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- Title
- FACTORS ASSOCIATED WITH COGNITIVE IMPAIRMENT IN WELLMOTIVATED CHRONIC NON-MALIGNANT PAIN PATIENTS EVALUATED FOR SPINAL CORD STIMULATION
- Creator
- Zalizniak, Kevin C.
- Date
- 2016, 2016-12
- Description
-
Cognitive impairment in individuals with chronic pain is frequently observed and clinically significant (McCracken, & Iverson, 2001). It has...
Show moreCognitive impairment in individuals with chronic pain is frequently observed and clinically significant (McCracken, & Iverson, 2001). It has long been recognized that emotional factors contribute to both patient perception of impaired cognition and verifiable cognitive impairment on testing (Burt, Zembar, & Niederehe, 1995). However, scientific consensus is lacking regarding how specific emotions, such as depression, anxiety, and pain catastrophizing impact cognition in chronic pain patients. Research seeking to clarify such relationships has been hampered by methodological shortcomings, which include limited sample sizes, non-objective measures, and failure to examine multiple emotional dimensions in unique samples (McCracken and Vowels, 2014; Moriarty, McGuire, & Finn, 2011). The present study examined factors that might contribute to cognitive impairment in this population using a sample of 78 chronic pain patients evaluated for surgical candidacy for spinal cord stimulator (SCS) implantation at the University of Illinois at Chicago. Use of such a sample ensured patients were wellmotivated to perform to the best of their ability, so as to increase their chance of being cleared for such a highly desirable procedure. Additionally, the vast majority of participants passed well-validated objective measures of effort. Hypothesized associations between attentional function as measured objectively by the RBANS attention index and a number of predictor variables: depression and anxiety, subjective pain experience, pain catastrophizing, somatization, and engagement in pain behaviors were not found, and subsequent analyses of proposed mediating relationships could not be performed. However, fully a third (35.9 percent) of our well-motivated sample did not show clinically significant impairment (below 85, or 1 SD below the mean), as was expected. Thus, it is possible that a well-motivated sample may have been less likely than samples used in previous investigations to show cognitive impairment overall. Strengths and limitations of the study are discussed, as well as clinical and research implications.
Ph.D. in Psychology, December 2016
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- Title
- DEVELOPMENT OF BIOMARKERS OF SMALL VESSEL DISEASE IN AGING
- Creator
- Makkinejad, Nazanin
- Date
- 2021
- Description
-
Age-related neuropathologies including cerebrovascular and neurodegenerative diseases play a critical role in cognitive dysfunction, and...
Show moreAge-related neuropathologies including cerebrovascular and neurodegenerative diseases play a critical role in cognitive dysfunction, and development of dementia. Designing methodologies for early prediction of these diseases are much needed. Since multiple pathologies commonly coexist in brains of older adults, clinical diagnosis lacks the specificity to isolate the pathology of interest, and gold standard is determined only at autopsy. Magnetic resonance imaging (MRI) provides a non-invasive tool to study abnormalities in brain characteristics that is unique to each pathology. Utilizing ex-vivo MRI for brain imaging proves to be useful as it eliminates two important biases of in-vivo MRI. First, no additional pathology would develop between imaging and pathologic examination, and second, frail older adults would not be excluded from MRI.Hence, the aims of this dissertation were two-fold: to study brain correlates of age- related neuropathologies, and to develop and validate classifiers of small vessel diseases by combining ex-vivo MRI and pathology in a large community cohort of older adults. The structure of the project is as follows.First, the association of amygdala volume and shape with transactive response DNA-binding protein 43 (TDP-43) pathology was investigated. Using a regularized regression technique, higher TDP-43 was associated with lower amygdala volume. Also, shape analysis of amygdala showed unique patterns of spatial atrophy associated with TDP-43 independent of other pathologies. Lastly, using linear mixed effect models, amygdala volume was shown to explain an additional portion of variance in cognitive decline above and beyond what was explained by the neuropathologies and demographics.Second, the previous study was extended to analyze other subcortical regions including the hippocampus, thalamus, nucleus accumbens, caudate, and putamen, and was also conducted in a larger dataset. The results showed unique contribution of TDP-43, neurofibrillary tangles (hallmark characteristic of Alzheimer’s disease pathology), and atherosclerosis (a cerebrovascular pathology) to atrophy on the surface of subcortical structures. Understanding the independent effects of each pathology on volume and shape of different brain regions can form a basis for the development of classifiers of age-related neuropathologies.Third, an in-vivo classifier of arteriolosclerosis was developed and validated. Arteriolosclerosis is one of the main pathologies of small vessel disease, is associated with cognitive decline and dementia, and currently has no standard biomarker available. In this work, the classifier was developed ex-vivo using machine learning (ML) techniques and was then translated to in-vivo. The in-vivo classifier was packaged as a software called ARTS, which outputs a score that is the likelihood of arteriolosclerosis when the required input is given to the software. It was tested and validated in various cohorts and showed to have high performance in predicting the pathology. It was also shown that higher ARTS score was associated with greater cognitive decline in domains that are specific to small vessel disease.Fourth, motivated by current trends and superiority of deep learning (DL) techniques in classification tasks in computer vision and medical imaging, a preliminary study was designed to use DL for training an ex-vivo classifier of arteriolosclerosis. Specifically, convolutional neural networks (CNNs) were applied on 3 Tesla ex-vivo MR images directly without providing prior information of brain correlates of arteriolosclerosis. One interesting aspect of the results was that the network learnt that white matter hyperintense lesions contributed the most to classification of arteriolosclerosis. These results were encouraging, and more future work will exploit the capability of DL techniques alongside the traditional ML approaches for more automation and possibly better performance.Finally, a preliminary classifier of arteriolosclerosis and small vessel atherosclerosis was developed since the existence of both pathologies in brain have devastating effects on cognition. The methodology was similar to the one used for development of arteriolosclerosis classifier with minor differences. The classifier showed a good performance in-vivo, although the testing needs to be assessed in more cohorts.The comprehensive study of age-related neuropathologies and their contribution to abnormalities of subcortical brain structures offers a great potential to develop a biomarker of each pathology. Also, the finding that the MR-based classifier of arteriolosclerosis showed high performance in-vivo demonstrate the potential of ex-vivo studies for development of biomarkers that are precise (because they are based on autopsy, which is the gold standard) and are expected to work well in-vivo. The implications of this study include development of biomarkers that could potentially be used in refined participant selection and enhanced monitoring of the treatment response in clinical drug and prevention trials.
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- Title
- Neuropsychological Pattern of Verbal and Nonverbal Processing Speed Discrepancy in Veterans with Co-Occurring mTBI and PTSD
- Creator
- VanLandingham, Hannah B.
- Date
- 2023
- Description
-
Rates of traumatic brain injury (TBI) exposure have increased over time (CDC, 2022). This pattern of increased TBI risk is additionally...
Show moreRates of traumatic brain injury (TBI) exposure have increased over time (CDC, 2022). This pattern of increased TBI risk is additionally associated with risk for development of posttraumatic stress disorder (PTSD; APA, 2013). Ongoing PTSD symptomology can lead to neuropsychological profiles in which deficits are more pronounced for verbally constrained performances when compared to nonverbal performances. However, less is known about this performance discrepancy in patients with a history of head injury with comorbid PTSD. Moreover, the little existing research focuses on the domains of executive functioning, learning, and memory, with little to no research on processing speed discrepancies. These findings could have significant implications for healthcare and cognitive intervention pre- and post-mTBI and/or trauma exposure because this discrepancy may impact clinical assessment and subsequent diagnosis. The analysis will include 1) determination of statistically and clinically significant differences for those with co-occurring PTSD and mTBI, and 2) examine within-subjects differences with and without the inclusion of covariates. The present research found that there are no differences between those with co-occurring PTSD and head injury compared to individuals without a co-occurring diagnosis, in addition to no significant discrepancies notes within the PTSD and mTBI group alone
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