Brain state and dynamic transition patterns of motor imagery revealed by the bayes hidden markov model-Reference-Cited by-同舟云学术

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Brain state and dynamic transition patterns of motor imagery revealed by the bayes hidden markov model

Published:2024-03-27 Issue: Volume: Page:
ISSN:1871-4080
Container-title:Cognitive Neurodynamics
language:en
Short-container-title:Cogn Neurodyn

Author:

Liu Yunhong,Yu Shiqi,Li Jia,Ma Jiwang,Wang Fei,Sun Shan,Yao Dezhong,Xu Peng,Zhang Tao

Funder

National Natural Science Foundation of China

National natural science foundation of china

Medical Science and Technology Research Fund of Guangdong Province

Publisher

Springer Science and Business Media LLC

Link

https://link.springer.com/content/pdf/10.1007/s11571-024-10099-9.pdf

Reference80 articles.

1. Ahrends, C., Vidaurre, D. (2023) Predicting individual traits from models of brain dynamics accurately and reliably using the Fisher kernel. bioRxiv:530638.

2. Beauchamp MS (2015) The social mysteries of the superior temporal sulcus. Trends Cogn Sci 19:489–490

3. Bencivenga F, Sulpizio V, Tullo MG, Galati G (2021) Assessing the effective connectivity of premotor areas during real vs imagined grasping: a DCM-PEB approach. Neuroimage 230:117806

4. Bishop CM, Nasrabadi NM (2006) Pattern recognition and machine learning. Springer

5. Burianová H, Marstaller L, Sowman P, Tesan G, Rich AN, Williams M, Savage G, Johnson BW (2013) Multimodal functional imaging of motor imagery using a novel paradigm. Neuroimage 71:50–58

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