Autism Spectrum Disorder (ASD) is a complex neurodevelopmental disorder marked by social interaction impairment, verbal and non-verbal communication deficit, and repetitive and restricted interests and behaviors. Individuals with ASD who have complex communication needs (CCNs), meaning they have impaired speech or language expression and/or comprehension that limit their social participation, can benefit from augmentative and alternative communication (AAC). However, accessing AAC services in developing countries, such as Saudi Arabia, is limited due to the lack of professionals who can provide such services. Speech language pathologists (SLPs) are the main health practitioners who are responsible for assisting those with communication disorders, especially individuals with CCNs. The purpose of this study is to address Saudi Arabian SLPs' perceived competence in providing AAC technologies and services as well as to examine the relationship between their perceived competence and other factors, including education, clinical training, and experience. This study addresses three primary aims. The first aim is to describe the SLP participants’ background. The second aim is to collect data about SLPs' attitudes and perceived competence in providing AAC services to those with ASD. The third aim is to highlight whether education, training, and years of experience are related to SLPs' perceived competence in providing AAC interventions.

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Assessment of diffuse brain disorders, where the brain may appear normal, has proven difficult to translate into personalized treatments. Previous methods based on brain magnetic resonance imaging (MRI) resting state blood oxygen level dependent (rs-BOLD) signal routinely rely on group analysis where large data sets are assessed using region-of interest (ROI) or probabilistic independent component analysis (PICA) to identify temporal synchrony or desynchrony among regions of the brain. Brain connectivity occurs in a complex, multilevel and multi-temporal manner, driving the fluctuations observed in local oxygen demand. These fluctuations have previously been characterized as fractal, as they auto-correlate at different time scales. In this study we propose a model-free complexity analysis based on the fractal dimension of the rs-BOLD signal, acquired with MRI. The fractal dimension can be interpreted as a measure of signal complexity and connectivity. Previous studies have suggested that reduction in signal complexity can be associated with disease. Therefore, we hypothesized that a detectable differences in rs-BOLD signal complexity could be observed between patients with diffuse or heterogeneous brain disorders and healthy controls. In this study, we obtained anatomical and functional data from patients with brain disorders where traditional methods have been insufficient to fully assess the condition. More specifically, we tested our method on mild traumatic brain injury, autism spectrum disorder, chemotherapy-induced cognitive impairment and chronic fatigue syndrome patients. Three major databases from the Neuroimaging Informatics Tools and Resources Clearinghouse (NITRC) project were used to acquire large numbers of age matched healthy controls. Healthy control data was downloaded from the the Autism Brain Imaging Data Exchange (ABIDE), the Alzheimer's Disease Neuroimaging Initiative (ADNI) and the Human Connectome Project specifically matching our experimental design. In all of our studies, the voxel-wise rs-BOLD signal fractal dimension was calculated following a procedure described by Eke and Herman et al. 2000. This method was previously used to assess brain rs-BOLD signal in small mammals and humans. The method consists of estimating the Hurst exponent in the frequency domain using a power spectral density approach and refining the estimation in the time domain with de-trended fluctuation analysis and signal summation conversion methods. Voxel-wise fractal dimension (FD) was then calculated for every subject in the control and patient groups to create ROI-based Z-scores for each individual patient. Voxel-wise validation of FD normality across controls was studied and non-Gaussian voxels, determined using kurtosis and skewness calculations, were eliminated from subsequent analysis. To maintain a 95 % confidence level, only regions where Z-score values were at least 2 standard deviations away from the mean were included in the analysis. In the case of chronic fatigue patients and chemotherapy induced cognitive impairment, DTI analysis was added to also determine whether white matter abnormalities were also relevent. Similar Z-score analysis on DTI metrics was also performed. Brain microscopic networks, modeled as complex systems, become affected in diffuse brain disorders. Z-scoring of the fractal rs-BOLD frequency domain delineated patient-specific regional brain anomalies which correlated with patient-specific symptoms. This technique can be used alone, or in combination with DTI Z-scoring, to characterize a single patient without any need for group analysis, making it ideal for personalized diagnostics. / Thesis / Doctor of Philosophy (PhD)

Perturbations to the upper limb in aiming tasks act to force individuals to modify their movements using online control processes. Individuals are able to successfully counteract these mechanical and perceptual perturbations to accurately acquire a specific target goal. What is less well understood is how individuals self-initiate a change to their trajectory during obstacle avoidance. A series of two studies were conducted to better understand the effects of a visual perturbation when performing two-dimensional sliding aiming movements during a manual obstacle avoidance task when a second set of obstacles appeared unexpectedly along the preferred, optimal trajectory. On each trial, a planned obstacle appeared at 25%, 50% or 75% of the movement amplitude. On some trials, a second set of obstacles appeared early or late in the movement to force participants to make online corrections or adapt their preferred trajectory to successfully reach the specified target. Results revealed that the mere possibility of the unexpected second obstacles influenced the overall trajectory and movement kinematics (i.e., whether that second obstacles appeared or not). Despite performing the movement in the same amount of time, participants executed a more lateral avoidance trajectory and reached higher accelerations later and further into the movement. We suggest that this pattern of behaviour is indicative of an optimal movement strategy such that the potential for an online correction resulted in individuals planning for the worst-case scenario. The presentation of a case-study for an individual with autism spectrum disorder (ASD) provides insight into potential differences in obstacle avoidance tasks when compared to a matched control. Despite relative differences in execution behaviour, the individual with an ASD successfully completed the task. This provides potential support for the sparing of motor execution processes within this population. Taken together, we suggest that optimal movement strategies may be better defined on a more individual basis. That is, what is optimal for one population might not be optimal for another. / Thesis / Master of Science (MSc) / It is well known that individuals are able to successfully aim to targets in environments that are both predictable and unpredictable. Additionally, these trajectories are successfully modified in the presence of an expected obstacle resulting in a change to the optimal movement to incorporate the location of the obstacle. What is less understood, however, is how individuals respond to the sudden onset of an obstacle along the optimal trajectory. This thesis characterizes these behaviours using a manual obstacle avoidance task wherein obstacles unexpectedly appear to obstruct the preferred movement pathway. The behavioural response to this perturbation is indicative of the performance of more cautious movements, adapted for the worst-case scenario. On average, individuals compromise between the biomechanical and computational demands of the task to execute wide trajectories that do not need to be updated during movement execution, a response that is potentially identified in an autism spectrum population.

<p dir="ltr">Children with autism may have delayed language skills. Deficits in pragmatic language can affect social interaction with adults and peers and academic performance as more complex language becomes required for reading comprehension and analysis of information (Ibrahimagic et al., 2021 p. 251) This research supports the study question, how can educators prepare children with autism during this transition program? The survey was sent to fifteen participants addressing their insights and experiences of the transition to kindergarten process and the transition strategies that were used in the classroom. The results from the survey indicated that teachers do not know about the transition to kindergarten process. For the transitional practices, 36% of teachers said they used social stories, 9% of teachers used a photo book of new people and school environments, and 27% of teachers used observations of the student in the preschool classroom. This research assisted in the production of a handbook.</p>