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Dive into the research topics where Frederick Shic is active.

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Featured researches published by Frederick Shic.


Frontiers in Neuroscience | 2017

JAKE® Multimodal Data Capture System: Insights from an Observational Study of Autism Spectrum Disorder

Seth Ness; Nikolay V. Manyakov; Abigail Bangerter; David Lewin; Shyla Jagannatha; Matthew Boice; Andrew Skalkin; Geraldine Dawson; Yvette M. Janvier; Matthew S. Goodwin; Robert L. Hendren; Bennett L. Leventhal; Frederick Shic; Walter Cioccia; Gahan Pandina

Objective: To test usability and optimize the Janssen Autism Knowledge Engine (JAKE®) systems components, biosensors, and procedures used for objective measurement of core and associated symptoms of autism spectrum disorder (ASD) in clinical trials. Methods: A prospective, observational study of 29 children and adolescents with ASD using the JAKE system was conducted at three sites in the United States. This study was designed to establish the feasibility of the JAKE system and to learn practical aspects of its implementation. In addition to information collected by web and mobile components, wearable biosensor data were collected both continuously in natural settings and periodically during a battery of experimental tasks administered in laboratory settings. This study is registered at clinicaltrials.gov, NCT02299700. Results: Feedback collected throughout the study allowed future refinements to be planned for all components of the system. The Autism Behavior Inventory (ABI), a parent-reported measure of ASD core and associated symptoms, performed well. Among biosensors studied, the eye-tracker, sleep monitor, and electrocardiogram were shown to capture high quality data, whereas wireless electroencephalography was difficult to use due to its form factor. On an exit survey, the majority of parents rated their overall reaction to JAKE as positive/very positive. No significant device-related events were reported in the study. Conclusion: The results of this study, with the described changes, demonstrate that the JAKE system is a viable, useful, and safe platform for use in clinical trials of ASD, justifying larger validation and deployment studies of the optimized system.


Pediatrics | 2018

Clinical Features of Children With Autism Who Passed 18-Month Screening

Roald A. Øien; Synnve Schjølberg; Fred R. Volkmar; Frederick Shic; Domenic V. Cicchetti; Anders Nordahl-Hansen; Nina Stenberg; Mady Hornig; Alexandra Havdahl; Anne-Siri Øyen; Pamela Ventola; Ezra Susser; Martin Eisemann; Katarzyna Chawarska

This is the first study in which researchers examine developmental and temperamental characteristics of boys and girls screening negative for autism at 18 months. OBJECTIVES: We compared sex-stratified developmental and temperamental profiles at 18 months in children screening negative for autism spectrum disorder (ASD) on the Modified Checklist for Autism in Toddlers (M-CHAT) but later receiving diagnoses of ASD (false-negative group) versus those without later ASD diagnoses (true-negative group). METHODS: We included 68 197 screen-negative cases from the Norwegian Mother and Child Cohort Study (49.1% girls). Children were screened by using the 6 critical items of the M-CHAT at 18 months. Groups were compared on domains of the Ages and Stages Questionnaire and the Emotionality Activity Sociability Temperament Survey. RESULTS: Despite passing M-CHAT screening at 18 months, children in the false-negative group exhibited delays in social, communication, and motor skills compared with the true-negative group. Differences were more pronounced in girls. However, with regard to shyness, boys in the false-negative group were rated as more shy than their true-negative counterparts, but girls in the false-negative group were rated as less shy than their counterparts in the true-negative group. CONCLUSIONS: This is the first study to reveal that children who pass M-CHAT screening at 18 months and are later diagnosed with ASD exhibit delays in core social and communication areas as well as fine motor skills at 18 months. Differences appeared to be more pronounced in girls. With these findings, we underscore the need to enhance the understanding of early markers of ASD in boys and girls, as well as factors affecting parental report on early delays and abnormalities, to improve the sensitivity of screening instruments.


Journal of Autism and Developmental Disorders | 2018

Challenges of Females with Autism: A Parental Perspective.

Marilena Mademtzi; Pavita Singh; Frederick Shic; Kathy Koenig

Most studies investigating the experiences and needs of individuals with ASD have largely focused on males. Hence, this study investigates parents’ perspectives on the challenges that their daughters with ASD face. In total, 40 parents of 40 females with autism (age range = 4–29 years; mean = 15.9) participated in the study. Five separate, 2-h long focus groups were conducted, with 7–10 participants in each group. Field notes were analyzed using thematic analysis. Some of the issues parents discussed were similar to those experienced by males with ASD, such as challenges in social interactions. However, other issues discussed were of particular relevance to girls with ASD, including difficulties socializing with other girls, sex-specific puberty issues, barriers in accessing intervention and sexual vulnerability.


international symposium on neural networks | 2017

An exploratory analysis targeting diagnostic classification of AAC app usage patterns

Adham Atyabi; Beibin Li; Yeojin Amy Ahn; Minah Kim; Erin Barney; Frederick Shic

Augmentative and Alternative Communication (AAC) apps are apps that enable non-speech communicative forms. One class of AAC apps are speech-generating devices (SGDs), where icons/pictures are tapped to produce spoken words. These apps are widely used to support communication and language learning for individuals with disabilities such as autism spectrum disorder (ASD). Given that these apps are used in everyday scenarios, they can generate massive streams of data, providing a wealth of information regarding individual usage patterns and for developing usage model profiles. However, the utility and potential of these streams of data has been little explored from a data mining perspective. The objective of this study is to evaluate several feature representations of usage patterns, coupled with data mining and data modelling techniques, for identifying differences in AAC usage patterns between users with and without ASD. The study is conducted using data streams aggregated from an AAC app called FreeSpeech, specifically designed for individuals with learning disabilities and ASD. Several feature representations for modeling usage profiles based on temporal, behavioral and frequency of usage, are investigated. The potential of each usage representation is assessed using a collection of well-known and well-established learning methods such as support vector machine and ensemble learning. While, in general, prediction performance was only slightly above chance in most representations, results from unsupervised class labeling experiments showed promising results regarding the potential of stationary keypress usage representations with bootstrapped ensembles for separating ASD from non-ASD users.


human factors in computing systems | 2018

Social Influences on Executive Functioning in Autism: Design of a Mobile Gaming Platform

Beibin Li; Adham Atyabi; Minah Kim; Erin Barney; Amy Yeojin Ahn; Yawen Luo; Madeline Aubertine; Sarah Corrigan; Tanya St. John; Quan Wang; Marilena Mademtzi; Mary Best; Frederick Shic

Most studies of executive function (EF) in Autism Spectrum Disorder (ASD) focus on cognitive information processing, emphasizing less the social interaction deficits core to ASD. We designed a mobile game that uses social and nonsocial stimuli to assess childrens EF skills. The game comprised three components involving different EF skills: cognitive flexibility (shifting/inference), inhibitory control, and short-term memory. By recruiting 65 children with and without ASD to play the mobile game, we investigated the potential of such platforms for capturing important phenotypic characteristics of individuals with autism. Results highlighted between-diagnostic-group differences in playing patterns with children with ASD showing broad patterns of EF deficits, but with relative strengths in nonsocial short-term memory, and preserved response to emotional inhibition cues. We showed the system could predict IQ, an important target for clinical treatment, towards the goal of developing platforms to act as long-term, efficient, and effective behavioral biomarkers for ASD.


Journal of Autism and Developmental Disorders | 2018

Sex-Differences in Children Referred for Assessment: An Exploratory Analysis of the Autism Mental Status Exam (AMSE)

Roald A. Øien; Sara Magelssen Vambheim; Logan Hart; Anders Nordahl-Hansen; Craig A. Erickson; Logan K. Wink; Martin Eisemann; Frederick Shic; Fred R. Volkmar; David Grodberg

The autism mental status exam is an eight-item observational assessment that structures the way we observe and document signs and symptoms of ASD. Investigations of test performance indicate strong sensitivity and specificity using gold-standard assessment as reference standard. This study aims to explore potential sex differences in AMSE test performance and observations of 123 children referred for autism assessment. Results indicates more language deficits in females with ASD than in males with ASD and less sensory symptoms in females compared to males with ASD. The AMSE performance is similar in identifying ASD and non-ASD in females compared to males. Less disruptive behaviors in females, might cause a need for a bigger hit to other areas of development to raise concern.


Journal of Autism and Developmental Disorders | 2018

Automatic Recognition of Posed Facial Expression of Emotion in Individuals with Autism Spectrum Disorder

Joseph Manfredonia; Abigail Bangerter; Nikolay V. Manyakov; Seth Ness; David Lewin; Andrew Skalkin; Matthew Boice; Matthew S. Goodwin; Geraldine Dawson; Robert L. Hendren; Bennett L. Leventhal; Frederick Shic; Gahan Pandina

Facial expression is impaired in autism spectrum disorder (ASD), but rarely systematically studied. We focus on the ability of individuals with ASD to produce facial expressions of emotions in response to a verbal prompt. We used the Janssen Autism Knowledge Engine (JAKE®), including automated facial expression analysis software (FACET) to measure facial expressions in individuals with ASD (n = 144) and a typically developing (TD) comparison group (n = 41). Differences in ability to produce facial expressions were observed between ASD and TD groups, demonstrated by activation of facial action units (happy, scared, surprised, disgusted, but not angry or sad). Activation of facial action units correlated with parent-reported social communication skills. This approach has potential for diagnostic and response to intervention measures.Trial Registration NCT02299700.


Autism Research | 2018

Visual Exploration in Autism Spectrum Disorder: Exploring Age Differences and Dynamic Features Using Recurrence Quantification Analysis: Visual exploration task in autism

Nikolay V. Manyakov; Abigail Bangerter; Meenakshi Chatterjee; Luke Mason; Seth Ness; David Lewin; Andrew Skalkin; Matthew Boice; Matthew S. Goodwin; Geraldine Dawson; Robert Hendren; Bennett L. Leventhal; Frederick Shic; Gahan Pandina

Eye‐tracking studies have demonstrated that individuals with autism spectrum disorder sometimes show differences in attention and gaze patterns. This includes preference for certain nonsocial objects, heightened attention to detail, and more difficulty with attention shifting and disengagement, which may be associated with restricted and repetitive behaviors. This study utilized a visual exploration task and replicates findings of reduced number of objects explored and increased fixation duration on high autism interest objects in a large sample of individuals with autism spectrum disorder (n = 129, age 6–54 years) in comparison with a typically developing group. These findings correlated with parent‐reported repetitive behaviors. Additionally, we applied recurrent quantification analysis to enable identification of new eye‐tracking features, which accounted for temporal and spatial differences in viewing patterns. These new features were found to discriminate between autism spectrum disorder and typically developing groups and were correlated with parent‐reported repetitive behaviors. Original and novel eye‐tracking features identified by recurrent quantification analysis differed in their relationships to reported behaviors and were dependent on age. Trial Registration: NCT02299700. Autism Research 2018, 11: 1554–1566.


Autism Research | 2018

In Search of Biomarkers for Autism Spectrum Disorder: Exploratory biomarkers in autism

Marta del Valle Rubido; James T. McCracken; Eric Hollander; Frederick Shic; Jana Noeldeke; Lauren Boak; Omar Khwaja; S. Sadikhov; Paulo Fontoura; Daniel Umbricht

Autism Spectrum Disorder (ASD) lacks validated measures of core social functions across development stages suitable for clinical trials. We assessed the concurrent validity between ASD clinical measures and putative biomarkers of core deficits, and their feasibility of implementation in human studies. Datasets from two adult ASD studies were combined (observational study [n = 19] and interventional study baseline data [n = 19]). Potential biomarkers included eye‐tracking, olfaction, and auditory and visual emotion recognition assessed via the Affective Speech Recognition test (ASR) and Reading‐the‐Mind‐in‐the‐Eyes Test (RMET). Current functioning was assessed with intelligence quotient (IQ), adaptive skill testing, and behavioral ratings. Autism severity was determined by the Autism Diagnostic Observation Scale‐2 and Social Communication Interaction Test (SCIT). Exploratory measures showed varying significant associations across ASD severity, adaptive skills, and behavior. Eye tracking endpoints showed little relationship to adaptive ability but correlated with severity and behavior. ASR scores significantly correlated with most adaptive behavior domains, as well as severity. Olfaction predicted visual and auditory emotion recognition. SCIT scores related moderately to multiple severity domains, and was the only measure not related with IQ. RMET accuracy was less related to ASD features. Eye tracking, SCIT, and ASR showed high test–retest reliability. We documented associations of proximal biomarkers of social functioning with multiple ASD dimensions. With the exception of SCIT, most correlations were modest, limiting utility as proxy measures of social communication. Feasibility and reliability were high for eye‐tracking, ASR, and SCIT. Overall, several novel experimental paradigms showed potential as social biomarkers or surrogate markers in ASD. Autism Research 2018, 11: 1567–1579.


Molecular Autism | 2018

Operationalizing atypical gaze in toddlers with autism spectrum disorders: a cohesion-based approach

Quan Wang; Daniel Campbell; Suzanne Macari; Katarzyna Chawarska; Frederick Shic

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Seth Ness

Janssen Pharmaceutica

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