Huaiyu Liu

I am a 4th-year Ph.D. from the Behavioral Science Institute (BSI) at the Radboud University, interested in computational models of learning and decision-making, behavioral training, and Bayesian statistics. In my current Ph.D. project, I amplified the effect of Go/NoGo training on food choice by incorporating reinforcement learning principles. Specifically, such training effect was maximized when reinforcing Go actions (toward some foods) with rewards and NoGo actions (toward other foods) with the avoidance of punishments.

Interests

Reinforcement Learning
Bayesian Statistics
Food Choice
Behavioral Training (e.g., Go/NoGo training)

Publications

Protocol of the Healthy Brain Study: An accessible resource for understanding the human brain and how it dynamically and individually operates in its bio-social context

Healthy Brain Study

PloS one, vol. 16, Public Library of Science San Francisco, CA USA, 2021, pp. e0260952

How can food choice best be trained? Approach-avoidance versus go/no-go training

Harm Veling, Iris AM Verpaalen, Huaiyu Liu, Farnaz Mosannenzadeh, Daniela Becker, Rob W Holland

Appetite, vol. 163, Elsevier, 2021, p. 105226

Updating the p-curve analysis of Carbine and Larson with results from preregistered experiments

Harm Veling, Zhang Chen, Huaiyu Liu, Julian Quandt, Rob W Holland

Health Psychology Review, vol. 14, Routledge, 2020, pp. 215--219

Publications

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