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A novel and effective fMRI decoding approach based on sliced inverse regression and its application to pain prediction.

Y. Tu, Z. Fu, A. Tan, G. Huang, L. Hu, Y. Hung, and Z. Zhang. Neurocomputing, (2018)

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Kilian Türk University of Stuttgart

Gregory-Jamie Tüzün University of Stuttgart

Gregory-Jamie Tüzün

Fabrizio Turco University of Stuttgart

Dr. phil. Rostislav Tumanov University of Stuttgart

Other publications of authors with the same name

A novel and effective fMRI decoding approach based on sliced inverse regression and its application to pain prediction.Y. Tu, Z. Fu, A. Tan, G. Huang, L. Hu, Y. Hung, and Z. Zhang. Neurocomputing, (2018)Single-trial analysis of electroencephalography and functional magnetic resonance imaging for brain decoding.Y. Tu. University of Hong Kong, Pokfulam, Hong Kong, (2016)base-search.net (ftunivhongkonghu:oai:hub.hku.hk:10722/233927).The role of negative emotions in sex differences in pain sensitivity.H. Zhang, Y. Bi, X. Hou, X. Lu, Y. Tu, and L. Hu. NeuroImage, (2021)Characterizing dynamic amplitude of low-frequency fluctuation and its relationship with dynamic functional connectivity: An application to schizophrenia.Z. Fu, Y. Tu, X. Di, Y. Du, G. Pearlson, J. Turner, B. Biswal, Z. Zhang, and V. Calhoun. NeuroImage, 180 (Part): 619-631 (2018)A neural mechanism of direct and observational conditioning for placebo and nocebo responses.Y. Tu, J. Park, S. Ahlfors, S. Khan, N. Egorova, C. Lang, J. Cao, and J. Kong. NeuroImage, (2019)Joint source separation of simultaneous EEG-fMRI recording in two experimental conditions using common spatial patterns.A. Tan, Z. Fu, Y. Tu, Y. Hung, and Z. Zhang. EMBC, page 2633-2636. IEEE, (2015)Normalization of Pain-Evoked Neural Responses Using Spontaneous EEG Improves the Performance of EEG-Based Cross-Individual Pain Prediction.Y. Bai, G. Huang, Y. Tu, A. Tan, Y. Hung, and Z. Zhang. Front. Comput. Neurosci., (2016)Decoding Subjective Intensity of Nociceptive Pain from Pre-stimulus and Post-stimulus Brain Activities.Y. Tu, A. Tan, Y. Bai, Y. Hung, and Z. Zhang. Front. Comput. Neurosci., (2016)L0-regularized time-varying sparse inverse covariance estimation for tracking dynamic fMRI brain networks.Z. Fu, S. Han, A. Tan, Y. Tu, and Z. Zhang. EMBC, page 1496-1499. IEEE, (2015)Identifying inter-individual differences in pain threshold using brain connectome: a test-retest reproducible study.Y. Tu, B. Zhang, J. Cao, G. Wilson, Z. Zhang, and J. Kong. NeuroImage, (2019)

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Disambiguation of "Tu, Yiheng"

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A novel and effective fMRI decoding approach based on sliced inverse regression and its application to pain prediction.

Please choose a person to relate this publication to

Kilian Türk University of Stuttgart

Gregory-Jamie Tüzün University of Stuttgart

Gregory-Jamie Tüzün

Fabrizio Turco University of Stuttgart

Dr. phil. Rostislav Tumanov University of Stuttgart

Other publications of authors with the same name

Disambiguation

PUMA

Disambiguation of "Tu, Yiheng"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML A novel and effective fMRI decoding approach based on sliced inverse regression and its application to pain prediction.

Please choose a person to relate this publication to

Kilian Türk University of Stuttgart

Gregory-Jamie Tüzün University of Stuttgart

Gregory-Jamie Tüzün

Fabrizio Turco University of Stuttgart

Dr. phil. Rostislav Tumanov University of Stuttgart

Other publications of authors with the same name

Disambiguation

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URL
DOI
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Chicago
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A novel and effective fMRI decoding approach based on sliced inverse regression and its application to pain prediction.