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- W2287184225 abstract "Ongoing spontaneous brain activity patterns raise ever-growing interest in the neuroscience community. Complex spatiotemporal patterns that emerge from a structural core and interactions of functional dynamics have been found to be far from arbitrary in empirical studies. They are thought to compose the network structure underlying human cognitive architecture. In this thesis, we use a biophysically realistic computer model to study key factors in producing complex spatiotemporal activation patterns. For the first time, we present a model of decreased physiological signal complexity in aging and demonstrate that delays shape functional connectivity in an oscillatory spiking-neuron network model for MEG resting-state data. Our results show that the inclusion of realistic delays maximizes model performance. Furthermore, we propose embracing a datadriven, comparative stance on decomposing the system into subnetworks." @default.
- W2287184225 created "2016-06-24" @default.
- W2287184225 creator A5091847794 @default.
- W2287184225 date "2015-03-11" @default.
- W2287184225 modified "2023-09-28" @default.
- W2287184225 title "Cortical resting state circuits: connectivity and oscillations" @default.
- W2287184225 hasPublicationYear "2015" @default.
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