Geraldine Dawson - US grants

This study will investigate brain functioning and language development in autistic, non-ausistic communication-handicapped, and mentally-retarded children. Research has suggested that the language impariment found in autistic children may be related to left hemisphere dysfunction. Also, it has been shown that autistic children typically exhibit an atypical pattern of hemispheric specialization, namely right hemisphere representation for language. This pattern is also found in cases of early left-sided brain trauma but unlike autism, the undamaged right hemisphere is capable of compensating for language. In the proposed research,m the reasons for the failure of right hemisphere compensation will be explored. It wil be determined whether (1) the age at which a child begins language therapy and/or (2) the integrity of right hemisphere functioning predicts an autistic child's level of language attainment. Since plasticity is presumed to decline with age it is predicted that language will be less likely to develop if therapy begins after age 5. In addition, it will be determined whether cerebral asymmetry is a necessary prerequisite for language acquisition in autistic children. By comparing autistic children to those with other forms of communication disorger and mental retardation, it will be determined whether these characteristics are unique to autism. Also, our understanding of these related disorders will be increased. Cerebral lateralization will be measured by the verbal dichotic listening technique. Measures of brain functioning will be simple motor tasks from the Halstead-Reitan Battery. These measures which assess motor weakness can be used to infer lateralizd brain dysfunction. The child will also be administered visuospatial tasks and comprehensive language evaluation. The information gained should allow us to make more educated decisions regarding what therapy should begin to optimize its benefits. More generally, this research seeks to elucidate the parameters and mechanisms underlying plasticity in the humain brain.

The specific aims of the project are (1) to determine the types of impairments of emotional expression and perception that are found in autism, and (2) to investigate the neuropsychological bases of these impairments. Measures will be taken on three groups of subjects: autistic children ranging from 6 to 18 years of age, and developmentally-matched normal and mentally retarded children. These three groups will be compared in terms of their ability to perceptually discriminate and categorize facial expressions, and in terms of their spontaneous expression of various emotions. Measures of spontaneous emotional behavior will be taken in both a controlled laboratory setting and in naturalistic school situations. Parents will also provide information about their child's emotional behavior in a questionnaire The above measures will be used to investigate whether individual differences in affective and social ability are related to specific patterns of frontal and parietal lobe functioning. Electroencephalographic (EEG) recordings of right and left frontal and parietal activity will be taken in response to a variety of affective and cognitive stimuli. EEG will be subjected to power spectrum analysis to yield measures of alpha band power frequency (8-13 Hz). Measures of right and left parietal and frontal integrated alpha will be used to infer differential cortical activation during affective and cognitive processing. Comparisons of patterns of brain activity will be made among autistic, and matched mentally retarded and normal subjects. Specific predictions regarding the pattern of brain dysfunction expected in autistic subjects are based on current neuropsychological models of emotion. The long term objectives of the research program are to shed light on the neuropsychological bases of early infantile autism and to use this information to develop more effective diagnostic and treatment methods for autistic persons.

The purpose of this project is to identify, and explore the nature of, psychophysiological characteristics that are related to depression. In particular, we are interested in the frontal lobe and its role in affective expression and regulation in depressed and non-depressed adolescent mothers and their infants. We seek to replicate our previous finding that infants of depressed and non-depressed mothers differ in their patterns of frontal EEG activity during emotional situations. Furthermore, we plan to extend this research by examining the contemporaneous and predictive relationships between measures of frontal lobe EEG activity and autonomic arousal, and "depressed" behavior in mothers and their infants. Participants will be 120 infants and their adolescent mothers, approximately half of whom will be depressed as reflected in their scores on the Center for Epidemiological Studies-Depression Scale. Infants' patterns of frontal EEG and autonomic arousal in resting and emotion-eliciting conditions will be studied longitudinally at 10, 20 and 30 months of age, along with measures of maternal depression and maternal affective and interactive style with her infant. Infants' social and affective behavior, and cognitive and language abilities also will be assessed longitudinally. A central question to be addressed by the longitudinal study is whether it is the case that infants' psychophysiological responses are relatively stable over time despite changes in maternal report of depression and/or maternal behavior toward the infant (Model 1), or, alternatively, that infants' psychophysiological responses are closely linked at any given time to mother's current report of depressive symptoms and/or her behavior toward her infant (Model 2). Finally, when infants are 10 and 30 months of age, frontal EEG activity and autonomic arousal also will be measured in the depressed and non-depressed adults were found to differ in their patterns of resting frontal EEG activity, and also allow us to examine more closely the linkage between infants' and mothers' affective and physiological responses.

The purpose of this project is to identify, and explore the nature of, psychophysiological characteristics that are related to depression. In particular, we are interested in the frontal lobe and its role in affective expression and regulation in depressed and non-depressed adolescent mothers and their infants. We seek to replicate our previous finding that infants of depressed and non-depressed mothers differ in their patterns of frontal EEG activity during emotional situations. Furthermore, we plan to extend this research by examining the contemporaneous and predictive relationships between measures of frontal lobe EEG activity and autonomic arousal, and "depressed" behavior in mothers and their infants. Participants will be 120 infants and their adolescent mothers, approximately half of whom will be depressed as reflected in their scores on the Center for Epidemiological Studies-Depression Scale. Infants' patterns of frontal EEG and autonomic arousal in resting and emotion-eliciting conditions will be studied longitudinally at 10, 20 and 30 months of age, along with measures of maternal depression and maternal affective and interactive style with her infant. Infants' social and affective behavior, and cognitive and language abilities also will be assessed longitudinally. A central question to be addressed by the longitudinal study is whether it is the case that infants' psychophysiological responses are relatively stable over time despite changes in maternal report of depression and/or maternal behavior toward the infant (Model 1), or, alternatively, that infants' psychophysiological responses are closely linked at any given time to mother's current report of depressive symptoms and/or her behavior toward her infant (Model 2). Finally, when infants are 10 and 30 months of age, frontal EEG activity and autonomic arousal also will be measured in the depressed and non-depressed adults were found to differ in their patterns of resting frontal EEG activity, and also allow us to examine more closely the linkage between infants' and mothers' affective and physiological responses.

The proposed research is designed to shed light on the psychophysiological bases of individual differences in infants' emotional expression and regulation, and to identify psychophysiological indices of vulnerability to the development of affective and/or other behavioral disorders in early childhood. In a previous study, it was found that infants of depressed mothers exhibit atypical patterns of frontal lobe electroencephalographic (EEG) activity, as compared to infants of non- depressed mothers. These findings are particularly interesting in light of research documenting the role of the frontal lobe in affect expression, and in adult depression. In the present application, a replication of these findings with an independent sample of mothers and infants is reported. The purpose of the proposed research is to further explore the nature and clinical significance of these findings. Specifically, the research is designed to examine the consistency of infants' patterns of frontal EEG across different situations, and to determine whether the relation between maternal depression and infant frontal EEG is mediated by the mother's behavior toward her infant, as measured in situations outside of the psychophysiology laboratory. In addition, the research is designed to determine the degree to which infants' patterns of frontal EEG are stable from infancy to toddlerhood, and whether changes over time in mothers' depressive symptoms influence stability. Finally, the extent to which measures of frontal EEG enhance our ability to predict infants' behavioral disturbances when the infants reach toddlerhood (30 months) will be examined. Participants will be 135 30-month-old infants and their mothers, who previously participated in psychophysiological (EEG) and behavioral testing when the infants were 14 months of age. At that time, 75 of the mothers reported elevated levels of depressive symptoms and 60 mothers reported very few or no depressive symptoms and no current or past major depressive episodes. Thirty-month-old infants and their mothers will participate in psychophysiological testing designed to measure frontal EEG and autonomic activity during baseline and emotion-eliciting conditions. Mothers and infants also will be observed outside the psychophysiological laboratory in situations designed to assess patterns of mother-infant interaction and infant mastery motivation. Infant behavioral measures will focus on the assessment of affective behavior, task persistence (attention and mastery motivation), and self-regulation. Maternal behavior will be examined in three parallel realms: affective behavior, maternal strategies for directing her infant's attention, and maternal strategies for facilitating self-regulation. Mother's and teacher's report of child problem behaviors also will be assessed.

Among the early impairments typically shown by children with autism is a failure to imitate the motor actions of other people. Imitation plays a central role in both in both social and cognitive development. Thus, autistic children's deficient imitation ability may help to explain many of the core symptoms of autism. Although impaired motor imitation is considered a diagnostic criterion for autism, very little is known about the nature or cause of this impairment. The primary aim of this research project is to explore the psychological nature and neurophysiological basis of autistic children's deficit in motor imitation. Three possible reasons for autistic children's impairment in motor imitation will be investigated using rigorous experimental methods that have been designed to assess imitation in normally-developing infants. Subjects will consist of developmentally-matched samples of young autistic, mentally-retarded, and normally-developing children. The first experiment is designed to determine whether the autistic child has difficulty recognizing the similarity between actions of the self and other, a possibility that has been raised by investigators in the field but has never been directly tested. The second experiment is designed to assess whether the autistic child, although recognizing the similarity between actions of self and other, is unable to translate this perceptual information into motor actions (immediate imitation). The third experiment is designed to assess whether the autistic child's failure to imitate is related to a general deficit in the ability to store and later act on internal representations of absent events (deferred imitation). Such a representational capability has been linked to the prefrontal cortex. To further explore the relations between frontal lobe functioning and motor imitation in autism, both behavioral and electrophysiological (EEG) measures of frontal lobe functioning will be obtained to examine whether these measures are predictive of children's level of imitation and social ability.

There are three aims of this project. The first aim is to demonstrate that autism can be distinghished from mental retardation in infants one year of age. This will be accomplished by observing 1st birthday home videotapes of 75 3-4 year old children later diagnosed with autism, and comparing them to 1st birthday party videotapes obtained from 50 3-4 year children with idiopathic mential retardation and from 75 children with typical development. The second aim is to determine whether variations in early course of development in autism (early vs late onset) are related to individual differences in later symptom expression and brain function. It is believed that approximately 25 percent of children with autism show a pattern of normal development followed by regression in the second or third year of life. Such patterns likely reflect different underlying brain mechanisms in autism and may index subtypes of the disorder. To investigate this possibility, children with early versus later onset of autistic symptoms, as reflected in observations from 1st and 2nd year videotapes, will be compared to determine whether they differ in terms of their patterns of symptom expression and neurocognitive profiles at 3-4 years of age. The third aim is to study more broadly the longitudinal development of children with autism from infancy through early childhood with the goal of identifying key factors related to outcome in autism. Children with autism and the comparison group of children with mental retardation will be followed longitudinally during the preschool period. Analyses will examine how three primary factors - age of symptom onset, early neurocognitive profile, and intensity of early intervention - are related to outcome by early elementary school age (6-7 years).

neurogenetics; behavioral /social science research tag; autism; longitudinal human study; neurobiology; preschool child (1-5); child mental disorders; child psychology;

DESCRIPTION (provided by applicant): The primary purpose of the Behavioral Science Core is to facilitate high quality, creative, and cost-effective research and to provide research facilities and consultation to support behavioral scientists investigating normal and atypical human development. Providing core facilities and a forum for behavioral scientists to communicate ideas, specific knowledge, and techniques regarding common conceptual and methodological issues involved in behavioral research accomplish this. Such issues include methodological techniques pertaining to behavioral observation and psychophysiology, and conceptual issues pertaining to measurement of specific constructs (e.g., parent-child interaction, peer relations, attachment) and the interface between behavioral and neurophysiological measures.

The UW STAART Center will address the following overall objectives: (1) To determine social, linguistic, neuropsychological, and electrophysiological characteristics that distinguish very young children with autism from children with developmental delay and those with typical development. Such research will enhance our ability to recognize autism early in life so that children with autism can be helped as early as possible, and their long-term outcome can be improved (Projects I and II). (2) To assess the efficacy of early intensive behavioral intervention for improving outcomes for children with autism, and to determine whether child neurocognitive factors moderate the effects of early intervention. Such knowledge will inform decisions regarding individualized interventions, elucidate brain mechanisms, and shed light on questions related to brain plasticity (Project I). (3) To increase our understanding of the neurobiological bases of autism by studying abnormalities in brain structure (via magnetic resonance imaging) and brain chemistry (via magnetic resonance spectroscopy) in very young children with autism, as compared to children with developmental delay and those with typical development (Project III). (4) To enhance our understanding of the cognitive neuroscience of autism by studying core social cognition impairments in high-functioning individuals with autism using event related brain potentials and functional magnetic resonance imaging. This information is relevant for early identification, development of more refined interventions, and measurement of quantitative genetic traits (Project IV). (5) To conduct molecular biology studies aimed at gene discovery in autism. Identification of susceptibility genes in autism is important for early identification, prevention, and medical treatment (Project V).

This project has three broad goals: (1) to improve early identification of autism, (2) to assess the efficacy of early intensive behavioral intervention (EIBI) for treatment of autism, and (3) to better understand individual child factors that account for variability in response to EIBI. The specific aims are: 1. To identify cognitive, social, neuropsychological, and electrical brain activity differences between 18-24 month old toddlers with autism versus 18-24 month olds with developmental (cognitive) delay (DD) and typical development. 2. To conduct a randomized study of EIBI to evaluate the efficacy of EIB! for improving outcomes of young children with autism, based on measures of cognitive, language, and social behavior. 3. To also evaluate the efficacy of EIBI for improving outcomes based on measures of brain activity. Our previous studies have shown that children with autism show atypical patterns of event related brain potentials in response to social stimuli. Given the emphasis on improving social behavior (e.g., eye contact) in EIBI, it is possible that EIBI may result in improved outcome on brain measures related to social processing. We will determine whether EIBI results in changes in brain activity such that, after treatment, children who have received EIBI will show more normal patterns of brain activity than those who do not receive such intervention. 4. To identify individual child factors that account for variation in response to EIBI in young children with autism. We hypothesize that three child factors will be important predictors of response to intervention. These are (1) IQ, (2) severity of autism symptoms, and (3) degree of early brain impairment, specifically, degree of medial temporal lobe dysfunction. A better understanding of factors related to response to early intervention would inform decisions regarding appropriate, individualized intervention methods and elucidate brain mechanisms involved in autism.

The overall UW ACE theme centers on a comprehensive developmental model of risk, risk processes, symptom emergence, and adaptation in autism spectrum disorder (ASD). According to this model, early autism risk factors (genetic/familial and environmental) lead to risk processes, namely altered patterns of interaction between the child and his/her environment, which contribute to the abnormal development of neural circuitry and atypical behaviors. By identifying infants at risk at an early age when the brain is developing and before core autism symptoms have emerged, it might be possible to alter the developmental trajectory of children at risk for the disorder and have a significant impact on long-term outcome. Both clinical progress and basic science will profit from the identification of endophenotypes [unreadable] intermediate, quantifiable traits that predict an individual's risk of having a disorder, which can be linked to underlying cause. The goals of Project II are two-fold: First, in a sample of infant sibs, we aim to investigate whether neurophysiological risk indices (endophenotypes) measured at 6-7 mos of age will improve our ability to identify infants who will develop autism or autism-related symptoms by age 2. Second, we will assess whether it is possible to alter risk processes via early intervention with high-risk infants, thereby reducing severity of autism symptoms. Specifically, we plan to investigate the efficacy of early intervention that is designed to enhance early social responsiveness and communication in infants who are at risk for autism (infant siblings of children with autism). Despite the fact that our ability to identify infants at risk for autism is rapidly improving, early interventions for infants at risk for autism have not yet been tested. This project represents a first step toward developing effective interventions for at-risk infants. The proposed work on early autism risk factors will have impact on several key areas: (1) Identification of the biological and/or behavioral risk indices in infancy, for the development of autism and autism- related symptoms, such as language and social impairments; (2) development of intervention methods for infants and toddlers to lower the age for which there are efficacious interventions; (3) identification of individual characteristics that predict response to behavioral treatment; and (4) provision of evidence that cases of autism might be secondarily prevented through early identification and early treatment.

Project Summary/Abstract The goal of this consortium is to establish tools that can be used as biomarkers and/or sensitive and reliable objective assays of social impairment in autism spectrum disorder (ASD) clinical trials. Specifically, we aim to accelerate the development of effective treatments for social impairment in ASD by validating (a) outcome measures that will be sensitive and reliable assessments of response to treatment and EEG and (b) eye-tracking (ET) biomarkers that can be used to reduce heterogeneity of samples via stratification, indicate early efficacy, and/or demonstrate target engagement. The consortium will conduct a naturalistic, longitudinal study of preschool (3-5 years) and school aged (6-11 years) children with ASD and typical development (TD) with IQ ranging from 50-115. Children will be assessed across three time points (T1: Baseline, T2: 6 weeks, T3: 24 weeks) using clinician, caregiver and lab-based (LB) measures of social impairment, along with a battery of conceptually related EEG and ET tasks and independent ratings of clinical status. This battery measures key facets of social-communication in ASD using well-validated paradigms appropriate for this developmental and cognitive range. Five Collaborating Implementation Sites (?Sites?), all highly experienced in multi-site collaborative clinical research using the methodologies proposed here in both typical and atypical development, will contribute equally to recruitment, screening, diagnosis, testing, and longitudinal assessment. The Data Coordinating Core (DCC) will provide a secure informatics infrastructure to streamline communication and data flow throughout the consortium to ensure organized, secure data management, quality control, and reliable upload to the National Database for Autism Research and NIH/NIMH Data Repositories. The Data Acquisition and Analysis Core (DAAC) will oversee consistent application of scientific standards and methodological rigor for standardized data collection, processing, and analytics. The Administrative Core will oversee the operations of the Sites, the DCC, and the DAAC to coordinate with federal and private partners in this cooperative agreement to: 1) Compare whether LB measures versus clinician and caregiver assessments of social impairment are more sensitive indicators of clinical status; 2) Evaluate whether this set of ET and EEG measures, individually or in combination, has potential utility as stratification biomarkers and/or sensitive and reliable measures of change in clinical trials, assessing viability in terms of: construct validity; test-retest reliability, consistency, and stability; discriminant validity ; convergent validity; and sensitivity to change; 3) Collect blood (DNA) samples from subjects and parents of ASD subjects for future genomic analyses and share raw, processed, and analyzed data to create a community resource accessible for use by all qualified investigators.

ABSTRACT ? Project 2: Neural signatures, developmental precursors, and outcomes in young children with ASD and ADHD Although recognized as distinct diagnostic conditions, autism spectrum disorder (ASD) and attention deficit hyperactivity disorder (ADHD) are highly comorbid. The overlap in clinical presentation, risk factors, and co- heritability of ASD and ADHD has led some authors to propose that these disorders share underlying biological mechanisms and that ADHD is a milder, less severe subtype within the ASD syndrome. Moreover, the presence of co-occurring ADHD has significant clinical implications, where individuals with comorbid ASD and ADHD have substantially poorer outcomes. To date, very little research has focused on the overlap of ASD and ADHD during early childhood. Thus, we know relatively little about the extent to which ASD and ADHD represent distinct conditions or the impact of co-occurring ADHD symptoms on early behavioral patterns and brain mechanisms in ASD. In Project 2, we will study the neural signatures, biomarkers, developmental trajectories, and clinical outcomes associated with comorbid ASD and ADHD with the overarching goal of generating knowledge that will allow earlier detection of these overlapping conditions and more individualized treatment approaches that take into account the additive and interactive effects of both conditions. The primary goals of Project 2 are to (1) elucidate shared and distinct neural signatures and biomarkers related to ASD vs. ADHD, (2) examine the functional and clinical impact of co-occurring ADHD symptoms in young children with ASD, and (3) identify early characteristics of infants and toddlers later diagnosed with ASD with and without elevated ADHD symptoms. To this end, in Project 2, we will recruit four groups of children between 36-72 months of age with the following clinical features: ASD only, ASD+ADHD, ADHD only, and typically-developing (TD) children. The specific aims to achieve our overall study goals are to (1) identify differences and commonalities in neural signatures and biomarkers based on neurophysiology and eye-gaze tracking across the four groups; (2) examine how these biomarkers are correlated with specific symptom profiles based on shared and distinct phenotypic characteristics of ASD and ADHD; (3) determine the clinical impact of ADHD in young children with ASD; and (4) explore the extent to which developmental precursors linked to diagnostic outcome can be detected during the infant-toddler period. The latter aim will be accomplished by analyzing home video recordings taken in the first and second year of life of children later diagnosed with ASD only, ADHD only, ASD+ADHD, vs. TD, based on observations made via automated computer vision analysis of movement and affect, as well as human coding of vocalizations/verbalizations, joint attention, gaze and orienting behavior, affect, and repetitive behaviors. Project 2 will provide a detailed, comprehensive understanding of unique developmental trajectories and impacts of co-occurring ADHD in children with ASD.

ABSTRACT ? Co-occurring ADHD in young children with ASD: Precursors, detection, neural signatures, and early treatment Attention deficit hyperactivity disorder (ADHD) occurs in ~40-60% of individuals with autism spectrum disorder (ASD) and substantially contributes to poorer clinical outcomes. Yet, very little research has focused on the overlap of ASD and ADHD during early childhood. Thus, little is known about how these two conditions co- emerge early in life. Given the high prevalence and clinical impact of the comorbidity of ASD and ADHD, the overall goal of the Duke Autism Center of Excellence is to characterize how co-occurring ADHD influences early screening, neural signatures, developmental trajectories, and response to early treatment of young children with ASD. Project 1 will characterize risk factors for and emergence of co-occurring ADHD symptoms in young children at risk for ASD and examine how these symptoms influence early detection and progression of ASD. This project will clarify why children who have co-occurring ADHD are diagnosed at a much later age and inform more effective early detection strategies. Following a large sample of toddlers receiving routine care in Duke pediatric primary clinics (N = ~ 2800 patients/year), Project 1 will prospectively identify children at risk for ASD and collect data on risk factors, ADHD, and developmental outcomes. Project 2 will elucidate shared and distinct neural signatures and attention-related biomarkers related to ASD and ADHD, examine the functional impact of co-occurring ADHD in young children with ASD, and identify precursor characteristics during infancy that are predictive of later emergence of comorbid ASD and ADHD. This project will characterize children with ASD alone, ASD+ADHD, ADHD alone, and typically-developing children, using state-of-the-art methods, including neurophysiology, eye-tracking, movement-tracking, and computer vision analysis. Project 3 will evaluate a novel early intervention model personalized for young children with ASD+ADHD that pharmacologically addresses ADHD symptoms prior to initiating early behavioral intervention, and identify changes in behavioral and neurophysiological activity that may underlie response to treatment. This project will accomplish these goals by evaluating whether stimulant treatment (Adzenys-XR-ODT) augments the efficacy of a parent-delivered behavioral intervention based on the Early Start Denver Model. This project will examine whether changes in outcome are correlated with improvements in social attention, measured via eye-tracking biomarkers, and social engagement during parent-child interaction. This project will also examine neurophysiological changes underlying improvements in behavior. These projects will be supported by four cores: Administrative Core, Recruitment and Assessment Core, Data Management and Analysis Core, and Dissemination and Outreach Core. Functioning as a whole, the Duke Autism Center of Excellence will offer the most comprehensive understanding to date of the impact of ADHD on young children with ASD, providing important information that will allow for biologically informed and personalized methods for early detection and treatment that could mitigate the negative impact of co-occurring ADHD on individuals with ASD.  

ABSTRACT ? Administrative Core The overall goal of the Duke Autism Center of Excellence is to characterize how co-occurring symptoms of attention deficit hyperactivity disorder (ADHD) influence the early detection, clinical presentation, neural signatures, developmental trajectories, and treatment outcomes of young children with autism spectrum disorder (ASD). The Administrative (?Admin?) Core will serve as the hub for the Center, coordinating and overseeing all research projects and cores so that they function effectively and efficiently as a whole in an integrated and synergistic fashion. The goals of the Admin Core are to promote communication and collaboration among team investigators, reduce the administrative burden on Center investigators, monitor regulatory compliance, and ensure scientific rigor, progress, and productivity. The Admin Core will be responsible for achieving the following specific aims: (1) coordinate, promote, and streamline communication across all components of the Center to ensure close collaboration and scientific progress through all phases of the research program. To accomplish this aim, the Admin Core will coordinate monthly Executive Committee and Center-wide meetings at which project and core Leads and other key personnel and staff members will review target recruitment goals, expenditure summaries, resources, timelines, and deliverables; identify any barriers to achieving the Center's goals; and develop and implement strategies for addressing barriers; (2) provide overall management and oversight of the Center. The Core will oversee and support the Center's scientific efforts by setting goals, defining deliverables, and closely monitoring and evaluating progress and productivity, thereby ensuring timely progress toward milestones and deliverables. Evaluation of each project and core, as well as the overall Center, will be based on scientific progress relative to these agreed-upon milestones and in relation to expected expenditures; and (3) provide timely financial accounting and ensure compliance with all institutional, state, and federal research and ethical guidelines. The Core will provide expertise and infrastructure to ensure financial management and compliance with relevant university, state, DHHS, NIH, and federal research regulations, including those related to human subjects research. The Admin Core will be closely connected to and will integrate all projects and cores. In this way, the Admin Core will ensure a unified, compliant research effort and will support the Center's overall goals to shed light on the early detection, developmental trajectories, neural signatures, and treatment of co-occurring ADHD symptoms in young children with ASD.  

ABSTRACT ? Novel Approaches to Infant Screening for ASD in Pediatric Primary Care The overall goal of this project is to develop and validate novel tools to identify risk for autism spectrum disorder (ASD) in infants 6-12 months of age in a pediatric primary care setting. Research has confirmed that ASD is associated with changes in brain and behavior that are evident during infancy, and proof-of-concept studies suggest that early intervention during the infant period can improve early brain function and developmental outcomes. Moreover, early universal autism screening has been shown to reduce existing disparities based on socioeconomic status (SES) and ethnicity/race in access to early diagnosis and treatment. This project leverages ongoing work that is currently funded as part of the Duke NIH Autism Center of Excellence (ACE) Award (NICHD P50 HD093074; Dawson, Center Director), which is evaluating a novel digital phenotyping tool for early ASD risk assessment in toddler-age children in a pediatric primary care setting. Our novel screening tool, SenseToKnow, is based on active closed-loop sensing, where children are shown brief, developmentally-appropriate, dynamic stimuli on a smart tablet or smartphone, while the sensors in the same device capture information for automatic, objective quantification of several behavioral risk markers, based on patterns of attention, orienting, affect, vocalizations, and motor behavior. The proposed research will 1) evaluate a novel infant version of the app, SenseToKnow-Infant, in a large population of infants in the context of routine pediatric care, and 2) examine the utility of a multi- modal approach to risk assessment that combines information from SenseToKnow-I with information from infant and maternal electronic health records (EHRs). Using both direct digital behavioral measurement via SenseToKnow-I and data readily available in the EHR, we aim to develop and validate a multimodal ASD risk assessment algorithm for use in infants (6-12 months of age) that can be deployed in the general population.

SCALABLE COMPUTATIONAL PLATFORM FOR ACTIVE CLOSED-LOOP BEHAVIORAL CODING IN AUTISM SPECTRUM DISORDER ABSTRACT Despite significant recent advances in molecular genetics and neuroscience, behavioral ratings based on clinical observations are still the gold standard for screening, diagnosing, and assessing outcomes in neurodevelopmental disorders, including autism spectrum disorder (ASD). Such behavioral ratings are subjective, require significant clinician expertise and training, typically do not capture data from the children in their natural environments, and are not scalable for large population screening, low-income communities, or longitudinal monitoring. The development of scalable digital approaches to standardized objective behavioral assessment is thus a significant unmet need in ASD, here addressed via machine learning and computer vision with the goal of providing scalable methods for assessing existing biomarkers, from eye tracking to movement and posture patterns, and tools for novel discovery. Our long-term goal is to develop validated scalable tools for the automatic behavioral analysis of neurodevelopmental disorders. The proposed computational project leverages results and big data derived from our previous studies (N=1,864 participants) and our recently funded NIH Autism Center of Excellence (ACE) award (N=7,436 participants). The ACE project will allow us to develop and validate our tools on several thousand toddlers recruited in Duke pediatric primary care and followed longitudinally for whom gold-standard diagnoses of ASD, attention deficit hyperactivity disorder (ADHD), developmental and language delay and extensive electronic health record (EHR) data will be available; and in a case control study of 224 age-matched groups of young children with ASD, ADHD, and typical development from whom gold-standard diagnostic, extensive phenotypic, Tobii eye- tracking, and EEG will be collected. This project aims to develop novel computational methods using these datasets, from sensing in scalable fashion behaviors such as attention and gaze (Aim 1) and motor/posture (Aim 2), to their multimodal integration (Aim 3). A unique aspect of our computational approach is the closed- loop integration of stimuli design for actively eliciting behavioral symptoms, use of consumer-grade sensors, and automatic behavioral analysis. This contrasts with the current approach of independently selecting stimuli and using expensive lab-based professional grade sensors with off-the-shelf algorithms to capture behavioral biomarkers expected from the stimuli. Our approach involves active elicitation of behavior which is also different from commonly used digital approaches that involve gathering large datasets from passive sensing, such as actigraphy monitoring of spontaneous behavior at home. Our framework results in active closed-loop sensing, where participants are engaged in short and developmentally appropriate activities on ubiquitous devices, while the sensors in the same device capture information for the automatic and quantitative analysis of behavioral biomarkers. This scalable, objective, and standardized way of stimulating, sensing, and analyzing allows the collection of large behavioral datasets for machine learning.