Evidence map›Paper›PMID 26466353›Full record

ArticleHuman brain mapping2015

Sparse representation of HCP grayordinate data reveals novel functional architecture of cerebral cortex.

Xi Jiang, Xiang Li, Jinglei Lv, Tuo Zhang, Shu Zhang, Lei Guo, Tianming Liu

Abstract read
In one paragraph

Article in Human brain mapping, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers.

0numbers the graph read from it
0cells of the map it votes in
35citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

35 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. UNSUPERVISED CORTICAL SURFACE REGISTRATION NETWORK FOR ALIGNING GYRALNET.Proceedings. IEEE International Symposium on Biomedical Imaging · 2025
    Article
  5. Article
  6. Article
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  8. Article
  9. Gyral peaks and patterns in human brains.Cerebral cortex (New York, N.Y. : 1991) · 2023
    Article
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  13. Article
  14. Review
  15. Article
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  17. Article
  18. TEMPORALLY ADAPTIVE-DYNAMIC SPARSE NETWORK FOR MODELING DISEASE PROGRESSION.Proceedings. IEEE International Symposium on Biomedical Imaging · 2020
    Article
  19. Article
  20. Article
4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

7 authors.

Xi JiangDepartment of Computer Science and Bioimaging Research Center, Cortical Architecture Imaging and Discovery Lab, The University of Georgia, Athens, Georgia.
Xiang LiDepartment of Computer Science and Bioimaging Research Center, Cortical Architecture Imaging and Discovery Lab, The University of Georgia, Athens, Georgia.
Jinglei LvDepartment of Computer Science and Bioimaging Research Center, Cortical Architecture Imaging and Discovery Lab, The University of Georgia, Athens, Georgia.
Tuo ZhangDepartment of Computer Science and Bioimaging Research Center, Cortical Architecture Imaging and Discovery Lab, The University of Georgia, Athens, Georgia.
Shu ZhangDepartment of Computer Science and Bioimaging Research Center, Cortical Architecture Imaging and Discovery Lab, The University of Georgia, Athens, Georgia.
Lei GuoSchool of Automation, Northwestern Polytechnical University, Xi'an, People's Republic of China.
Tianming LiuDepartment of Computer Science and Bioimaging Research Center, Cortical Architecture Imaging and Discovery Lab, The University of Georgia, Athens, Georgia.

Funding

Assessing Large-scale Connectivities in Prenatal Cocaine Exposure Affected BrainsR01DA033393 · NIDA · UNIVERSITY OF GEORGIA · PI HU, XIAOPING P, LIU, TIANMING · 2012 to 2016
$1.6M
Assessing Large-scale Brain Connectivities in Mild Cognitive ImpairmentR01AG042599 · NIA · UNIVERSITY OF GEORGIA · PI LIU, TIANMING · 2013 to 2017
$1.4M
NIA NIH HHS AG042599NIA NIH HHS R01 AG042599NIDA NIH HHS DA033393NIDA NIH HHS R01 DA033393
6 · The paper itself

Abstract

The recently publicly released Human Connectome Project (HCP) grayordinate-based fMRI data not only has high spatial and temporal resolution, but also offers group-corresponding fMRI signals across a large population for the first time in the brain imaging field, thus significantly facilitating mapping the functional brain architecture with much higher resolution and in a group-wise fashion. In this article, we adopt the HCP grayordinate task-based fMRI (tfMRI) data to systematically identify and characterize task-based heterogeneous functional regions (THFRs) on cortical surface, i.e., the regions that are activated during multiple tasks conditions and contribute to multiple task-evoked systems during a specific task performance, and to assess the spatial patterns of identified THFRs on cortical gyri and sulci by applying a computational framework of sparse representations of grayordinate brain tfMRI signals. Experimental results demonstrate that both consistent task-evoked networks and intrinsic connectivity networks across all subjects and tasks in HCP grayordinate data are effectively and robustly reconstructed via the proposed sparse representation framework. Moreover, it is found that there are relatively consistent THFRs locating at bilateral parietal lobe, frontal lobe, and visual association cortices across all subjects and tasks. Particularly, those identified THFRs locate significantly more on gyral regions than on sulcal regions. These results based on sparse representation of HCP grayordinate data reveal novel functional architecture of cortical gyri and sulci, and might provide a foundation to better understand functional mechanisms of the human cerebral cortex in the future.

Indexed as

Brain MappingConnectomeModels, NeurologicalCerebral CortexEmotionsFemaleHumansImage Processing, Computer-AssistedLanguageMagnetic Resonance ImagingMaleMotor ActivityNeural PathwaysOxygenOxygencortical gyri and sulcigrayordinatesparse representationtask-based fMRItask-based heterogeneous functional region

Identifiers

PMID26466353
PMCPMC4715563

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.