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Exploring Dynamic Brain Functional Networks Using Continuous “State-Related” Functional MRI

We applied a “temporal decomposition” method, which decomposed a single brain functional network into several “modes”; each of them dominated a short temporal period, on a continuous, “state-” related, “finger-force feedback” functional magnetic resonance imaging experiment. With the hypothesis that...

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Detalles Bibliográficos
Autores principales: Li, Xun, Zang, Yu-Feng, Zhang, Han
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4564637/
https://www.ncbi.nlm.nih.gov/pubmed/26413546
http://dx.doi.org/10.1155/2015/824710
Descripción
Sumario:We applied a “temporal decomposition” method, which decomposed a single brain functional network into several “modes”; each of them dominated a short temporal period, on a continuous, “state-” related, “finger-force feedback” functional magnetic resonance imaging experiment. With the hypothesis that attention and internal/external information processing interaction could be manipulated by different (real and sham) feedback conditions, we investigated functional network dynamics of the “default mode,” “executive control,” and sensorimotor networks. They were decomposed into several modes. During real feedback, the occurrence of “default mode-executive control competition-related” mode was higher than that during sham feedback (P = 0.0003); the “default mode-visual facilitation-related” mode more frequently appeared during sham than real feedback (P = 0.0004). However, the dynamics of the sensorimotor network did not change significantly between two conditions (P > 0.05). Our results indicated that the visual-guided motor feedback involves higher cognitive functional networks rather than primary motor network. The dynamics monitoring of inner and outside environment and multisensory integration could be the mechanisms. This study is an extension of our previous region-specific and static-styled study of our brain functional architecture.