Details

Autor(en) / Beteiligte

• Li, Fali
• Chen, Bei
• Li, He
• Zhang, Tao
• Wang, Fei
• Jiang, Yi
• Li, Peiyang
• Ma, Teng
• Zhang, Rui
• Tian, Yin
• Liu, Tiejun
• Guo, Daqing
• Yao, Dezhong
• Xu, Peng

Titel

The Time-Varying Networks in P300: A Task-Evoked EEG Study

Ist Teil von

• IEEE transactions on neural systems and rehabilitation engineering, 2016-07, Vol.24 (7), p.725-733

Ort / Verlag

United States: IEEE

Erscheinungsjahr

2016

Quelle

MEDLINE

Beschreibungen/Notizen

• P300 is an important event-related potential that can be elicited by external visual, auditory, and somatosensory stimuli. Various cognition-related brain functions (i.e., attention, intelligence, and working memory) and multiple brain regions (i.e., prefrontal, frontal, and parietal) are reported to be involved in the elicitation of P300. However, these studies do not investigate the instant interactions across the neural cortices from the hierarchy of milliseconds. Importantly, time-varying network analysis among these brain regions can uncover the detailed and dynamic information processing in the corresponding cognition process. In the current study, we utilize the adaptive directed transfer function to construct the time-varying networks of P300 based on scalp electroencephalographs, investigating the time-varying information processing in P300 that can depict the deeper neural mechanism of P300 from the network. Our analysis found that different stages of P300 evoked different brain networks, i.e., the center area performs as the central source during the decision process stage, while the source region is transferred to the right prefrontal cortex (rPFC) in the neuronal response stage. Moreover, during the neuronal response stage, the directed information that flows from the rPFC to the parietal cortex are remarkably important. These findings indicate that the two brain hemispheres exhibit asymmetrical functions in processing related information for different P300 stages, and this work may provide new evidence for our better understanding of the neural mechanism of P300 generation.