Qiufang Fu. Associate Professor
  • Name: Qiufang Fu
  • Office Address: 16 Lincui Road, Chaoyang District, Beijing 100101, China 100101
  • TEL: 010-64845395
  • FAX: 010-64872070
  • E-MAIL: fuqf@psych.ac.cn
Research interests
l    Implicit learning
l    Unconscious knowledge
l    Subliminal perception

1. 2011-2015 "Cognitive Features of Visual Media" , Sub-Project of a 973 program funded by Chinese Ministry of Science and Technology.
2. 2013-2016"The cognitive and neural mechnism of implicit category learning", Fund by the National Natural Science Foundation of China (31270024).
3. 2010-2012 "Learning from doing---the emergence of unconscious knowledge in implicit learning and its neural correlates",  Young Scientists Fund by the National Natural Science Foundation of China (30900395).


2/2010–present                  Assistant professor, Institute of Psychology, Chinese Academy of Sciences

9/2008 – 9/2009                Visiting scholar in School of Psychology, University of Sussex

7/2006–2/2010                  Assistant professor, Institute of Psychology, Chinese Academy of Sciences


9/2003 – 7/2006                Ph.D.     Cognitive Psychology, Institute of Psychology, CAS

(Advisor: Xiaolan Fu)

9/2000 – 7/2003                M. S.     Cognitive Psychology, Shandong Normal University

(Advisor: Yongfang Liu)

9/1996 – 7/2000                B. S.     Education, Qufu Normal University


1.        Li, K., Fu, Q., Sun, X., Zhou, X., & Fu, X. (in press). Paired-associate and feedback-based weather prediction tasks support multiple category learning systemshas. Frontiers in Psychology.  

2.        Fu, Q., Liu, Y. J., Dienes, Z., Wu, J., Chen, W., & Fu, X. (2016). The role of edge-based and surface-based information in natural scene categorization: Evidence from behavior and event-related potentials. Consciousness and Cognition, 43, 152–166. DOI:  http://dx.doi.org/10.1016/j.concog.2016.06.008

3.        Yu, M., Liu, Y. J., Wang, S. J., Fu, Q., Fu, X. (2016). A PMJ-inspired cognitive framework for natural scene categorization in line drawings. Eurocomputing, 173, 2041–2048.

4.        Fu, Q., Wang, J., Zhang, L., Yi, Zhang., & Fu, X (2015). Computational models of implicit sequence learning: Distinguishing abstract processes from chunking processes. In: Advances in Computational Psychophysiology (Science/AAAS, Washington, DC, 2015), p.2224.

5.        李婷婷, 付秋芳*, 傅小兰. (2015). 大学生发散性思维与创造力倾向的相关研究. 中华行为医学与脑科学杂志, 24(2), 166- 168.

6.        Liu, Y. J., Yu, M., Fu, Q., Chen, W. F., Liu, Y., & Xie, L. (2014). Cognitive mechanism related to line drawings and its applications in intelligent process of visual media: a survey. Front. Comput. Sci. 57: 032114(15), doi: 10.1007/s11432-013-4911-9.

7.        Liu*, Y. J., Ma, C. X., Fu, Q., Fu, X., Qin, S. F., & Xie, L. (2014). A sketch-based approach for interactive organization of video clips. ACM Trans. Multimedia Comput. Commun. Appl., 11( 1), Article 2, 21 pages. DOI: http://dx.doi.org/10.1145/2645643

8.      Fu, Q*., Dienes, Z., Shang, J., & Fu, X. (2013). Cultural difference on hierarchical stimuli in implicit sequence learning. PLoS ONE 8(8): e71625. doi:10.1371/journal.pone.0071625

9.      Shang, J., Fu, Q*., Dienes, Z., & Fu, X. (2013). Negative affects reduce performance in implicit sequence learning. PLoS ONE 8(1): e54693. doi:10.1371/journal.pone.0054693

10.  Fu, Q*., Bin, G., Dienes, Z., Fu, X, & Gao, X. (2013). Learning without consciously knowing: Evidence from event-related potentials in sequence learning. Consciousness and Cognition, 22, 2234

11.  Liu*, Y. J., Fu, Q., Liu , Y., & Fu, X. (2013). A distributed computational cognitive model for object recognition. Science in China (Series F: Information Sciences), 56(9), 113.

12.  Liu*, Y. J., Fu, Q., Liu, Y., & Fu, X. (2012). 2D-line-drawing-based 3D object recognition. Lecture Notes in Computer Science, 7633, 146153.

13.  Rohrmeier, M*., Fu, Q., & Dienes, Z. (2012). Implicit learning of recursive, hierarchical grammatical structures. PLoS ONE 7(10): e45885. doi:10.1371/journal.pone.0045885.  

14.  Li, K., Fu, Q*., & Fu, X. (2012). Cognitive neural mechanism of probabilistic category learning. Progress in Biochemistry and Biophysics, 39(11), 1037–1044. (in Chinese)

15.  Fu, Q*., Dienes, Z., & Fu, X. (2010). The distinction between intuition and guessing in the SRT task generation: A reply to Norman and Price. Consciousness and Cognition, 19, 478-480.  

16.  Fu, Q*., Dienes, Z., &Fu, X. (2010). Can unconscious knowledge allow control in sequence learning? Consciousness and Cognition, 19, 462-474.   

17.  Liu, Y., Fu, Q., & Fu, X*. (2009). The interaction between cognition and emotion. Chinese Science Bulletin, 54, 4102-4116.  

18.  Fu, Q., Fu, X*., & Dienes, Z. (2008). Implicit sequence learning and conscious awareness. Consciousness and Cognition, 17, 185-202. 

19.  Fu, Q*., & Fu, X. (2010). The effects of secondary task on implicit sequence learning. Psychological Science, 19, 462-474.   (In Chinese)

20.  Fu, Q., & Fu, X*. (2006). Relationship between implicit sequence learning and attention. Advances in Psychological Science, 14, 817-821.  (In Chinese)

21.  Fu, Q., & Fu, X*. (2006). Relationship between representations and consciousness in implicit learning. Advances in Psychological Science, 14, 18-22. (In Chinese)

22.  Fu, Q., & Fu, X*. (2005). The effects of exemplar quantity on implicit sequence learning. Psychological Science, 28, 801-805.  (In Chinese)

23.  Fu, Q., & Liu, Y*. (2004). The effects of implicit learning on sequence learning. Psychological Science, 27, 1107-1111.  (In Chinese)

24.  Fu, Q., Liu, Y*., & Fu, X. (2004). The effects of type and feature of knowledge on implicit sequence learning. Acta Psychologica Sinica, 36, 525-533.   (In Chinese).

25.  Fu, Q., & Liu, Y*. (2003). Some new development in the research of implicit learning mechanism. Advances in Psychological Science, 11, 405-410.   (In Chinese)



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