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Xia Liang, B.S.

Pre-doctoral Visiting Fellow |

Xia received her B.A. in Automation from Beijing Institute of Technology in 2008 and started to pursue her Ph.d in the State Key Laboratory of Cognitive Neurosciences and Learning in Beijing Normal University in the field of neuroimaing and brain connectomics. During her graduate training, she was involved in the development of brain network analytical methodology and its application to understand the brain mechanisms. Xia joined the Neuroimaging Research Branch at NIDA in 2011 as a pre-doctoral visiting fellow under Dr. Yihong Yang. 

Research Projects:

  • Combining resting-fMRI and graph theory based brain network approach to assess the disruption of functional brain network organization in chronic cocaine dependents
  • Study the physiological correlate of functional network hubs of the human brain by coupling functional connectivity obtained from resting-state fMRI and regional blood flow from ASL imaging
  • Understand the modulation effects of task load on the topological organization of functional brain networks


  • Liang X, Zou QH, He Y, Yang YH. Coupling of functional connectivity  and regional cerebral blood flow reveals a physiological basis for network hubs of the human brain. PNAS, accepted.
  • Wei T, Liang X, He Y, Zhang YF, Han ZZ, Caramazza A, Bi YC. Predicting Conceptual Processing Capacity from Spontaneous Neuronal Activity of the Left Middle Temporal Gyrus. The Journal of Neuroscience, 2012, 32(2): 481-489.
  • Liang X, Wang JH, Yan CG, Shu N, Xu K, Gong GL, He Y. Effects of Different Correlation Metrics and Preprocessing Factors on Small-World Brain Functional Networks: A Resting-State Functional MRI Study. PLoS ONE 7(3): e32766.
  • Kang J, Wang L, Yan CG, Wang JH, Liang X, He Y. Characterizing dynamic functional connectivity in the resting brain using variable parameter regression and Kalman filtering approaches. NeuroImage, 2011, 56(3): 1222-1234.
  • Liang X, Wang JH, He Y. Human connectome: Structural and functional brain networks (in Chinese). Chinese Sci Bull (Chinese Ver), 2010, 55:1565-1583.
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