Ozkurt, Tolga Esat
(2009)
Spatial Filtering of Magnetoencephalographic Data in Spherical Harmonics Domain.
Doctoral Dissertation, University of Pittsburgh.
(Unpublished)
Abstract
We introduce new spatial filtering methods in the spherical harmonics domain for constraining magnetoencephalographic (MEG) multichannel measurements to user-specified sphericalregions of interests (ROI) inside the head. The main idea of the spatial filtering is to emphasize those signals arising from an ROI, while suppressing the signals coming from outsidethe ROI. We exploit a well-known method called the signal space separation (SSS), whichcan decompose MEG data into a signal component generated by neurobiological sourcesand a noise component generated by external sources outside the head. The novel methodspresented in this work, expanded SSS (exSSS) and generalized expanded SSS (genexSSS)utilize a beamspace optimization criterion in order to linearly transform the inner signal SSScoefficients to represent the sources belonging to the ROI. The filters mainly depend on theradius and the center of the ROI. The simplicity of the derived formulations of our methodsstems from the natural appropriateness to spherical domain and orthogonality properties ofthe SSS basis functions that are intimately related to the vector spherical harmonics. Thus,unlike the traditional MEG spatial filtering techniques, exSSS and genexSSS do not needany numerical computation procedures on discretized headspace. The validation and performance of the algorithms are demonstrated by experiments utilizing both simulated and realMEG data.
Share
Citation/Export: |
|
Social Networking: |
|
Details
Item Type: |
University of Pittsburgh ETD
|
Status: |
Unpublished |
Creators/Authors: |
|
ETD Committee: |
|
Date: |
29 June 2009 |
Date Type: |
Completion |
Defense Date: |
29 January 2009 |
Approval Date: |
29 June 2009 |
Submission Date: |
16 February 2009 |
Access Restriction: |
No restriction; Release the ETD for access worldwide immediately. |
Institution: |
University of Pittsburgh |
Schools and Programs: |
Swanson School of Engineering > Electrical Engineering |
Degree: |
PhD - Doctor of Philosophy |
Thesis Type: |
Doctoral Dissertation |
Refereed: |
Yes |
Uncontrolled Keywords: |
Biomagnetism; EEG; Inverse Problem; MEG; Signal Processing; Spatial Filtering; Spherical Harmonics |
Other ID: |
http://etd.library.pitt.edu/ETD/available/etd-02162009-185922/, etd-02162009-185922 |
Date Deposited: |
10 Nov 2011 19:31 |
Last Modified: |
15 Nov 2016 13:36 |
URI: |
http://d-scholarship.pitt.edu/id/eprint/6362 |
Metrics
Monthly Views for the past 3 years
Plum Analytics
Actions (login required)
 |
View Item |