A Whole Brain Atlas with Sub-parcellation of Cortical Gyri using Resting fMRI

被引:7
|
作者
Joshi, Anand A. [1 ]
Choi, Soyoung [1 ]
Sonkar, Gaurav [2 ]
Chong, Minqi [1 ]
Gonzalez-Martinez, Jorge [3 ]
Nair, Dileep [3 ]
Shattuck, David W. [4 ]
Damasio, Hanna [5 ]
Leahy, Richard M. [1 ]
机构
[1] Univ Southern Calif, Signal & Image Proc Inst, Los Angeles, CA 90007 USA
[2] Natl Inst Technol Warangal, Dept Comp Sci, Warangal, Andhra Pradesh, India
[3] Cleveland Clin Fdn, Epilepsy Ctr, 9500 Euclid Ave, Cleveland, OH 44195 USA
[4] Univ Calif Los Angeles, Ahmanson Lovelace Brain Mapping Ctr, Los Angeles, CA USA
[5] Univ Southern Calif, Dornsife Neurosci Imaging Inst, Los Angeles, CA USA
来源
关键词
Brain; Atlas; MRI; fMRI; Parcellation; HUMAN CEREBRAL-CORTEX; FRONTAL-CORTEX; ORGANIZATION; AREAS;
D O I
10.1117/12.2254681
中图分类号
O43 [光学];
学科分类号
070207 ; 0803 ;
摘要
The new hybrid-BCI-DNI atlas is a high-resolution MPRAGE, single-subject atlas, constructed using both anatomical and functional information to guide the parcellation of the cerebral cortex. Anatomical labeling was performed manually on coronal single-slice images guided by sulcal and gyral landmarks to generate the original (non-hybrid) BCI-DNI atlas. Functional sub-parcellations of the gyral ROIs were then generated from 40 minimally preprocessed resting fMRI datasets from the HCP database. Gyral ROIs were transferred from the BCI-DNI atlas to the 40 subjects using the HCP grayordinate space as a reference. For each subject, each gyral ROI was subdivided using the fMRI data by applying spectral clustering to a similarity matrix computed from the fMRI time-series correlations between each vertex pair. The sub-parcellations were then transferred back to the original cortical mesh to create the subparcellated hBCI-DNI atlas with a total of 67 cortical regions per hemisphere. To assess the stability of the gyral subdivisons, a separate set of 60 HCP datasets were processed as follows: 1) coregistration of the structural scans to the hBCI-DNI atlas; 2) coregistration of the anatomical BCI-DNI atlas without functional subdivisions, followed by sub-parcellation of each subject's resting fMRI data as described above. We then computed consistency between the anatomically-driven delineation of each gyral subdivision and that obtained per subject using individual fMRI data. The gyral sub-parcellations generated by atlas-based registration show variable but generally good overlap of the confidence intervals with the resting fMRI-based subdivisions. These consistency measures will provide a quantitative measure of reliability of each subdivision to users of the atlas.
引用
收藏
页数:9
相关论文
共 50 条
  • [1] A hybrid high-resolution anatomical MRI atlas with sub-parcellation of cortical gyri using resting fMRI
    Joshi, Anand A.
    Choi, Soyoung
    Liu, Yijun
    Chong, Minqi
    Sonkar, Gaurav
    Gonzalez-Martinez, Jorge
    Nair, Dileep
    Wisnowski, Jessica L.
    Haldar, Justin P.
    Shattuck, David W.
    Damasio, Hanna
    Leahy, Richard M.
    [J]. JOURNAL OF NEUROSCIENCE METHODS, 2022, 374
  • [2] Cohesive parcellation of the human brain using resting-state fMRI
    Nemani, Ajay
    Lowe, Mark J.
    [J]. JOURNAL OF NEUROSCIENCE METHODS, 2022, 377
  • [3] A Supervoxel-Based Method for Groupwise Whole Brain Parcellation with Resting State fMRI Data
    Wang, Jing
    Wang, Haixian
    [J]. FRONTIERS IN HUMAN NEUROSCIENCE, 2016, 10
  • [4] Robust brain parcellation using sparse representation on resting-state fMRI
    Yu Zhang
    Svenja Caspers
    Lingzhong Fan
    Yong Fan
    Ming Song
    Cirong Liu
    Yin Mo
    Christian Roski
    Simon Eickhoff
    Katrin Amunts
    Tianzi Jiang
    [J]. Brain Structure and Function, 2015, 220 : 3565 - 3579
  • [5] Robust brain parcellation using sparse representation on resting-state fMRI
    Zhang, Yu
    Caspers, Svenja
    Fan, Lingzhong
    Fan, Yong
    Song, Ming
    Liu, Cirong
    Mo, Yin
    Roski, Christian
    Eickhoff, Simon
    Amunts, Katrin
    Jiang, Tianzi
    [J]. BRAIN STRUCTURE & FUNCTION, 2015, 220 (06): : 3565 - 3579
  • [6] A sub plus cortical fMRI-based surface parcellation
    Lewis, John D.
    Bezgin, Gleb
    Fonov, Vladimir S.
    Collins, D. Louis
    Evans, Alan C.
    [J]. HUMAN BRAIN MAPPING, 2022, 43 (02) : 616 - 632
  • [7] Multi-Session Parcellation of the Human Brain Using Resting-State fMRI
    Ma, Haoyu
    Lei, Renhao
    Sun, Junxiao
    Kong, Youyong
    [J]. PROCEEDINGS OF THE 2018 IEEE 22ND INTERNATIONAL CONFERENCE ON COMPUTER SUPPORTED COOPERATIVE WORK IN DESIGN ((CSCWD)), 2018, : 336 - 340
  • [8] Generation of Individual Whole-Brain Atlases With Resting-State fMRI Data Using Simultaneous Graph Computation and Parcellation
    Wang, J.
    Hao, Z.
    Wang, H.
    [J]. FRONTIERS IN HUMAN NEUROSCIENCE, 2018, 12
  • [9] A generic framework for the parcellation of the cortical surface into gyri using geodesic Voronoi diagrams
    Cachia, A
    Mangin, JF
    Rivière, D
    Papadopoulos-Orfanos, D
    Kherif, F
    Bloch, I
    Régis, J
    [J]. MEDICAL IMAGE ANALYSIS, 2003, 7 (04) : 403 - 416
  • [10] Spatially constrained hierarchical parcellation of the brain with resting-state fMRI
    Blumensath, Thomas
    Jbabdi, Saad
    Glasser, Matthew F.
    Van Essen, David C.
    Ugurbil, Kamil
    Behrens, Timothy E. J.
    Smith, Stephen M.
    [J]. NEUROIMAGE, 2013, 76 (01) : 313 - 324