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Файл:Ординатура / Хирургия / Библиотека им академика М.И. Перельмана / Книга_5251_Библиотеки_им_академика_М_И_Перельмана
.pdf
UCLA
UCLA Electronic Theses and Dissertations
Title
Improvements to Simultaneous Electroencephalography – functional Magnetic Resonance
Imaging and Electroencephalographic Source Localization
Permalink
https://escholarship.org/uc/item/3gg3z2q6
Author
Rodriguez, Cameron
Publication Date
2016
Peer reviewed|Thesis/dissertation
eScholarship.org Powered by the California Digital Library
University of California
2016
UNIVERSITY OF CALIFORNIA
Los Angeles
IMPROVEMENTS TO
SIMULTANEOUS ELECTROENCEPHALOGRAPHY –
FUNCTIONAL MAGNETIC RESONANCE IMAGING AND
ELECTROENCEPHALOGRAPHIC SOURCE LOCALIZATION
A dissertation submitted in partial satisfaction of the
requirements for the degree Doctor of Philosophy
in Bioengineering
by
Cameron Rodriguez
2016
© Copyright by
Cameron Rodriguez
ii
ABSTRACT OF THESIS
Improvements to
Simultaneous Electroencephalography –
functional Magnetic Resonance Imaging and
Electroencephalographic Source Localization
By
Cameron Rodriguez
Doctor of Philosophy in Bioengineering
University of California, Los Angeles, 2016
Professor Mark S. Cohen, Chair
Both the method of simultaneous electroencephalography – functional magnetic
resonance imaging (EEG-fMRI) and the method of electroencephalographic source
localization are opening up new understandings in neuroscience, but both are also
technically very challenging. Simultaneous EEG-fMRI combines the strengths of each
modality: the temporal resolution of electroencephalography (EEG) with the spatial
resolution of functional magnetic resonance imaging (fMRI). EEG source localization
provides a non-invasive means of locating in the brain the sources of electrical signals
measured on the surface of the head. The potential for these methods is not limited to
research neuroscience; each has much to offer in fields like clinical neurology and
psychiatry. In clinical neurology, for example, both methods have been used in the
location of epileptic foci. Simultaneous EEG-fMRI is technically very challenging as
iii
each modality serves as a source of artifact and safety concerns for the other. Two
contaminants prominent in EEG acquired in the MRI environment are the gradient
artifact (GA) and the ballistocardiogram artifact (BCG). The GA occurs only during an
active MRI acquisition, while the BCG is always present, as its origins arise from the
cardiovascular system of the subject. The current method to remove the GA from the
EEG recording is called moving windowed average template subtraction (MWATS), the
windows of which are time-locked to the repetition time of the MR acquisition. The
problem with MWATS is that there are a number of options on how to implement it and
little consensus or consistency in the field on how it is done. Current methods of
removing the BCG artifact from the EEG recording all rely on establishing its timing
based upon a simultaneously acquired electrocardiogram (ECG) signal. One issue with
using the ECG signal is that the differential method for acquiring it implemented by the
manufactures of the MR compatible EEG systems has a high rate of failure.
Source localization is technically very challenging in part because it relies on
multiple measurements for its solution. Two of the measurements required for accurate
source location are the measurement of the EEG electrode positions with respect to the
underlying anatomy and the measurement of the underlying anatomy itself. At present,
these measurements are made separately: the underlying anatomy is measured with an
anatomical MRI scan, while the electrode positions are measured with either an
electromagnetic digitization device or a photogrammetry system, neither of which is MR
compatible. As such the two measurements must be registered to one another, typically
through the location of fiducial markers on the surface of the head in both of the
measurements. By aligning the markers, the two measurements can be brought into
iv
register. The issues with this technique are two fold. First, aligning the separate
measurements introduces a potential source of error. Second, both of the current methods
for measuring the electrode positions are very time consuming. This thesis focuses in
robust solutions to these issues.
Specifically what follows is: 1) an analysis of the consequences of all the
principal options for implementing the moving windowed average template subtraction;
2) a method to eliminate the need of the separately recorded ECG signal for establishing
the timing of the BCG artifact; and 3) a method for automatically locating and identifying
EEG electrodes in an anatomical MRI scan. The analysis of the MWATS method permits
more informed decisions to be made in its implementation. The method to eliminate the
need for the ECG signal is to both simplify the experimental setup and to make the EEG-
fMRI recording more robust. Automatically locating and identifying EEG electrodes in
an anatomical MRI scan eliminates both a measurement step and a registration step. The
elimination of the registration step eliminates a potential source of error. In addition, the
combination of the elimination of the measurement step and the automatic way in which
the algorithm progresses greatly reduces the time required for this process.
v
The thesis of Cameron Rodriguez is approved.
Daniel B. Ennis
Martin M. Monti
Daniel Jiong Jion Wang
Mark S. Cohen, Chair
University of California, Los Angeles
2016
vi
DEDICATION
There are several people to whom I wish to dedicate this work: my father and
mother, my brother, my wife, and my three sons. Their love, support, and the sacrifices
they made for me all have helped me get to where I am today. Beyond where am I, they
have also helped me become who I am today. My parents were the first in their families
to go to college; my father also being the first to receive a law degree. They have worked
tirelessly to both push and support my brother and me. They gave us both a foundation to
become good and caring people and the tools to become successful as well. As a child, I
am pretty sure they thought I would burn down the house with one of my “experiments,”
but they never tried to restrain my curiosity; in fact, they helped it flourish. My brother
has and will always be there for me. It was also his words that motivated me to go to
college. My wife has been with me through this entire process. Without her, this would
have not been possible. She is always in my corner. My sons, well, they are my greatest
inspiration. They bring enumerable joy to my life. I hope that I can do for them, what
my parents did for me.
vii
TAB LE O F C O N T E N T S
ACKNOWLEDGEMENTS ......................................................................................................................... X
BIOGRAPHICAL SKETCH ...................................................................................................................... XI
INTRODUCTION ......................................................................................................................................... 1
HOW MRI WORKS IN BRIEF ......................................................................................................................... 3
HOW EEG WORKS IN BRIEF ......................................................................................................................... 5
WHAT IS EEG SOURCE LOCALIZATION ........................................................................................................ 5
SAFETY CONCERNS WITH COMBING EEG AND MRI .................................................................................... 6
EEG SIGNAL ISSUES CAUSED BY MRI ......................................................................................................... 7
MRI SIGNAL ISSUES CAUSED BY EEG ......................................................................................................... 9
WHAT IS DONE TO FIX THE EEG RECORDING ............................................................................................ 11
WHAT IS DONE TO FIX THE MR RECORDING .............................................................................................. 13
LIMITATION OF THE CURRENT METHODS & HOW THEY CAN BE IMPROVED ............................................. 14
Analysis of Moving Windowed Average Template Subtraction ............................................................. 14
An ECG-free Method for Establishing Ballistocardiogram Timing ...................................................... 15
Automatic Identification of the EEG Electrodes in a 3D Volume ......................................................... 16
REFERENCES ............................................................................................................................................... 19
1: ANALYSIS OF MOVING WINDOWED AVERAGE TEMPLATE SUBTRACTION .................. 22
ABSTRACT .................................................................................................................................................. 22
KEYWORDS ................................................................................................................................................. 23
INTRODUCTION ........................................................................................................................................... 23
METHODS ................................................................................................................................................... 36
EEG Recording System .......................................................................................................................... 36
MRI System and Scan Settings ............................................................................................................... 37
Data Processing ..................................................................................................................................... 37
Creating the Synthetic EEG + BCG Signal ........................................................................................... 38
Subjects .................................................................................................................................................. 38
Synthetic EEG + BCG Signal Generation ............................................................................................. 39
Recording the Transmitted Synthetic EEG + BCG Signal .................................................................... 39
Analyzing the Synthetic EEG + BCG Signal ......................................................................................... 40
RESULTS FROM THE SYNTHETIC EEG ACQUISITION .................................................................................. 41
Overall Data Quality ............................................................................................................................. 41
Comparison of Casual Versus Centered Cleaners ................................................................................ 43
Comparison of Various Window Lengths and Weighting Types ........................................................... 44
DISCUSSION ................................................................................................................................................ 46
Should a Causal or Centered Filter be used? ....................................................................................... 47
Should the TR to be Cleaned be Included or Excluded from the Template? ......................................... 50
How Should the Weighting be Applied? ................................................................................................ 51
What type of Weighting Should be Applied and How Many TRs Should be Included? ......................... 53
CONCLUSION .............................................................................................................................................. 60
REFERENCES ............................................................................................................................................... 61
2: AN ECG-FREE METHOD FOR EXTABLISHING BALLISTOCARDIOGRAM TIMING ........ 64
ABSTRACT .................................................................................................................................................. 64
KEYWORDS ................................................................................................................................................. 65
INTRODUCTION ........................................................................................................................................... 65
Faraday’s Law of Induction .................................................................................................................. 67
Scalp Pulsation ...................................................................................................................................... 67
Head Rotations and Translations .......................................................................................................... 69
Hall Effect .............................................................................................................................................. 70
ECG Method .......................................................................................................................................... 71
viii
Existing Non-ECG Method (MAS/GFP) ................................................................................................ 74
New EEG Based Method (LR mean) ..................................................................................................... 77
LR mean Channel Selection ................................................................................................................... 78
LR mean Reference Scheme ................................................................................................................... 80
Peak Detection Algorithm ...................................................................................................................... 82
Step 1: LR mean Signal Conditioning / Filtering ............................................................................ 84
Step 2.1: Shannon Energy Envelope ............................................................................................... 85
Step 2.2: LR mean Peak Detection Round 1 – SEE ....................................................................... 85
Step 2.3: Error Checking Round 1 .................................................................................................. 86
Step 2.4: IBI calculation and Mean BCG Pattern Template ........................................................... 87
Step 3.1: LR mean Cross Correlated with BCG Pattern Template ................................................. 87
Step 3.2: LR mean Peak Detection Round 2 – Cross Correlation .................................................. 88
Step 3.3: Error Checking and Correction – Inter-beat Interval Evaluation ................................... 89
Step 3.4: Appling the Timing to the Wider Bandwidth .................................................................... 90
Testing the New EEG Based Algorithm ................................................................................................. 90
METHODS ................................................................................................................................................... 91
Subjects .................................................................................................................................................. 91
EEG Recording System .......................................................................................................................... 91
MRI System and Scan Settings ............................................................................................................... 92
Data Processing ..................................................................................................................................... 92
GA Cleaning .......................................................................................................................................... 92
ECG Peak Timing Extraction ................................................................................................................ 92
BCG Peak Timing Extraction ................................................................................................................ 93
Determining Corrupted Recording Sections ......................................................................................... 93
ECG & BCG Missed and False Detections ........................................................................................... 93
BCG-ECG Peak Lag Comparison ......................................................................................................... 94
RESULTS AND DISCUSSION ......................................................................................................................... 94
Overall Data Quality ............................................................................................................................. 94
ECG Results ........................................................................................................................................... 95
BCG Results ........................................................................................................................................... 98
ECG specificity, sensitivity and accuracy compared to the BCG ....................................................... 100
ECG to BCG Lag ................................................................................................................................. 101
ECG and BCG Windowed Averages .................................................................................................... 104
Case Versus Control Peak Detection Performance ............................................................................. 107
CONCLUSION ............................................................................................................................................ 107
Future Improvements ........................................................................................................................... 108
Future Study ......................................................................................................................................... 108
Final Thoughts ..................................................................................................................................... 111
REFERENCES ............................................................................................................................................. 111
3: AUTOMATIC INDENTIFICATION OF EEG ELECTRODES IN A 3D VOLUME .................. 115
ABSTRACT ................................................................................................................................................ 115
KEYWORDS ............................................................................................................................................... 116
INTRODUCTION ......................................................................................................................................... 116
Current Methods for the Measurement of Electrode Positions ........................................................... 118
Drawbacks of the Current Methods for the Measurement of Electrode Positions .............................. 120
New Method for the Automatic Location and Identification of EEG Electrodes in an MRI Scan ...... 121
Step 0: The Electrode Template .................................................................................................... 121
Step 0.1: Template Creation .................................................................................................. 122
Step 1: Electrode Detection ........................................................................................................... 122
Step 1.1: Preprocessing, Applying the Knowledge of Location ............................................. 123
Step 1.1.1: Background Signal Removal ......................................................................... 124
Step 1.1.1.1: Applying an Intensity Threshold ........................................................ 125
Step 1.1.1.2: Applying a Connectivity Threshold ................................................... 126
Step 1.1.1.3: Applying a Bounding Box Threshold ................................................. 126
Step 1.1.2: Shell Extraction ............................................................................................ 126
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