Connectomics signature for characterizaton of mild cognitive impairment and schizophrenia

Dajiang Zhu, Dinggang Shen, Xi Jiang, Tianming Liu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Citations (Scopus)

Abstract

Human connectomes constructed via neuroimaging data offer a comprehensive description of the macro-scale structural connectivity within the brain. Thus quantitative assessment of connectome-scale structural and functional connectivities will not only fundamentally advance our understanding of normal brain organization and function, but also have significant importance to systematically and comprehensively characterize many devastating brain conditions. In recognition of the importance of connectome and connectomics, in this paper, we develop and evaluate a novel computational framework to construct structural connectomes from diffusion tensor imaging (DTI) data and assess connectome-scale functional connectivity alterations in mild cognitive impairment (MCI) and schizophrenia (SZ) from concurrent resting state fMRI (R-fMRI) data, in comparison with their healthy controls. By applying effective feature selection approaches, we discovered informative and robust functional connectomics signatures that can distinctively characterize and successfully differentiate the two brain conditions of MCI and SZ from their healthy controls (classification accuracies are 96% and 100%, respectively). Our results suggest that connectomics signatures could be a general, powerful methodology for characterization and classification of many brain conditions in the future.

Original languageEnglish
Title of host publication2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages325-328
Number of pages4
ISBN (Print)9781467319591
Publication statusPublished - 2014 Jul 29
Externally publishedYes
Event2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014 - Beijing, China
Duration: 2014 Apr 292014 May 2

Other

Other2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014
CountryChina
CityBeijing
Period14/4/2914/5/2

Fingerprint

Connectome
Brain
Schizophrenia
Diffusion tensor imaging
Neuroimaging
Macros
Feature extraction
Diffusion Tensor Imaging
Cognitive Dysfunction
Magnetic Resonance Imaging

Keywords

  • Connectome
  • Network-based signature

ASJC Scopus subject areas

  • Biomedical Engineering
  • Radiology Nuclear Medicine and imaging

Cite this

Zhu, D., Shen, D., Jiang, X., & Liu, T. (2014). Connectomics signature for characterizaton of mild cognitive impairment and schizophrenia. In 2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014 (pp. 325-328). [6867874] Institute of Electrical and Electronics Engineers Inc..

Connectomics signature for characterizaton of mild cognitive impairment and schizophrenia. / Zhu, Dajiang; Shen, Dinggang; Jiang, Xi; Liu, Tianming.

2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014. Institute of Electrical and Electronics Engineers Inc., 2014. p. 325-328 6867874.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Zhu, D, Shen, D, Jiang, X & Liu, T 2014, Connectomics signature for characterizaton of mild cognitive impairment and schizophrenia. in 2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014., 6867874, Institute of Electrical and Electronics Engineers Inc., pp. 325-328, 2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014, Beijing, China, 14/4/29.
Zhu D, Shen D, Jiang X, Liu T. Connectomics signature for characterizaton of mild cognitive impairment and schizophrenia. In 2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014. Institute of Electrical and Electronics Engineers Inc. 2014. p. 325-328. 6867874
Zhu, Dajiang ; Shen, Dinggang ; Jiang, Xi ; Liu, Tianming. / Connectomics signature for characterizaton of mild cognitive impairment and schizophrenia. 2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014. Institute of Electrical and Electronics Engineers Inc., 2014. pp. 325-328
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