caa a22 4500 606201734 CHVBK 20210128100949.0 cr unu---uuuuu 210128e20151101xx s 000 0 eng 10.1007/s00429-014-0874-x doi (NATIONALLICENCE)springer-10.1007/s00429-014-0874-x Robust brain parcellation using sparse representation on resting-state fMRI [Elektronische Daten] [Yu Zhang, Svenja Caspers, Lingzhong Fan, Yong Fan, Ming Song, Cirong Liu, Yin Mo, Christian Roski, Simon Eickhoff, Katrin Amunts, Tianzi Jiang] Resting-state fMRI (rs-fMRI) has been widely used to segregate the brain into individual modules based on the presence of distinct connectivity patterns. Many parcellation methods have been proposed for brain parcellation using rs-fMRI, but their results have been somewhat inconsistent, potentially due to various types of noise. In this study, we provide a robust parcellation method for rs-fMRI-based brain parcellation, which constructs a sparse similarity graph based on the sparse representation coefficients of each seed voxel and then uses spectral clustering to identify distinct modules. Both the local time-varying BOLD signals and whole-brain connectivity patterns may be used as features and yield similar parcellation results. The robustness of our method was tested on both simulated and real rs-fMRI datasets. In particular, on simulated rs-fMRI data, sparse representation achieved good performance across different noise levels, including high accuracy of parcellation and high robustness to noise. On real rs-fMRI data, stable parcellation of the medial frontal cortex (MFC) and parietal operculum (OP) were achieved on three different datasets, with high reproducibility within each dataset and high consistency across these results. Besides, the parcellation of MFC was little influenced by the degrees of spatial smoothing. Furthermore, the consistent parcellation of OP was also well corresponding to cytoarchitectonic subdivisions and known somatotopic organizations. Our results demonstrate a new promising approach to robust brain parcellation using resting-state fMRI by sparse representation. The Author(s), 2014 Resting state nationallicence Functional connectivity nationallicence Robust brain parcellation nationallicence Medial frontal cortex nationallicence Parietal operculum nationallicence Sparse representation nationallicence Zhang Yu Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, 100190, Beijing, China aut Caspers Svenja Institute of Neuroscience and Medicine (INM-1), Research Centre Juelich, 52425, Juelich, Germany aut Fan Lingzhong Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, 100190, Beijing, China aut Fan Yong Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, 100190, Beijing, China aut Song Ming Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, 100190, Beijing, China aut Liu Cirong Queensland Brain Institute, The University of Queensland, 4072, St Lucia, QLD, Australia aut Mo Yin The First Affiliated Hospital of Kunming Medical University, 650032, Kunming, People's Republic of China aut Roski Christian Institute of Neuroscience and Medicine (INM-1), Research Centre Juelich, 52425, Juelich, Germany aut Eickhoff Simon Institute of Neuroscience and Medicine (INM-1), Research Centre Juelich, 52425, Juelich, Germany aut Amunts Katrin Institute of Neuroscience and Medicine (INM-1), Research Centre Juelich, 52425, Juelich, Germany aut Jiang Tianzi Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, 100190, Beijing, China aut Brain Structure and Function Springer Berlin Heidelberg 220/6(2015-11-01), 3565-3579 1863-2653 220:6<3565 2015 220 429 https://doi.org/10.1007/s00429-014-0874-x text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s00429-014-0874-x text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Zhang Yu Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, 100190, Beijing, China aut NATIONALLICENCE 700 1- Caspers Svenja Institute of Neuroscience and Medicine (INM-1), Research Centre Juelich, 52425, Juelich, Germany aut NATIONALLICENCE 700 1- Fan Lingzhong Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, 100190, Beijing, China aut NATIONALLICENCE 700 1- Fan Yong Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, 100190, Beijing, China aut NATIONALLICENCE 700 1- Song Ming Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, 100190, Beijing, China aut NATIONALLICENCE 700 1- Liu Cirong Queensland Brain Institute, The University of Queensland, 4072, St Lucia, QLD, Australia aut NATIONALLICENCE 700 1- Mo Yin The First Affiliated Hospital of Kunming Medical University, 650032, Kunming, People's Republic of China aut NATIONALLICENCE 700 1- Roski Christian Institute of Neuroscience and Medicine (INM-1), Research Centre Juelich, 52425, Juelich, Germany aut NATIONALLICENCE 700 1- Eickhoff Simon Institute of Neuroscience and Medicine (INM-1), Research Centre Juelich, 52425, Juelich, Germany aut NATIONALLICENCE 700 1- Amunts Katrin Institute of Neuroscience and Medicine (INM-1), Research Centre Juelich, 52425, Juelich, Germany aut NATIONALLICENCE 700 1- Jiang Tianzi Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, 100190, Beijing, China aut NATIONALLICENCE 773 0- Brain Structure and Function Springer Berlin Heidelberg 220/6(2015-11-01), 3565-3579 1863-2653 220:6<3565 2015 220 429