DOI
10.17077/etd.bvzcg1u7
Document Type
Dissertation
Date of Degree
Summer 2016
Degree Name
PhD (Doctor of Philosophy)
Degree In
Applied Mathematical and Computational Sciences
First Advisor
Rodica Curtu
Second Advisor
John Spencer
First Committee Member
John Spencer
Second Committee Member
Palle Jorgensen
Third Committee Member
Colleen Mitchell
Fourth Committee Member
Michelle Voss
Fifth Committee Member
Rodica Curtu
Abstract
In the field of cognitive neuroscience, there is a need for theory-based approaches to fMRI data analysis. The dynamic neural field model-based approach has been developing to meet this demand. This dissertation describes my contributions to this approach. The methods and tools were demonstrated through a case study experiment on response selection and inhibition. The experiment was analyzed via both the standard behavioral approach and the new model-based method, and the two methods were compared head to head. The methods were quantitatively comparable at the individual-level of the analysis. At the group level, the model-based method reveals distinct functional networks localized in the brain. This validates the dynamic neural field model-based approach in general as well as my recent contributions.
Pages
viii, 90 pages
Bibliography
Includes bibliographical references (pages 87-90).
Copyright
Copyright 2016 Joseph Paul Ambrose
Recommended Citation
Ambrose, Joseph Paul. "Dynamic field theory applied to fMRI signal analysis." PhD (Doctor of Philosophy) thesis, University of Iowa, 2016.
https://doi.org/10.17077/etd.bvzcg1u7
Comments
This material is based upon work supported by the National Science Foundation under Grant Number HSD-0527698 and Grant Number BCS-1029082.