Graduation Semester and Year

2018

Language

English

Document Type

Dissertation

Degree Name

Doctor of Philosophy in Biomedical Engineering

Department

Bioengineering

First Advisor

Hanli Liu

Second Advisor

Georgios Alexandrakis

Third Advisor

Khosrow Behbehani

Abstract

Functional connectivity and neurovascular coupling are important phenomena that occur in the brain. Functional connectivity is the study of functional brain networks and their characteristics. While neurovascular coupling is the relationship or link between neuronal activity and corresponding cerebral blood flow in the brain. Up until now, both functional connectivity and neurovascular coupling have not been studied in different vigilance states of the brain from wakeful rest state to sleep state, using simultaneous EEG-fNIRS measurements. Also, the neurovascular coupling in different states of breath-holding has not been studied using simultaneous EEG-fNIRS measurements Therefore, my doctoral research utilized a whole-head simultaneous EEG-fNIRS instrumentation set up to investigate both functional connectivity and neurovascular coupling in different vigilance states of the brain from wakeful rest to sleep state, and the neurovascular coupling in different states of voluntary breath-holding. A total of 18 subjects (16 males and 2 females) with a mean age of 23 years were recruited for this research study. This research study was subdivided into three main study aims. For Aim 1, the functional connectivity of the brain was investigated in four different vigilance states which were eyes-open (EO), eyes-closed (EC), sleep-stage 1 (SS1), and sleep-stage 2 (SS2). In addition, a mathematical tool known as graph theory analysis (GTA) was applied to EEG data collected in each vigilance state to quantitatively describe the changes in both global and local measures of functional connectivity across the four vigilance states. Specifically, the global measures analyzed were mean global clustering coefficient and mean global efficiency; while the local measures analyzed were the nodal clustering coefficient and nodal efficiency. Also, the analysis was performed in four separate EEG frequency bands: delta (1-4 Hz), theta (4-8 Hz), alpha (8 – 12 Hz), and beta (12 – 30 Hz), to have a detailed description of the changes in the functional connectivity. The results of this study showed that brain networks are significantly altered (p < 0.05) in functional connectivity during the transition from wakeful rest to sleep. Specifically, the anterior subsystem of the “default-mode” brain network showed significant changes (p < 0.05) in clustering coefficient from wakeful rest to sleep state, and this was majorly in the alpha and beta bands. Also, the posterior subsystem of the “default mode” brain network showed significant changes (p < 0.05) in global efficiency from wakeful rest to sleep states, and this was majorly in alpha and beta bands. For Aim 2, the neurovascular coupling in the brain was examined in three different vigilance states of eyes-open, eyes-closed, and sleep-stage 1, in four different brain sites. A time-frequency method known as wavelet coherence analysis was utilized for this study. The analysis was performed in three different EEG frequency bands which were theta (4 -8 Hz), alpha (8 – 12 Hz), and beta (12 – 30 Hz). In addition, three specific components of neurovascular coupling, which were endogenic (0.01 – 0.02 Hz), neurogenic (0.02 – 0.04 Hz), and myogenic (0.04 – 0.15 Hz) components, were quantified for each vigilance state in each frequency band. This analysis showed differences in neurovascular coupling (p < 0.05) across vigilance states; significant difference (p < 0.05, corrected) for “endogenic” component in alpha band between eyes-open and eyes-closed state were reported in both left frontal and right occipital brain sites; also, significant difference for “endogenic” component in alpha band (p < 0.05, corrected) between eyes-open and sleep-stage 1 were reported in left occipital site; significant difference for “endogenic” component in alpha band between eyes-closed and sleep-stage 1 were reported in left occipital site. In addition, significant difference for “myogenic” component in theta band (p < 0.05, corrected) between eyes-open and sleep-stage 1 was reported in left frontal brain site. For Aim 3, the neurovascular coupling of the brain was investigated during three different states of voluntary breath-holding, which were rest/normal breathing state, short breath-hold state, and long breath-hold state. Also, the wavelet coherence method was utilized to show the neurovascular coupling for each state. In addition, this analysis was also done in three frequency bands of EEG which were theta, alpha, and beta Furthermore, the endogenic, neurogenic, and myogenic components of neurovascular coupling were quantified for each breath-hold state in four brain sites which were the left frontal, right frontal, left occipital, and right occipital sites. The results showed differences in neurovascular coupling (p < 0.05) across different states of voluntary breath-holding. Specifically, a significant difference was reported for the endogenic component in both alpha and beta bands (p < 0.05, corrected) between rest and long breath-holding in both left frontal and right occipital brain sites. Also, a significant difference was also reported for endogenic component in theta band between short and long breath-holding in right occipital brain site. Also, a significant difference (p<0.05, corrected) was reported for neurogenic component in theta band between rest and long breath-holding in right occipital site. Taken together, this research study showed that during the brain’s transition from wakeful rest to sleep states, the brain’s functional connectivity and neurovascular coupling characteristics are significantly altered. In addition, the study shows that neurovascular coupling is also affected by voluntary breath-holding, and this is readily detected by simultaneous EEG-FNIRS measurements.

Keywords

EEG, fNIRS, Graph theory, Wavelet coherence, ELORETA

Disciplines

Biomedical Engineering and Bioengineering | Engineering

Comments

Degree granted by The University of Texas at Arlington

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28350-2.zip (7206 kB)
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