Browsing by Subject "Autism"

Gaze estimation, the ability to predict where a person is looking, has become an indispensable technology in healthcare research. Current tools for gaze estimation rely on specialized hardware and are typically used in well-controlled laboratory settings. Novel appearance-based methods directly estimate a person's gaze from the appearance of their eyes, making gaze estimation possible with ubiquitous, low-cost devices, such as webcams and smartphones. This dissertation presents new methods on appearance-based gaze estimation as well as applying this technology to solve challenging problems in practical healthcare applications.

One limitation of appearance-based methods is the need to collect a large amount of training data to learn the highly variant eye appearance space. To address this fundamental issue, we develop a method to synthesize novel images of the eye using data from a low-cost RGB-D camera and show that this data augmentation technique can improve gaze estimation accuracy significantly. In addition, we explore the potential of utilizing visual saliency information as a means to transparently collect weakly-labelled gaze data at scale. We show that the collected data can be used to personalize a generic gaze estimation model to achieve better performance on an individual.

In healthcare applications, the possibility of replacing specialized hardware with ubiquitous devices when performing eye-gaze analysis is a major asset that appearance-based methods brings to the table. In the first application, we assess the risk of autism in toddlers by analyzing videos of them watching a set of expert-curated stimuli on a mobile device. We show that appearance-based methods can be used to estimate their gaze position on the device screen and that differences between the autistic and typically-developing populations are significant. In the second application, we attempt to detect oculomotor abnormalities in people with cerebellar ataxia using video recorded from a mobile phone. By tracking the iris movement of participants while they watch a short video stimuli, we show that we are able to achieve high sensitivity and specificity in differentiating people with smooth pursuit oculomotor abnormalities from those without.

This dissertation presents novel methods for behavioral analysis with a focus on early risk marker identification for autism. We present current contributions including a method for pose-invariant facial expression recognition, a self-contained mobile application for behavioral analysis, and a framework to calibrate a trained deep model with data synthesis and augmentation. First we focus on pose-invariant facial expression recognition. It is known that 3D features have higher discrimination power than 2D features; however, usually 3D features are not readily available at testing time. For pose-invariant facial expression recognition, we utilize multi-modal features at training and exploit the cross-modal relationship at testing. We extend our pose-invariant facial expression recognition method and present other methods to characterize a multitude of risk behaviors related to risk marker identification for autism. In practice, identification of children with neurodevelopmental disorders requires low specificity screening with questionnaires followed by time-consuming, in-person observational analysis by highly-trained clinicians. To alleviate the time and resource expensive risk identification process, we develop a self-contained, closed- loop, mobile application that records a child’s face while he/she is watching specific, expertly-curated movie stimuli and automatically analyzes the behavioral responses of the child. We validate our methods to those of expert human raters. Using the developed methods, we present findings on group differences for behavioral risk markers for autism and interactions between motivational framing context, facial affect, and memory outcome. Lastly, we present a framework to use face synthesis to calibrate trained deep models to deployment scenarios that they have not been trained on. Face synthesis involves creating novel realizations of an image of a face and is an effective method that is predominantly employed only at training and in a blind manner (e.g., blindly synthesize as much as possible). We present a framework that optimally select synthesis variations and employs it both during training and at testing, leading to more e cient training and better performance.

Background: Early detection and early intervention for autism spectrum disorder (ASD) is critical because it can reduce the severity of core ASD symptoms, and result in significant long-term improvements in language acquisition, social skills, cognitive abilities, and adaptive behaviors. Involving caregivers in the delivery of early ASD intervention is becoming increasingly important, particularly in low-resource settings, due to limited access to specialist ASD services. Currently, there is no published research on early ASD intervention in South Africa or sub-Saharan Africa (SSA). In addition, there are no published descriptions of caregiver-child joint activity routines, in which early intervention techniques can be embedded, or perceptions of the acceptability of a caregiver coaching approach.

Study Aims: This study aimed to elicit qualitative descriptions of caregiver-child joint activity routines in order to understand how the Early Start Denver Model (ESDM), an evidence-based early ASD intervention, could fit in a low resource South African setting. It also aimed to gauge the acceptability of a caregiver coaching intervention from South African caregivers of young children with ASD who received two taster sessions of caregiver coaching.

Methods: Participants were recruited from the Western Cape Education Department autism waiting list through convenience sampling. Four focus group discussions were conducted with 22 caregivers of young children with ASD, which gathered data on caregiver-child joint activity routines. Four additional families were recruited to participate in two caregiver coaching sessions each. Four in-depth interviews were subsequently conducted with the six caregivers from these families, which gathered data on joint activity routines and acceptability of a caregiver coaching intervention. Data were analyzed through a qualitative content analysis approach, which used a combination of inductive and deductive methods to determine the salient themes and subthemes within the data.

Results: Caregiver descriptions of joint activity routines aligned with ESDM themes of object-based play, sensory social routines, and family routines. In object-based play caregivers reported engaging in turn-taking with their children, teaching skills across developmental domains, embracing child-directed activities, and managing challenges related to play in resource limited settings. In sensory social routines, caregivers described physical play, an awareness of the child’s affect and engagement, increased child expressive communication, and willingness of the child to engage with different play partners. In family routines, caregivers reported child participation in meals and bath time. Caregivers reported that a caregiver coaching approach was acceptable and that they had acquired a variety of skills, including strategies to enhance their child’s social communication. Caregivers preferred receiving coaching in their homes as opposed to in a clinic setting; however, limitations in physical space and financial resources were important considerations.

Conclusion: Training caregiver coaches and non-specialist workers narrows the treatment gap by providing access to children in need of early ASD intervention. This is essential, because of the scarcity of psychologists and psychiatrists working in mental health in low and middle-income countries (LMIC). Descriptions from South African caregivers of caregiver-child joint activity routines and acceptability of the caregiver coaching approach contextualize the caregiver coaching intervention. These data will inform the adaptation and piloting of an early ASD intervention within a low-resource South African setting.

Introduction

Methods

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Abstract

There is a population of individuals classified as having Autism Spectrum Disorder (ASD). This group of people should be included in places of worship, the schools they attend and the communities where they reside. Consequently, they are sometimes excluded from some occurrences that others experience.

Utilizing personal stories (of successes and sometimes failures), ASD parent interviews and research, I will offer suggestions for inclusion and enlighten the areas where there tends to be exclusion. My focus is the church and how church leaders may become involved in the lives of ASD parishioners to enhance inclusion in not only the church, but the school and the community as well.

My research shows that ASD parents would like their children to experience church as they have. Although willing, most churches, may lack the ability to oblige for various reasons. Schools where inclusion is not encouraged, rests primarily on the shoulders of the principals. Like pastors in churches, principals in schools have influence and can spearhead inclusion efforts in their respective entities. Community entities are willing to accommodate ASD clientele and have done so when approached to comply.

I contend where any of these entities are not willing to foster inclusion, then the church can and most often should become involved to assist, with the necessary training. In other words, the church must do what the church has always done – stand up for those who are unable to do so for themselves.

Keywords: Autism, church, community, inclusion, parents, school

Abstract

There is a population of individuals classified as having Autism Spectrum Disorder (ASD). This group of people should be included in places of worship, the schools they attend and the communities where they reside. Consequently, they are sometimes excluded from some occurrences that others experience.

Utilizing personal stories (of successes and sometimes failures), ASD parent interviews and research, I will offer suggestions for inclusion and enlighten the areas where there tends to be exclusion. My focus is the church and how church leaders may become involved in the lives of ASD parishioners to enhance inclusion in not only the church, but the school and the community as well.

My research shows that ASD parents would like their children to experience church as they have. Although willing, most churches, may lack the ability to oblige for various reasons. Schools where inclusion is not encouraged, rests primarily on the shoulders of the principals. Like pastors in churches, principals in schools have influence and can spearhead inclusion efforts in their respective entities. Community entities are willing to accommodate ASD clientele and have done so when approached to comply.

I contend where any of these entities are not willing to foster inclusion, then the church can and most often should become involved to assist, with the necessary training. In other words, the church must do what the church has always done – stand up for those who are unable to do so for themselves.

Keywords: Autism, church, community, inclusion, parents, school

Mutations in the gene SHANK2, which encodes a synaptic scaffolding protein, have been shown to cause a spectrum of neuropsychiatric disorders including: intellectual disability, autism spectrum disorders (ASDs), bipolar disorder (BD), and schizophrenia. However, many aspects of SHANK2 including the array of isoforms expressed, the expression pattern of the protein, biochemical and regulatory mechanisms, and in vivo protein function remain elusive. This body of work aims to uncover the function of the SHANK2 gene and its role in neuropsychiatric disorders using in vitro and in vivo experimental systems.

Using a molecular genetics approach, I revealed the transcript architecture of the mouse Shank2 gene including characterization of promoters, isoforms and protein domains. I then outlined the temporal and spatial pattern of the Shank2 isoform expression throughout development. To further explore the protein’s function, we sought to identify novel SHANK2 interacting proteins using a yeast-2-hybrid screen and characterized the interacting proteins. Lastly, in order to understand how Shank2 deficiencies alter brain function we generated and characterized both Shank2 conventional (∆e24) and conditional mutant mice (e24floxed) by deleting or floxing exon 24 that encodes the Homer binding site and has nonsense mutations in human patients with neuropsychiatric disorders.

Collectively, these studies 1) provide insight into the transcriptional regulation of Shank2 during brain development; 2) support the value of using Shank2 to further dissect the pathophysiology and circuitry mechanism underlying manic and autism like behaviors; 3) offers a novel mechanistic link between ubiquitination-mediated protein modification and SHANK2 function that may elucidate the molecular basis underlying SHANK2-related neuropsychiatric disorders. Ultimately, these findings may lead to the development of new therapeutic interventions for SHANK2-related neuropsychiatric disorders.

Popular expressions of contemporary Christianity emphasize a version of the faith is not a religion, but a relationship. What would such a statement mean for people on the autism spectrum whose diagnosis in DSM-5 describes their kind of relating with words like disability, deficiency, and disorder? Are they to be considered disabled in their ability to relate to God? The answer is no. By first identifying the way that projection is at play in our phenomenology of relationships, this project takes the diagnostic criteria for Autism Spectrum Disorder found in DSM-5 and locates examples where the Bible witnesses to God behaving in a similar manner. This overlap of neurodiverse relational patterns and divine conduct does two things: First, it provides an opportunity for people on the spectrum to find their kind of relating in the God of the Bible. Second, it expands the palette of language and metaphor the church can draw upon to describe how people relate to God and how God relates to people. The final chapter includes captured learnings and examples for how a work like this can be implemented in parish ministry. In all this, autism reveals both where our relational theology is insufficient, as well as where new avenues of Christian faithfulness lie.

Popular expressions of contemporary Christianity emphasize a version of the faith is not a religion, but a relationship. What would such a statement mean for people on the autism spectrum whose diagnosis in DSM-5 describes their kind of relating with words like disability, deficiency, and disorder? Are they to be considered disabled in their ability to relate to God? The answer is no. By first identifying the way that projection is at play in our phenomenology of relationships, this project takes the diagnostic criteria for Autism Spectrum Disorder found in DSM-5 and locates examples where the Bible witnesses to God behaving in a similar manner. This overlap of neurodiverse relational patterns and divine conduct does two things: First, it provides an opportunity for people on the spectrum to find their kind of relating in the God of the Bible. Second, it expands the palette of language and metaphor the church can draw upon to describe how people relate to God and how God relates to people. The final chapter includes captured learnings and examples for how a work like this can be implemented in parish ministry. In all this, autism reveals both where our relational theology is insufficient, as well as where new avenues of Christian faithfulness lie.

Human beings are inherently social. As we grow, the interactions we have with those around us become the foundation of the relationships with our families, friends, educators, and caretakers. Aberrant social behavioral traits can put a strain on these relationships and negatively impact an individual's quality of life. When severe, these disruptions represent core etiological features of many neurodevelopmental and behavioral disorders, including addiction, schizophrenia, and autism spectrum disorder (ASD).

Advances in the fields of psychology, psychiatry, neuroscience, and the behavioral sciences have developed a wide range of techniques to disentangle the biological and behavioral components of complex social traits, often with the goal of developing targeted interventions to improve outcomes for affected individuals. Still, there remains a massive unmet need for pharmaceutical interventions that ameliorate these aberrant social phenotypes, and current interventions are costly and labor intensive. A particularly promising candidate to address this unmet need is \Oxy, an endogenously expressed neuropeptide, with demonstrated pro-social effects in both humans and animal models, and low incidence of adverse effects. However, clinical trials of \oxy in ASD have had mixed results, likely due to a range of issues from inadequately powered study designs, difficulty in quantifying changes in social behavior over time, heterogeneous study populations, and an inadequate understanding of the underlying mechanisms of \oxy signaling in the brain.

The work described in this dissertation aims to address some of these gaps in knowledge. First, the results of a collaboration with a phase-2 clinical trial of \inoxy are discussed, in which I contributed to identifying a number of biological markers that were associated with \enoxy production in human participants. I discuss how this may be an important component of predicting an individuals response to \exoxy.

I will then discuss our findings in the \cd{} mouse model of ASD-like behaviors. These mice exhibit a unique socially divergent phenotype in which some mice will display very little social motivation within litters while the others behave normally. Importantly, these antisocial mice are responsive to treatment with \exoxy, but the mechanisms behind their unique social phenotype and responsiveness to \oxy remain unknown. I quantified broad patterns of differential gene expression and DNA methylation in the brains of \cd{} mice and their closely related but highly social \cs{} counterparts. This work identified a pattern of differential gene expression in the hippocampus of \cs{} mice that may offer insights into the nature of their naturally occurring social divergence.

Collectively, the findings of these two projects provide valuable information to the field of \oxy and ASD research. The results of the human trial can be used to guide new studies into the endogenous regulation of \oxy, providing potential targets for future interventions to responsive candidates. The results of the mouse experiments identified a myriad of underlying biological pathways that distinguish \cd{} from \cs{} mice, which can serve as the foundation for new targeted hypotheses and to test expanded pharmaceutical interventions to enhance the effects of \exoxy.

Research on biomarkers of brain disorders is an actively developing area. Biomarkers may allow for the early detection of diseases, which is essential for early intervention and improved outcomes. Biomarkers for monitoring the changes in the patient’s state can potentially increase the efficiency of clinical trials. Digital biomarkers, which emerged in recent years, rely on applications of machine learning methods to the data gathered by low-cost sensors, often embedded in consumer devices. Digital biomarkers have the potential to provide low-cost and more objective, granular, and sensitive to change metrics than traditional clinical ratings used in assessments of neurological and neurodevelopmental disorders. On the other hand, in traditional electrophysiological methods measuring brain activity, such as electroencephalography (EEG), biomarkers historically were based on visual analysis by clinicians, classical signal processing measures, or event-related potential (ERP) technique. Search for machine learning-based EEG biomarkers is an active area of research. This dissertation aims to build novel digital behavioral and EEG-based biomarkers and outcome measures by applying machine learning to behavioral, EEG, and concurrently recorded behavioral and EEG data. Machine learning models for the detection of gaze, human face and body landmarks, and automatic speech recognition achieve good performance on publicly available datasets. However, applying these models to a new clinical dataset immediately incurs a dataset shift problem, since the conditions under which real clinical video and audio data are recorded differe from the training dataset (e.g. different video camera angles, or audio noise). Furthermore, clinical datasets are in general much smaller than those used for training such models, and there are not enough human resources in the clinical setting to perform data labeling, making re-training not feasible. Yet, the question remains – whether the predictions from pre-trained models can provide valuable insight into human behavior and neurophysiology in the clinical setting, and whether they can be a source of clinically relevant findings. In this dissertation, we first explore this question in two use cases: (1) building digital measures of caregiver-child interaction in neurodevelopmental disorders using pre-trained pose detection deep learning models; (2) creating a digital biomarker of ataxic dysarthria using pre-trained automatic speech recognition deep learning models. We show that in the first case, our method enables to distinguish different clusters of caregiver responsiveness which are associated with a child’s caregiver- and clinician-reported socialization, communication, and language abilities, thus demonstrating the feasibility of using digital measures of caregiver-child interaction in clinical trials. In the second case, we demonstrate the convergent validity of our novel biomarker with clinician-reported scores and the greater sensitivity to change than clinician-reported scores on a longitudinal dataset. Second, we propose a novel deep learning model for detecting seizures in neonates from EEG data. We demonstrate the model’s high generalizability by evaluating it on an independent dataset from another hospital and show that model by design can be applied in different facilities with different EEG hardware. This approach has the potential to be clinically validated and will allow to scale up studies of neonatal seizures by increasing the sample sizes (including data from multiple clinical centers). Finally, we turn to the problem of combining EEG and behavioral biomarkers, which can improve biomarker sensitivity, but also provide new insights into brain-behavior relationships. In the study of autism, we propose a new metric of attentional preference to social/non-social stimuli and show that not only it distinguishes between autistic and neurotypical children, but also is differently associated with brain activity as measured by EEG. Then we turn to the question of scaling up EEG and behavior studies and provide the tool that allows measuring participants’ attention to the screen during EEG recording. This tool will allow to reduce human effort and make measurements of participants’ visual attention more objective, thus scaling up data preprocessing and allowing for multi-center studies of concurrent EEG and behavior.

Numerous mouse models of autism spectrum disorder (ASD) have been generated to determine the molecular and circuit mechanisms underlying the condition. In this dissertation, I characterize the behavior of two mouse models mimicking some of the most common mutations found in human patients, which is an important step in establishing them as models.

One important application of mouse models is our ability to use them to test specific treatments in a preclinical setting. These treatments are primarily pharmacological in nature, but some work has also been done to test the effects of the environment on the presentation of phenotypes. In particular, environmental enrichment has been shown to prevent the manifestation of ASD-like behaviors in several different mouse models of the disorder. In this dissertation, I tested the effects of environmental enrichment on our Shank3 mouse model of ASD and found that it did not rescue any of the behavioral phenotypes we previously observed, but rather exacerbated some common comorbidities.

More recently, methods have been developed to manipulate gene expression in mice over space and time and have been utilized to gain a clearer picture of the cell types, circuits, brain regions, and developmental time periods involved in autism spectrum disorder. I utilized conditional knockout technology to test whether behavioral phenotypes associated with ASD could be induced by deleting Shank3 in adult and developing mice. We found that Shank3 may play a role in development and that inducing mutations in adult mice is insufficient to cause ASD-like behaviors. Unfortunately, technical concerns limit our interpretation of the data, and this study adds to the growing concern of the limitations inherent in this technology.

Autism spectrum disorders (ASDs) are increasingly prevalent, and the costs associated with caring for affected patients across the lifespan are immense. However, the pathophysiology and brain regions involved in characteristic behavioral impairments remain poorly defined, which hinders progress towards targeted therapeutic development. Different brain regions have been suggested from human neuroimaging studies but the circuit mechanism is not known and cannot be easily defined in human studies. Genetic studies indicate that SHANK3, a gene encoding a scaffolding protein at the postsynaptic density, is a strong ASD causative gene. Studies of various isoform-specific knockout mice support these mice as valid models to dissect the pathophysiology of ASDs and implicate differential involvement of brain regions such as hippocampus and striatum. However, none of these mice recapitulate the most frequent SHANK-related mutation found in ASD patients: a deletion of the entire SHANK3 gene.

For this reason, we have created conventional complete knockout mice by deleting almost the entire coding region of exons 4 to 22, Shank3 Δe4-22, and performed a thorough characterization of their behavioral phenotypes. Their abnormalities in complex social and communication behaviors in addition to their profound display of repetitive and restrictive behaviors in combination with comorbid anxiety, locomotor, and learning phenotypes support them as a mouse model for SHANK3-causing autism with good construct and face validity. Additional studies by collaborators identified a striatal-centered model of circuit and synaptic dysfunction. Manipulation of metabotropic glutamate receptor 5 (mGluR5) activity attenuated the excessive grooming and instrumental learning differentially in Δe4-22-/- mice. These findings show that deficiency of the autism-associated Shank3 gene can impair mGluR5-Homer scaffolding, resulting in cortico-striatal circuit abnormalities which underlie deficits in learning and ASD-like behaviors. These data suggest causal links between genetic, molecular, and circuit mechanisms underlying the pathophysiology of ASDs.

However, because these and other existing Shank3 mutant mice are not region specific, causality between different brain regions and ASD-like behaviors cannot be firmly established. In order to define anatomic regions implicated in behavioral manifestations of ASD, conditional knockout mice lacking Shank3 proteins in different brain regions including forebrain excitatory neurons (NEX-Cre) and striatal inhibitory neurons (Dlx5/6-Cre), as well as distinct cell populations including direct (D1-Cre) and indirect (D2-Cre) medium spiny neurons, were generated and subjected to behavioral phenotyping. Different autism-relevant behaviors as well as comorbid behaviors were recapitulated by targeting Shank3 deletion to different brain regions or cell types. Electrophysiological and biochemical studies further identified synaptic defects resulting from region- or cell-autonomous loss of Shank3, with different biochemical pathways implicated when Shank3 deletion was targeted to the cortex and hippocampus versus the basal ganglia. This study demonstrates the impact of specific brain regions in modulating ASD-related behavior and identifies key molecular defects which are restricted to specific brain regions in SHANK3-deficient ASD, thus providing future therapeutic targets.

Lastly, as one of the major advantages of modeling ASDs in mice is their amenability for pre-clinical studies of interventions, we have tested two different cellular therapies hypothesized to modulate neuronal circuit function either through direct differentiation of stem cells into brain cells including neurons, glia, and microglia or through indirect effects on neuro-immune modulation. While neither perinatal nor young adulthood treatment with human umbilical cord blood derived stem cells affected significant improvements in the behaviors of Shank3 knockout mice, these experiments underscored the robust, reliable behavioral phenotypes of this animal model as well as supported the safety and tolerability of these treatments in a rodent pre-clinical model with a relevant genetic construct.