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Segregation between the parietal memory network and the default mode network: effects of spatial smoothing and model order in ICA
Hu, Yang1,2; Wang, Jijun3; Li, Chunbo3; Wang, Yin-Shan1,2; Yang, Zhi1,2,3; Zuo, Xi-Nian1; Z. Yang
2016-12-01
Source PublicationSCIENCE BULLETIN
Correspondent Emailyangz@psych.ac.cn
ISSN2095-9273
SubtypeArticle
Volume61Issue:24Pages:1844-1854
Abstract

A brain network consisting of two key parietal nodes, the precuneus and the posterior cingulate cortex, has emerged from recent fMRI studies. Though it is anatomically adjacent to and spatially overlaps with the default mode network (DMN), its function has been associated with memory processing, and it has been referred to as the parietal memory network (PMN). Independent component analysis (ICA) is the most common data-driven method used to extract PMN and DMN simultaneously. However, the effects of data preprocessing and parameter determination in ICA on PMN-DMN segregation are completely unknown. Here, we employ three typical algorithms of group ICA to assess how spatial smoothing and model order influence the degree of PMN-DMN segregation. Our findings indicate that PMN and DMN can only be stably separated using a combination of low-level spatial smoothing and high model order across the three ICA algorithms. We thus argue for more considerations on parametric settings for interpreting DMN data.

KeywordDefault mode network Parietal memory network Independent component analysis Model order Resting-state fMRI Spatial smoothing
DOI10.1007/s11434-016-1202-z
Indexed BySCI
Language英语
Funding OrganizationNational Basic Research (973) Program(2015CB351702) ; National Natural Science Foundation of China(81571756 ; Beijing Nova Program(XXJH2015B079) ; Outstanding Young Investigator Award of Institute of Psychology, Chinese Academy of Sciences ; Hundred Talents Program of the Chinese Academy of Sciences(KSZD-EW-TZ-002) ; Key Research Program of the Chinese Academy of Sciences(KSZD-EW-TZ-002) ; 81270023 ; 81278412 ; 81171409 ; 81000583 ; 81471740 ; 81220108014)
WOS Research AreaScience & Technology - Other Topics
WOS SubjectMultidisciplinary Sciences
WOS IDWOS:000390668600003
WOS HeadingsScience & Technology
WOS KeywordINDEPENDENT COMPONENT ANALYSIS ; RESTING-STATE FMRI ; INTRINSIC FUNCTIONAL CONNECTIVITY ; ALZHEIMERS-DISEASE ; HUMAN BRAIN ; GROUP PICA ; MRI ; PSYCHOPATHOLOGY ; REPRODUCIBILITY ; SEGMENTATION
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Document Type期刊论文
Identifierhttp://ir.psych.ac.cn/handle/311026/20975
Collection中国科学院行为科学重点实验室
Corresponding AuthorZ. Yang
Affiliation1.Chinese Acad Sci, Key Lab Behav Sci, Lab Human Connectome & Dev, Inst Psychol,Magnet Resonance Res Ctr, Beijing 100101, Peoples R China
2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
3.Shanghai Jiao Tong Univ, Sch Med, Shanghai Key Lab Psychot Disorders, Shanghai Mental Hlth Ctr, Shanghai 200030, Peoples R China
Recommended Citation
GB/T 7714
Hu, Yang,Wang, Jijun,Li, Chunbo,et al. Segregation between the parietal memory network and the default mode network: effects of spatial smoothing and model order in ICA[J]. SCIENCE BULLETIN,2016,61(24):1844-1854.
APA Hu, Yang.,Wang, Jijun.,Li, Chunbo.,Wang, Yin-Shan.,Yang, Zhi.,...&Z. Yang.(2016).Segregation between the parietal memory network and the default mode network: effects of spatial smoothing and model order in ICA.SCIENCE BULLETIN,61(24),1844-1854.
MLA Hu, Yang,et al."Segregation between the parietal memory network and the default mode network: effects of spatial smoothing and model order in ICA".SCIENCE BULLETIN 61.24(2016):1844-1854.
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