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 © 2012 Airiti Press Inc. & Taiwanese Psychology Association Neural Mechanisms of Implicit Visual Probability Learning Philip Tseng, 1,2 Hui-Yan Chiau, 1,2,3 Chia-Lun Liu, 1,2,3 Tzu-Yu Hsu, 1,2,3 Chi-Fu Chang, 1,2 Chang-Mao Chao, 1,3 Wei-Kuang Liang, 1,2 and Chi-Hung Juan 1,2 1 Institute of Cognitive Neuroscience, National Central University 2 Laboratories for Cognitive Neuroscience, National Yang-Ming University 3 Institute of Neuroscience, National Yang-Ming University 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 ield, supplementary eye ield, 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) Regularities can be found ubiquitously in our visual world. Take traffic lights, for example; there is a serial order for which signals light up (temporal), as well as the color (feature based) and location (spatial) of each light, thus reflecting regularities in several domains of one’s daily life. This information can be fully predictive of future events if they are always 100% valid, such as the trafic light. But even with partial predictive power (not always 100% valid), which we refer to as probabilistic, it remains advantageous to pick up such information, as the knowledge of any regularities can help the visual system reduce its computational load because future events can be anticipated and better managed in advance. Indeed, several studies have demonstrated the visual system’s capability to learn and exhibit knowledge of regularities in the environment with and without subjective awareness (e.g., Chun & Jiang, 1998; Fiser & Aslin, 2001; Geng & Behrmann, 2005; Kristjánsson, Chen, & Nakayama, 2001; Nakayama, Maljkovic, & Kristjánsson, 2004). Eye movement studies have also shown that people can direct their eyes and attention to highly probable locations faster than to low-probability locations without employing an Received: March 5, 2011; First Revision: July 29, 2011; Second Revision: October 16, 2011; Third Revision: November 21, 2011; Accepted: November 25, 2011 Correspondence Author: Chi-Hung Juan (chijuan@cc.ncu.edu.tw) No. 300, Jhongda Rd., Jhongli City, 32001 Taiwan. Institute of Cognitive Neuroscience, National Central University Acknowledgements: This work was sponsored by the National Science Council, Taiwan (99-2410-H-008-022-MY3, 97-2511-S-008- 005-MY3, 98-2410-H-008-010-MY3, 98-2517-S-004-001-MY3, 97-2511-S-008-008-MY5). WKL is supported by the National Science Council, Taiwan (99-2811-H-008-005). CHJ was supported by the National Science Council, Taiwan (98-2918-I-008-011, 099-2811-H-008-005) and the Fulbright scholarship, Taiwan-USA. 09-Juan.indd 115 2012/3/22 下午 01:49:23