Specifically, we find that the congruence between the inherent value and the acquired reward influences the neural coding of learning rate. We also show for the first time that neuroimaging signals coding the learning rate, prediction error, and acquired value follow the multiplicative Rescorla-Wagner learning rule, a finding predicted by reinforcement learning theory.

KW - Adult

KW - Algorithms

KW - Brain Mapping

KW - Cues

KW - Decision Making

KW - Face

KW - Female

KW - Humans

KW - Image Processing, Computer-Assisted

KW - Magnetic Resonance Imaging

KW - Male

KW - Models, Theoretical

KW - Photic Stimulation

KW - Reward

KW - Social Desirability

KW - Ventral Striatum

KW - Young Adult

KW - Journal Article

KW - Research Support, Non-U.S. Gov't

U2 - 10.1523/JNEUROSCI.3084-15.2016

DO - 10.1523/JNEUROSCI.3084-15.2016

M3 - SCORING: Journal article

C2 - 27147653

VL - 36

SP - 5003

EP - 5012

JO - J NEUROSCI

JF - J NEUROSCI

SN - 0270-6474

IS - 18

ER -