Implementing dynamic time warping algorithm for estimation training performance 
in fMRI neurofeedback

Izyurov, I; Krylova, M; Alizadeh, S; Jamalabadi, H; Li, M; Walter, M

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Implementing dynamic time warping algorithm for estimation training performance in fMRI neurofeedback

MPS-Authors

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Li, M
Max Planck Institute for Biological Cybernetics, Max Planck Society;
Department High-Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Walter, M
Max Planck Institute for Biological Cybernetics, Max Planck Society;
Department High-Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Max Planck Society;

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https://nenaconference.files.wordpress.com/2019/10/abstractbook_nena2019.pdf
(Abstract)

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Citation

Izyurov, I., Krylova, M., Alizadeh, S., Jamalabadi, H., Li, M., & Walter, M. (2019). Implementing dynamic time warping algorithm for estimation training performance in fMRI neurofeedback. Poster presented at 20th Conference of Junior Neuroscientists (NeNa 2019), Schramberg, Germany.

Cite as: https://hdl.handle.net/21.11116/0000-0004-F77D-A

Abstract

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