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Abstract:
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Brain activity is multi-faceted. Various imaging modalities aim to probe specific aspects of brain activity. In particular, electroencephalograms (EEGs) capture electrical activity while functional near-infrared spectroscopy (fNIRS) captures cortical hemodynamic activity. Emerging technology now allows for simultaneous collecting of both signals. However, the interaction between EEG and fNIRS at a macroscopic scale is still unclear, and there is evidence that not all electrical recordings can be directly correlated to neurological activity. In this talk, we will develop statistical models for joint EEG+fNIRS data, which we hope unveil a more comprehensive characterization of the inherent complex dynamics in the brain. Our proposed model for multimodal spatial-temporal brain dynamics has the potential to offer a description of the brain self-regulating mechanisms. We will introduce some statistical spectral dependence measurements, including multimodal spectral causality and cross-frequency coupling metrics, that have the potential to contribute in distinguish between EEG components related to scalp (endothelial) vasomotion processes from neurological brain dynamics.
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