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

Curtu, Rodica

Second Advisor

Spencer, John

First Committee Member

Spencer, John

Second Committee Member

Jorgensen, Palle

Third Committee Member

Mitchell, Colleen

Fourth Committee Member

Voss, Michelle

Fifth Committee Member

Curtu, Rodica

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).

Comments

This material is based upon work supported by the National Science Foundation under Grant Number HSD-0527698 and Grant Number BCS-1029082.

Copyright

Copyright 2016 Joseph Paul Ambrose

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