Brain Structure and Function

, Volume 220, Issue 5, pp 2485–2507 | Cite as

Toward neurobiological characterization of functional homogeneity in the human cortex: regional variation, morphological association and functional covariance network organization

  • Lili Jiang
  • Ting Xu
  • Ye He
  • Xiao-Hui Hou
  • Jinhui Wang
  • Xiao-Yan Cao
  • Gao-Xia Wei
  • Zhi Yang
  • Yong He
  • Xi-Nian Zuo
Original Article


Local functional homogeneity of the human cortex indicates the boundaries between functionally heterogeneous regions and varies remarkably across the cortical mantle. It is unclear whether these variations have the neurobiological and structural basis. We employed structural and resting-state functional magnetic resonance imaging scans from 482 healthy subjects and computed the vertex-wise regional homogeneity of low-frequency fluctuations (2dReHo) and five measures of cortical morphology. We then used these metrics to examine regional variation, morphological association and functional covariance network of 2dReHo. Within the ventral visual stream, increases of 2dReHo reflect reduced complexity of information processing or functional hierarchies. Along the divisions of the prefrontal cortex and posteromedial cortex, the gradients of 2dReHo revealed the hierarchical organization within the two association areas, respectively. Individual differences in 2dReHo are associated with those of cortical morphology, and their whole-brain inter-regional covariation is organized into a functional covariance network, comprising five hierarchically organized modules with hubs of both primary sensory and high-order association areas. These highly reproducible observations suggest that local functional homogeneity has neurobiological relevance that is likely determined by anatomical, developmental and neurocognitive factors and should serve as a neuroimaging marker to investigate the human brain function.


Functional homogeneity Prefrontal cortex Posteromedial cortex Functional hierarchy Structural morphometry Functional covariance Network 



The authors would like to thank Drs. Olaf Sporns, Michael Peter Milham, Yu-Feng Zang and Hui-Jie Li for comments on an early version of the manuscript. All authors declare no competing financial interests. This work is partially supported by the National Key Technologies R&D Program of China (No. 2012BAI36B01), the Startup Foundation for Young Talents of Institute of Psychology (Y1CX222005, LJ), the Hundred Talents Program and the Key Research Program (KSZD-EW-TZ-002, XNZ) of Chinese Academy of Sciences, the Major Joint Fund for International Cooperation and Exchange of the National Natural Science Foundation (81220108014, XNZ) and others from Natural Science Foundation of China (11204369, 81270023, 81171409). Data were provided [in part] by the HCP WU-Minn Consortium, which is funded by the 16 NIH institutes and centers that support the NIH Blueprint for Neuroscience Research 1U54MH091657 (PIs: David Van Essen and Kamil Ugurbil), the McDonnell Center for Systems Neuroscience at Washington University.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Lili Jiang
    • 1
  • Ting Xu
    • 1
  • Ye He
    • 1
    • 2
  • Xiao-Hui Hou
    • 1
    • 2
  • Jinhui Wang
    • 3
  • Xiao-Yan Cao
    • 1
    • 3
  • Gao-Xia Wei
    • 1
  • Zhi Yang
    • 1
  • Yong He
    • 4
    • 5
  • Xi-Nian Zuo
    • 1
    • 5
  1. 1.Laboratory for Functional Connectome and Development, Key Laboratory of Behavioral Science and Magnetic Resonance Imaging Research Center, Institute of PsychologyChinese Academy of SciencesBeijingChina
  2. 2.University of Chinese Academy of SciencesBeijingChina
  3. 3.Center for Cognition and Brain Disorders and the Affiliated HospitalHangzhou Normal UniversityHangzhouChina
  4. 4.State Key Laboratory of Cognitive Neuroscience and Learning and International Data Group/McGovern Institute for Brain ResearchBeijing Normal UniversityBeijingChina
  5. 5.Center for Collaboration and Innovation in Brain and Learning SciencesBeijing Normal UniversityBeijingChina

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