Vol.5 No.3 (March 2015)
Change of Effective Connective of the ACT-R Network in the Resting State Based on Granger Causality Analysis
Recently, the organization of functional network promotes the understanding of the human brain. To further explore the functional reorganization affected by a short-time cognitive performance in human brain, we used the method of Granger causality analysis (GCA) to compare two resting fMRI data before and after a problem solving task. Distinguished from the view of the brain network as a whole in previous studies, GCA focused on the internal organization within a brain network. The re-sults showed that taking the ACT-R network as an example, the effective connectivity within the ACT-R network significantly changed after the brief cognitive task. In the post-resting state, proce-dural module (Cad) acted as a main information receiver received influence from other modules.
李 川 , 周海燕 , 周 军 , 熊玉琨 , 秦裕林 , 钟 宁 (2015) 静息态下基于格兰杰因果分析的ACT-R网络有效连接变化研究。 心理学进展， 5， 173-179. doi: 10.12677/AP.2015.53024
 左西年, 张喆, 贺永, 等(2013). 人脑功能连接组: 方法学, 发展轨线和行为关联. 科学通报, 35期, 3399-3413.
 Anderson, J. R. (1996). ACT: A simple theory of complex cognition. American Psychologist, 51, 355-365.
 Anderson, J. R., & Matessa, M. (1998). The rational analysis of categorization and the ACT-R architecture. Rational models of cognition, ed. M. Oaksford & N. Chater, 197-217.
 Anderson, J. R., & Schunn, C. D. (2000). Im-plications of the ACT-R learning theory: No magic bullets. In R. Glaser, (Ed.), Advances in Instructional Psychology, Educational Design and Cognitive Science (pp. 1-33). Mahwah, NJ: Lawrence Erlbaum Associates.
 Anderson, J. R., Bothell, D., Byrne, M. D., Douglass, S., Lebiere, C., & Qin, Y. (2004). An integrated theory of the mind. Psychological Review, 111, 1036-1060.
 Anderson, J. R., Fincham, J. M., Qin, Y., & Stocco, A. (2008). A central circuit of the mind. Trends in Cognitive Sciences, 12, 136-143.
 Deshpande, G., LaConte, S., James, G. A., Peltier, S., & Hu, X. (2009). Multivariate Granger causality analysis of fMRI data. Human Brain Mapping, 30, 1361-1373.
 Friston, K. J. (1994). Functional and effective connectivity in neuroimaging: A synthesis. Human Brain Mapping, 2, 56-78.
 Geweke, J. (1982). Measurement of linear dependence and feedback between multiple time series. Journal of the American Statistical Association, 77, 304-313.
 Granger, C. W. J. (1969). Investigating causal relations by econometric models and cross-spectral methods. Econometrica, 37, 424-438.
 Lebiere, C., & Anderson, J. R. (2008). A connectionist im-plementation of the ACT-R production system. Carnegie Mellon University, 635-640.
 Qin, Y., Bothell, D., & An-derson, J. R. (2007). ACT-R meets fMRI. In Web Intelligence Meets Brain Informatics (pp. 205-222). Berlin: Sprin-ger.
 Rubinov, M., & Sporns, O. (2010). Complex network measures of brain connectivity: Uses and interpretations. Neuroimage, 52, 1059-1069.
 Sohn, M. H., Ursu, S., Anderson, J. R., Stenger, V. A., & Carter, C. S. (2000). The role of prefrontal cortex and posterior parietal cortex in task switching. Proceedings of the National Academy of Sciences of the United States of America, 97, 13448-13453.
 Stewart, T. C., & West, R. L. (2007). Cognitive redeployment in ACT-R: Salience, vision, and memory. In 8th International Conference on Cognitive Modelling, Ann Arbor, 26-29 July 2007, 313-318.
 Wang, Z., Liu, J., Zhong, N., Qin, Y., Zhou, H., & Li, K. (2012). Changes in the brain intrinsic organization in both on-task state and post-task resting state. Neuroimage, 62, 394-407.
 Zang, Z. X., Yan, C. G., Dong, Z. Y., Huang, J., & Zang, Y. F. (2012). Granger causality analysis implementation on MATLAB: A graphic user interface toolkit for fMRI data processing. Journal of Neuroscience Methods, 203, 418-426.
 Zhang, H., Long, Z., Ge, R., Xu, L., Jin, Z., Yao, L., & Liu, Y. (2014). Motor Imagery Learning Modulates Functional Connectivity of Multiple Brain Systems in Resting State. PloS One, 9, e85489.