A multivariate sparse deconvolution algorithm for multi echo fMRI.

This thesis presents a novel algorithm for the deconvolution of multi echo fMRI data with no prior information on the timings of the neuronal events. Based on previous work on the field, a new signal model is proposed in order to take the processing from a voxelwise analysis to an entire brain one...

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Hlavní autoři: Uruñuela-Tremiño, E. (Eneko), Ortiz-de-Solorzano, C. (Carlos)
Médium: info:eu-repo/semantics/masterThesis
Jazyk:eng
Vydáno: Servicio de Publicaciones. Universidad de Navarra 2019
Témata:
On-line přístup:https://hdl.handle.net/10171/58374