學刊論文
Neural Mechanisms of Implicit Visual Probability Learning

中華心理學刊 民101,54卷,1期,115-131
Chinese Journal of Psychology 2012, Vol.54, No.1, 115-131


Philip Tseng(Institute of Cognitive Neuroscience, National Central University;Laboratories for Cognitive Neuroscience, National Yang-Ming University);Hui-Yan Chiau(Institute of Cognitive Neuroscience, National Central University;Laboratories for Cognitive Neuroscience, National Yang-Ming University;Institute of Neuroscience, National Yang-Ming University);Chia-Lun Liu(Institute of Cognitive Neuroscience, National Central University;Laboratories for Cognitive Neuroscience, National Yang-Ming University;Institute of Neuroscience, National Yang-Ming University);Tzu-Yu Hsu(Institute of Cognitive Neuroscience, National Central University;Laboratories for Cognitive Neuroscience, National Yang-Ming University;Institute of Neuroscience, National Yang-Ming University);Chi-Fu Chang(Institute of Cognitive Neuroscience, National Central University;Laboratories for Cognitive Neuroscience, National Yang-Ming University);Chang-Mao Chao(Institute of Cognitive Neuroscience, National Central University;Institute of Neuroscience, National Yang-Ming University);Wei-Kuang Liang(Institute of Cognitive Neuroscience, National Central University;Laboratories for Cognitive Neuroscience, National Yang-Ming University);Chi-Hung Juan(Institute of Cognitive Neuroscience, National Central University;Laboratories for Cognitive Neuroscience, National Yang-Ming University)

 

Abstract

Predictive information exists ubiquitously in the visual environment. Such information signals the probability or likelihood of upcoming events, thus facilitating the visual system in preparing optimal responses in advance. This ability of the visual system to implicitly acquire predictive and probabilistic information has been well documented by behavioral evidence from many domains (e.g., spatial, temporal, and abstract probability). Recently, neurophysiological studies have begun to elucidate the neural mechanisms underlying these learning processes and suggest a critical involvement of the fronto-parietal network and medial temporal lobe. In this paper we review evidence for such learning at the visual attention and oculomotor control levels. We also review some of the studies that delineate the neural substrates that contribute to probability learning at both levels: including the frontal eye field, supplementary eye field, posterior parietal cortex, and medial temporal lobe. Together, each of these regions provides a unique and critical contribution to probability learning in visual attention and oculomotor control.


Keywords: visual attention, probability, predictability, eye movements, transcranial magnetic stimulation (TMS)

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