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Supervised multimodal fusion and its application in searching joint neuromarkers of working memory deficits in schizophrenia.

Publication ,  Conference
Shile Qi, ; Calhoun, VD; van Erp, TGM; Damaraju, E; Bustillo, J; Yuhui Du, ; Turner, JA; Mathalon, DH; Ford, JM; Voyvodic, J; Mueller, BA ...
Published in: Annu Int Conf IEEE Eng Med Biol Soc
August 2016

Multimodal fusion is an effective approach to better understand brain disease. To date, most current fusion approaches are unsupervised; there is need for a multivariate method that can adopt prior information to guide multimodal fusion. Here we proposed a novel supervised fusion model, called "MCCAR+jICA", which enables both identification of multimodal co-alterations and linking the covarying brain regions with a specific reference signal, e.g., cognitive scores. The proposed method has been validated on both simulated and real human brain data. Features from 3 modalities (fMRI, sMRI, dMRI) obtained from 147 schizophrenia patients and 147 age-matched healthy controls were included as fusion input, who participated in the Function Biomedical Informatics Research Network (FBIRN) Phase III study. Our aim was to investigate the group co-alterations seen in three types of MRI data that are also correlated with working memory performance. One joint IC was found both significantly group-discriminating (p=7.4E-06, 0.001, 7.0E-09) and highly correlated with working memory scores(r=0.296, 0.241, 0.301) and PANSS negative scores (r=-0.229, -0.276, -0.240) for fMRI, dMRI and sMRI, respectively. Given the simulation and FBIRN results, MCCAR+jICA is shown to be an effective multivariate approach to extract accurate and stable multimodal components associated with a particular measure of interest, and promises a wide application in identifying potential neuromarkers for mental disorders.

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Published In

Annu Int Conf IEEE Eng Med Biol Soc

DOI

EISSN

2694-0604

Publication Date

August 2016

Volume

2016

Start / End Page

4021 / 4026

Location

United States

Related Subject Headings

  • Schizophrenia
  • Multimodal Imaging
  • Memory, Short-Term
  • Memory Disorders
  • Magnetic Resonance Imaging
  • Humans
  • Brain Mapping
 

Citation

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Shile Qi, ., Calhoun, V. D., van Erp, T. G. M., Damaraju, E., Bustillo, J., Yuhui Du, ., … Jing Sui, . (2016). Supervised multimodal fusion and its application in searching joint neuromarkers of working memory deficits in schizophrenia. In Annu Int Conf IEEE Eng Med Biol Soc (Vol. 2016, pp. 4021–4026). United States. https://doi.org/10.1109/EMBC.2016.7591609
Shile Qi, F., Vince D. Calhoun, Theo G. M. van Erp, Eswar Damaraju, Juan Bustillo, Juan Yuhui Du, Jessica A. Turner, et al. “Supervised multimodal fusion and its application in searching joint neuromarkers of working memory deficits in schizophrenia.” In Annu Int Conf IEEE Eng Med Biol Soc, 2016:4021–26, 2016. https://doi.org/10.1109/EMBC.2016.7591609.
Shile Qi, Calhoun VD, van Erp TGM, Damaraju E, Bustillo J, Yuhui Du, et al. Supervised multimodal fusion and its application in searching joint neuromarkers of working memory deficits in schizophrenia. In: Annu Int Conf IEEE Eng Med Biol Soc. 2016. p. 4021–6.
Shile Qi, F., et al. “Supervised multimodal fusion and its application in searching joint neuromarkers of working memory deficits in schizophrenia.Annu Int Conf IEEE Eng Med Biol Soc, vol. 2016, 2016, pp. 4021–26. Pubmed, doi:10.1109/EMBC.2016.7591609.
Shile Qi, Calhoun VD, van Erp TGM, Damaraju E, Bustillo J, Yuhui Du, Turner JA, Mathalon DH, Ford JM, Voyvodic J, Mueller BA, Belger A, McEwen S, Potkin SG, Preda A, Birn F, Tianzi Jiang, Jing Sui. Supervised multimodal fusion and its application in searching joint neuromarkers of working memory deficits in schizophrenia. Annu Int Conf IEEE Eng Med Biol Soc. 2016. p. 4021–4026.

Published In

Annu Int Conf IEEE Eng Med Biol Soc

DOI

EISSN

2694-0604

Publication Date

August 2016

Volume

2016

Start / End Page

4021 / 4026

Location

United States

Related Subject Headings

  • Schizophrenia
  • Multimodal Imaging
  • Memory, Short-Term
  • Memory Disorders
  • Magnetic Resonance Imaging
  • Humans
  • Brain Mapping