Theses and Dissertations
Date of Award
2021
Document Type
Dissertation
Degree Name
Doctor of Philosophy (PhD)
Department
College of Psychology
First Advisor
Charles J. Golden
Second Advisor
Lisa Lashley
Third Advisor
Thomas Kennedy
Keywords
cerebral blood flow, default mode network, psychopathology, resting state, SPECT
Abstract
Resting-state (RS) networks (neural regions demonstrating a temporal correlation when a person is not engaged in deliberate activity) are a new topic in neuroscience and neuropsychology, not gaining significant traction in the literature until 2005. Few studies have used single-photon emission computed tomography (SPECT) regional cerebral blood flow (rCBF) to analyze RS. The omission is critical because SPECT RS networks have a different structure and statistical representation than functional magnetic resonance imaging (fMRI) RS networks. Moreover, recent fMRI research has explored RS differences in persons with psychopathology but have not studied brain-behavior assessment with the potential of application of neuropsychological assessment of psychopathology. SPECT may offer a cheaper, faster, and more accessible option for detecting psychopathology, increasing public access to mental healthcare, and enhancing treatment efficacy research.
The principal objective of this study was to describe human RS rCBF patterns in persons with clinical neuropathologies and psychopathologies using SPECT. A robust exploratory factor analysis (EFA) of 12,217 clinical participants was implemented with techniques to increase reliability and replicability, such as parallel and bootstrapped analysis, multiple extraction and rotation comparisons, minimum covariance determinant (MCD) control for outliers, multiple imputation for missing data, and oblique rotation with higher-order factor extraction. This study reliably established eight first-order and four second-order latent constructs explanatory of 66% of the total variance in RS rCBF in 12,217 participants with clinical psychopathology and neuropathology. These factors were interpreted based on functional contributions from 67 structural regions of the brain, and informed by previous fMRI RS research. Results of the second-order interpretation included factors of Spontaneous Cognition, Control, Visuoperception, and Homeostasis. The derived latent constructs may be used in a future confirmatory analysis of RS rCBF models, or alternately, in the design of other follow-up studies to clarify interpretation.
This research supplements existing publications using fMRI that have already reliably characterized RS networks (e.g., the default mode network, salience network, and dorsal attention network.).
This study is a unique and substantial supplement to the basic neuropsychological understanding of brain-behavior relationships and provides an opportunity for follow-up into RS rCBF relationships with specific pathological signs and symptoms.
NSUWorks Citation
Harcourt, S.
(2021). Resting-State Cerebral Perfusion Patterns: An Exploratory Factor Analysis of Single-Photon Emission Computed Tomography Clinical Data. .
Available at: https://nsuworks.nova.edu/cps_stuetd/144