This thesis explores the interplay of aphasia symptoms and brain connectivityusing resting-state functional Magnetic Resonance Imaging (MRI). The research presented here is a step towards understanding the neural basis of linguistic prosody in particular, and its relationship with language impairments in post-stroke aphasia. This study focuses on examining the functional connectivities of the frontal-parietal control network and the dorsal attention networks with specific regions within traditional language networks, as a growing body of research suggests that prosodic cues in speech may recruit control and attention networks to support language processing. Using resting- state fMRI, the present study examined the functional connectivity of the frontal parietal control and dorsal attention networks with traditional language regions in 28 participants who have experienced a stroke-related language impairment (i.e. aphasia) and 32 matched neurotypical adults. Overall, the study reveals significant functional connectivity differences of the frontoparietal control and dorsal attention networks between the stroke and control groups, indicating that individuals with aphasia have brain connectivity differences beyond the traditional language networks. Multiple regression analyses were then used to determine if functional connectivities of the frontoparietal control and dorsal attention networks within themselves and with traditional language regions could predict aphasia symptoms, as measured by the Western Aphasia Battery (WAB). Overall, the regression results indicate that greater functional connectivity between the frontoparietal control and dorsal attention networks with traditional language regions is associated with improved language abilities, with different connectivities predicting different types of aphasia symptoms (e.g. speech, naming / word finding, auditory comprehension, overall impairment). Altogether this study contributes to the understanding of the neural bases of language impairments post-stroke, highlighting the intricate connections between language and other cognitive networks, which may be mediated by prosody.

Autistic adults face heightened risk of psychiatric disorders, with depression occurrence estimated at quadruple the rate of the general population. Mindfulness Based Stress Reduction (MBSR), an intensive 8-week in-person intervention, reduces depressive symptoms in adults with autism spectrum disorder (ASD). However, access to these programs is restricted due to financial, geographic, and scheduling limitations. Additionally, lapses in practice post-intervention cause these effects to be short-lived. This study examines antidepressant effects of an 8-week app-delivered mindfulness meditation intervention using Ten Percent Happier in adults with ASD and explores whether anchoring meditation practice to a preexisting behavior will improve therapy compliance and depression-related efficacy. Ninety-seven participants were randomly assigned to either App Only (n=30), App + Habit training (n=27) or Waitlist Control (n=40). App Only and App + Habit groups were requested to meditate a minimum of 10 minutes per day, 5 days per week for 8 consecutive weeks using the mobile application. The App + Habit group received additional instruction to anchor leaving the bathroom each morning with meditation; The App Only group was only provided with education on habit formation. Participants completed the Beck Depression Inventory-II (BDI-II) at pre- and post-intervention. All groups received weekly ecological momentary assessments (EMAs) to assess frequency and length of practice. The App + Habit group was additionally assessed for cue-initiated meditation frequency. Data were analyzed using repeated measures analysis of variance (ANOVA). Pre-to-post changes on BDI-II scores indicated a group by time interaction (p=0.04) and a main effect of time (p <0.001). Post-hoc analysis revealed the App + Habit group exclusively showed significant decline in depressive symptoms (p<0.001). The App + Habit group showed greater number of days meditated, average minutes per day of meditating, and continuation of meditation practice 8-weeks after the intervention period, compared to the App Only group. Findings support app-delivered mindfulness interventions as an accessible and cost-effective alternative to traditional in-person mindfulness training for Autistic adults. However, results suggest app-based mindfulness tools may only be effective when delivered with specific habit formation instruction. Additionally, habit formation instruction led to greater adherence to meditation practice after the study period ended.

Autism shows a pronounced and replicable sex bias with approximately three-to-four males diagnosed for every one female. Sex-related biology is thought to play a role in the sex bias, such that female biology may be protective and/or male biology may increase vulnerability to autism in the context of similar genetic risk. Beyond etiology, sex-related biology has also been implicated in lifespan risk for health and psychiatric conditions that show common co-morbidity in autism. Thus, understanding how sex-related biology impacts autism etiology and progression has important implications for prognosis and treatment. Neuroimaging offers a powerful tool for in-vivo characterization of brain-based sex differences in autism, especially given emerging efforts to develop large, well-characterized longitudinal samples. To date, however, neuroimaging studies have shown mixed and inconsistent findings, which remain challenging to integrate in the broader literature context. In a recent systematic review of neuroimaging studies of typical sex differences, few to no replicable effects were found beyond brain size, suggesting the brain is not “sexually dimorphic.” Instead, it is argued that the brain is a “mosaic” of features from various sources, including masculine and feminine biological processes as well as individual genetics and environment. Thus, designing neuroimaging studies that are sensitive to brain-based sex differences in autism likely requires careful study design and analytical method selection. Through a series of studies, the overarching dissertation aim was to identify optimal methods for characterizing neuroimaging-based sex differences in autism and to test these methods in preliminary samples. Study 1 comprised a systematic review of studies examining neuroimaging-based sex differences in autism with the aim of identifying optimal study designs, neuroimaging modalities, and analytical methods. Study 2 focused on examining the sensitivity of a connectome-wide approach to identify functional connectivity hubs underlying sex-biased behavior associated with autism (e.g., camouflaging). Study 3 used a connectome-wide functional connectivity approach to characterize sex differences in longitudinal changes associated with autistic traits vs. categorical diagnosis. These studies suggest that optimizing study design and methods improves identification of biologically plausible and clinically meaningful brain sex differences in autism. The relevance of findings to etiology and prognosis are discussed.

The present study aimed to compare brain activity changes related to proactive and reactive control strategies in patients with Parkinson’s disease during “On” levodopa and “Off” levodopa conditions. The study consisted of two participants who had received a prior diagnosis of Parkinson’s Disease. The participants completed AX-CPT task as a measure of attention control in two sessions: a) “On Levodopa” and b) “Off Levodopa” while they were in the fMRI scanner. Prior to the analysis, the T1- weighted anatomical scan images and the BOLD multiband functional images of both the participants were BIDS (Brain Imaging Data Structure) validated and preprocessed using the standard FMRIPrep pipeline. The imaging data was then analyzed using SPM12 (Statistical parametric mapping) software. Individual-level analysis of the imaging data was conducted by creating General Linear models for both the participants on “ON” and “OFF” levodopa conditions. The BOLD responses were compared using AY>BY and BX > BY contrasts. Where BX >, BY contrast, measured BOLD activity related to reactive control strategy and AY> BY contrast measured BOLD activity related to the proactive control strategy. It was observed that participants tended towards reactive control strategy in both “On” and “Off” levodopa conditions.

Behavior challenges impact children and educational professionals on a daily basis; however, it is difficult for educators to obtain high quality training in behavior management. The purpose of this study was to compare cognitive apprenticeship and group work, two teaching methods, to determine which provides better knowledge and implementation outcomes for educators taking a course on behavior analysis. Seventeen educational professionals currently working with students who display challenging behavior were randomly assigned to the cognitive apprenticeship or group work conditions. The difference between the conditions is the introduction of a coach in the cognitive apprenticeship condition. The coach guides learners through the process of understanding and using behavior analysis throughout the course by providing feedback, scaffolding, and encouraging reflection and exploration. Participants completed pre-, post-, and post-posttests that measured their knowledge of behavior analysis and how well they implemented the skills taught in the course. Additionally, they completed weekly quizzes and reported how often they used the skills in real-life situations. Overall group differences across time points for knowledge and implementation scores were analyzed using a repeated measures analysis of variance (ANOVA). There were significant differences across time for both scores but not condition or time by condition. A covariance pattern model was used to determine if self-efficacy, self-confidence, previous behavior knowledge, or overall quiz performance predicted the variance in knowledge and implementation scores on the pre-, post-, and post-posttests across conditions. Time was the only significant predictor of knowledge scores, while time, condition and self-efficacy significantly predicted the variance in implementation scores. Additionally, one-way ANOVAs were used to find condition-based differences in quiz scores and practical skill use, neither of which were significant. Finally, a linear regression was used to determine if on quiz performance predicts the use of skills in real-world settings, which it did not. The courses impact on learning, skill use, and student behavior as well as future applications are discussed.

Adults with autism spectrum disorder (ASD) face heightened risk of co-occurring psychiatric conditions, especially depression and anxiety disorders, which contribute to seven-fold higher suicide rates than the general population. Mindfulness-based stress reduction (MBSR) is an 8-week meditation intervention centered around training continuous redirection of attention toward present moment experience, and has been shown to improve mental health in autistic adults. However, the underlying therapeutic neural mechanisms and whether behavioral and brain changes are mindfulness-specific have yet to be elucidated. In this randomized clinical trial, I utilized functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) to characterize fMRI functional activity (Study 1) and connectivity (Study 2) and EEG neurophysiological (Study 3) changes between MBSR and a social support/relaxation education (SE) active control group. Study 1 revealed an MBSR-specific increase in the midcingulate cortex fMRI blood oxygen level dependent signal which was associated with reduced depression. Study 2 identified nonspecific intervention improvements in depression, anxiety, and autistic, and MBSR-specific improvements in the mindfulness trait ‘nonjudgment toward experience’ and in the executive functioning domain of working memory. MBSR-specific decreases in insula-thalamus and frontal pole-posterior cingulate functional connectivity was associated with improvements in anxiety, mindfulness traits, and working memory abilities. Both MBSR and SE groups showed decreased amygdala-sensorimotor and frontal pole-insula connectivity which correlated with reduced depression. Study 3 consisted of an EEG spectral power analysis at high-frequency brainwaves associated with default mode network (DMN) activity. Results showed MBSR-specific and nonspecific decreases in beta- and gamma-band power, with effects being generally more robust in the MBSR group; additionally, MBSR-specific decreases in posterior gamma correlated with anxiolytic effects. Collectively, these studies suggest: 1) social support is sufficient for improvements in depression, anxiety, and autistic traits; 2) MBSR provides additional benefits related to mindfulness traits and working memory; and 3) distinct and shared neural mechanisms of mindfulness training in adults with ASD, implicating the salience and default mode networks and high-frequency neurophysiology. Findings bear relevance to the development of personalized medicine approaches for psychiatric co-morbidity in ASD, provide putative targets for neurostimulation research, and warrant replication and extension using advanced multimodal imaging approaches.

Individuals with autism spectrum disorder (ASD) are known to show impairments in various domains of executive function (EF) such as behavioral flexibility or inhibitory control. Research suggests that EF impairment in adults with ASD may relate to ASD core symptoms, restrictive behaviors and social communication deficits. Mindfulness-based stress reduction (MBSR) has shown promise for improving EF abilities in neurotypical adults, but research has not explored its efficacy or neural mechanisms in adults with ASD. This pilot study examines the effects of an 8-week MBSR intervention on self-report measures of EF and resting-state functional connectivity in a sample of adults with ASD. Fifty-four participants were assigned either to an MBSR group (n = 29) or a social support group (n = 25). Executive function was measured using the BRIEF-2 before and after the intervention for the twenty-seven participants in the second cohort. MBSR-specific improvements in EF were found for BRIEF measures of initiation, inhibition, and working-memory. Resting-state fMRI data was analyzed using independent component analysis (ICA), and group by time resting-state functional connectivity differences were observed between the cerebellar network and frontal regions including the right frontal pole (rFP), medial frontal cortex (MFC) and left and right superior frontal gyri (SFG). The MBSR group showed increases in functional connectivity between the cerebellum and EF regions which correlated with improvements in BRIEF-2 measures. These findings suggest that MBSR may improve EF domains in adults with ASD, and that increases in functional connectivity between the cerebellum and frontal regions while at rest may be a mechanism for such improvements.

The aim of this study was to explore cross-sectional and longitudinal aging differences in immediate and delayed visual and verbal memory abilities in individuals with Autism Spectrum Disorder (ASD) compared with neurotypicals (NTs). We measured hippocampal size, fornix fractional anisotropy (FA), and hippocampal and fornix freewater to understand how aging impacts memory structures. Longitudinal findings highlight vulnerabilities in immediate verbal memory and hippocampal volume, while cross-sectional findings indicate fornix freewater may increase at a faster rate in adults with ASD. Future research will examine cognitive and structural sex differences and will study how cognitive measures correlate with structural measures.

The rapid development in acquiring multimodal neuroimaging data provides opportunities to systematically characterize human brain structures and functions. For example, in the brain magnetic resonance imaging (MRI), a typical non-invasive imaging technique, different acquisition sequences (modalities) lead to the different descriptions of brain functional activities, or anatomical biomarkers. Nowadays, in addition to the traditional voxel-level analysis of images, there is a trend to process and investigate the cross-modality relationship in a high dimensional level of images, e.g. surfaces and networks.

In this study, I aim to achieve multimodal brain image fusion by referring to some intrinsic properties of data, e.g. geometry of embedding structures where the commonly used image features reside. Since the image features investigated in this study share an identical embedding space, i.e. either defined on a brain surface or brain atlas, where a graph structure is easy to define, it is straightforward to consider the mathematically meaningful properties of the shared structures from the geometry perspective.

I first introduce the background of multimodal fusion of brain image data and insights of geometric properties playing a potential role to link different modalities. Then, several proposed computational frameworks either using the solid and efficient geometric algorithms or current geometric deep learning models are be fully discussed. I show how these designed frameworks deal with distinct geometric properties respectively, and their applications in the real healthcare scenarios, e.g. to enhanced detections of fetal brain diseases or abnormal brain development.

With a growing number of adults with autism spectrum disorder (ASD), more and more research has been conducted on majority male cohorts with ASD from young, adolescence, and some older age. Currently, males make up the majority of individuals diagnosed with ASD, however, recent research states that the gender gap is closing due to more advanced screening and a better understanding of how females with ASD present their symptoms. Little research has been published on the neurocognitive differences that exist between older adults with ASD compared to neurotypical (NT) counterparts, and nothing has specifically addressed older women with ASD. This study utilized neuroimaging and neuropsychological tests to examine differences between diagnosis and sex of four distinct groups: older men with ASD, older women with ASD, older NT men, and older NT women. In each group, hippocampal size (via FreeSurfer) was analyzed for differences as well as correlations with neuropsychological tests. Participants (ASD Female, n = 12; NT Female, n = 14; ASD Male, n = 30; NT Male = 22), were similar according to age, IQ, and education. The results of the study indicated that the ASD Group as a whole performed worse on executive functioning tasks (Wisconsin Card Sorting Test, Trails Making Test) and memory-related tasks (Rey Auditory Verbal Learning Test, Weschler Memory Scale: Visual Reproduction) compared to the NT Group. Interactions of sex by diagnosis approached significance only within the WCST non-perseverative errors, with the women with ASD performing worse than NT women, but no group differences between men. Effect sizes between the female groups (ASD female vs. NT female) showed more than double that of the male groups (ASD male vs. NT male) for all WCST and AVLT measures. Participants with ASD had significantly smaller right hippocampal volumes than NT participants. In addition, all older women showed larger hippocampal volumes when corrected for total intracranial volume (TIV) compared to all older men. Overall, NT Females had significant correlations across all neuropsychological tests and their hippocampal volumes whereas no other group had significant correlations. These results suggest a tighter coupling between hippocampal size and cognition in NT Females than NT Males and both sexes with ASD. This study promotes further understanding of the neuropsychological differences between older men and women, both with and without ASD. Further research is needed on a larger sample of older women with and without ASD.