Print Email Facebook Twitter Frequency Domain Joint Estimation of HRF and Stimulus from fUS Data Title Frequency Domain Joint Estimation of HRF and Stimulus from fUS Data Author Tao, Yitong (TU Delft Electrical Engineering, Mathematics and Computer Science) Contributor Hunyadi, Borbala (mentor) Hendriks, R.C. (graduation committee) Kruizinga, P. (graduation committee) Degree granting institution Delft University of Technology Programme Electrical Engineering | Circuits and Systems Date 2022-09-22 Abstract To better understand how brain signals are processed and even how the human mind works, analyzing the hemodynamic signal model is one of the most essential steps. In the CUBE group of Erasmus MC, functional ultrasound (fUS) data of a mouse’s brain is recorded. By using this fUS dataset, this thesis will solve the problem regarding the joint estimation of hemodynamic response function (HRF) and the underlying stimulus. Usually, hemodynamic responses are investigated in the time domain, while this thesis provides another perspectivefrom frequency domain signal processing. We consider the hemodynamic response as a convolutive signal mixture, then try to transform it into an instantaneous mixing model by converting the context into the frequency domain. By applying independent vector analysis (IVA), this estimation problem can be solved without facing permutation ambiguity which is a well-unknown problem regarding independent component analysis (ICA). Additional steps before and after IVA are also discussed so that a whole estimation road map is formed.Both simulation and experimental analysis are provided to validate this estimation algorithm. Results show that by using this method, both stimulus and HRF estimation can be achieved satisfyingly in a suitable experimental setting. This thesis provides insights and future potentials for IVA to be further investigated in neural signal processing problems. Subject functional ultrasoundhemodynamic responseIVA To reference this document use: http://resolver.tudelft.nl/uuid:fa380802-6834-4530-ba69-4f0de2f528ca Part of collection Student theses Document type master thesis Rights © 2022 Yitong Tao Files PDF _Final_Thesis_Yitong_Tao.pdf 3.52 MB Close viewer /islandora/object/uuid:fa380802-6834-4530-ba69-4f0de2f528ca/datastream/OBJ/view