2016 Affiliated Papers

1. Cheng, W., Rolls, E., Qiu, J., Liu, W., Tang, Y., Huang, C.C., Wang, X., Zhang, J., Lin, W., Zheng, L., Pu, J., Tsai, S.J., Yang, A., Lin, C.P., Wang, F., Xie, P., & Feng, J. (2016). Medial reward and lateral non-reward orbitofrontal cortex circuits change in opposite directions in depression. Brain, 139, 3296-3309. Medial reward and lateral non-reward orbitofrontal cortex circuits change in opposite directions in depression.pdf

2. Gao, Z.K., Cai, Q., Dong, N., Zhang, S.S., Bo, Y., & Zhang, J. (2016). Complex network inference from P300 signals: Decoding brain state under visual stimulus for able-bodied and disabled subjects. Physica a-Statistical Mechanics and Its Applications, 460, 294-303. Complex network inference from P300 signals Decoding brain state under visual stimulus for able-bodied and disabled subjects.pdf

3. Guo, S., Palaniyappan, L., Liddle, P., & Feng, J. (2016). Dynamic cerebral reorganization in the pathophysiology of schizophrenia: a MRI-derived cortical thickness study. Psychological Medicine, 46(10), 2201-2214.

4. Huang, L., Qu, H., Ji, P., Liu, X., & Fan, Z. (2016). A novel coordinated path planning method using k-degree smoothing for multi-UAVs. Applied Soft Computing, 48, 182-192.

5. Jia, T., Macare, C., Desrivieres, S., Gonzalez, D., Tao, C., Ji, X., Ruggeri, B., Nees, F., Banaschewski, T., Barker, G., Bokde, A., Bromberg, U., Buechel, C., Conrod, P., Dove, R., Frouin, V., Gallinat, J., Garavan, H., Gowland, P., Heinz, A., Ittermann, B., Lathrop, M., Lemaitre, H., Martinot, J.L., Paus, T., Pausova, Z., Poline, J.B., Rietschel, M., Robbins, T., Smolka, M., Mueller, C., Feng, J., Rothenfluh, A., Flor, H., Schumann, G., & Consortium, I. (2016). Neural basis of reward anticipation and its genetic determinants. Proceedings of the National Academy of Sciences of the United States of America, 113(14), 3879-3884. Neural basis of reward anticipation and its genetic determinants.pdf

6. Karaman, M., Wang, H., Sui, Y., Engelhard, H., Li, Y., & Zhou, X. (2016). A fractional motion diffusion model for grading pediatric brain tumors. Neuroimage-Clinical, 12, 707-714. A fractional motion diffusion model for grading pediatric brain tumors.pdf

7. Politi, N., Feng, J., Lu, W., & Ieee (2016). Comparing Data Assimilation Filters for Parameter Estimation in a Neuron Model. In International Joint Conference on Neural Networks (IJCNN) (pp. 4767-4774).

8. Tao, C., & Feng, J. (2016). Nonlinear association criterion, nonlinear Granger causality and related issues with applications to neuroimage studies. Journal of Neuroscience Methods, 262, 110-132. Nonlinear association criterion, nonlinear Granger causality and related issues with applications to neuroimage studies.pdf

9. Weng, T., Zhang, J., Khajehnejad, M., Small, M., Zheng, R., & Hui, P. (2016). Navigation by anomalous random walks on complex networks. Scientific Reports, 6. Navigation by anomalous random walks on complex networks.pdf

10. Zhang, J., Cheng, W., Liu, Z., Zhang, K., Lei, X., Yao, Y., Becker, B., Liu, Y., Kendrick, K., Lu, G., & Feng, J. (2016). Neural, electrophysiological and anatomical basis of brain-network variability and its characteristic changes in mental disorders. Brain, 139, 2307-2321. Neural, electrophysiological and anatomical basis of brain-network variability and its characteristic changes in mental disorders.pdf