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Dr
Computational Brain Dynamics Team, RIKEN Center for Advanced Intelligence Project, Japan; Department of Computational Brain Imaging, ATR Neural Information Analysis Laboratories, Japan
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Schedule
Saturday, April 29, 2023
2:00 AM Asia/Tokyo
Recording provided by the organiser.
Domain
NeuroscienceHost
Sydney Systems Neuroscience and Complexity SNAC
Duration
60 minutes
Repetitive spatiotemporal patterns in resting-state brain activities have been widely observed in various species and regions, such as rat and cat visual cortices. Since they resemble the preceding brain activities during tasks, they are assumed to reflect past experiences embedded in neuronal circuits. Moreover, spatiotemporal patterns involving whole-brain activities may also reflect a process that integrates information distributed over the entire brain, such as motor and visual information. Therefore, revealing such patterns may elucidate how the information is integrated to generate consciousness. In this talk, I will introduce our proposed method to estimate repetitive spatiotemporal patterns from resting-state brain activity data and show the spatiotemporal patterns estimated from human resting-state magnetoencephalography (MEG) and electroencephalography (EEG) data. Our analyses suggest that the patterns involved whole-brain propagating activities that reflected a process to integrate the information distributed over frequencies and networks. I will also introduce our current attempt to reveal signal flows and their roles in the spatiotemporal patterns using a big dataset. - Takeda et al., Estimating repetitive spatiotemporal patterns from resting-state brain activity data. NeuroImage (2016); 133:251-65. - Takeda et al., Whole-brain propagating patterns in human resting-state brain activities. NeuroImage (2021); 245:118711.
Yusuke Takeda
Dr
Computational Brain Dynamics Team, RIKEN Center for Advanced Intelligence Project, Japan; Department of Computational Brain Imaging, ATR Neural Information Analysis Laboratories, Japan
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