Matching Items (4)
Filtering by

Clear all filters

157470-Thumbnail Image.png
Description
Autism spectrum disorder (ASD) is a developmental neuropsychiatric condition with early childhood onset, thus most research has focused on characterizing brain function in young individuals. Little is understood about brain function differences in middle age and older adults with ASD, despite evidence of persistent and worsening cognitive symptoms. Functional Magnetic

Autism spectrum disorder (ASD) is a developmental neuropsychiatric condition with early childhood onset, thus most research has focused on characterizing brain function in young individuals. Little is understood about brain function differences in middle age and older adults with ASD, despite evidence of persistent and worsening cognitive symptoms. Functional Magnetic Resonance Imaging (MRI) in younger persons with ASD demonstrate that large-scale brain networks containing the prefrontal cortex are affected. A novel, threshold-selection-free graph theory metric is proposed as a more robust and sensitive method for tracking brain aging in ASD and is compared against five well-accepted graph theoretical analysis methods in older men with ASD and matched neurotypical (NT) participants. Participants were 27 men with ASD (52 +/- 8.4 years) and 21 NT men (49.7 +/- 6.5 years). Resting-state functional MRI (rs-fMRI) scans were collected for six minutes (repetition time=3s) with eyes closed. Data was preprocessed in SPM12, and Data Processing Assistant for Resting-State fMRI (DPARSF) was used to extract 116 regions-of-interest defined by the automated anatomical labeling (AAL) atlas. AAL regions were separated into six large-scale brain networks. This proposed metric is the slope of a monotonically decreasing convergence function (Integrated Persistent Feature, IPF; Slope of the IPF, SIP). Results were analyzed in SPSS using ANCOVA, with IQ as a covariate. A reduced SIP was in older men with ASD, compared to NT men, in the Default Mode Network [F(1,47)=6.48; p=0.02; 2=0.13] and Executive Network [F(1,47)=4.40; p=0.04; 2=0.09], a trend in the Fronto-Parietal Network [F(1,47)=3.36; p=0.07; 2=0.07]. There were no differences in the non-prefrontal networks (Sensory motor network, auditory network, and medial visual network). The only other graph theory metric to reach significance was network diameter in the Default Mode Network [F(1,47)=4.31; p=0.04; 2=0.09]; however, the effect size for the SIP was stronger. Modularity, Betti number, characteristic path length, and eigenvalue centrality were all non-significant. These results provide empirical evidence of decreased functional network integration in pre-frontal networks of older adults with ASD and propose a useful biomarker for tracking prognosis of aging adults with ASD to enable more informed treatment, support, and care methods for this growing population.
ContributorsCatchings, Michael Thomas (Author) / Braden, Brittany B (Thesis advisor) / Greger, Bradley (Thesis advisor) / Schaefer, Sydney (Committee member) / Arizona State University (Publisher)
Created2019
131928-Thumbnail Image.png
Description
Motor skill acquisition, the process by which individuals practice and consolidate
movement to become faster, more accurate and efficient, declines with age. Initial skill acquisition is dominated by cortical structures; however as learning proceeds, literature from
rodents and songbirds suggests that there is a transition away from cortical execution. Recent
evidence indicates that

Motor skill acquisition, the process by which individuals practice and consolidate
movement to become faster, more accurate and efficient, declines with age. Initial skill acquisition is dominated by cortical structures; however as learning proceeds, literature from
rodents and songbirds suggests that there is a transition away from cortical execution. Recent
evidence indicates that the reticulospinal system plays an important role in integration and
retention of learned motor skills. The brainstem has known age-rated deficits including cell
shrinkage & death. Given the role of the reticulospinal system in skill acquisition and older
adult’s poor capacity to learn, it begs the question: are delays in the reticulospinal system
associated with older adult’s poor capacity to learn?
Our objective was to evaluate if delays in the reticulospinal system (measured via the
startle reflex) and corticospinal system (measured via Transcranial Magnetic Stimulation (TMS) are correlated to impairment of motor learning in older adults. We found that individuals with fast startle responses resembling those of younger adults show the most improvement and retention while individuals with delayed startle responses show the least. We also found that there was no relationship between MEP latencies and improvement and retention. Moreover, linear regression analysis indicated that startle onset latency exists within a continuum of learning outcomes suggesting that startle onset latency may be a sensitive measure to predict learning deficits in older adults. As there exists no method to determine an individual’s relative learning capacity, these results open the possibility of startle, which is an easy and inexpensive behavioral measure and can be used to determine learning deficits in older adults to facilitate better dosing during rehabilitation therapy.
ContributorsRangarajan, Vishvak (Author) / Honeycutt, Claire (Thesis director) / Schaefer, Sydney (Committee member) / Harrington Bioengineering Program (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
132702-Thumbnail Image.png
Description
Motor skill acquisition, the process by which individuals practice and consolidate movement to become faster, more accurate and efficient, declines with age. Initial skill acquisition is dominated by cortical structures; however as learning proceeds, literature from rodents and songbirds suggests that there is a transition away from cortical execution. Recent

Motor skill acquisition, the process by which individuals practice and consolidate movement to become faster, more accurate and efficient, declines with age. Initial skill acquisition is dominated by cortical structures; however as learning proceeds, literature from rodents and songbirds suggests that there is a transition away from cortical execution. Recent evidence indicates that the reticulospinal system plays an important role in integration and retention of learned motor skills. The brainstem has known age-rated deficits including cell shrinkage & death. Given the role of the reticulospinal system in skill acquisition and older adult’s poor capacity to learn, it begs the question: are delays in the reticulospinal system associated with older adult’s poor capacity to learn?
Our objective was to evaluate if delays in the reticulospinal system (measured via the startle reflex) are correlated to impairment of motor learning in older adults. We found that individuals with fast startle responses resembling those of younger adults show the most learning and retention of that learning while individuals with delayed startle responses show the least. Moreover, linear regression analysis indicated that startle onset latency exists within a continuum of learning outcomes suggesting that startle onset latency may be a sensitive measure to predict learning deficits in older adults. As there exists no method to determine an individual’s relative learning capacity, these results open the possibility of startle, which is an easy and inexpensive behavioral measure, being used to predict learning deficits in older adults to facilitate better dosing during rehabilitation therapy.
ContributorsSchreiber, Joseph James (Author) / Honeycutt, Claire (Thesis director) / Schaefer, Sydney (Committee member) / Harrington Bioengineering Program (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
168788-Thumbnail Image.png
Description
Little is known about how cognitive and brain aging patterns differ in older adults with autism spectrum disorder (ASD). However, recent evidence suggests that individuals with ASD may be at greater risk of pathological aging conditions than their neurotypical (NT) counterparts. A growing body of research indicates that older adults

Little is known about how cognitive and brain aging patterns differ in older adults with autism spectrum disorder (ASD). However, recent evidence suggests that individuals with ASD may be at greater risk of pathological aging conditions than their neurotypical (NT) counterparts. A growing body of research indicates that older adults with ASD may experience accelerated cognitive decline and neurodegeneration as they age, although studies are limited by their cross-sectional design in a population with strong age-cohort effects. Studying aging in ASD and identifying biomarkers to predict atypical aging is important because the population of older individuals with ASD is growing. Understanding the unique challenges faced as autistic adults age is necessary to develop treatments to improve quality of life and preserve independence. In this study, a longitudinal design was used to characterize cognitive and brain aging trajectories in ASD as a function of autistic trait severity. Principal components analysis (PCA) was used to derive a cognitive metric that best explains performance variability on tasks measuring memory ability and executive function. The slope of the integrated persistent feature (SIP) was used to quantify functional connectivity; the SIP is a novel, threshold-free graph theory metric which summarizes the speed of information diffusion in the brain. Longitudinal mixed models were using to predict cognitive and brain aging trajectories (measured via the SIP) as a function of autistic trait severity, sex, and their interaction. The sensitivity of the SIP was also compared with traditional graph theory metrics. It was hypothesized that older adults with ASD would experience accelerated cognitive and brain aging and furthermore, age-related changes in brain network topology would predict age-related changes in cognitive performance. For both cognitive and brain aging, autistic traits and sex interacted to predict trajectories, such that older men with high autistic traits were most at risk for poorer outcomes. In men with autism, variability in SIP scores across time points trended toward predicting cognitive aging trajectories. Findings also suggested that autistic traits are more sensitive to differences in brain aging than diagnostic group and that the SIP is more sensitive to brain aging trajectories than other graph theory metrics. However, further research is required to determine how physiological biomarkers such as the SIP are associated with cognitive outcomes.
ContributorsSullivan, Georgia (Author) / Braden, Blair (Thesis advisor) / Kodibagkar, Vikram (Thesis advisor) / Schaefer, Sydney (Committee member) / Wang, Yalin (Committee member) / Arizona State University (Publisher)
Created2022