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Applicable nonlinear time-series and graph methods to neurodynamics and functional imaging
Ivan J. Roijals-Miras
Lindstedtsvägen 24, Stockholm
In this talk, I wish to put into perspective why and how we apply complexity metrics to brain imaging and interpret its findings, with current and own research. To this end, two parallel lines will be followed: First we will scrutinize few non-linear time-series measures applied to fMRI and its ability to find patterns of functional activity, despite its noisy and short nature, as compared with neurodynamics. Then we will turn to network connectivity measures, precisely community structure statistics, in order to characterize resting-state brain activity. We would then end in discussion about on new the application of new methods in network dynamics and how these can help us to better model the complexity of neural oscillations in different settings.