期刊
CORTEX
卷 145, 期 -, 页码 212-225出版社
ELSEVIER MASSON, CORP OFF
DOI: 10.1016/j.cortex.2021.09.017
关键词
Active inference; Bayesian; Predictive coding; Visuomotor; Virtual reality
资金
- Economic and Social Research Council [ES/P000630/1]
- South-West Doctoral Training Partnership PhD studentship
The study found that participants' predictive gaze behaviors were adjusted in different environmental stability conditions during a virtual racquetball task, in line with Bayesian optimal behavior patterns. Additionally, unpredictability in environmental probability changes was found to increase the speed of associative learning.
This study examined the application of active inference to dynamic visuomotor control. Active inference proposes that actions are dynamically planned according to uncertainty about sensory information, prior expectations, and the environment, with motor adjust-ments serving to minimise future prediction errors. We investigated whether predictive gaze behaviours are indeed adjusted in this Bayes-optimal fashion during a virtual racquetball task. In this task, participants intercepted bouncing balls with varying levels of elasticity, under conditions of higher or lower environmental volatility. Participants' gaze patterns differed between stable and volatile conditions in a manner consistent with generative models of Bayes-optimal behaviour. Partially observable Markov models also revealed an increased rate of associative learning in response to unpredictable shifts in environmental probabilities, although there was no overall effect of volatility on this parameter. Findings extend active inference frameworks into complex and unconstrained visuomotor tasks and present important implications for a neurocomputational under-standing of the visual guidance of action. (c) 2021 Elsevier Ltd. All rights reserved.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据