Proactive Information Sampling in Value-Based Decision-Making: Deciding When and Where to Saccade

• Main Authors: Mingyu Song, Xingyu Wang, Hang Zhang, Jian Li
• Format: Article
• Language: English
• Published: Frontiers Media S.A. 2019-02-01
• Series: Frontiers in Human Neuroscience
• Subjects: decision-making; eye-tracking; information sampling; Bayesian inference; drift-diffusion model
• Online Access: https://www.frontiersin.org/article/10.3389/fnhum.2019.00035/full

Evidence accumulation has been the core component in recent development of perceptual and value-based decision-making theories. Most studies have focused on the evaluation of evidence between alternative options. What remains largely unknown is the process that prepares evidence: how may the decision-maker sample different sources of information sequentially, if they can only sample one source at a time? Here we propose a theoretical framework in prescribing how different sources of information should be sampled to facilitate the decision process: beliefs for different noisy sources are updated in a Bayesian manner and participants can proactively allocate resource for sampling (i.e., saccades) among different sources to maximize the information gain in such process. We show that our framework can account for human participants' actual choice and saccade behavior in a two-alternative value-based decision-making task. Moreover, our framework makes novel predictions about the empirical eye movement patterns.