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SIGNAL PROCESSING METHODS FOR INTERACTION ANALYSIS OF
FUNCTIONAL BRAIN IMAGING DATA
by
Hua Brian Hui
A Dissertation Presented to the
FACULTY OF THE USC GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
DOCTOR OF PHILOSOPHY
(ELECTRICAL ENGINEERING)
May 2010
Copyright 2010 Hua Brian Hui
Object Description
| Title | Signal processing methods for interaction analysis of functional brain imaging data |
| Author | Hui, Hua Brian |
| Author email | hhui@usc.edu; brianhuahui@gmail.com |
| Degree | Doctor of Philosophy |
| Document type | Dissertation |
| Degree program | Electrical Engineering |
| School | Viterbi School of Engineering |
| Date defended/completed | 2009-12-21 |
| Date submitted | 2010 |
| Restricted until | Unrestricted |
| Date published | 2010-03-28 |
| Advisor (committee chair) | Leahy, Richard |
| Advisor (committee member) |
Nayak, Krishna Singh, Manbir |
| Abstract | Modeling functional brain interaction networks using non-invasive EEG and MEG data is more challenging than using intracranial recordings data. This is because most interaction measures are not robust to cross-talk (interference) between cortical regions, which may arise due to the limited spatial resolution of EEG/MEG inverse procedures. We describe a modified beamforming approach to accurately measure cortical interactions from EEG/MEG data, designed to suppress cross-talk between cortical regions. We estimate interaction measures from the output of the modified beamformer and test for statistical significance using permutation tests. Since the underlying neuronal sources and their interactions are unknown in real MEG data, we demonstrate the performance of the proposed beamforming method in a novel simulation scheme, where intracranial recordings from a macaque monkey are used as neural sources to simulate realistic MEG signals. The advantage of this approach is that local field potentials are more realistic representations of true neuronal sources than simulation models and therefore are more suitable to evaluate the performance of our nulling beamforming method.; Intracranial recordings have minimal cross-talk and therefore interactions can be measured more reliably. However, performing group level studies is a challenging task because of the sparsity and variable coverage of electrodes on each subjects' brain. We describe a set of group analysis procedures for intracranial EEG recordings, which include registration of MRI volumes and cortical surfaces, and parcellation of anatomical regions of interest. We use a parametric probability model to test for equality of phase synchrony, and use Fisher's combined p-value method to pool test results from electrodes on individual subjects into the parcellated regions of interest. We apply our group analysis procedure to intracranial EEG data recorded in a working memory experiment and find an interaction network that is modulated by memory load. |
| Keyword | beamformer; cross-talk; functional interaction; intracranial EEG; MEG; phase synchrony |
| Language | English |
| Part of collection | University of Southern California dissertations and theses |
| Publisher (of the original version) | University of Southern California |
| Place of publication (of the original version) | Los Angeles, California |
| Publisher (of the digital version) | University of Southern California. Libraries |
| Provenance | Electronically uploaded by the author |
| Type | texts |
| Legacy record ID | usctheses-m2879 |
| Rights | Hui, Hua Brian |
| Repository name | Libraries, University of Southern California |
| Repository address | Los Angeles, California |
| Repository email | http://www.usc.edu/isd/libraries/services/ask_a_librarian/email/ |
| Filename | etd-Hui-3497 |
| Archival file | uscthesesreloadpub_Volume44/etd-Hui-3497.pdf |
Description
| Title | Page 1 |
| Full text | SIGNAL PROCESSING METHODS FOR INTERACTION ANALYSIS OF FUNCTIONAL BRAIN IMAGING DATA by Hua Brian Hui A Dissertation Presented to the FACULTY OF THE USC GRADUATE SCHOOL UNIVERSITY OF SOUTHERN CALIFORNIA In Partial Fulfillment of the Requirements for the Degree DOCTOR OF PHILOSOPHY (ELECTRICAL ENGINEERING) May 2010 Copyright 2010 Hua Brian Hui |
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